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https://img.denu5.com/tags/poland 2026-07-25T22:31:16.237Z weekly 0.4 https://img.denu5.com/tags/porsche 2026-06-18T09:48:37.186Z weekly 0.4 https://img.denu5.com/tags/porsche-911 2026-10-28T14:59:53.083Z weekly 0.4 https://img.denu5.com/tags/porsche-991 2026-10-28T15:00:16.787Z weekly 0.4 https://img.denu5.com/tags/q22 2026-07-25T22:31:18.404Z weekly 0.4 https://img.denu5.com/tags/rafale 2026-07-25T22:31:14.999Z weekly 0.4 https://img.denu5.com/tags/remus 2026-07-25T22:31:17.249Z weekly 0.4 https://img.denu5.com/tags/roads 2026-07-25T22:31:14.623Z weekly 0.4 https://img.denu5.com/tags/schwyz 2026-06-18T09:48:37.652Z weekly 0.4 https://img.denu5.com/tags/sky 2026-07-25T22:31:17.527Z weekly 0.4 https://img.denu5.com/tags/sorrento 2026-07-25T22:31:18.078Z weekly 0.4 https://img.denu5.com/tags/stoos 2026-07-25T22:31:16.055Z weekly 0.4 https://img.denu5.com/tags/susten-pass 2026-10-28T14:59:54.126Z weekly 0.4 https://img.denu5.com/tags/swiss-air-force 2026-06-18T09:48:36.715Z weekly 0.4 https://img.denu5.com/tags/swiss-alps 2026-07-25T22:31:16.007Z weekly 0.4 https://img.denu5.com/tags/swiss-international-air-lines 2026-07-25T22:31:16.555Z weekly 0.4 https://img.denu5.com/tags/swiss-mountain-passes 2026-07-25T22:31:17.343Z weekly 0.4 https://img.denu5.com/tags/switzerland 2026-07-25T22:31:15.886Z weekly 0.4 https://img.denu5.com/tags/three-point-towers 2026-07-25T22:31:17.476Z weekly 0.4 https://img.denu5.com/tags/vrieske 2026-07-25T22:31:15.206Z weekly 0.4 https://img.denu5.com/tags/warsaw 2026-10-28T14:59:59.501Z weekly 0.4 https://img.denu5.com/videos/d5-llm weekly 0.6 https://img.denu5.com/videos/d5-llm/blazor-community-standup-generative-ui-with-ag-ui-a2ui Blazor Community Standup: Generative UI with AG-UI & A2UI https://i.ytimg.com/vi/aYe12ryuB4s/maxresdefault.jpg Join us to learn how AI agents can dynamically create and adapt application experiences using AG-UI, A2UI, Microsoft Agent Framework, and Blazor. ⌚ Chapters: 00:00 Countdown (silent) 02:33 Welcome and Intros 04:38 What is Generative UI (Agentic UI) 08:15 Why do we need Generative UI 10:50 Generative UI types 17:39 Agentic UI in .NET Blazor Applications - architecture 22:30 Microsoft Agent Framework 25:20 AG-UI Protocol overview 25:47 Support for AG-UI in .NET 30:45 AG-UI - using an agent int he app (pseudocode) 32:36 A2UI: dynamically rendering UI from JSON sent from an agent 34:55 A2UI - sample component definition 36:12 Demo 42:56 Q&A 47:58 Resources & links 48:30 Key takeaways 56:17 Wrap 🔗 Links: https://www.theurlist.com/blazor-standup-20260714 🎙️ Featuring: Daniel Roth, Javier Calvarro Nelson, Maya Mateva, Stamo Gochev #dotnet #aspnetcore #blazor https://www.youtube.com/embed/aYe12ryuB4s 3450 2026-07-15T06:03:02.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/lessons-learned-scaling-observability-at-blackrock-drivewealth Lessons Learned Scaling Observability at BlackRock & DriveWealth https://i.ytimg.com/vi/2jOT__oF0k4/sddefault.jpg Learn from real-world observability journeys in this expert panel featuring Grafana Labs, BlackRock, and DriveWealth. Senior leaders share how they scaled observability, moved from logs to metrics, tackled tool sprawl, and aligned observability with business outcomes. Topics include maturity models, open standards, AI-assisted observability, cost control, and cultural adoption. A must-watch for engineers and platform teams building resilient, scalable systems. Chapters: 00:00 - Introductions & Observability Context 01:55 - Why Observability Matters to the Business 03:50 - Biggest Challenges: Scale, Tool Sprawl, and Costs 06:07 - Maturity Models, Governance, and Culture 07:36 - Why Grafana: Scalability, Open Standards, Usability 10:58 - What’s Next: Metrics, Profiling, AI, and Automation 17:00 - Organizing for Observability: Centralized vs Federated 19:13 - Advice for Teams Starting Their Observability Journey 21:42 - Audience Q&A: Logs vs Metrics, Tracing, Cost, and MTTX Relevant links: ☁️ Grafana Cloud is the easiest way to get started with Grafana dashboards, metrics, logs, and traces. Our forever-free tier includes access to 10k metrics, 50GB logs, 50GB traces and more. We also have plans for every use case. Sign up: https://grafana.com/get/ ❓ Have a question that isn't related to this video? Check out the Official Grafana Community Forums and ask your question or find your answer: https://community.grafana.com/ --- Thanks for watching! 👍 Was this video helpful? Like and subscribe to our channel for more videos. Connect with Grafana Labs: X: (https://www.twitter.com/grafana) LinkedIn: (https://www.linkedin.com/company/grafana-labs/) Facebook: (https://www.facebook.com/grafana) #Grafana #Observability https://www.youtube.com/embed/2jOT__oF0k4 2188 2026-01-23T21:15:14.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-ai-distillation-cookbook The AI Distillation Cookbook https://i.ytimg.com/vi/ErDS9TIQoWU/maxresdefault.jpg While the rest of the industry chases massive models, LinkedIn quietly achieved a major engineering breakthrough by going small. In this episode of Beyond the Pilot, Erran Berger (VP of Product Engineering, LinkedIn) opens the "cookbook" on how they distilled massive 7B parameter models down to ultra-efficient 600M parameter "student" models—scaling AI to 1.2 billion users without breaking the bank. AI Gets Real Here. This isn't theory. Erran details the exact architecture, the "Multi-Teacher" distillation process, and the organizational shift that forced Product Managers to write evals instead of specs. In this episode, we cover: The Distillation Pipeline: How to train a 7B "Teacher" and distill it to a 1.7B intermediate and 0.6B "Student" for production. Synthetic Data Strategy: Using GPT-4 to generate the "Golden Dataset" for training. Multi-Teacher Architecture: Why they separated "Product Policy" and "Click Prediction" into different teacher models to solve alignment issues. 10x Efficiency Hacks: Specific techniques (Pruning, Quantization, Context Compression) that slashed latency. Org Design: Why the "Eval First" culture is the new requirement for AI engineering teams. 🚀 CHAPTERS 00:00 - Intro: LinkedIn's Massive "Small Model" Feat 04:00 - Why Commercial Models Failed at LinkedIn Scale 08:00 - The "Product Policy" Funnel & Synthetic Data Generation 12:00 - The Pipeline: 7B → 1.7B → 600M Parameters 19:00 - The "Multi-Teacher" Breakthrough (Relevance vs. Clicks) 23:00 - How They Achieved 10x Latency Reduction (Pruning/Compression) 31:00 - Changing the Culture: Why PMs Must Write Evals 35:00 - The "Bright Green Matrix": Measuring Success & Future Roadmap If you enjoy these conversations, you need to be in Menlo Park this July. VB Transform 2026 is VentureBeat's flagship enterprise AI event, built entirely around one question: How do you orchestrate AI autonomy at scale? July 14–15, Hotel Nia. Real projects, proprietary research, no fluff. 50% off for listeners with code BEYONDTHEPILOT: https://bit https://www.youtube.com/embed/ErDS9TIQoWU 2439 2026-01-21T14:30:00.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/what-was-my-worst-lunch-ai-powered-blood-sugar-analysis-with-github-copilot-claude-code-skills "What was my worst lunch?" AI-Powered Blood Sugar Analysis with GitHub Copilot + Claude Code Skills https://i.ytimg.com/vi/on5R6PWj8Wg/maxresdefault.jpg I've been having trouble with my blood sugar spiking after lunch. So I asked GitHub Copilot CLI to help me figure out what's going on - and when it couldn't answer my question, we fixed the skill together, live. Using my Nightscout CGM data and a custom Copilot skill, I asked "what was my worst lunch this week?" The AI found the problem (yesterday, peaked at 294 mg/dL 😬) but needed to write a custom Python script to do it. That's a sign the tool is missing something! So we added two new commands: - day - drill into exactly what happened on a specific date - worst - find your problem days ranked by peak glucose We also removed hard-coded "meal presets" because everyone eats at different times (and this needs to work globally). Now the AI just asks "what hours do you eat lunch?" and uses those. This is the magic of AI-assisted development: the AI uses the tool, hits a limitation, and helps you fix it - all in the same conversation. 🔗 Nightscout CGM Skill: https://github.com/shanselman/nightscout-cgm-skill 🔗 Agent Skills standard: https://github.com/agentskills/agentskills #GitHubCopilot #Diabetes #Nightscout #T1D #AIAssistant #LiveCoding https://www.youtube.com/embed/on5R6PWj8Wg 1546 2026-01-17T21:48:01.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-infinite-software-crisis-jake-nations-netflix The Infinite Software Crisis – Jake Nations, Netflix https://i.ytimg.com/vi/eIoohUmYpGI/maxresdefault.jpg In 1968, the term ""Software Crisis"" emerged when systems grew beyond what developers could manage. Every generation since has ""solved"" it with more powerful tools, only to create even bigger problems. Today, AI accelerates the pattern into the Infinite Software Crisis. AI-generated codebases mirror the meandering conversations that created them. Every clarification and pivot gets baked into your architecture. We're vibecoding our way to disaster. The solution: choose simple over easy. One long conversation is easy. Separate phases with clean boundaries are simple. This talk presents a three-phase methodology: - Research to understand the existing system - Planning to design the approach - Implementation with clean context While everyone races to generate code at machine speed, the engineers who thrive will be those who know when a system is getting tangled. In the age of infinite code generation, human judgment applied at the right moments becomes your competitive advantage. Speaker: Jake Nations | Engineering, Netflix https://www.linkedin.com/in/jakenations/ https://github.com/Nayshins Timestamps: 00:00 The Modern Confession: Shipping Code We Don’t Understand 01:53 The History of the Software Crisis (1968 to Present) 03:30 Fred Brooks and "No Silver Bullet" 04:12 Simple vs. Easy (Rich Hickey’s Definition) 05:40 The AI Trap: "Vibecoding" and Conversational Complexity 06:39 The problem with iterative AI chat interfaces 15:12 Implementation Phase: Using Manual Migration as a Seed 16:14 The Knowledge Gap: Code Generation vs. Code Understanding 17:40 Conclusion: Software is a Human Endeavor --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/eIoohUmYpGI-infinite-software-crisis Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference https://www.youtube.com/embed/eIoohUmYpGI 1137 2025-12-20T17:00:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/stanford-cs230-autumn-2025-lecture-9-career-advice-in-ai Stanford CS230 | Autumn 2025 | Lecture 9: Career Advice in AI https://i.ytimg.com/vi/AuZoDsNmG_s/maxresdefault.jpg For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai November 18, 2025 This lecture covers career advice and a guest speaker. To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs230-deep-learning Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/ View the playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNRRGdS0rBbXOUGA0wjdh1X Guest Speaker Laurence Moroney Best-selling AI author and award-winning researcher Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department https://www.youtube.com/embed/AuZoDsNmG_s 6309 2025-12-17T00:44:02.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/stanford-ai-club-jeff-dean-on-important-ai-trends Stanford AI Club: Jeff Dean on Important AI Trends https://i.ytimg.com/vi/AnTw_t21ayE/maxresdefault.jpg This talk was recorded as part of the Stanford AI Club’s Speaker Series, and was facilitated by Stanford AI Club Leadership Jason Zhang + Tanvir Bhathal. Jeff Dean is one of the most influential computer scientists of the modern computing era, best known as Google’s Chief Scientist and a co-founder of Google Brain. His work has shaped the foundations of large-scale distributed systems and modern machine learning—spanning breakthroughs in search infrastructure, deep learning frameworks like TensorFlow, and today’s frontier AI research. https://www.youtube.com/embed/AnTw_t21ayE 2505 2025-11-24T16:46:15.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/unlocking-ai-interoperability-a-deep-dive-into-the-model-context-protocol Unlocking AI Interoperability: A Deep Dive into the Model Context Protocol https://i.ytimg.com/vi/xqsaRaMOpXI/maxresdefault.jpg Imagine a world where AI agents can easily connect to any data source, tool, or API without having to rely on one-off custom integrations. That world exists, and it’s based on Model Context Protocol (MCP) – an open standard that's fundamentally changing how Large Language Models interact with external systems. In this technical deep dive, we'll explore the architecture behind MCP, from its transport layer to its primitive abstraction patterns. You will learn how MCP servers expose capabilities through a standard interface, enabling AI models to dynamically discover and interact with everything from databases to development environments. We’ll have both practical demos as well as see how major AI platforms are adopting MCP to break down integration silos. You'll leave the session with a comprehensive understanding of MCP's security model, best practices for server development, and strategies for migrating existing integrations to this game-changing standard. Whether you're building AI applications, maintaining APIs, or architecting the next generation of developer tools, this session will equip you with the knowledge needed to start using MCP and help shape the future of AI interoperability. Azure free trial: https://aka.ms/AzureFreeTrialYT Visual Studio: http://visualstudio.com VS Live on-demand sessions: https://aka.ms/vslivehq25 Missed the fun at MS HQ?! Join one of these upcoming events, we’ll see you there! VSLive events: https://aka.ms/VSS/VSLive Subscriptions portal: https://my.visualstudio.com https://www.youtube.com/embed/xqsaRaMOpXI 3133 2025-08-14T14:45:20.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/agi-is-not-coming AGI is not coming! https://i.ytimg.com/vi/hkAH7-u7t5k/maxresdefault.jpg jack Morris's investigation into GPT-OSS training data https://x.com/jxmnop/status/1953899426075816164?t=3YRhVQDwQLk2gouTSACoqA&s=09 https://www.youtube.com/embed/hkAH7-u7t5k 429 2025-08-09T10:39:28.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/using-github-copilot-and-mcp-servers-to-not-write-code Using GitHub Copilot and MCP servers to NOT write code https://i.ytimg.com/vi/VdYR_Qf-j38/sddefault.jpg Liam is here to show you how he is using Visual Studio Code and GitHub Copilot Agent mode with MCP servers to automate his daily task list and NOT write any code. He uses the GitHub MCP server to pull back open pull requests and assigned issues and a LeetCode MCP server to grab the daily challenge to scratch his coding itch. Looking to learn more about MCP? Join MCP Dev Days on July 29th and 30th! https://aka.ms/MCPDevDays 🔎 Chapters: 00:00 Intro 00:25 Demo 03:18 Closing 🔗 Links: https://github.com/github/github-mcp-server https://github.com/features/copilot 🎙️ Featuring: Liam Hampton Twitter: https://x.com/liamchampton LinkedIn: https://www.linkedin.com/in/liam-conroy-hampton/ 📲 Follow VS Code: * X: https://x.com/code * Bluesky: https://bsky.app/profile/vscode.dev * LinkedIn: https://aka.ms/VSCode/LinkedIn * GitHub: https://github.com/microsoft/vscode #vscode #mcpserver #githubcopilot https://www.youtube.com/embed/VdYR_Qf-j38 215 2025-07-18T20:27:10.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/build-your-own-ai-copilot-for-financial-apps-with-postgresql Build your own AI Copilot for financial apps with PostgreSQL https://i.ytimg.com/vi/CEzUxJQ-0Cc/maxresdefault.jpg Join us to explore how to transform a traditional financial application into an intelligent, AI-powered solution using PostgreSQL and Azure. In this hands-on session, you'll learn how to integrate generative AI to deliver high-quality responses to financial queries through a smart copilot that leverages PDF-based Statements of Work (SOWs) and invoices. We'll guide you through: - Performing AI-driven data validation - Using the Azure AI extension for PostgreSQL - Implementing vector search with DiskANN indexes - Enhancing results with semantic re-ranking - Building with the LangChain agent/tools framework - Applying GraphRAG on Azure Database for PostgreSQL By the end of the session, you'll have built a practical, end-to-end AI-driven application---and gained the skills to apply these techniques to your own data and projects. 📌 This session is a part of a series. Learn more here: https://aka.ms/BuildAIapps/PostgreSQL #MicrosoftReactor #learnconnectbuild Chapters: 00:00 - Welcome & Housekeeping 00:57 - Meet the Speakers: Aaron Wislang & Ismael Mejia 01:48 - Series Recap & Today’s Use Case 03:20 - Automating Contract & Invoice Validation 05:02 - Architecture Overview 08:08 - Document Flow & AI Services 10:03 - Document Examples: SOWs & Invoices 13:23 - Setting Up the Lab Environment 16:32 - Exploring the PostgreSQL Schema 20:05 - Database Setup & Extensions 25:00 - AI-Driven Document Validation 33:02 - Embeddings, Indexing & Vector Search 43:01 - Chunking & Summarization with Azure AI 47:00 - Prompt Engineering for Validation 54:03 - Building the AI Copilot Chat 1:00:00 - LangChain Integration & Agent Tools 1:04:00 - Live Demo: Chat UI in Action 1:07:16 - Improving Accuracy with Semantic Ranking 1:09:01 - GraphRAG & Graph Queries in PostgreSQL 1:12:21 - Final Thoughts & Resources [eventID:26070] https://www.youtube.com/embed/CEzUxJQ-0Cc 4593 2025-07-16T05:23:05.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/let-s-learn-mcp-c Let's Learn MCP: C# https://i.ytimg.com/vi/4zkIBMFdL2w/maxresdefault.jpg 💡​Demo code: https://aka.ms/letslearnmcp-csharp Let's learn about the Model Context Protocol (MCP), a cutting-edge framework designed to standardize interactions between AI models and client applications. Through this beginner-friendly workshop, we'll introduce you to MCP and guide you through creating your first MCP server. 🌍 Want to watch the session in another programming or natural language? https://aka.ms/letslearnmcp ⭐ Register for MCP Dev Days (July 29 & 30): https://aka.ms/mcpdevdays Chapters: 00:00 What is MCP 17:13 Setting up and using MCP servers 56:04 MCP Deep Dive 1:12:10 Build an MCP server 1:37:42 MCP at Microsoft 🎙️ Featuring: Katie Savage and James Montemagno #dotnet #mcp #csharp https://www.youtube.com/embed/4zkIBMFdL2w 6338 2025-07-09T17:53:52.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/end-to-end-development-with-github-copilot-mcp-server-full-workflow-demo End-to-end development with GitHub Copilot + MCP server | Full Workflow Demo https://i.ytimg.com/vi/HN47tveqfQU/maxresdefault.jpg Use GitHub Copilot and the GitHub MCP Server together for seamless, end-to-end software development - right from your IDE. In this walkthrough, we’ll show you how Copilot and the remote MCP server help streamline the dev experience: from triaging issues and accessing repo context directly in VS Code, to authoring and reviewing pull requests - all without switching tools. Whether you're working on your next big project or building at enterprise scale, see how this integrated setup can boost productivity, reduce friction, and help you ship faster. #GitHub #Copilot #MCP #DevOps #VSCode #RemoteDevelopment #AI #DeveloperTools ▬▬▬▬▬▬ TIMESTAMPS ⌚ ▬▬▬▬▬▬ 00:00 Introduction to GitHub MCP server 00:10 Starting the server & authentication 00:17 Creating issues in GitHub via Copilot 00:43 Enabling Agent mode and Issue creation workflow 01:11 Reviewing created issues in repository 01:43 Searching issues using MCP and Copilot 02:12 Triage assistance with Copilot 02:38 Implementing issue code via Agent Mode 03:12 Creating pull request with Copilot 03:54 Reviewing pull request details 04:01 Benefits of using GitHub MCP server with Copilot Stay up-to-date on all things GitHub by connecting with us: YouTube: https://gh.io/subgithub Blog: https://github.blog X: https://twitter.com/github LinkedIn: https://linkedin.com/company/github Insider newsletter: https://resources.github.com/newsletter/ Instagram: https://www.instagram.com/github TikTok: https://www.tiktok.com/@github About GitHub It’s where over 100 million developers create, share, and ship the best code possible. It’s a place for anyone, from anywhere, to build anything—it’s where the world builds software. https://github.com https://www.youtube.com/embed/HN47tveqfQU 266 2025-07-01T14:00:33.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/using-the-tableau-mcp-with-claude-on-superstore Using the Tableau MCP with Claude on Superstore https://i.ytimg.com/vi/G-KtYXUeUSQ/maxresdefault.jpg Just tested the newly released Tableau MCP (Model Context Protocol)… and wow, it works like magic, especially when paired with Claude.ai. Imagine asking Claude a business question, and watching it interact live with governed Tableau data sources — no prompt engineering, no guessing, just results. 🧠 It’s like having a data concierge built into your AI. 💡 What’s so powerful about Tableau MCP? ✅ Access to Published Data Sources via the VizQL Data Service (VDS) ✅ Pull field-level metadata using the Metadata API ✅ Fully compatible with tools like Claude, Cursor, and more ✅ Works with Tableau Cloud and Server, including on-prem deployments ✅ Keeps all queries within your security boundaries With VizQL Data Service now GA, LangChain connectors live, and MCP opening the door for AI/agent integrations, Tableau is building a serious foundation for the future of AI + Analytics. Watch out, Tableau Concierg, your open-source cousin just arrived. 💬 Curious how it works in your own Tableau Server environment? Get in touch with Biztory! hashtag#Tableau hashtag#AI hashtag#Analytics hashtag#ClaudeAI hashtag#MCP hashtag#VizQL hashtag#MetadataAPI hashtag#TableauServer hashtag#DataFam https://www.youtube.com/embed/G-KtYXUeUSQ 193 2025-06-25T18:47:01.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/ai-agents-with-mcp-explained AI Agents with MCP Explained https://i.ytimg.com/vi/wGz955ZeLpc/maxresdefault.jpg In this video, we break down how AI agents work in tandem with MCP servers to deliver powerful, orchestrated experiences. Learn how Agents, AI orchestrators, and MCP servers collaborate to manage tasks, delegate responsibilities, and scale intelligent workflows across systems. ⌚ Chapters: 00:00 Intro 00:25 AI Agent 03:15 MCP 05:42 MCP Server & Client 11:48 Agent to Agent 12:52 Outro 🔗 Links: https://aka.ms/azmcp https://aka.ms/azmcp/docs https://modelcontextprotocol.io/introduction https://google-a2a.github.io/A2A 🎙️ Featuring: Jeffery Richter Follow us on social: Blog - https://aka.ms/azuredevelopers/blog Twitter - https://aka.ms/azuredevelopers/twitter LinkedIn - https://aka.ms/azuredevelopers/linkedin Twitch - https://aka.ms/azuredevelopers/twitch #azuredeveloper #azure https://www.youtube.com/embed/wGz955ZeLpc 849 2025-06-17T14:01:23.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-model-context-protocol-mcp The Model Context Protocol (MCP) https://i.ytimg.com/vi/CQywdSdi5iA/maxresdefault.jpg Theo Chu, David Soria Parra and Alex Albert dive into the Model Context Protocol (MCP), the standard that's changing how AI applications connect with external data and tools. Anthropic open-sourced MCP in November 2024. Learn more about MCP: https://modelcontextprotocol.io Read the initial announcement: https://anthropic.com/news/model-context-protocol 0:00 Introduction 0:35 MCP and core components 3:13 How it started 6:22 Launching MCP and reception 8:12 Making it open source 9:55 Current state 13:23 Tips for getting started 14:57 Favorite MCP servers 16:23 Claude 4 improvements 18:18 What's next https://www.youtube.com/embed/CQywdSdi5iA 1175 2025-06-16T13:03:20.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-linkedin-built-their-first-ai-agent-for-hiring-with-langgraph-langchain-interrupt How LinkedIn Built Their First AI Agent for Hiring with LangGraph | LangChain Interrupt https://i.ytimg.com/vi/NmblVxyBhi8/maxresdefault.jpg Discover how LinkedIn built their breakthrough AI agent for hiring in this technical deep-dive with David Tag from LinkedIn's AI team. David walks through the LangGraph-powered architecture of LinkedIn Hiring Assistant and shares the production framework that enabled 20+ teams to develop AI agents at scale. Watch all of our recorded sessions from Interrupt here: https://interrupt.langchain.com/video/?utm_medium=social&utm_source=youtube&utm_campaign=q2-2025_interrupt-2025_co Learn more about LangGraph Platform: https://www.langchain.com/langgraph-platform/?utm_medium=social&utm_source=youtube&utm_campaign=q2-2025_interrupt-2025_co https://www.youtube.com/embed/NmblVxyBhi8 925 2025-06-13T17:16:56.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-blackrock-built-production-ai-agents-for-asset-management-with-langgraph-langchain-interrupt How BlackRock Built Production AI Agents for Asset Management with LangGraph | LangChain Interrupt https://i.ytimg.com/vi/oyqeCHFM5U4/maxresdefault.jpg Discover how BlackRock's AI engineering team built production-ready AI agents that power the Aladdin platform, serving $11 trillion in assets across 100+ applications globally. Brennan Rosales and Pedro Vicente Valdez reveal their enterprise agentic architecture built on LangGraph, including their plugin registry system that enables 50+ engineering teams to contribute tools and agents, plus their evaluation-driven development approach with daily CI/CD testing. Watch all of our recorded sessions from Interrupt here: https://interrupt.langchain.com/video/?utm_medium=social&utm_source=youtube&utm_campaign=q2-2025_interrupt-2025_co https://www.youtube.com/embed/oyqeCHFM5U4 905 2025-06-12T17:19:54.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/fastmcp-the-best-way-to-build-an-mcp-server-with-python FastMCP — the best way to build an MCP server with Python https://i.ytimg.com/vi/rnljvmHorQw/maxresdefault.jpg AGENTIC CODING CLUB [ ⚡ my official community ] ► https://www.skool.com/zazencodes-agentic-coding-club-7823 ⚡ Weekly code-with-me sessions to ask questions ⚡ Full AI Engineer Roadmap course access NEWSLETTER [ 🚀 weekly email + zen guide for developers ] ► https://zazencodes.substack.com/ FASTMCP EXAMPLE [ 💾 source code ] ► https://github.com/zazencodes/zazencodes-season-2/tree/main/src/fastmcp-tutorial 1:01 - MCP Crash Course 3:10 - FastMCP Python Library 5:20 - Building an MCP Server with Claude Code 7:40 - How FastMCP Projects Work 10:46 - Running an MCP Server with FastMCP 12:50 - Connecting a FastMCP Server to Claude Desktop 16:32 - Resources and Prompts with FastMCP 20:43 - Inspecting Local MCP Servers 23:15 - Distributing Python MCP Servers https://www.youtube.com/embed/rnljvmHorQw 1676 2025-06-11T14:01:19.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/session-pragmatic-scaling-of-enterprise-genai-with-mcp-with-sambhav-kothari-at-bloomberg [Session] Pragmatic Scaling of Enterprise GenAI with MCP with Sambhav Kothari at Bloomberg https://i.ytimg.com/vi/usc2XRStxbw/maxresdefault.jpg [Session] Pragmatic Scaling of Enterprise GenAI with MCP 🎤 Sambhav Kothari, Engineering Manager, Head of AI Productivity - Bloomberg ✨ MCP Developers Summit 2025 📅 May 23, 2025 📍 San Francisco, CA https://www.youtube.com/embed/usc2XRStxbw 811 2025-06-03T15:21:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/state-of-the-art-prompting-for-ai-agents State-Of-The-Art Prompting For AI Agents https://i.ytimg.com/vi/DL82mGde6wo/maxresdefault.jpg At first, prompting seemed to be a temporary workaround for getting the most out of large language models. But over time, it's become critical to the way we interact with AI. On the Lightcone, Garry, Harj, Diana, and Jared break down what they've learned from working with hundreds of founders building with LLMs: why prompting still matters, where it breaks down, and how teams are making it more reliable in production. They share real examples of prompts that failed, how companies are testing for quality, and what the best teams are doing to make LLM outputs useful and predictable. The prompt from Parahelp (S24) discussed in the episode: https://parahelp.com/blog/prompt-design Apply to Y Combinator: https://ycombinator.com/apply Work at a startup: https://workatastartup.com Chapters (Powered by https://chapterme.co/) - 0:00 Intro 0:58 Parahelp’s prompt example 4:59 Different types of prompts 6:51 Metaprompting 7:58 Using examples 12:10 Some tricks for longer prompts 14:18 Findings on evals 17:25 Every founder has become a forward deployed engineer (FDE) 23:18 Vertical AI agents are closing big deals with the FDE model 26:13 The personalities of the different LLMs 27:26 Lessons from rubrics 29:47 Kaizen and the art of communication 31:00 Outro https://www.youtube.com/embed/DL82mGde6wo 1886 2025-05-30T14:00:19.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/why-mcp-really-is-a-big-deal-model-context-protocol-with-tim-berglund Why MCP really is a big deal | Model Context Protocol with Tim Berglund https://i.ytimg.com/vi/FLpS7OfD5-s/maxresdefault.jpg Blog: https://www.confluent.io/blog/ai-agents-using-anthropic-mcp | Tim Berglund is back at the lightboard with *MCP* (Model Context Protocol). MCP really _is_ a big deal, but most people are missing the point. It's not just about enhancing desktop applications with agentic functionality—it's about exposing reusable tools and resources (including real-time data from sources like Apache Kafka) to build _agentic microservices._ Doing this takes us beyond basic LLM chatbots to dynamic, problem-solving systems that deliver real value in real professional settings. LEARN MORE ► Blog: Powering AI Agents with MCP & Confluent: https://www.confluent.io/blog/ai-agents-using-anthropic-mcp ► GitHub: Confluent MCP Server: https://github.com/confluentinc/mcp-confluent ► Webinar on MCP & Confluent: https://www.confluent.io/resources/online-talk/ai-agents-with-anthropic-mcp-claude ► Confluent Developer: https://developer.confluent.io CHAPTERS 00:00 - The need for broader vision with Model Context Protocol (MCP) and agentic AI applications 01:30 - How LLMs work and their limitations in taking actions 03:00 - The importance of tools and resources for agentic behavior 04:30 - MCP architecture: Host app, client library, and server 06:30 - Example: Building an agentic appointment scheduling app 09:00 - Workflow: Prompting, accessing resources, and invoking tools CONNECT Subscribe, if you dare: https://www.youtube.com/@ConfluentDeveloper?sub_confirmation=1 Community Slack: https://confluentcommunity.slack.com X: https://x.com/confluentinc Linkedin: https://www.linkedin.com/company/confluent GitHub: https://github.com/confluentinc Site: https://developer.confluent.io ABOUT CONFLUENT DEVELOPER Confluent Developer provides comprehensive resources for developers looking to learn about Apache Kafka®, Apache Flink®, Confluent Cloud, Confluent Platform, and any other technology related to the broader Data Streaming Platform. Content on Confluent Developer includes courses, getting started guides, topical deep-dives, patterns, tutorials, https://www.youtube.com/embed/FLpS7OfD5-s 669 2025-05-27T12:01:02.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/your-api-is-not-an-mcp-demfp786 Your API is not an MCP | DEMFP786 https://i.ytimg.com/vi/eeOANluSqAE/maxresdefault.jpg This is one of many innovative Featured Partner sessions from Microsoft Build 2025. View more information from this partner at https://aka.ms/Build25_Neon A lot of companies have jumped on the MCP bandwagon by quickly auto-generating their MCP servers from their APIs. This isn’t right as MCP servers are made to be consumed by LLMs and not by humans. Join us to better understand why MCPs have to be thought of carefully. Experience examples of tools that make sense for agents but not for humans, and why you should be careful designing your MCP set of tools and resources. To learn more, please check out these resources: * https://neon.tech/msbuild 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * David Gomes 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Build 2025 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com DEMFP786 | English (US) | AI, Copilot & Agents #MSBuild, #AI https://www.youtube.com/embed/eeOANluSqAE 884 2025-05-23T23:25:26.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-making-of-nlweb-brk240 The Making of NLWeb | BRK240 https://i.ytimg.com/vi/EF6uywH-Yzo/maxresdefault.jpg Join a session deep diving into NLWeb, exploring practical uses of the tool on your website. NLWeb is an open project that simplifies the creation of natural language interfaces for websites by pairing existing structured data on the web like Schema.org or RSS with LLMs. We’ll cover how to deploy the sample locally for testing, modify websites, import data, and use MCP servers. NLWeb supports all major operating systems and models, empowering you to create intelligent, interactive experiences. To learn more, please check out these resources: * https://aka.ms/build25/github/BRK240 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Ramanathan Guha * Jennifer Marsman 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Build 2025 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com BRK240 | English (US) | Breakout #MSIgnite, #AI,Copilot&Agents Chapters: 0:00 - Overview of Speaker's Experience 00:00:27 - Purpose and Value of NL Web 00:01:05 - Limitations of Current Digital Interfaces 00:31:29 - Getting Started with Vector Databases 00:33:26 - Integrations and Transformation Capabilities within Vector Database 00:34:41 - Overview of 'Hello World' Process with Vector Database Setup 00:46:22 - Chelsea queries about spicy crunchy snacks 00:47:04 - Visual demonstration of query processing 00:47:47 - Interactive Q&A session on implementation details https://www.youtube.com/embed/EF6uywH-Yzo 3587 2025-05-23T17:49:27.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/use-azure-sre-agent-to-automate-tasks-and-increase-site-reliability-dem550 Use Azure SRE Agent to automate tasks and increase site reliability | DEM550 https://i.ytimg.com/vi/bK3SIQoE_Nc/maxresdefault.jpg The SRE Agent is now in public preview! Learn how to use natural language to describe intent, which is then translated by the AI agent into a series of tasks that the agent can execute with developer approval. It iterates through target applications and carries out the requested task(s), all without the need for developers to remember myriad CLI commands and syntaxes. Microsoft Azure Free Trial: http://aka.ms/devrelFT 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Deepthi Chelupati * Yutang Lin 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Build 2025 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com DEM550 | English (US) | Cloud Platform #MSBuild, #CloudPlatform Chapters: 0:00 - Presenters Introduction: Deepti and Utong 00:00:28 - Azure SRE Agent Overview and Capabilities 00:03:46 - Azure SRE Agent Identifies and Suggests Mitigation for Deployment Issue 00:05:11 - Interactive Queries with SRE Agent 00:07:30 - Change Management Analysis 00:09:12 - Introduction to SRE Agent's Knowledge Graph 00:10:27 - Checking App's Current State in Demo 00:11:11 - AI-Driven Production App Management 00:13:19 - Comprehensive Data Analysis by Agent https://www.youtube.com/embed/bK3SIQoE_Nc 952 2025-05-22T16:28:59.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/eric-schmidt-on-ai-replacing-your-friend-group Eric Schmidt on AI Replacing Your Friend Group https://i.ytimg.com/vi/GIvOw5YI_4A/maxresdefault.jpg A rare and timely conversation with Eric Schmidt, former Chairman & CEO of Google, exploring the powerful intersections of technology, public policy, education, and philanthropy. With deep insight from decades at the forefront of the digital revolution, Schmidt reflects on the future of artificial intelligence, the role of innovation in national security, and the global impact of the Schmidt Science Foundation, which supports breakthrough scientific research for the public good. Guided by moderator Sean McManus of M+D Advisors, this thought-provoking discussion spans the future of education, the ethical dimensions of AI, and bold strategies for advancing human progress in an increasingly complex world. 🔔 Subscribe to @FaenaRose1 for more conversations with today’s most influential thinkers and leaders. #EricSchmidt #FaenaRose #ArtificialIntelligence #TechPolicy #FutureOfTech https://www.youtube.com/embed/GIvOw5YI_4A 4090 2025-05-21T20:00:14.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/cloudflare-ceo-on-the-rise-of-zero-click-searches-it-ll-be-much-harder-to-be-a-content-creator Cloudflare CEO on the rise of 'zero-click searches': It'll be much harder to be a content creator https://i.ytimg.com/vi/WQf-eB2xSew/maxresdefault.jpg Cloudflare co-founder and CEO Matthew Prince joins 'Squawk Box' to discuss the rise of zero-click searches, how AI is disrupting the search economy, the future of content creators, and more. https://www.youtube.com/embed/WQf-eB2xSew 352 2025-05-21T12:43:08.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/interrupt-2025-keynote-harrison-chase-langchain Interrupt 2025 Keynote | Harrison Chase | LangChain https://i.ytimg.com/vi/DrygcOI-kG8/maxresdefault.jpg Watch all of our recorded sessions from Interrupt here: https://interrupt.langchain.com/video/?utm_medium=social&utm_source=youtube&utm_campaign=q2-2025_interrupt-2025_co Join Harrison Chase at LangChain's Interrupt conference for the main keynote on the evolution of agent engineering and the company's vision for making intelligent agents ubiquitous. Harrison shares insights from LangChain's journey since launching as an open-source project over two years ago to becoming more downloaded than OpenAI's SDK, revealing how they're tackling the industry's biggest hurdle: converting the "wow factor" of AI prototypes into reliable, business-ready agent deployments. LangGraph Platform is now Generally Available: Deploy & manage long-running, stateful Agents: https://blog.langchain.dev/langgraph-platform-ga/ #LangGraph #LangChain #AIAgents #AgentDevelopment #LLM https://www.youtube.com/embed/DrygcOI-kG8 1405 2025-05-20T19:56:58.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/introducing-azure-ai-foundry-agent-service Introducing Azure AI Foundry Agent Service https://i.ytimg.com/vi/Q1BGjTMuXhE/maxresdefault.jpg Azure AI Foundry Agent Service is now generally available—empowering you to design, deploy, and scale production-grade AI agents with built-in reliability. As a fully managed service, it handles infrastructure, orchestration, and scaling so your team can focus on agent design. Learn more: https://msft.it/6057SjuIF Get started with Azure AI Foundry https://msft.it/6058SjuI2 #Microsoft https://www.youtube.com/embed/Q1BGjTMuXhE 39 2025-05-19T03:09:02.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/net-ai-community-standup-what-s-next-for-net-and-ai-at-build-2025 .NET AI Community Standup - What’s Next for .NET and AI at Build 2025 https://i.ytimg.com/vi/Fe_7Od0HKqg/maxresdefault.jpg Curious about what’s coming for .NET and AI at Microsoft Build 2025? Join Bruno, Pablo Lopes, and Japhlet as they share their insights on the upcoming announcements, themes, and innovations to watch. This session isn’t just talk—we’ll dive into eShopLite, a powerful open-source sample that shows how to bring AI into a modern .NET eCommerce app using RAG, Azure AI Search, MCP, Realtime Voice, and more. Come for the predictions, stay for the code! 🔗 https://aka.ms/eShopLite/repo ⌚ Chapters: 00:00 Countdown 01:36 Welcome and Intros 06:30 eShopLite Repo: ​​https://aka.ms/eshoplite/repo 08:50 Demo 14:13 Q&A and Microsoft Build Preview 01:00:19 Wrap 🔗 Community Links: https://learn.microsoft.com/en-us/collections/66ypt7t662q1dq 🎙️ Featuring: Bruno Capuano (@elbruno), Pablo Lopes (@pablolopes), Japhlet Nwamu (@japhletnwamu) #MicrosoftBuild #eShopLite #DotNet #AzureAI #AIForDevelopers #OpenSource #Build2025 https://www.youtube.com/embed/Fe_7Od0HKqg 3638 2025-05-08T06:06:20.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/develop-an-ai-agents-with-semantic-kernel-mvpconnect Develop an AI agents with Semantic Kernel | #MVPConnect https://i.ytimg.com/vi/_zYEm3TlLvM/maxresdefault.jpg In this session we will delve into the capabilities of semantic kernel, will learn how the semantic kernel connects code to LLMs to extend functionality with generative artificial intelligence. Additionally we will create and test an Agent using semantic kernel SDKs, understand the purpose of semantic kernel plugins hands-on, creating prompt templates and understanding usage of personas in prompts with hands-on. Focus on: Semantic Kernel high-level overview, evolution of agents, semantic kernel architecture, components of agents, building your agents using semantic kernel SDKs, built in plugins, creating prompt templates, and using personas in prompts. What will you learn: Attendees will gain a solid understanding of how to use Semantic Kernel to connect with an Azure AI Foundry project, build AI agents using the Semantic Kernel SDKs, and integrate plugin functions into their AI agents. They will also learn how to implement prompt templates and personas within prompts using the Semantic Kernel SDKs. Learn more: 1. https://aka.ms/Intro-SemanticKernel 2. https://aka.ms/AIAgent-SemanticKernel Speaker Bio: Janarthanan Selvaraj is a Microsoft MVP in AI, MCT Community Lead, Microsoft Certified Trainer, Microsoft Learn Expert with expertise in AI, Machine Learning, Data Science and Microsoft Azure technologies. Currently he is working as Senior Specialist & AI Expert at Atos. [Event:25699] https://www.youtube.com/embed/_zYEm3TlLvM 3490 2025-05-07T22:37:32.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/llamacon-2025-conversation-with-mark-zuckerberg-and-satya-nadella Llamacon 2025 - Conversation with Mark Zuckerberg and Satya Nadella https://i.ytimg.com/vi/WaJOONFllLc/maxresdefault.jpg Join us for an insightful afternoon at LlamaCon 2025 as we delve into the latest trends in AI. This session features a compelling discussion between Meta Founder and CEO Mark Zuckerberg and Microsoft Chairman and CEO Satya Nadella. Together, they will explore the cutting-edge developments in AI, from development to deployment, and share strategies on how to excel in today’s competitive environment. https://www.youtube.com/embed/WaJOONFllLc 1911 2025-05-07T22:13:09.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/mcp-vs-api-simplifying-ai-agent-integration-with-external-data MCP vs API: Simplifying AI Agent Integration with External Data https://i.ytimg.com/vi/7j1t3UZA1TY/maxresdefault.jpg Ready to become a certified Solution Implementer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdnPFQ Learn more about API here → https://ibm.biz/BdnPFT MCP or API: Which transforms AI integration? Martin Keen explains how the Model Context Protocol (MCP) revolutionizes AI agents by enabling dynamic discovery, tool execution, and seamless external data retrieval. Discover how MCP simplifies LLM workflows and outpaces traditional APIs. 🚀 AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdnPFw #modelcontextprotocol #api #aiintegration https://www.youtube.com/embed/7j1t3UZA1TY 791 2025-05-05T11:00:12.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/mongodb-mcp-vs-code-demo MongoDB MCP - VS Code Demo https://i.ytimg.com/vi/D9xY_W6l6sg/maxresdefault.jpg Find out more in our announcement blog → https://mdb.link/mcp-D9xY_W6l6sg Sign-up for a free cluster → https://mdb.link/free-D9xY_W6l6sg Subscribe to MongoDB YouTube→ https://mdb.link/subscribe https://www.youtube.com/embed/D9xY_W6l6sg 45 2025-04-30T17:34:53.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/rag-vs-fine-tuning-vs-prompt-engineering-optimizing-ai-models RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models https://i.ytimg.com/vi/zYGDpG-pTho/maxresdefault.jpg Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdndTs Learn more about RAG vs. Fine-Tuning vs. Prompt Engineering here → https://ibm.biz/BdndTi How do AI chatbots deliver better responses? 🤔 Martin Keen explains RAG 🛠️, fine-tuning 🎯, and prompt engineering ✏️—methods that extend knowledge, refine responses, and build domain expertise. Learn how these strategies optimize large language models and improve AI outputs today! 🚀 AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdndTj #retrievalaugmentedgeneration #finetuning #promptengineering https://www.youtube.com/embed/zYGDpG-pTho 790 2025-04-14T11:01:27.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/develop-a-custom-copilot-with-prompt-flow-ai-3016 Develop a custom copilot with Prompt Flow​ AI-3016 https://i.ytimg.com/vi/GoMrEgzmU7c/maxresdefault.jpg Join Peter in this professional training video to learn how to develop a custom copilot using Prompt Flow. You'll explore the components, see how they work, and learn how to use them. Additionally, you'll discover how to integrate Retrieval-Augmented Generation (RAG) into your custom copilot, utilize your own data, and explore content filters. 00:06 - Introduction 00:53 - Use RAG in your custom copilot​ Learn more about this course on Microsoft Learn: https://aka.ms/AI-3016onLearn https://www.youtube.com/embed/GoMrEgzmU7c 3393 2025-04-09T21:00:22.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-to-use-model-context-protocol-mcp-tools-with-net-semantic-kernel How to use Model Context Protocol (MCP) tools with .NET Semantic Kernel https://i.ytimg.com/vi/0GweCrPC3qg/maxresdefault.jpg Authorised Territory code examples - This #ai .NET #tutorial shows how to connect to Model Context Protocol (MCP) with #dotnet Semantic Kernel. Console application is created to convert MCP tools offered by the MCP server to Semantic Kernel plugins. LLM granite3.2 is connected to via Ollama connector for chat service. Finally prompt is written and invoked via Semantic Kernel and later by ChatCompletionAgent. Pre-requisit to re-create the tutorial is having Ollama and Node/npm installed. https://www.youtube.com/embed/0GweCrPC3qg 835 2025-04-07T04:15:00.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/build-remote-mcp-servers-using-azure-functions-in-typescript Build Remote MCP servers using Azure Functions in TypeScript https://i.ytimg.com/vi/U9DsLcP5vEk/maxresdefault.jpg In this video, Dan Wahlin walks through how to create a remote MCP server that plugs into your AI systems and improve functionality. Get started: https://aka.ms/mcp-remote 🔎 Chapters: 00:00 Intro 00:26 Get started 00:45 Demo - TypeScript MCPs with Functions 12:26 Outro 🔗 Links: Repo: https://aka.ms/mcp-remote Blog: https://aka.ms/RemoteMCP 🎙️ Featuring: Dan Wahlin Follow us on social: Blog - https://aka.ms/azuredevelopers/blog Twitter - https://aka.ms/azuredevelopers/twitter LinkedIn - https://aka.ms/azuredevelopers/linkedin Twitch - https://aka.ms/azuredevelopers/twitch #azuredeveloper #azure #typescript https://www.youtube.com/embed/U9DsLcP5vEk 765 2025-04-04T19:27:45.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/enhancing-ai-accuracy-with-graph-rag Enhancing AI Accuracy with Graph RAG https://i.ytimg.com/vi/eNyaZbr7Y_s/maxresdefault.jpg The surge of Large Language Models continues to reshape traditional business processes, offering great promise for automating previously challenging, time-intensive creative activities. But what part of your business can be wrong 20% of the time? The hard truth right now is that accuracy is the Achilles' heel of GenAI. Enter, Graph RAG! While Retrieval-Augmented Generation can improve the integrity of LLM outputs somewhat, it still has difficulty getting over 90%. So, what part of your business can be wrong 10% of the time? Probably not much, which is where Graph comes into the picture. When deployed properly, Graph RAG can crank up accuracy levels to 98, even 99%. Now, we're getting somewhere! In this Briefing Room Webinar hear Bloor Group CEO Eric Kavanagh explain why Graph RAG is the missing link for GenAI. He'll be joined by Philip Rathle, CTO of Neo4j, and Jon Brewton, CEO and Co-Founder of data², who will each give detailed presentations about how Graph RAG delivers much richer, and significantly more accurate outputs from any LLM. They'll explain how your organization can minimize, even eliminate hallucinations, thus opening the door for a wave of AI innovation. https://www.youtube.com/embed/eNyaZbr7Y_s 5370 2025-04-03T15:07:35.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/junior-devs-shouldn-t-use-ai-is-the-ai-discussion-repetitive Junior Devs Shouldn’t Use AI + Is the AI Discussion Repetitive? https://i.ytimg.com/vi/r6RDOgL69zE/maxresdefault.jpg In this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson get real about the current state of AI in software development. They talk about what’s working, what’s frustrating, and why so much of the conversation around AI feels repetitive or disconnected from reality. They explore how AI is actually being used day to day—and where it still falls short. They also discuss the risks of relying too heavily on AI, especially for junior devs, and why understanding fundamentals still matters. Keypoints from this episode: - AI fatigue is setting in among developers, with many eager to move beyond hype and explore tools that solve real problems and deliver everyday value. - Danny built a conversational AI agent named Nexie, trained specifically on Next.js and Vercel documentation, showing how personalized agents can provide focused, meaningful assistance. - Over-relying on AI can backfire for junior developers. Using it to generate code without understanding the underlying logic undermines learning and growth. - AI tools are starting to shift how we think about software quality. In some cases, speed and cost-effectiveness may outweigh traditional goals like maintainability. Chapters 00:00 – Should Juniors Use AI? 01:04 – Real Talk on AI Conferences 03:00 – Building Nexi: A Personal Dev Agent 05:13 – Beyond the Hype: Finding Real AI Use Cases 09:36 – Why Senior Devs Struggle with AI Tools 15:55 – Mentorship, Theory, and Learning the Right Way 21:10 – When to Use AI (and When Not To) 26:50 – The Growing Gap in Dev Skills 30:31 – AI Is Redefining “Good Software” 32:09 – Final Thoughts + Where to Find Us Follow This Dot Media on Twitter/X: x.com/thisdotmedia Sponsored by This Dot: thisdotlabs.com https://www.youtube.com/embed/r6RDOgL69zE 2021 2025-04-02T17:34:05.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/explore-no-code-graphrag-agents-in-10-minutes-on-your-own-data Explore No-Code GraphRAG Agents in 10 Minutes on Your Own Data https://i.ytimg.com/vi/0LJuGTsgTgw/maxresdefault.jpg Want to see how GenAI, RAG, and knowledge graphs actually come together—with zero coding required? This video is your starting point. Neo4j Solutions Engineer Chris Booth walks you through the LLM Knowledge Graph Builder—a reference application that enables non-technical users to explore how their own data can power GraphRAG. ✅ No-code interface ✅ Bring your own documents ✅ Build a working prototype in under 10 minutes ✅ See how explainable AI works with GraphRAG ✅ Visualize answers and the reasoning behind them 🔗 Try it yourself: hhtps://llm-graph-builder.neo4jlabs.com 🔗 Start your free Neo4j instance: https://console.neo4j.io/ 🔗 Learn more about Graphs, AI & Agents: https://bit.ly/3YgB1wh https://www.youtube.com/embed/0LJuGTsgTgw 650 2025-04-02T14:17:33.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/using-genai-on-your-code-what-could-possibly-go-wrong Using GenAI on your code, what could possibly go wrong? - https://i.ytimg.com/vi/krDJlrw5mM0/maxresdefault.jpg This talk was recorded at NDC Security in Oslo, Norway. #ndcsecurity #ndcconferences #security #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndc-security.com/ Subscribe to our YouTube channel and learn every day: @NDC Follow our Social Media! https://www.facebook.com/ndcconferences https://twitter.com/NDC_Conferences https://www.instagram.com/ndc_conferences #artificialintelligence #machinelearning #ai #ml #genai #security #application #apps With GenAI, developers are shifting from traditional code reuse to generating new code snippets by prompting GenAI, leading to a significant change in the ways software gets developed. Several academic studies show that AI generated code based on LLM's that are trained on vulnerable OSS implementations lead to vulnerable generated code. Another study showed that developers tend to trust GenAI created code more than human created code. Combining that with the higher code velocity it will result in more vulnerabilities in it's output. Using an AI system that runs an LLM also has additional risks tied to it, related to jailbreaks, data poisoning and malicious agents, recursive learning and IP infringements. In this presentation, we will examine real-world data from several academic studies to understand how GenAI is changing software security, the risks it introduces, and possible strategies to address these emerging issues. https://www.youtube.com/embed/krDJlrw5mM0 3066 2025-03-25T09:13:21.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-magic-of-llm-distillation-rishabh-agarwal-google-deepmind The Magic of LLM Distillation — Rishabh Agarwal, Google DeepMind https://i.ytimg.com/vi/O1AR4iL30mg/sddefault.jpg Slides: https://drive.google.com/file/d/1xMohjQcTmQuUd_OiZ3hB1r47WB1WM3Am/view https://x.com/jxmnop/status/1877761437931581798 - the screenshot thumbnail https://www.youtube.com/embed/O1AR4iL30mg 2802 2025-03-23T23:03:27.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/langsmith-studio-an-ide-for-visualizing-and-debugging-agents LangSmith Studio: An IDE for visualizing and debugging agents https://i.ytimg.com/vi/T9qYg_WFfQo/maxresdefault.jpg Note: LangGraph Platform is now LangSmith Deployment. LangGraph Studio is now LangSmith Studio. LangSmith consists of several components that work together to support the development, deployment, debugging, and monitoring of LangGraph applications. LangSmith Studio is a central components of this and is a specialized IDE to enable visualization, interaction, and debugging of LangGraph applications. Here, we explain how Studio works and review a few common usage patterns, such as threads, assistants, and debugging with LangSmith. Docs: https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/ Video notes: https://mirror-feeling-d80.notion.site/Tour-of-LangGraph-Studio-1bd808527b17807eb995da7fe824a281?pvs=4 Chapters: 00:00 - Introduction to LangSmith Studio 00:21 - Demo: Local Deep Researcher in Studio 00:56 - Understanding Graph Execution in Real-time 01:17 - LangSmith Deployment Components Overview 02:07 - Memory in LangSmith Deployment 02:35 - Studio's Role in the Platform 03:00 - Application Structure Requirements 03:25 - Configuration File Overview 04:05 - Application Structure Components 04:46 - Running LangSmith Deployment Locally 05:19 - Using uvx for Environment Management 05:55 - Launching the Local Development Server 06:17 - Exploring API Documentation 06:42 - Studio UI Introduction 07:07 - Graph Visualization and Node Mapping 07:55 - Understanding Input and State Management 08:46 - Running a Graph in Studio 09:17 - State Updates During Execution 09:58 - Thread Management and History 10:46 - Memory Button and LangGraph Store 11:14 - LangSmith Integration 11:33 - Thread View in LangSmith 12:10 - Assistant Configurations Management 12:44 - Creating New Assistants 13:27 - Configuration Settings Customization 14:00 - Studio Features Recap 14:48 - Conclusion https://www.youtube.com/embed/T9qYg_WFfQo 916 2025-03-22T14:55:45.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/yann-lecun-mathematical-obstacles-on-the-way-to-human-level-ai Yann LeCun "Mathematical Obstacles on the Way to Human-Level AI" https://i.ytimg.com/vi/ETZfkkv6V7Y/maxresdefault.jpg Yann LeCun, Meta, gives the AMS Josiah Willard Gibbs Lecture at the 2025 Joint Mathematics Meetings on “Mathematical Obstacles on the Way to Human-Level AI.” This talk was introduced by Bryna Kra, Northwestern University, President of the AMS. https://www.youtube.com/embed/ETZfkkv6V7Y 3383 2025-03-21T14:39:54.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/booking-com-personalizes-travel-at-scale-with-ai-powered-experiences Booking.com personalizes travel at scale with AI-powered experiences https://i.ytimg.com/vi/yUVL76cGXA4/maxresdefault.jpg What happens when one of the world’s largest travel platforms meets the world’s most powerful AI models? A new era of intent-driven travel. Booking.com worked closely with OpenAI to build and launch an AI Trip Planner in just 10 weeks, helping travelers discover new places, plan smarter itineraries, and get real-time answers to their most specific questions. They've since expanded use of OpenAI’s models across Smart Filters, Property Q&A, and review summarization - making the travel experience more conversational, contextual, and efficient for millions of users. Read the full story at https://openai.com/index/booking-com/ https://www.youtube.com/embed/yUVL76cGXA4 161 2025-03-21T06:00:43.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/day-5-livestream-5-day-gen-ai-intensive-course-kaggle DAY 5 Livestream - 5-Day Gen AI Intensive Course | Kaggle https://i.ytimg.com/vi/eZ-8UQ_t4YM/maxresdefault.jpg Day 5: MLOps for Generative AI ​​Kaggle Discord Server: http://discord.gg/kaggle. Complete Unit 5 - “MLOps for Generative AI”: 1. Listen to the summary podcast episode (https://www.youtube.com/watch?v=Hbk8UXavHrk&list=PLqFaTIg4myu_yKJpvF8WE2JfaG5kGuvoE&index=7) for this unit. 2. To complement the podcast, read the “MLOps for Generative AI” whitepaper https://www.kaggle.com/whitepaper-operationalizing-generative-ai-on-vertex-ai-using-mlops 3. No codelab for today! During the livestream tomorrow, we will do a code walkthrough and live demo of goo.gle/agent-starter-pack (https://goo.gle/e2e-gen-ai-app-starter-pack), a resource created for making MLOps for Gen AI easier and accelerating the path to production. Please go through the repository (https://goo.gle/e2e-gen-ai-app-starter-pack) in advance. 4. Want to have an interactive conversation (https://support.google.com/notebooklm/answer/15731776?hl=en&ref_topic=14272601&sjid=16012842710481496794-EU)? Try adding the whitepaper to NotebookLM https://notebooklm.google.com/?original_referer=https:%2F%2Fwww.google.com%23&pli=1 SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_confirmation=1&utm_medium=youtube&utm_source=channel&utm_campaign=yt-sub About Kaggle: Kaggle is the world's largest community of data scientists. Join us to compete, collaborate, learn, and do your data science work. Kaggle's platform is the fastest way to get started on a new data science project. Spin up a Jupyter notebook with a single click. Build with our huge repository of free code and data. Stumped? Ask the friendly Kaggle community for help. Follow Kaggle online: Visit the WEBSITE: http://www.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-kg Like Kaggle on FACEBOOK: http://www.facebook.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-fb Follow Kaggle on TWITTER: http://twitter.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-tw Check out our BLOG: http://blog.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-bl https://www.youtube.com/embed/eZ-8UQ_t4YM 3641 2025-03-20T20:13:12.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/emil-eifrem-at-humanx Emil Eifrem at HumanX https://i.ytimg.com/vi/P2bV0OhSsdU/maxresdefault.jpg How did Klarna replace 1,200 SaaS tools, eliminate Salesforce & Workday, and transform operations with AI & Knowledge Graphs & Retrieval-Augmented Generation (GraphRAG)? Emil Eifrem reveals the blueprint behind Klarna’s transformation and how any enterprise can apply the same strategy to cut costs, boost efficiency, and build an AI-driven future -- reshaping business and powering intelligent systems that outperform traditional software. More about this case: https://bit.ly/4bIHOVh #Neo4j #KnowledgeGraphs #GraphRAG #AI https://www.youtube.com/embed/P2bV0OhSsdU 1431 2025-03-20T11:10:28.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/keynote-the-past-present-and-future-of-ai-for-application-developers-steve-sanderson Keynote: The past, present, and future of AI for application developers - Steve Sanderson https://i.ytimg.com/vi/awztkr8n0AA/maxresdefault.jpg This talk was recorded at NDC London in London, England. #ndclondon #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndclondon.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.facebook.com/ndcconferences https://twitter.com/NDC_Conferences https://www.instagram.com/ndc_conferences/ #ai #ui So we all know AI is changing the software industry right now. Whether you build backend systems, web or native UIs, or embedded devices, you keep hearing it: the next generation of users will simply expect your software to carry out their tasks intelligently. Let's start with how we got here. I'll demo AI systems from the 1960s primordial soup up to the emergence of large language models (LLMs). We'll see a GPT-2 implementation in C code, and train it from scratch on nothing but NDC talks (what will it say??). We'll then build up to modern chat/assistant/agent systems. The point of this is to give you a deep intuition for the capabilities and limitations of LLM-based systems. This sets the scene for present-day app development. We'll run through practical examples of intelligent features you could add to your products today, coding up features like automatic data cleaning, sentiment scoring, anomaly detection, and the use of vision. Finally we'll consider what this means for the future: will the concept of UIs eventually be obsolete, or can it be reinvented to be much more fluid and intelligent? Let's see what we can do... https://www.youtube.com/embed/awztkr8n0AA 3466 2025-03-20T10:01:04.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/chinese-ai-pioneer-questions-openai-s-sustainability Chinese AI Pioneer Questions OpenAI's Sustainability https://i.ytimg.com/vi/_CCewc-mn9c/maxresdefault.jpg Chinese entrepreneur and AI pioneer Kai-Fu Lee says he questions the sustainability of OpenAI, and discusses the impact of DeepSeek on global AI development. The former Google executive also gives his top AI picks on Bloomberg Television. -------- More on Bloomberg Television and Markets Like this video? Subscribe and turn on notifications so you don't miss any videos from Bloomberg Markets & Finance: https://tinyurl.com/ysu5b8a9 Visit http://www.bloomberg.com for business news & analysis, up-to-the-minute market data, features, profiles and more. Connect with Bloomberg Television on: X: https://twitter.com/BloombergTV Facebook: https://www.facebook.com/BloombergTelevision Instagram: https://www.instagram.com/bloombergtv/ Connect with Bloomberg Business on: X: https://twitter.com/business Facebook: https://www.facebook.com/bloombergbusiness Instagram: https://www.instagram.com/bloombergbusiness/ TikTok: https://www.tiktok.com/@bloombergbusiness?lang=en Reddit: https://www.reddit.com/r/bloomberg/ LinkedIn: https://www.linkedin.com/company/bloomberg-news/ More from Bloomberg: Bloomberg Radio: https://twitter.com/BloombergRadio Bloomberg Surveillance: https://twitter.com/bsurveillance Bloomberg Politics: https://twitter.com/bpolitics Bloomberg Originals: https://twitter.com/bbgoriginals Watch more on YouTube: Bloomberg Technology: https://www.youtube.com/@BloombergTech Bloomberg Originals: https://www.youtube.com/@business Bloomberg Quicktake: https://www.youtube.com/@Bloomberg-News Bloomberg Espanol: https://www.youtube.com/@bloomberg_espanol Bloomberg Podcasts: https://www.youtube.com/@BloombergPodcasts https://www.youtube.com/embed/_CCewc-mn9c 718 2025-03-20T05:23:48.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/why-can-t-ai-make-its-own-discoveries-with-yann-lecun Why Can't AI Make Its Own Discoveries? — With Yann LeCun https://i.ytimg.com/vi/qvNCVYkHKfg/maxresdefault.jpg Yann LeCun is the chief AI scientist at Meta. He joins Big Technology Podcast to discuss the strengths and limitations of current AI models, weighing in on why they've been unable to invent new things despite possessing almost all the world's written knowledge. LeCun digs deep into AI science, explaining why AI systems must build an abstract knowledge of the way the world operates to truly advance. We also cover whether AI research will hit a wall, whether investors in AI will be disappointed, and the value of open source after DeepSeek. Tune in for a fascinating conversation with one of the world's leading AI pioneers. Chapters: 00:00 Introduction to Jan LeCun and AI's limitations 01:12 Why LLMs can't make scientific discoveries 05:40 Reasoning in AI systems: limitations of chain of thought 10:13 LLMs approaching diminishing returns and the need for a new paradigm 16:29 "A PhD next to you" vs. actual intelligent systems 21:36 Consumer AI adoption vs. enterprise implementation challenges 25:37 Historical parallels: expert systems and the risk of another AI winter 29:37 Four critical capabilities AI needs for true understanding 33:19 Testing AI's physics understanding with the paper test 37:24 Why video generation systems don't equal real comprehension 43:33 Self-supervised learning and its limitations for understanding 51:10 JEPA: Building abstract representations for reasoning and planning 54:33 Open source vs. proprietary AI development 58:57 Conclusion https://www.youtube.com/embed/qvNCVYkHKfg 3563 2025-03-19T19:42:21.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/what-are-agents What are Agents? https://i.ytimg.com/vi/wiEXRtJU-3o/maxresdefault.jpg Curious about agents and how they can revolutionize your business processes? In this video, we'll explore what makes up an agent, where to build them and which agents can help you streamline your operations. Click the link to find out more: https://aka.ms/trycopilotstudio #Microsoft #Microsoft365copilot #Agents #CopilotChat #CopilotStudio #PowerPlatform https://www.youtube.com/embed/wiEXRtJU-3o 196 2025-03-19T19:04:44.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-to-build-an-ai-agent-with-semantic-kernel-mongodb-atlas-c-and-openai How to Build an AI Agent with Semantic Kernel, MongoDB Atlas, C# and OpenAI https://i.ytimg.com/vi/lvQ-EC5afIA/maxresdefault.jpg There’s a new MongoDB YouTube channel dedicated to developers. Click the link to find new tutorials and resources to help you learn the MongoDB data platform: https://www.youtube.com/@MongoDBDevelopers If you prefer to follow a written tutorial, it can be found here: https://mdb.link/lvQ-EC5afIA-tutorial Code Snippets: https://gist.github.com/LuceCarter/2efd3ae606da16aed1916ace5ef88595 Subscribe to MongoDB YouTube→ https://mdb.link/subscribe Have you ever wanted to write an AI Agent with Semantic Kernel? Join Developer Advocate Luce Carter in this tutorial to create a food agent to help you decide if you can cook tonight or should just go to a restaurant! Watch Getting Started with Microsoft Semantic Kernel with MongoDB Atlas in C# → https://youtu.be/qXswaD4IGUU?si=FacxfJK8PBYmtt3y Microsoft Learn Course: https://learn.microsoft.com/en-gb/training/paths/develop-ai-agents-azure-open-ai-semantic-kernel-sdk/%7C Vector Search Index Documentation: https://mdb.link/lvQ-EC5afIA-doc Visit Mongodb.com → https://www.mongodb.com Read the MongoDB Blog → https://www.mongodb.com/blog Check out the MongoDB Developer Center → https://www.mongodb.com/developer https://www.youtube.com/embed/lvQ-EC5afIA 1382 2025-03-19T12:01:13.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/npm-install-agents-with-sunil-pai-and-rita-kozlov-vp-ai-of-cloudflare npm install Agents — with Sunil Pai and Rita Kozlov (VP AI) of Cloudflare https://i.ytimg.com/vi/8W_9lUYGa2U/maxresdefault.jpg https://blog.cloudflare.com/build-ai-agents-on-cloudflare/ https://github.com/cloudflare/agents/ https://github.com/cloudflare/agents-starter https://www.youtube.com/embed/8W_9lUYGa2U 2136 2025-03-19T01:15:54.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/get-data-into-databricks-generative-ai-databricks-apps Get Data Into Databricks - Generative AI Databricks Apps https://i.ytimg.com/vi/OGD6PPothpk/maxresdefault.jpg Try Databricks today: https://dbricks.co/3EAWLK6. Description: Introducing Databricks Apps: A fast and secure solution for building and deploying web applications directly within Databricks. Enjoy effortless app development with built-in infrastructure and robust data security. Seamlessly integrate with the Databricks Data Intelligence Platform, including Databricks SQL, Model Serving and Unity Catalog. Focus on creating cutting-edge Generative AI applications with ease. https://www.youtube.com/embed/OGD6PPothpk 398 2025-03-18T23:16:18.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/build-rag-from-scratch-phil-nash-ndc-london-2025 Build RAG from Scratch - Phil Nash - NDC London 2025 https://i.ytimg.com/vi/cwxH9cxW-wQ/maxresdefault.jpg This talk was recorded at NDC London in London, England. #ndclondon #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndclondon.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.facebook.com/ndcconferences https://twitter.com/NDC_Conferences https://www.instagram.com/ndc_conferences/ #ai #javascript Retrieval augmented generation (RAG) provides large language models with up to date information and helps them hallucinate less. But how does it all work beneath the covers? In this live coding session we'll build the components of a RAG system from scratch. (Aside from the LLM, there probably isn't time for that!) By building our own, we'll understand vectorisation, similarity search, and the role of embedding models and vector databases. We'll then plug it all together to see our augmented bot in action. You'll get a good grounding in the components of successful chatbots and why they work. https://www.youtube.com/embed/cwxH9cxW-wQ 3190 2025-03-18T14:30:46.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/digital-twins-cbs-presented-by-olivier-toubia Digital Twins @ CBS presented by Olivier Toubia https://i.ytimg.com/vi/jL7Av0hI5mA/maxresdefault.jpg AI in Business: Cutting-Edge Research and Real-World Impact, Columbia AI Summit satellite workshop at Columbia Business School AI is transforming the way businesses operate, compete, and innovate. This session showcases cutting-edge research from Columbia University faculty, exploring how AI is driving decision-making, shaping strategy, and redefining industries. Join us for insights into the opportunities and challenges of AI in business, backed by the latest academic research and real-world applications. https://www.youtube.com/embed/jL7Av0hI5mA 735 2025-03-18T14:28:32.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/github-copilot-for-azure-deploy-an-ai-rag-app-to-aca-using-azd GitHub Copilot for Azure: Deploy an AI RAG App to ACA using AZD https://i.ytimg.com/vi/jX1fa9r5gqE/maxresdefault.jpg Learn how GitHub Copilot for Azure can guide you through the process of finding and deploying an AI RAG application to an Azure Container Apps using azd. Resources: To get started, download and install the GitHub Copilot extension from: https://aka.ms/GetGitHubCopilotForAzure Azure Container Apps: https://learn.microsoft.com/azure/container-apps/ Serverless LlamaIndex: https://learn.microsoft.com/azure/developer/javascript/ai/get-started-app-chat-template-llamaindex?tabs=github-codespaces https://www.youtube.com/embed/jX1fa9r5gqE 164 2025-03-17T20:42:46.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/noam-shazeer-and-jack-rae-scaling-test-time-compute-reactions-to-ilya-agi Noam Shazeer and Jack Rae: Scaling Test-time Compute, Reactions to Ilya & AGI https://i.ytimg.com/vi/atMRWzgHEGg/maxresdefault.jpg On the latest episode of Unsupervised Learning, Jacob is joined by two of the most influential minds in AI today. 🔹 Noam Shazeer, co-inventor of the Transformer 🔹 Jack Rae, Research Director at DeepMind and one of the leads behind Gemini’s Flash Thinking We got to ask them all of the top-of-mind questions in AI today about where we are, where we’re headed and what it means for businesses and the world. Some key take-aways: 0:00 Intro 2:07 Exploring Gemini 2.0 4:41 Challenges with Evals and Benchmarks 6:51 Reinforcement Loops and AI Productivity 8:52 Agentic Coding and AI in Development 13:39 Multimodal Capabilities and Applications 15:58 Future of AI: Complexity and Reliability 19:39 Test Time Compute and Data Efficiency 31:57 AI Research Culture and Breakthroughs 39:36 Reflecting on Large Language Models 40:14 The Rise of Vision-Based Models 41:38 Native Image Generation and General Purpose Models 42:12 AI in Healthcare and Specialized Models 44:09 Shifting Timelines and Rapid Adoption 47:25 Open Source Models and Competitive Edge 50:07 AI's Impact on Education and Personal Lives 55:47 AGI Risks and Safety Considerations 58:10 Future of AI Companions 1:02:54 Quickfire With your co-hosts:  @jacobeffron  - Partner at Redpoint, Former PM Flatiron Health  @patrickachase  - Partner at Redpoint, Former ML Engineer LinkedIn  @ericabrescia  - Former COO Github, Founder Bitnami (acq’d by VMWare)  @jordan_segall  - Partner at Redpoint https://www.youtube.com/embed/atMRWzgHEGg 4224 2025-03-17T15:36:18.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/rag-vs-cag-solving-knowledge-gaps-in-ai-models RAG vs. CAG: Solving Knowledge Gaps in AI Models https://i.ytimg.com/vi/HdafI0t3sEY/maxresdefault.jpg Ready to become a certified watsonx Generative AI Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdGtmQ Learn more about RAG here → https://ibm.biz/BdGtm3 What if your AI can't answer who won the Oscars last year? 🎥 Martin Keen explains how RAG (Retrieval-Augmented Generation) and CAG (Cache-Augmented Generation) address knowledge gaps in AI. 🚀 Discover their strengths in real-time retrieval, scalability, and efficient workflows for smarter AI systems. 💻 AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdGtmw #retrievalaugmentedgeneration #aiworkflow #machinelearning https://www.youtube.com/embed/HdafI0t3sEY 960 2025-03-17T11:00:31.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/creating-agents-with-the-teams-toolkit Creating agents with the Teams Toolkit https://i.ytimg.com/vi/d6qaUS8UIAY/sddefault.jpg 📺 Learn how to create agents using the Teams Toolkit! This demo explores leveraging the Teams Toolkit to build intelligent agents integrated with Microsoft 365 Copilot, enhancing collaboration and productivity. 📽️ This demo is from the Microsoft 365 & Power Platform community call on December 19, 2024 - https://www.youtube.com/watch?v=orvZcU1Zfn4 ✨ Presenter: • Nico De Cleyre (ConXioN) - https://www.linkedin.com/in/nicodecleyre/ 📅 Access the resources: • Microsoft 365 Copilot Extensibility Overview - https://learn.microsoft.com/en-us/microsoft-365-copilot/extensibility/ • Copilot Developer Camp - https://microsoft.github.io/copilot-camp/ • Teams Toolkit - https://marketplace.visualstudio.com/items?itemName=TeamsDevApp.ms-teams-vscode-extension 👋 Do you have something exciting to share with the Microsoft 365 & Power Platform community? Volunteer to present in our next community call demo at https://aka.ms/community/request/demo. 💡 Learn more about the Microsoft 365 & Power Platform community: • Microsoft 365 & Power Platform Unified Sample gallery - https://aka.ms/community/samples • Microsoft Community Learning on YouTube - https://aka.ms/community/videos • Microsoft 365 & Power Platform - https://aka.ms/community/home Sharing is caring! You are awesome! 🧡 #Microsoft365Dev #Agent #MicrosoftTeams #Copilot https://www.youtube.com/embed/d6qaUS8UIAY 1170 2025-03-17T08:00:36.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/codeconcise-a-new-era-for-legacy-modernization-rachel-laycock-yow-2024 CodeConcise: A New Era for Legacy Modernization • Rachel Laycock • YOW! 2024 https://i.ytimg.com/vi/Qdits--aoT4/maxresdefault.jpg This presentation was recorded at YOW! Australia 2024. #GOTOcon #YOW https://yowcon.com Rachel Laycock - Chief Technology Officer at Thoughtworks RESOURCES https://twitter.com/rachellaycock https://www.linkedin.com/in/rachellaycock https://github.com/caek ABSTRACT So far, most attention to GenAI in software development is on generating code. But there is as much, if not more, value in understanding existing code - particularly long-lived, large, and complex legacy systems. At Thoughtworks we have been experimenting with using this technology with our clients, embodied in a tool called CodeConcise, which combines an LLM with a knowledge graph derived from the abstract syntax trees of a codebase. We have found this useful both to draw out low-level requirements and to build a high-level explanation of a system. This talk will show what we have learned and how it could change the age old challenge of wrangling legacy at speed, iteratively and with zero downtime. [...] TIMECODES 00:00 Intro 01:30 Legacy modernization is hard 02:09 Why is it hard? 07:23 What's GenAI got to do with it? 17:53 Understanding code 29:23 Demo 31:08 Outcomes of approach 33:34 Conclusion 34:53 Outlook 37:03 Outro Download slides and read the full abstract here: https://yowcon.com/brisbane-2024/sessions/3484 RECOMMENDED BOOKS Martin Fowler • Refactoring • https://amzn.to/3n7GAhk Martin Fowler • Domain-Specific Languages • https://amzn.to/3n14HOO Jez Humble & Dave Farley • Continuous Delivery • https://amzn.to/3ocIHwd Henney & Monson-Haefel • 97 Things Every Software Architect Should Know • https://amzn.to/3pZuHsQ https://bsky.app/profile/gotocon.com https://twitter.com/GOTOcon https://www.linkedin.com/company/goto- https://www.instagram.com/goto_con https://www.facebook.com/GOTOConferences #Legacy #LegacyModernization #LegacyCode #GenAI #LegacyTech #TechRadar #CodeConciseSolutionModel #CodeConcise #RAG #LLM #Thoughtworks #Programing #SoftwareEngineering #RachelLaycock CHANNEL MEMBERSHIP BONUS Join this channel to get early access to https://www.youtube.com/embed/Qdits--aoT4 2235 2025-03-16T13:00:37.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/mcp-protocol-explained-for-traders-connect-your-trading-platform-to-ai MCP Protocol Explained for Traders: Connect Your Trading Platform to AI https://i.ytimg.com/vi/iMuE31nbOM8/sddefault.jpg Ever wanted your AI to understand the language of trading? Model Context Protocol (MCP) is making that a reality! In this video, I'll break down what MCP is in simple terms, even if you're not a tech whiz. Python Live Mentorship Program for Traders : https://learn.marketcalls.in/courses/QuantFlow-10---Code-the-Markets-6790ea9dea360e1293a62e27 I'll show you a practical example using Claude Desktop and OpenAlgo, demonstrating how you can: Get real-time stock prices directly within your AI chatbot. Place orders (e.g., "Buy 100 shares of Zomato") using natural language. Request data in specific formats (e.g., "Put the stock prices in a table"). MCP is Client and Server Architecture. We'll also peek behind the scenes at: The basic client-server architecture of MCP. The Python helper code that makes it all work. How to configure the claude_desktop_config.json file to connect Claude to your trading platform (OpenAlgo, in this example). Why should traders care? MCP opens up exciting possibilities for: Streamlined trading workflows: Get information and execute trades without switching between apps. Custom AI-powered tools: Imagine creating your own trading assistant tailored to your specific strategies. Faster decision-making: Access real-time data and insights directly through your AI interface. Resources: Full Python Code & JSON Config: Get the complete code and configuration setup from my blog: https://www.marketcalls.in/claude/model-context-protocol-mcp-explained-in-simple-terms-to-traders.html Chapters: 00:00 Introduction to Model Context Protocol 00:06 Demo with Claude Desktop & OpenAlgo 01:37 Peeking behind the screens to understand the code 03:03 MCP Introduction from Anthropic 03:25 MCP - An Open Protocol for AI Applications 04:05 MCP Architecture Tags: #MCP #ModelContextProtocol #Anthropic #Claude #OpenAlgo #AITrading #AlgorithmicTrading #PythonTrading #TradingAutomation #FinTech #LargeLanguageModels #LLM #StockMarket #TradingTools #AI https://www.youtube.com/embed/iMuE31nbOM8 516 2025-03-15T08:46:27.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/stop-gluing-search-systems-together-vector-text-filters-in-one-pass Stop Gluing Search Systems Together. Vector + Text + Filters in one Pass. https://i.ytimg.com/vi/lzdheBfvHig/maxresdefault.jpg Modern search is broken. There are too many pieces that are glued together. - Vector databases for semantic search - Text engines for keywords - Rerankers to fix the results - LLMs to understand queries - Metadata filters for precision Each piece works well alone. Together, they often become a mess. When you glue these systems together, you create: - **Data Consistency Gaps** Your vector store knows about documents your text engine doesn't. Which is right? - **Timing Mismatches** New content appears in one system before another. Users see different results depending on which path their query takes. - **Complexity Explosion** Every new component doubles your integration points. Three components means three connections. Five means ten. - **Performance Bottlenecks** Each hop between systems adds latency. A 200ms search becomes 800ms after passing through four components. - **Brittle Chains** When one system fails, your entire search breaks. More pieces mean more breaking points. I recently built a system where we had query specific post-filters but the requirement to deliver a fixed number of results to the user. A lot of times, the query had to be run multiple times to achieve the desired amount. So we had an unpredictable latency. A high load on the backend, where some queries hammered the database 10+ times. A relevance cliff, where results 1-6 look great, but the later ones were poor matches. Today on How AI Is Built, we are talking to Marek Galovic from TopK. We talk about how they built a new search database with modern components. "How would search work if we built it today?” Cloud storage is cheap. Compute is fast. Memory is plentiful. One system that handles vectors, text, and filters together - not three systems duct-taped into one. One pass handles everything: ``` Vector search + Text search + Filters → Single sorted result ``` Built with hand-optimized Rust kernels for both x86 and ARM, the system scales to 100M documents with 200ms P99 latency. The goal is to do search in 5 lines https://www.youtube.com/embed/lzdheBfvHig 3209 2025-03-13T11:30:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/palantir-ceo-alexander-karp-with-andrew-ross-sorkin-the-technological-republic Palantir CEO Alexander Karp with Andrew Ross Sorkin: The Technological Republic https://i.ytimg.com/vi/jUK-VYCh5go/maxresdefault.jpg Join Palantir CEO Alexander Karp with New York Times DealBook creator Andrew Ross Sorkin on the promises and peril of Silicon Valley, tech’s changing relationship with Washington, and what it means for our future — and his new book, The Technological Republic. Named “Best CEO of 2024” by The Economist, Alexander Karp is a vital player in Silicon Valley as the CEO of Palantir — and he’s concerned that the drift of American tech has led the country astray. When did marketing algorithms overtake intellectual ambition? How can Silicon Valley get back to its roots of offering us world-changing technologies and solutions to our society’s most pressing issues? Offering a stark warning about Silicon Valley’s evolving relationship to power and society, in The Technological Republic Karp issues a rallying cry on the intersection of technology, government, and innovation. Hear him and Sorkin discuss the new threats to American progress, tech’s changing role in our culture, how we can renew technological ambition in service of democratic values, and more. Recorded Feb 18, 2025 at 92nd Street Y, New York. Your support helps us continue creating online content for our community. Donate now: http://www.92NY.org/Donate Facebook: facebook.com/92ndStreetY Instagram: Instagram.com/92ndStreetY TikTok: tiktok.com/@92ndstreety Archives: 92ny.org/archives https://www.youtube.com/embed/jUK-VYCh5go 3927 2025-03-12T14:13:46.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/self-host-a-local-ai-platform-ollama-open-webui Self-Host a local AI platform! Ollama + Open WebUI https://i.ytimg.com/vi/RQFfK7xIL28/maxresdefault.jpg Check out Twingate and supercharge your security: https://bit.ly/3Y1OaZi In this video, I'll show you my new self-hosted AI platform deployed in my HomeLab using the free and open-source Ollama platform. I'll walk you through setting up OpenWebUI for an easy-to-use web interface with advanced features even ChatGPT might envy—and securing it with Traefik and Authentik. Plus, I’ll share some valuable tips to avoid common pitfalls when building your own local AI server. References - Ollama GPU Requirements: https://github.com/ollama/ollama/blob/main/docs/gpu.md -AMD ROCm: https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/native_linux/install-radeon.html Learn more - Traefik: https://www.patreon.com/posts/114924172 - Authentik: https://www.patreon.com/posts/100779796 ________________ 💜 Support me and become a Fan! → https://www.youtube.com/channel/UCZNhwA1B5YqiY1nLzmM0ZRg/join 💬 Join our Community! → https://christianlempa.de/discord 👉 Follow me everywhere → https://christianlempa.de ________________ Read my Tech Documentation https://christianlempa.de/docs My Gear and Equipment https://christianlempa.de/kit ________________ Timestamps: 00:00 Introduction 02:38 Hardware Requirements 06:58 Software Planning 08:35 Problems with Proxmox… 10:55 Installing a new LXC Container 14:44 Install Ollama on Linux 17:41 Ollama basics 19:56 Install OpenWeb UI 27:37 OpenWebUI basics 31:05 Using AI models 35:01 Web Searching 37:18 Why I still don’t trust AI ________________ Links can include affiliate links. https://www.youtube.com/embed/RQFfK7xIL28 2347 2025-03-11T15:00:38.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-future-of-u-s-ai-leadership-with-ceo-of-anthropic-dario-amodei The Future of U.S. AI Leadership with CEO of Anthropic Dario Amodei https://i.ytimg.com/vi/esCSpbDPJik/maxresdefault.jpg Anthropic Chief Executive Officer and Cofounder Dario Amodei discusses the future of U.S. AI leadership, the role of innovation in an era of strategic competition, and the outlook for frontier model development. The CEO Speaker series is a unique forum for leading global CEOs to share their insights on issues at the center of commerce and foreign policy, and to discuss the changing role of business globally. Subscribe to our channel: https://goo.gl/WCYsH7 This work represents the views and opinions solely of the author. The Council on Foreign Relations is an independent, nonpartisan membership organization, think tank, and publisher, and takes no institutional positions on matters of policy. Visit the CFR website: http://www.cfr.org Follow CFR on Twitter: http://www.twitter.com/cfr_org Follow CFR on Facebook: https://www.facebook.com/councilonforeignrelations/ https://www.youtube.com/embed/esCSpbDPJik 3755 2025-03-11T11:44:29.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/transformers-need-glasses-federico-barbero Transformers Need Glasses! [Federico Barbero] https://i.ytimg.com/vi/FAspMnu4Rt0/maxresdefault.jpg SPONSOR MESSAGES: *** CentML offers competitive pricing for GenAI model deployment, with flexible options to suit a wide range of models, from small to large-scale deployments. Check out their super fast DeepSeek R1 hosting! https://centml.ai/pricing/ Federico Barbero (DeepMind/Oxford) is the lead author of 'Transformers Need Glasses!', a paper revealing fundamental architectural limitations in transformer-based language models. The conversation explores why LLMs fail at seemingly trivial tasks like copying the last token of a sequence or counting repeated elements, tracing these failures to representation collapse — where internal representations of distinct inputs converge below machine precision as context length grows. Federico connects these findings to information propagation theory from graph neural networks, showing how causal attention creates an inherent bias toward the start of a sequence, while training dynamics push models to attend to the most recent tokens, leaving the middle of long contexts as a blind spot. The discussion covers connections to spectral graph theory, heat equations on graphs, Petar Veličković's work on graph attention networks, the role of softmax in limiting sharp attention, and practical 'glasses' — architectural tweaks that can help transformers see more clearly. --- REFERENCES: paper: [00:01:05] Transformers Need Glasses! https://proceedings.neurips.cc/paper_files/paper/2024/file/b1d35561c4a4a0e0b6012b2af531e149-Paper-Conference.pdf [00:05:30] Softmax is Not Enough https://arxiv.org/abs/2410.01104 [00:15:05] Graph Attention Networks https://arxiv.org/abs/1710.10903 [00:43:23] Neural Networks and the Chomsky Hierarchy https://arxiv.org/abs/2207.02098 [00:51:04] On the Measure of Intelligence https://arxiv.org/abs/1911.01547 [01:00:35] Epistemic Foraging https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2016.00056/full --- LINKS: Full Transcript: https://app.rescript.info/share/d43b3918dc7cb8c8b822ebef40b8f66f Download PDF transcript: http https://www.youtube.com/embed/FAspMnu4Rt0 3655 2025-03-08T22:09:11.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/i-automated-my-gmail-inbox-with-ai-agents-crewai-tutorial I automated my Gmail Inbox with AI Agents (#crewai tutorial) https://i.ytimg.com/vi/zz0SA8xMBCo/maxresdefault.jpg 📨 Tired of spending hours sorting through your inbox? 🔥 In this video, I walk you through how I built a complete Gmail automation system using CrewAI and Python that intelligently manages my emails. This AI-powered system: ✅ Automatically categorizes emails (newsletters, promotions, personal, etc.) ✅ Assigns priority levels based on content and sender ✅ Organizes emails with Gmail labels and stars ✅ Generates draft responses for important emails ✅ Sends Slack notifications for high-priority messages ✅ Safely cleans up low-priority emails ✅ Protects important content like YouTube notifications I'll show you the entire codebase and explain how the different AI agents work together to create a powerful email management system that saves me hours every week. 📋 What you'll learn: - How to set up CrewAI agents for different email tasks - Connecting to Gmail securely using IMAP - Building intelligent categorization and prioritization systems - Creating automated response drafts with AI - Setting up Slack notifications for important emails - Implementing safe cleanup rules for low-priority content 🔗 Get the code: https://github.com/tonykipkemboi/crewai-gmail-automation 💻 Technologies used: - #Python - CrewAI - #IMAP for #Gmail - OpenAI's GPT models - #Slack API If you found this helpful, please like and subscribe for more AI and automation content! Join this channel to get access to perks: https://www.youtube.com/channel/UCApiD66gf36M9hZanbjgNaw/join #GmailAutomation #CrewAI #PythonTutorial #AIAutomation #EmailManagement #InboxZero https://www.youtube.com/embed/zz0SA8xMBCo 2784 2025-03-07T20:59:14.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/ceo-of-microsoft-on-ai-agents-quantum-satya-nadella CEO of Microsoft on AI Agents & Quantum | Satya Nadella https://i.ytimg.com/vi/ZUPJ1ZnIZvE/maxresdefault.jpg While he hardly needs an introduction, few leaders have shaped the future of technology quite like Satya Nadella. He stepped into Microsoft’s top job at a catalytic moment—making bold bets on the cloud, embedding AI into the fabric of computing, all while staying true to Microsoft’s vision of becoming a “software factory.” In this conversation with Aditya Agarwal and Ruchi Sanghvi, Satya discusses: • his approach to building early at Microsoft and why we all need to continue “refounding” • the future of AI and why critical thinking will remain at a premium • Microsoft’s partnership with OpenAI, his vision for quantum, and more Connect with us here: 1. Satya Nadella – https://x.com/satyanadella 2. Ruchi Sanghvi – https://x.com/rsanghvi 3. Aditya Agarwal – https://x.com/adityaag 4. South Park Commons – https://x.com/southpkcommons Apply for SPC: https://www.southparkcommons.com/apply 00:00 Trailer 00:57 Introduction 02:03 Joining Microsoft 06:39 Culture and relevance 11:21 Winning and not winning 17:37 Making that turnaround happen 22:30 Contrarian leadership belief 23:35 Investments in startups 27:33 Foundation models 31:07 Artificial intelligence 36:32 The future 40:39 Quantum computing 44:53 Multiverse 45:33 The next generation 50:10 Being competitive 52:34 Outro https://www.youtube.com/embed/ZUPJ1ZnIZvE 3188 2025-03-07T15:00:46.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/keynote-ai-without-the-bs-for-humans-scott-hanselman-ndc-london-2025 Keynote: AI without the BS, for humans - Scott Hanselman - NDC London 2025 https://i.ytimg.com/vi/kYUicaho5k8/maxresdefault.jpg This talk was recorded at NDC London in London, England. #ndclondon #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndclondon.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.facebook.com/ndcconferences https://twitter.com/NDC_Conferences https://www.instagram.com/ndc_conferences/ #ai AI is fun to say, but is it BS? Join Scott Hanselman as he explores "LMs both VL and S" (very large and small) and learns if they are useful or not? What about NPUs on your phone or laptop? What can a small model do that can save power and money? How many TOPS (tensor operations) are needed for a model to add value in your life and be worth your time? How does Scott use AI in his day to day to be more productive, without turning into an AI Grifter? https://www.youtube.com/embed/kYUicaho5k8 3540 2025-03-06T12:38:23.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/rag-is-two-things-prompt-engineering-and-search-keep-it-separate-s2-e28 RAG is two things. Prompt Engineering and Search. Keep it Separate | S2 E28 https://i.ytimg.com/vi/MXwf5-nTPlE/maxresdefault.jpg John Berryman moved from aerospace engineering to search, then to ML and LLMs. His path: Eventbrite search → GitHub code search → data science → GitHub Copilot. He was drawn to more math and ML throughout his career. **RAG Explained** "RAG is not a thing. RAG is two things." It breaks into: 1. Search - finding relevant information 2. Prompt engineering - presenting that information to the model These should be treated as separate problems to optimize. **The Little Red Riding Hood Principle** When prompting LLMs, stay on the path of what models have seen in training. Use formats, structures, and patterns they recognize from their training data: - For code, use docstrings and proper formatting - For financial data, use SEC report structures - Use Markdown for better formatting Models respond better to familiar structures. **Testing Prompts** Testing strategies: - Start with "vibe testing" - human evaluation of outputs - Develop systematic tests based on observed failure patterns - Use token probabilities to measure model confidence - For few-shot prompts, watch for diminishing returns as examples increase **Managing Token Limits** When designing prompts, divide content into: - Static elements (boilerplate, instructions) - Dynamic elements (user inputs, context) Prioritize content by: 1. Must-have information 2. Nice-to-have information 3. Optional if space allows Even with larger context windows, efficiency remains important for cost and latency. **Completion vs. Chat Models** Chat models are winning despite initial concerns about their constraints: - Completion models allow more flexibility in document format - Chat models are more reliable and aligned with common use cases - Most applications now use chat models, even for completion-like tasks **Applications: Workflows vs. Assistants** Two main LLM application patterns: - **Assistants**: Human-in-the-loop interactions where users guide and correct - **Workflows**: Decomposed tasks where LLMs handle well-defined steps with safeguards **Brea https://www.youtube.com/embed/MXwf5-nTPlE 3764 2025-03-06T11:00:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/azure-ai-foundry-overview Azure AI Foundry Overview https://i.ytimg.com/vi/Sq8Cq7RZM2o/maxresdefault.jpg A review of the pro-code Azure AI tooling in Azure AI Foundry. 🔎 Looking for content on a particular topic? Search the channel. If I have something it will be there! 🤔 Due to the channel growth and number of people wanting help I no longer can answer or even read questions and they will just stay in the moderation queue never to be seen so please post questions to other sites like Reddit, Microsoft Community Hub etc. ▬▬▬▬▬▬ C H A P T E R S ⏰ ▬▬▬▬▬▬ 00:00 - Introduction 00:39 - Copilots 01:05 - Capital C Copilots 03:02 - Little c copilots 04:25 - Copilot Studio 09:39 - How to pick 10:43 - Azure AI Foundry core capabilities 13:20 - Types of model 15:24 - Trends in AI 18:10 - Traditional AI services and generative 22:39 - Portal and SDK 23:39 - Model collection 29:19 - Model lack of memory 30:25 - Where the model is running 32:06 - Benchmarks 37:57 - GitHub Marketplace 43:46 - Deployment options 44:13 - Serverless endpoint 48:16 - Managed compute 49:40 - Interacting with generative AI 52:51 - Retirements 54:58 - Evaluations 57:25 - Tracing 58:33 - Fine tuning 1:03:23 - Distillation 1:05:25 - Inferencing API 1:08:06 - Safety 1:14:35 - Agents 1:17:59 - Orchestrators 1:20:23 - Azure AI Search 1:21:35 - Hubs and projects 1:24:22 - Integration 1:26:47 - Close ▬▬▬▬▬▬ K E Y L I N K S 🔗 ▬▬▬▬▬▬ ► Video whiteboard: 🔗 https://github.com/johnthebrit/RandomStuff/raw/master/Whiteboards/AzureAIFoundry.png ► Microsoft Docs: 🔗 https://azure.microsoft.com/products/ai-foundry/ ► Foundry portal: 🔗 https://ai.azure.com ► GitHub Marketplace Rate Limits: 🔗 https://docs.github.com/en/github-models/prototyping-with-ai-models#rate-limits ► Data Storage: 🔗 https://techcommunity.microsoft.com/blog/azure-ai-services-blog/data-storage-in-azure-openai-service/4382502 ► Retirements: 🔗 https://learn.microsoft.com/en-us/azure/ai-studio/concepts/model-lifecycle-retirement https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/model-retirements ▬▬▬▬▬▬ Want to learn more? 🚀 ▬▬▬▬▬▬ 📖 Recommended Learning Path for Az https://www.youtube.com/embed/Sq8Cq7RZM2o 5255 2025-03-05T19:36:42.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/the-rise-of-ai-native-companies-and-product-leadership-with-sc-moatti-of-mighty-capital The Rise of AI-Native Companies and Product Leadership with SC Moatti of Mighty Capital https://i.ytimg.com/vi/4GDWYdmYK7Y/maxresdefault.jpg The most valuable asset in business today isn’t technology — it’s data. Those who control it, refine it and protect it will dominate their industries. SC Moatti, Managing Partner of Mighty Capital, shares insights on the evolving role of product managers, the impact of AI on product development and how businesses can leverage data to drive innovation and market leadership. Specifically, SC discusses: (2:50) Mighty Capital invests in top startups and connects them with 500,000 product managers. (5:08) Most waves of innovation, from the mobile era to AI and Web3, start with the same type of problem. (10:25) AI is reshaping patents and copyright laws, but machines will never own intellectual property. (11:58) Are we at a Napster moment with AI and how will it reshape business models? (16:04) Product managers will use AI agents to streamline work and decision-making. (20:05) Why product managers are now at the center of the data revolution. (24:17 The future of onboarding and why the best experience may require no onboarding at all. (32:15) The risks and opportunities AI presents in intellectual property, ownership and industry disruption. (37:08) The rising trend of AI-native companies and their capital-efficient business models. (40:12) The future of product managers is changing fast, with more growth ahead. Resources Mentioned: SC Moatti - https://www.linkedin.com/in/scmoatti/ Mighty Capital | LinkedIn - https://www.linkedin.com/company/mighty-capital/ Mighty Capital | Website - https://mighty.capital Products That Count - https://www.productsthatcount.org Amplitude - https://amplitude.com This episode is brought to you by: Leverage community-led growth to skyrocket your business. From Grassroots to Greatness by author Lloyed Lobo will help you master 13 game-changing rules from some of the most iconic brands in the world — like Apple, Atlassian, CrossFit, Harley-Davidson, HubSpot, Red Bull and many more — to attract superfans of your own that will propel you to new heights. Grab your copy https://www.youtube.com/embed/4GDWYdmYK7Y 2477 2025-03-05T05:00:03.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/using-agentic-ai-to-create-smarter-solutions-with-multiple-llms-step-by-step-process Using Agentic AI to create smarter solutions with multiple LLMs (step-by-step process) https://i.ytimg.com/vi/O0GNrvO7wD0/maxresdefault.jpg In this video, I dive into the world of agentic AI, a concept that's set to be a major buzzword in 2025. We explore how agentic AI combines multiple agents—some of which are language models (LLMs) and others that are tools—to create more sophisticated and effective AI workflows. We walk through a simple example of how an AI agent can draft a marketing plan, another can critique it, and a third can refine it based on the feedback. We also discuss how some agents can be tools, like a Google search to gather data, and how an orchestrator agent can manage the entire process, adjusting steps as needed. Leave me a comment if you have new topics I should be discussing. Check out my LinkedIn: https://www.linkedin.com/in/donwoodlock/ --- YouTube Timestamps 0:00 – 0:20 Welcome 0:21 – 0:50 Introduction to the concept of Agentic AI 0:51 – 3:50 Explanation of how Agentic AI works 3:50 – 4:08 Advertisement plug-in 4:08 – 5:20 Example of using compound LLM’s 5:21 – 5:55 Why you should use a compound LLM approach 5:57 – 6:45 Best way to train and use LLM’s for optimal outcome 6:45 – 7:40 How to think of LLM as agents 7:41 – 10:05 Not every agent needs to be an LLM 10:06 - 10:50 Possibility of having an orchestrator agent 10:51 – 12:50 How to use these agents 12:51 – 13:26 Closing remarks --- ABOUT INTERSYSTEMS Established in 1978, InterSystems Corporation is the leading provider of data technology for extremely critical data in healthcare, finance, and logistics. It’s cloud-first data platforms solve interoperability, speed, and scalability problems for large organizations around the globe. InterSystems Corporation is ranked by Gartner, KLAS, Forrester and other industry analysts as the global leader in Data Access and Interoperability. InterSystems is the global market leader in Healthcare and Financial Services. Website: https://www.intersystems.com/ Youtube: https://www.youtube.com/@InterSystemsCorp LinkedIn: https://www.linkedin.com/company/intersystems/ Twitter: https://twitter.com/InterSystems #agentica https://www.youtube.com/embed/O0GNrvO7wD0 827 2025-03-04T16:00:26.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/deep-learning-day-agents Deep Learning Day: Agents https://i.ytimg.com/vi/4IxahtQz3cg/maxresdefault.jpg Antonio Torralba, Faculty Head of Artificial Intelligence and Decision-Making in MIT EECS and the Delta Electronics Professor of Electrical Engineering and Computer Science, discusses AI agents. Torralba’s talk was part of Deep Learning Day for the MIT Schwarzman College of Computing's Expanding Horizons in Computing series. Organized by MIT faculty, the series comprised of four sessions that delved into key topics in computing — deep learning, societal impact, cryptography and security, and quantum technology. Watch more videos from the MIT Schwarzman College of Computing: https://youtube.com/@mitcomputing  The mission of the MIT Schwarzman College of Computing is to address the opportunities and challenges of the computing age — from hardware to software to algorithms to artificial intelligence — by transforming the capabilities of academia in three key areas: strengthen core computer science and AI; infuse the forefront of computing with disciplines across MIT; and advance social, ethical, and policy dimensions of computing. Learn more at computing.mit.edu. https://www.youtube.com/embed/4IxahtQz3cg 3171 2025-03-03T15:30:02.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/semantic-kernel-intro-16-how-to-include-image-in-a-prompt-call Semantic Kernel Intro 16: How to include image in a prompt call https://i.ytimg.com/vi/HDviXzmvqZI/maxresdefault.jpg One of the cool feature of Semantic Kernel is the ability to shield the programmer from the underling interface of the API you are using. When it is time to include images in the prompt, to use multimodality of the model, Semantic Kernel make it possible to perform this task in very few lines of code. Being able to call a LLM with images is one of the key point in RAG system where you have documents with lots of images. As usual you can find the code here: https://github.com/alkampfergit/ai-notebooks/blob/master/semantic-kernel-base/210-send-image-functioncall-new.dib https://www.youtube.com/embed/HDviXzmvqZI 681 2025-03-02T09:44:35.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-i-use-llms How I use LLMs https://i.ytimg.com/vi/EWvNQjAaOHw/maxresdefault.jpg The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series on LLMs. In this more practical followup, I take you through the many ways I use LLMs in my own life. Chapters 00:00:00 Intro into the growing LLM ecosystem 00:02:54 ChatGPT interaction under the hood 00:13:12 Basic LLM interactions examples 00:18:03 Be aware of the model you're using, pricing tiers 00:22:54 Thinking models and when to use them 00:31:00 Tool use: internet search 00:42:04 Tool use: deep research 00:50:57 File uploads, adding documents to context 00:59:00 Tool use: python interpreter, messiness of the ecosystem 01:04:35 ChatGPT Advanced Data Analysis, figures, plots 01:09:00 Claude Artifacts, apps, diagrams 01:14:02 Cursor: Composer, writing code 01:22:28 Audio (Speech) Input/Output 01:27:37 Advanced Voice Mode aka true audio inside the model 01:37:09 NotebookLM, podcast generation 01:40:20 Image input, OCR 01:47:02 Image output, DALL-E, Ideogram, etc. 01:49:14 Video input, point and talk on app 01:52:23 Video output, Sora, Veo 2, etc etc. 01:53:29 ChatGPT memory, custom instructions 01:58:38 Custom GPTs 02:06:30 Summary Links - Tiktokenizer https://tiktokenizer.vercel.app/ - OpenAI's ChatGPT https://chatgpt.com/ - Anthropic's Claude https://claude.ai/ - Google's Gemini https://gemini.google.com/ - xAI's Grok https://grok.com/ - Perplexity https://www.perplexity.ai/ - Google's NotebookLM https://notebooklm.google.com/ - Cursor https://www.cursor.com/ - Histories of Mysteries AI podcast on Spotify https://open.spotify.com/show/3K4LRyMCP44kBbiOziwJjb - The visualization UI I was using in the video: https://excalidraw.com/ - The specific file of Excalidraw we built up: https://drive.google.com/file/d/1DN3LU3MbKI00udxoS-W5ckCHq99V0Uqs/view?usp=sharing - Discord channel for Eureka Labs and this video: https://discord.gg/3zy8kqD9Cp Educational Use Licensing This video is freely available for educational and internal training purposes. Educators, https://www.youtube.com/embed/EWvNQjAaOHw 7872 2025-02-27T22:29:56.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-microsoft-engineers-build-ai-learn-about-scalable-rag-enabled-ai-apps How Microsoft Engineers Build AI - Learn About Scalable RAG-enabled AI Apps https://i.ytimg.com/vi/6qQqgq7_G1k/maxresdefault.jpg We are thrilled to introduce the first episode of new Microsoft Engineering Video Series: How Microsoft Engineers Build AI! In this series, we will be deep diving with Microsoft engineers on how they are building AI applications here at Microsoft. We’ll cover many different topics in this series, starting with one of the most common updates that developers are making with AI: implementing retrieval-augmented generation (RAG) into applications. In this video we will learn directly from the Microsoft Engineering team on how they used RAG to develop the Ask Learn function on Copilot for Azure at scale! From discussing chunking strategies to how to avoid hallucination, deep dive into how Microsoft builds their own AI.! Chapters 00:00 Introduction 00:49 Demo 03:25 What is RAG? 07:30 What part of this product is being used from Microsoft? 09:50 Why do you think it was necessary to create this plugin for Ask Learn? 11:35 What was so special about this project? 13:01 What challenges did you face building this tool? 17:10 If there is a bad response, how do you improve it for next time? 18:24 Were there any surprises you faced and how did you deal with them? 21:25 What steps do you take to clean and preprocess data before it’s ingested into the system? 24:08 There is a lot of information on Microsoft Learn, how did you break it down, what was your strategy? 27:25 How did you manage data changes consistently? 29:49 How do you keep a balance between a fast and good answer? 32:33 How do you know that Ask Learn is doing well and how do you monitor it? 34:34 How do you avoid hallucination and ensure safety? 36:22 Security Concerns 37:28 What advice would you give to developers who are new to building RAG-based applications? 39:33 What are some mistakes/traps to avoid? 43:20 Conclusion ✔️Get Started: AI for Developer Hub: https://aka.ms/AIforDeveloper 📌 Let's connect: Brian Steggeman | LinkedIn https://www.linkedin.com/in/briansteggeman/ Eric Imasogie | LinkedIn https://www.linkedin.com/in/eric-imasogie/ Tianqi Z https://www.youtube.com/embed/6qQqgq7_G1k 2659 2025-02-26T17:00:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/artificial-intelligence-past-present-future-prof-w-eric-grimson Artificial Intelligence - Past, Present, Future: Prof. W. Eric Grimson https://i.ytimg.com/vi/dyt42j7XJaQ/maxresdefault.jpg 2025 MIT Bangkok Symposium Artificial Intelligence - Past, Present, Future Chancellor for Academic Advancement, Prof. W. Eric L. Grimson Bernard M. Gordon Professor of Medical Engineering, MIT Read more about Prof. W Eric Grimson: https://orgchart.mit.edu/leadership/chancellor-academic-advancement/biography See more of the 2025 MIT Bangkok Symposium here: https://ilp.mit.edu/Bangkok25 _________________________________________________________________ Find us at: https://ilp.mit.edu/about Get in touch: https://ilp.mit.edu/connect Follow us on: ….https://www.linkedin.com/company/mit-industrial-liaison-program https://www.youtube.com/embed/dyt42j7XJaQ 2775 2025-02-25T13:14:52.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/ai-in-the-enterprise-what-works-what-doesn-t-and-what-s-next AI in the Enterprise: What Works, What Doesn’t, and What’s Next https://i.ytimg.com/vi/3sYBe7yEJ3U/maxresdefault.jpg In this moderated discussion, Professor Haim Mendelson is joined by guest speaker Yoav Shoham, a renowned AI expert, co-founder of several successful AI companies (the most recent being AI21 Labs), and professor emeritus of computer science at Stanford University. Together, they delve into the evolving landscape of AI in the enterprise, examining its current state and future trajectory. Shoham addresses key questions, such as why enterprise deployments often lag behind consumer adoption, the limitations of LLMs in enterprise applications, and whether AI agents represent meaningful progress or simply the latest hype. He also offers tips for successful AI implementations and shares his insights on what’s ahead for enterprise AI, including the expected shift from models to complete AI systems, the implications of AI on the workforce, and more. This event is part of the Value Chain Innovation Speaker Series and is organized by the Value Chain Innovation Initiative. The series explores how emerging technologies are reshaping business models, value chains, and consumer preferences. Each one-hour webinar features a dynamic conversation led by Professor Haim Mendelson, faculty director of VCII, with one or more leading innovators in the field. Visit the VCII Events page at goto.stanford.edu/vcii-events for a list of upcoming events and to access past event recordings. –––––– 00:00 Introduction 02:50 Yoav’s entrepreneurship journey 05:33 About AI21 Labs 09:35 Evolution of AI in the enterprise 12:24 AI21’s Jamba model 16:17 Factors impacting enterprise adoption 18:14 The future of AI solutions 22:11 AI agents: promise and hype 24:52 Tips for AI implementation 30:42 AI systems as a product category 34:02 Q&A: Impact on workforce 38:32 Q&A: Additional hurdles to AI adoption 39:45 Q&A: Education’s role in maximizing AI value 41:50 Q&A: Buzz around DeepSeek 45:33 Q&A: Open vs. closed source 46:38 Q&A: Enterprise priorities for 2025 48:02 Q&A: Global perspective 51:56 Preview of next webinar 52:56 Closing remarks https://www.youtube.com/embed/3sYBe7yEJ3U 3302 2025-02-21T22:17:23.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-ai-is-changing-enterprise How AI Is Changing Enterprise https://i.ytimg.com/vi/aIKfA3gIXwo/maxresdefault.jpg The Lightcone hosts sit down with Aaron Levie, the co-founder & CEO of Box, to hear reports from the front of how large enterprise and Fortune 500 companies are adapting to the AI age. Apply to Y Combinator: https://ycombinator.com/apply Chapters (Powered by https://bit.ly/chapterme-yc) - 0:00 Intro 1:15 Why the GPT wrapper was a bad meme 4:44 Enterprise users just care about getting workflow done 8:38 What does it mean for startups as intelligence becomes a commodity? 12:47 Do Fortune 500’s have any interest in underlying models? 20:19 What are enterprise execs thinking about AI right now? 27:04 Is Box investing in internal AI tools? 28:17 What will enterprises build internally and what will they buy solutions for? 34:50 Is enterprise concerned with third-parties and security? 36:16 Shout-outs to Aaron! 39:46 The transition from cloud to AI 48:38 Outro https://www.youtube.com/embed/aIKfA3gIXwo 2969 2025-02-19T15:00:00.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/autonomous-multi-agent-group-chat-working-with-copilot-agent-plugins-in-microsoft-semantic-kernel Autonomous Multi-Agent Group Chat working with Copilot Agent Plugins in Microsoft Semantic Kernel https://i.ytimg.com/vi/RYQmSbmd-WY/maxresdefault.jpg 🔹 Agents are now collaborating to refine and execute queries across Contacts, Calendar, Email, and even a Legal Secretary Agent ensuring compliance and multilingual support! 🔹 And YES... Easter eggs at 8:26 and 9:09 – stick around for the surprises! 🎭 🔹 This is a game-changer for developers building intelligent, structured AI workflows with Microsoft’s tech stack. 💬 What do you think? Drop a comment if you’re excited about Multi-Agent Group Chat in SK! 🔗 Resources & Code: Demo Sample on my GitHub Repo: https://go.fabswill.com/LCaps Get Copilot Agent Plugins Now!: https://aka.ms/m365caps 📌 Hidded Gems you dont want to miss Timestamps: 08:26 - First Easter Egg 🐣 09:09 - Second Easter Egg - The Reveal🕵️ 🔥 LIKE & SUBSCRIBE and smash that Notification Bell for more! #SemanticKernel #MultiAgentAI #MicrosoftCopilot #AzureAI #Microsoft365 #ArtificialIntelligence #AgentCollaboration #CopilotAgentPlugins #AIWorkflows #ChatAI #SKCAPs #MultiAgentChat #AIChatbots #CopilotDevelopment #EasterEggs 🎭 https://www.youtube.com/embed/RYQmSbmd-WY 939 2025-02-17T00:31:31.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/using-azure-ai-foundry-sdk-for-your-ai-apps-and-agents Using Azure AI Foundry SDK for your AI apps and agents https://i.ytimg.com/vi/NR_FQwtyRbc/maxresdefault.jpg Build custom AI app experiences grounded on your own data in Azure AI Foundry — deploy models like GPT-4o, add Retrieval Augmented Generation with vector search, orchestrate multi-step agents, and run evaluations and monitoring as part of GenAIOps. Azure AI Foundry gives developers 1,800+ models, prebuilt Azure AI services, and end-to-end tooling to build, evaluate, and monitor generative AI apps directly from your code. 👥 Who it's for: Developers and AI engineers building generative AI apps, Azure developers choosing and deploying models, and teams standing up GenAIOps for evaluation and production monitoring. ⏱️ Chapters: 00:00 Build custom AI apps in Azure AI Foundry 00:27 Model catalog & benchmarks to pick a model 01:37 Ground apps on your own custom data 03:03 Add Retrieval Augmented Generation (RAG) 03:48 Create a vector search index with hybrid search 04:17 Set up your code with the OpenAI SDK 06:11 Orchestrate multi-step AI agents in code 07:16 Debug model calls with traces 07:45 Evaluate quality with Azure AI evaluators 08:19 Monitor production apps in Application Insights 08:58 What to build first in Azure AI Foundry Azure AI Foundry (now generally available) brings the studio and Azure AI together so you can go from picking a model to shipping a grounded, production-ready app in code. Start in the model catalog to browse 1,800+ models from OpenAI, Microsoft, Meta, Mistral and more, then use model benchmarks — accuracy, coherence, groundedness, fluency, and relevance — to choose the right one. Prebuilt Azure AI services add cognitive skills like speech, language and translation, vision and OCR, and content safety to detect harmful inputs and outputs. Dan Taylor, Principal Product Architect for the Azure AI Foundry SDK, shows how to create a project, deploy GPT-4o, and set a system message in the playground. To ground responses on your data, he adds Retrieval Augmented Generation (RAG), uploading product files to automatically build an Azure AI Search vector index with hybrid keyword + vector searc https://www.youtube.com/embed/NR_FQwtyRbc 561 2025-02-04T21:15:08.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/prompt-engineering-for-llms-best-practices-with-john-berryman-of-arcturus-labs Prompt Engineering for LLMs: Best Practices With John Berryman of Arcturus Labs https://i.ytimg.com/vi/6DjFKzUrNao/maxresdefault.jpg LLMs are bringing so much to the table right now, with the potential to solve complex problems and automate tasks like never before. But getting the most out of these models requires new skills. And today, we’ve got just the expert to help you do that! Meet John Berryman, a true leader in the field of LLMs. He is the Founder and Principal Consultant at Arcturus Labs, where he consults on LLM application development and is a specialist in prompt engineering. Before founding Arcturus, he was a senior machine learning researcher at GitHub, where he played a pivotal role in developing both the Copilot code completions product and the chat product. His most recent book is titled Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications. In this episode of Scaling Tech, Arin and John dive deep into prompt engineering for LLMs. John shares practical techniques for best communicating with LLMs, making efficient prompts, and ultimately building LLM-powered applications. Ready to level up your understanding of LLMs and prompt engineering? Don’t miss this episode! About Guest: Name: John Berryman What he does: He’s a Consultant in Large Language Model Application Development. Company: Arcturus Labs Where to find John: LinkedIn Key Insights ⚡AI is moving towards more agency. As tech advances, language learning models are more autonomous and can perform tasks on behalf of the user. However, it still requires human involvement in the process. John explains, “What we're kind of getting at the extreme of this is something that people are calling agency. Now, agency is another one of those terms. It's going to be another one of those terms for a while. It's kind of a buzzword. And when everyone says that, they have a different thing in mind. But when I think of agency with the technology we currently have on hand, I'm thinking about something that is allowing these language models to take multiple steps and do things on the behalf of the user but, at this poin,t still very much inco https://www.youtube.com/embed/6DjFKzUrNao 3101 2025-02-04T20:00:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/openai-o1-isn-t-a-chat-model-and-that-s-the-point OpenAI o1 isn’t a chat model (and that’s the point) https://i.ytimg.com/vi/NkHcSpOOC60/sddefault.jpg How Ben Hylak turned from ol pro skeptic to fan by overcoming his skill issue. https://www.latent.space/p/o1-skill-issue In this episode of the Late in Space podcast, Alessio, Ben Hylak, and Dan McAteer discuss their experiences with the O1 AI model, exploring its capabilities, the importance of effective prompting, and the challenges of using AI in coding and other applications. They delve into the distinctions between O1 and previous models, the nuances of crafting prompts, and the significance of understanding return formats and tone in AI outputs. The conversation also touches on the future of AI, model routing, and unique applications in research, concluding with insights on how to evaluate and utilize AI models effectively. Chapters 00:00 Introduction to O1 and Perspectives on AI Models 02:40 Experiences with O1: Impressions and Use Cases 05:36 Understanding the Distinction: O1 vs Previous Models 08:12 Crafting Effective Prompts for O1 10:45 Navigating Tone and Return Formats in Prompts 13:34 Evaluating AI Models for Specific Use Cases 15:59 The Future of AI: Insights and Model Routing 18:28 Exploring Unique Applications of O1 21:12 Final Thoughts and Future Directions https://www.youtube.com/embed/NkHcSpOOC60 1919 2025-01-17T23:11:31.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/part-9b-azure-ai-foundry-cohere-rerank Part 9B - Azure AI Foundry - Cohere Rerank https://i.ytimg.com/vi/sccoaCeX3zw/maxresdefault.jpg In this video, we will demonstrate the use of the Cohere Rerank took and the needed deployment of the model and setting up the connection correctly to be able to produce higher quality RAG in your application. https://www.youtube.com/embed/sccoaCeX3zw 285 2025-01-05T19:48:01.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/ilya-sutskever-sequence-to-sequence-learning-with-neural-networks-at-neurips-2024 Ilya Sutskever: Sequence to Sequence Learning with Neural Networks at NeurIPS 2024 https://i.ytimg.com/vi/WQQdd6qGxNs/maxresdefault.jpg paper: https://arxiv.org/abs/1409.3215 Test of Time Paper Awards for NeurIPS 2024 https://blog.neurips.cc/2024/11/27/announcing-the-neurips-2024-test-of-time-paper-awards/ 00:00 Award. 01:34 What we did 02:04 What we got right 03:20 What we got right: Autoregressive Models 04:17 What we got wrong: the LSTM 05:00 Early distributed training: Parallelization 06:00 The core idea 07:18 The age of Pre-Training 08:20 Pre-Training as we know it will end 08:45 The age of pre-training will end due to that the data is not growing 09:00 What comes next? 09:53 What comes next? Example from nature 12:45 What comes next? The long term 16:30 The end of talk: Q&A 16:46 Question 1: Now in 2024, are there other biological structures that are part of human cognition that you think are worth exploring in a similar way or that you're interested in anyway? 18:16 Question 2: Hallucinations in today's models 20:31 Question 3: How do you create the right incentive mechanisms for humanity to actually create it in a way that gives it the freedoms that we have as homosapiens? 22:23 Question 4: Do you think LLMs generalize multi-hop reasoning out of distribution? https://www.youtube.com/embed/WQQdd6qGxNs 1477 2024-12-14T03:26:29.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/gemini-beyond-limits-unified-multimodal-analysis-with-2m-token-context-windows Gemini Beyond Limits: Unified Multimodal Analysis with 2M Token Context Windows https://i.ytimg.com/vi/79XN4PA-WzY/sddefault.jpg **Video Description:** 🔍 **Exploring Gemini 1.5: Redefining Context Windows with Unified Multimodal Analysis** In this video, we dive deep into the groundbreaking capabilities of **Google’s Gemini 1.5**, a language model with an astonishing **2-million-token context window**. Gone are the days of sifting through hours of content or juggling multiple formats of data. Whether it's lengthy team meetings, extensive document archives, YouTube playlists, or even images and audio recordings, Gemini 1.5 has you covered! **Import links**: Google Gemini API: aistudio.google.com/prompts/new_chat Kaggle Notebook: Search for Gemini Beyond Limits: Unified Multimodal Analysis with 2M Token Context Windows 🌟 **Use Case Highlight:** We present our **Unified Multimodal Analysis** pipeline, which enables seamless querying across diverse formats like videos, audio transcripts, documents, and images—delivering **structured insights with timestamps**. Imagine asking one question and getting instant, precise answers without wasting time scrubbing through hours of irrelevant information. 💡 **What You'll Learn in This Video:** - The **problem** of managing and retrieving information from various data formats in corporate settings. - The **solution** we built using Gemini 1.5: an advanced workflow to process, cache, and query multimodal content efficiently. - A walkthrough of the **data processing pipeline** and how we leverage Gemini’s caching mechanism to boost efficiency. - Insights into how this solution can save hours of effort, making knowledge extraction faster, more accurate, and user-friendly. 🤖 **Meet Francis:** Adding a touch of charm to our journey is Francis, our sarcastic yet insightful AI assistant. With witty remarks and on-point commentary, Francis makes complex tech concepts relatable and fun! 🎯 **Why This Video Matters:** This is not just a technical showcase; it’s a practical demonstration of how cutting-edge AI can revolutionize the way we handle and analyze data in real-world scen https://www.youtube.com/embed/79XN4PA-WzY 363 2024-12-01T20:12:00.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/exploring-open-webui-features-models-tools-updated Exploring Open WebUI: Features, Models, & Tools [Updated] https://i.ytimg.com/vi/CDiVq3mPZc8/maxresdefault.jpg 🔔 2026 UPDATE — You can now build your own completely customizable AI system. Free course below. ▶ Free 6-lesson course — Own Your AI: https://youtube.com/playlist?list=PL_rTgQnnMXsVkg29Lm9syjUyVQmRG_4y_ In this video, we dive into the powerful functionalities of the OpenWebUI interface! After showing you how to install OpenWebUI using a Docker container in the previous video, we now explore its various features and capabilities. Learn how to navigate through the interface, utilize chat controls, work with system prompts, and select different models like Llama ChatGPT and Claude. We also demonstrate how to create reusable prompts, interact with documents, and access the vast collection of tools and functions provided by the OpenWebUI community. Whether you're looking to code, run Python scripts, or explore advanced techniques like Retrieval Augmented Generation (RAG), this video has you covered. Make sure to stay tuned for upcoming videos where we’ll dive deeper into these tools and more! 👉 Subscribe for more tutorials on OpenWebUI, AI, and much more! #OpenWebUI #AItutorial #Docker #LLM #LargeLanguageModels #Llama32 #Python #AItools #MachineLearning #OpenSourceAI #Coding #RAG #TechTutorial #EnsembleLearning #ModelComparison #AIcommunity #Workspace #PromptEngineering #ModelTraining #PythonCode #TechExploration #InterfaceGuide #AItools #FutureOfAI https://www.youtube.com/embed/CDiVq3mPZc8 468 2024-11-28T04:23:41.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/unlocking-the-ai-revolution-studio07 Unlocking the AI revolution | Studio07 https://i.ytimg.com/vi/WbjedY3vNew/maxresdefault.jpg Join us for this insightful interview with Asha Sharma where she will outline the forward direction for AI products, focusing on how they can assist administrators and IT professionals in managing costs and enhancing their operations. Asha will also highlight exciting use cases and real-world applications of AI that have emerged over the past year and a half. 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Seth Juarez * Asha Sharma 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com Studio07 | English (US) #MSIgnite https://www.youtube.com/embed/WbjedY3vNew 736 2024-11-25T22:58:06.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/how-azure-ai-search-enables-retrieval-augmented-generation-rag-at-scale How Azure AI Search Enables Retrieval-Augmented Generation (RAG) at Scale https://i.ytimg.com/vi/NVp9jiMDdXc/maxresdefault.jpg Millions of people use Azure AI Search every day without knowing it. You can enable your apps with the same search that enables retrieval-augmented generation (RAG) capabilities when you build Custom GPTs or attach files in your ChatGPT prompts. Pablo Castro, Microsoft CVP and Distinguished Engineer Azure AI Search, joins Jeremy Chapman to share how with Azure AI Search, you can create custom applications that retrieve the most relevant information quickly and accurately, even from billions of records. Manage massive-scale datasets while maintaining high-quality search results with ultra-compact, binary quantized vector search indexes that use Matryoshka Representation Learning (MRL) and oversampling to equal the search accuracy of vector indexes up to 96 times larger. These approaches drive significant cost savings by optimizing your vector indexes without compromising quality. ► QUICK LINKS: 00:00 - RAG powered by Azure AI Search 00:50 - Azure AI Search role in ChatGPT 02:01 - Azure AI Search use case - AT&T 03:27 - Start in Azure Portal 04:35 - Massive scale and vector index 06:08 - Scalar & Binary Quantization 07:21 - Martyoshka technique 09:07 - Oversampling 11:31 - How to build an app using Azure AI Search 13:00 - See it in action 14:28 - Enable binary quantization with oversampling 14:54 - Wrap up ► Link References Get sample code on GitHub at https://aka.ms/SearchQuantizationSample Check out search solutions at https://aka.ms/AzureAISearch ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep gettin https://www.youtube.com/embed/NVp9jiMDdXc 940 2024-11-04T15:50:25.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/an-intro-to-rerankers-a-uniform-api-for-reranking-models An intro to rerankers: A uniform API for reranking models https://i.ytimg.com/vi/cKI7yjxW87Q/maxresdefault.jpg In this video, we'll learn how to use rerankers, a new library by Jeremy Howard and his team at Answer AI. rerankers provides a uniform API over various re-ranking models, making it super easy to switch/change/test the different models. Re-ranking is a technique where you re-sort a set of documents against a provided query to make sure that the most relevant documents are at the top of the list. It's used to improve the retrieval quality in a Retrieval Augmented Generation pipelines. ➡️ Resources 🟡 Code - https://github.com/mneedham/LearnDataWithMark/blob/main/rerankers-playground/rerankers.ipynb 🟡 rerankers - https://github.com/answerdotai/rerankers 🟡 Blog - https://www.markhneedham.com/blog/2024/09/28/intro-to-rerankers/ ➡️ Chapters 00:00 What is rerankers? 00:20 Why do we need reranking? 01:14 Initialising reranker 01:33 A hello world example 02:08 An Olympics opening ceremony example 02:35 Querying the data with vector search 03:48 Improving the results with rerankers https://www.youtube.com/embed/cKI7yjxW87Q 283 2024-09-29T07:16:48.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/skeleton-of-thought-faster-more-efficient-ai-text-generation Skeleton of Thought: Faster, More Efficient AI Text Generation https://i.ytimg.com/vi/yusIrre_27E/maxresdefault.jpg Discover the "Skeleton of Thought" technique for AI text generation, based on a 2024 ICLR paper. This video explains how this method mimics human writing processes to create more efficient and faster AI-generated content compared to traditional sequential methods. Learn how to implement this technique using Langflow, with step-by-step explanations of the prompt engineering process and parallel text generation. Key topics covered: 0:00 - Introduction to Skeleton of Thought technique 0:35 - Comparison with traditional LLM decoding 0:45 - Efficiency and reduced latency of parallel generation 0:57 - Explanation of the skeleton prompt template 1:36 - Implementation in Langflow 2:22 - Demonstration of generating initial skeleton points 2:39 - Process of expanding skeleton points 3:34 - Combining expanded responses 4:27 - Conclusion and benefits of the technique Try out this template in the Langflow store and experience the power of Skeleton of Thought for yourself! https://www.youtube.com/embed/yusIrre_27E 277 2024-09-03T12:53:07.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/a-fun-absurd-introduction-to-vector-databases-alexander-chatzizacharias-goto-2024 A Fun & Absurd Introduction to Vector Databases • Alexander Chatzizacharias • GOTO 2024 https://i.ytimg.com/vi/5hAGhmHNTQQ/maxresdefault.jpg This presentation was recorded at GOTO Amsterdam 2024. #GOTOcon #GOTOams https://gotoams.nl Alexander Chatzizacharias - Software Engineer at JDriven RESOURCES https://bsky.app/profile/glycin.bsky.social https://twitter.com/alex90_ch https://www.linkedin.com/in/alexander-chatzizacharias ABSTRACT Vector databases have emerged as an exciting new tech in the world of data storage. Unsurprisingly enough, they have become the go-to choice for storing vectors (who would have thought?!) and are widely used in conjunction with generative AI. Apart from their use in AI applications, they can also be extremely handy as search engines, especially if you are looking to implement natural language interfaces. If you're reading this and eager to harness the power of vector databases to bring your application to the next level, then this talk is tailor-made for you! Whether you're an experienced database professional or an adventurous developer seeking fresh perspectives, Alexander will guide you through the process of getting started with a Vector Database. He will demonstrate how to translate your data into vectors and master the art of querying that data. From text search to image search to generative search, Alexander's goal is to provide an engaging introduction to Vector Databases and, hopefully, inspire you to explore their full potential. [...] TIMECODES 00:00 Intro 01:11 Goal of this talk 02:19 Vectors 05:00 Machine learning 06:35 Vector databases 12:52 Demo 17:32 Implementing our own search 21:14 Demo: HNSW 24:24 Demo: Matrix 28:40 Demo: D&D 33:52 Demo: Pokemon 38:51 Demo: D&D 43:24 Demo: Duncan Hills 47:43 Outro Download slides and read the full abstract here: https://gotoams.nl/2024/sessions/3113 RECOMMENDED BOOKS Alex Castrounis • AI for People and Business • https://amzn.to/3NYKKTo Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ Holden Karau, Trevor Grant, Boris Lublinsky, Richard Liu & Ilan Filonenko • Kubeflow for Machine Learning • https://amzn.to/3JVngcx Kelleher & Tierney • Data Science (T https://www.youtube.com/embed/5hAGhmHNTQQ 2893 2024-08-30T12:00:10.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/ai-and-the-productivity-paradox AI and the Productivity Paradox https://i.ytimg.com/vi/iaisOHeJLC4/maxresdefault.jpg Explore IBM AI Solutions → https://ibm.biz/BdKzXp In a rapidly evolving world, we need to balance the fear surrounding AI and its role in the workplace with its potential to drive productivity growth. In this special live episode of Smart Talks with IBM, Malcolm Gladwell is joined onstage during NY Tech Week by Rob Thomas, Senior Vice President of Software and Chief Commercial Officer at IBM. They discuss “the productivity paradox”, the importance of open source AI, and a future where AI will touch every industry.  AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM.→ https://ibm.biz/BdKzXV This is a paid advertisement from IBM. The conversations on this podcast don't necessarily represent IBM's positions, strategies or opinions. https://www.youtube.com/embed/iaisOHeJLC4 2347 2024-07-23T11:00:43.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/building-a-swiss-train-timetable-copilot-plugin Building a Swiss train timetable copilot plugin​ https://i.ytimg.com/vi/7FFtR1pHnFU/sddefault.jpg 📺 Learn about building a Swiss train timetable copilot plugin in this session from the Microsoft 365 & Power Platform community call on April 11, 2024. 🧑‍🤝‍🧑 Demo presenter: • David Schneider (isolutions) - https://www.linkedin.com/in/david-schneider/ 📝 Learn more: • Message extensions for Microsoft Copilot for Microsoft 365 - https://learn.microsoft.com/en-us/microsoft-365-copilot/extensibility/overview-message-extension-bot • Copilot for Microsoft 365 plugins samples - https://github.com/OfficeDev/Copilot-for-M365-Plugins-Samples 👋 Do you have something exciting to share with the Microsoft 365 & Power Platform community? Volunteer to present in our next community call demo at https://aka.ms/community/request/demo. 💡 Learn more about the Microsoft 365 & Power Platform community: • Microsoft 365 & Power Platform Unified Sample gallery - https://aka.ms/community/samples • Microsoft Community Learning YouTube channel - https://aka.ms/community/youtube • Microsoft 365 & Power Platform - https://aka.ms/community/home Sharing is caring! You are awesome! 🧡 #Microsoft365 #Microsoft365Dev #Copilot https://www.youtube.com/embed/7FFtR1pHnFU 490 2024-07-02T07:00:05.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/azure-ai-search Azure AI Search https://i.ytimg.com/vi/h6D6YKs9gzw/maxresdefault.jpg Learn about Azure AI's robust search capabilities, which enable the indexing and retrieval of enterprise data. This session will highlight how Azure AI Search can serve as a foundational component for RAG, providing the necessary data scaffolding for LLMs to draw upon. [eventID:22832] https://www.youtube.com/embed/h6D6YKs9gzw 3579 2024-06-22T00:04:58.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/enhancing-vs-code-extensions-with-github-copilot-brk195 Enhancing VS Code extensions with GitHub Copilot | BRK195 https://i.ytimg.com/vi/YI7kjWzIiTM/maxresdefault.jpg GitHub Copilot helps you write code faster and smarter in Visual Studio Code. You can use chat conversations to help with refactoring code, improving your understanding, and configuring VS Code. VS Code enables extension authors to integrate with GitHub Copilot via chat extensions, which can provide specialized answers to user queries within a domain. Join us for this deep dive on GitHub Copilot, including a tour of how you can create your own chat extensions. 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Gaurab Aryal * Matthew Bierner * Joyce Er * Ian McCrystal * Aaron Munger * Brigit Murtaugh 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This video is one of many sessions delivered for the Microsoft Build 2024 event. View the full session schedule and learn more about Microsoft Build at https://build.microsoft.com BRK195 | Developer Tools #MSBuild https://www.youtube.com/embed/YI7kjWzIiTM 2235 2024-05-24T12:26:19.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/build-your-next-genai-breakthrough-with-neo4j Build Your Next GenAI Breakthrough with Neo4j https://i.ytimg.com/vi/7kbHw7dniUc/maxresdefault.jpg See how Neo4j's industry-leading knowledge graph powers cutting-edge Generative AI (GenAI) applications. In this demo, we'll explore a real-world use case to demonstrate how Neo4j’s knowledge graph, combined with vector search, enables superior Retrieval Augmented Generation (RAG). Learn how Neo4j helps overcome common GenAI challenges like hallucinations and lack of explainability while improving the relevance and quality of Large Language model (LLM) responses. With Neo4j, you can: -Build a grounding knowledge graph from structured and unstructured data -Use graph pattern matching with vector search to provide deeper domain context, enhancing the relevance and explainability of LLM responses -Apply advanced graph analytics, such as Graph Data Science, to gain -valuable insights into grounding data, allowing you to continually analyze, monitor, and improve grounding data quality over time. Resources Demo Code on GitHub: https://bit.ly/3Tq2b0u GenAI Developer & Educational Resources: https://bit.ly/3Tpxxo8 More Neo4j GenAI Resources: https://bit.ly/4ajVELA https://www.youtube.com/embed/7kbHw7dniUc 473 2024-03-29T02:17:16.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/why-does-diffusion-work-better-than-auto-regression Why Does Diffusion Work Better than Auto-Regression? https://i.ytimg.com/vi/zc5NTeJbk-k/maxresdefault.jpg Have you ever wondered how generative AI actually works? Well the short answer is, in exactly the same as way as regular AI! In this video I break down the state of the art in generative AI - Auto-regressors and Denoising Diffusion models - and explain how this seemingly magical technology is all the result of curve fitting, like the rest of machine learning. Come learn the differences (and similarities!) between auto-regression and diffusion, why these methods are needed to perform generation of complex natural data, and why diffusion models work better for image generation but are not used for text generation. The following generative models were featured as demos in this video: Images: Adobe Firefly (https://www.adobe.com/products/firefly.html) Text: ChatGPT (https://chat.openai.com) Audio: Suno.ai (suno.ai) Code: Gemini (gemini.google.com/app) Video: Lumiere (Lumiere-video.github.io) Chapters: 00:00 Intro to Generative AI 02:40 Why Naïve Generation Doesn't Work 03:52 Auto-regression 08:32 Generalized Auto-regression 11:43 Denoising Diffusion 14:19 Optimizations 14:30 Re-using Models and Causal Architectures 16:35 Diffusion Models Predict the Noise Instead of the Image 18:19 Conditional Generation 19:08 Classifier-free Guidance https://www.youtube.com/embed/zc5NTeJbk-k 1218 2024-02-16T21:00:25.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/4-methods-of-prompt-engineering 4 Methods of Prompt Engineering https://i.ytimg.com/vi/1c9iyoVIwDs/maxresdefault.jpg Explore watsonx → https://ibm.biz/explore-ibm-watsonx Dig Deeper: What is prompt engineering? → https://ibm.biz/prompt-engineering Learn generative AI → https://ibm.biz/generative-ai-for-developers Have you heard of these AI prompt engineering methods? • Retrieval Augmented Generation (RAG) • Chain-of-Thought (COT) • ReACT (Reason + Act) • Directional Stimulus Prompting (DSP) Wondering what the differences and values of each are? In this video, IBM Distinguished Engineer Suj Perepa explains those differences and values, provides an example of each method, and tells how they can be best used and even combined. Introduction 0:00 RAG 1:16 Chain of Thought (COT) 3:33 ReACT 6:30 Directional Stimulus Prompting (DSP) 10:48 Combinations 12:05 Get started for free on IBM Cloud → https://ibm.biz/sign-up-now Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now #ai #neuralnetworks #promptengineering #genai https://www.youtube.com/embed/1c9iyoVIwDs 762 2024-01-22T12:00:04.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/azure-ai-search-generating-the-right-answers-every-time Azure AI Search: Generating the right answers, every time https://i.ytimg.com/vi/_2Ax43Dd3Fg/sddefault.jpg Microsoft Azure Free Trial: http://aka.ms/devrelFT Chapters 00:00 Welcome to the AI Show 00:18 On today's show 00:46 Azure Cognitive Search is now Azure AI Search 01:07 Semantic search is now Semantic ranker 01:56 Azure AI Search Announcements from Ignite 03:08 Semantic ranker pricing 04:22 Integrated vectorization 06:37 Demo 18:20 Learn More On this episode, we'll dive into the future of search with Azure AI Search: 🌐 Revolutionary vector database technology 🔍 Cutting-edge search ranking for superior user experiences 🔄 Advanced retrieval capabilities: vector search, hybrid search, semantic re-ranking 🤝 Deep platform integrations for seamless AI app experiences Learn more: https://Aka.ms/AISearchIgnite2023 Connect: Seth | https://twitter.com/sethjuarez Watch on-demand at https://aka.ms/AIShow/OnDemand AI Show Live Playlist: https://aka.ms/AIShowPlaylist Join us every Monday, for an AI Show livestream on YouTube https://aka.ms/AIShowLive https://www.youtube.com/embed/_2Ax43Dd3Fg 1180 2023-12-11T17:30:07.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/timo-schick-toolformer-language-models-can-teach-themselves-to-use-tools Timo Schick | Toolformer: Language Models Can Teach Themselves to Use Tools https://i.ytimg.com/vi/UID_oXuN-0Y/maxresdefault.jpg New Technologies in Mathematics Seminar Speaker: Timo Schick, Meta AI Title: Toolformer: Language Models Can Teach Themselves to Use Tools Abstract: Language models exhibit remarkable abilities to solve new tasks from just a few examples or textual instructions, especially at scale. They also, paradoxically, struggle with basic functionality, such as arithmetic or factual lookup, where much simpler and smaller models excel. In this talk, we show how these limitations can be overcome by letting language models teach themselves to use external tools via simple APIs. We discuss Toolformer, a model trained to independently decide which APIs to call, when to call them, what arguments to pass, and how to best incorporate the results into future token prediction. Through this, it achieves substantially improved zero-shot performance across a variety of downstream tasks without sacrificing its core language modeling abilities. https://www.youtube.com/embed/UID_oXuN-0Y 3343 2023-04-26T20:53:43.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/20-option-price-and-probability-duality 20. Option Price and Probability Duality https://i.ytimg.com/vi/eG_aRPy1KVE/maxresdefault.jpg MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013 View the complete course: http://ocw.mit.edu/18-S096F13 Instructor: Stephen Blyth This guest lecture focuses on option price and probability duality. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu https://www.youtube.com/embed/eG_aRPy1KVE 4829 2015-01-06T18:18:56.000Z monthly 0.5 https://img.denu5.com/videos/d5-llm/1-introduction-financial-terms-and-concepts 1. Introduction, Financial Terms and Concepts https://i.ytimg.com/vi/wvXDB9dMdEo/maxresdefault.jpg MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013 View the complete course: http://ocw.mit.edu/18-S096F13 Instructor: Peter Kempthorne, Choongbum Lee, Vasily Strela, Jake Xia View newer version of the course: https://ocw.mit.edu/courses/18-642-topics-in-mathematics-with-applications-in-finance-fall-2024/ YouTube Playlist (Fall 2024): https://www.youtube.com/playlist?list=PLUl4u3cNGP601Q2jo- In the first lecture of this course, the instructors introduce key terms and concepts related to financial products, markets, and quantitative analysis. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu https://www.youtube.com/embed/wvXDB9dMdEo 3630 2015-01-06T18:18:47.000Z monthly 0.5 https://img.denu5.com/videos/test weekly 0.6 https://img.denu5.com/videos/test/managing-structured-products-with-less-time-and-effort-beyond-60-40-ep-29 Managing Structured Products With Less Time and Effort | Beyond 60/40 Ep. 29 https://i.ytimg.com/vi/czvH5LPkfSQ/maxresdefault.jpg In this segment of Beyond 60/40, we tackle a viewer question of the month: Structured products have seen significant growth in business volume. Is there another way to manage these structured products without so much time and effort involved? Our expert guest, Steve Czick, iCapital's Managing Director, Structured Products, delves into an efficient solution—utilizing separately managed accounts (SMAs) for structured products. Steve explains how SMAs can help advisors maintain strategic exposure to structured products while outsourcing the operational burden of managing individual notes to free up valuable time for advisors to focus on tactical investments and other portfolio management activities. Have a question about alternative investments? Email yourquestion@icapitalnetwork.com to be answered on an upcoming episode. https://www.youtube.com/embed/czvH5LPkfSQ 304 2024-11-20T19:54:20.000Z monthly 0.5 https://img.denu5.com/videos/test/barrier-reverse-convertibles-kurz-erkl-rt Barrier Reverse Convertibles – kurz erklärt https://i.ytimg.com/vi/8NH2UJk47UI/maxresdefault.jpg Barrier Reverse Convertibles gehören zu den beliebtesten Strukturierten Produkten in der Schweiz. Sie zeichnen sich durch einen fixen Coupon sowie einen gewissen Sicherheitspuffer aus. In diesem Video wird kurz und knapp erklärt, was Barrier Reverse Convertibles auszeichnet und wie sie funktionieren. https://www.youtube.com/embed/8NH2UJk47UI 163 2024-09-25T09:12:20.000Z monthly 0.5 https://img.denu5.com/videos/test/structured-products-buffer-etfs-explained-by-a-cfa-charterholder Structured Products & Buffer ETFs Explained By a CFA Charterholder https://i.ytimg.com/vi/JPLA5XZZn5A/maxresdefault.jpg Structured Products & Buffer ETFs Explained By a CFA Charterholder. Structured products and buffer ETFs that allow you to buy stocks with less downside risk are exploding in popularity. In this video, I'm going to simplify structured products and buffer ETFs. If you are an investing enthusiast and want to learn more about investing, join our FREE Discord: https://www.fundamentalsoffinance.com/discord 00:00 Intro 1:26 Step 1: Owning the Asset By Itself 1:42 Step 2: Owning An Option By Itself 2:45 Step 3: Combining Asset & Option(s) To Create A Structure 4:33 Step 4: Combining Asset & Option(s) to Create A Structure 6:18 Buffer ETF Step 1: Creating Synthetic VOO Exposure 8:43 Buffer ETF Step 2: Adding Downside Protection 9:30 Buffer ETF Step 3: Paying For Downside Protection 11:41 Buffer ETF Recap 12:42 Things You Should Consider #structuredproducts #fundamentalsoffinance #bufferetfs Disclaimer: Not Financial Advice The content provided on this channel, "Fundamentals of Finance," is for informational and educational purposes only. The information shared is not intended to be, and does not constitute, financial advice, investment advice, trading advice, or any other advice. You should not make any decision, financial, investment, trading, or otherwise, based on any of the information presented in this channel without undertaking independent due diligence and consultation with a professional broker or financial advisory. The opinions expressed in this channel are those of the authors and do not necessarily reflect the views of any sponsors or affiliated parties. Any financial decision you make is at your own risk. "Fundamentals of Finance" will not be held liable for any losses or damages incurred as a result of your reliance on information provided on this channel. Remember to always do your own research and consult with a qualified financial advisor before making any financial decisions. https://www.youtube.com/embed/JPLA5XZZn5A 866 2024-06-15T17:04:02.000Z monthly 0.5 https://img.denu5.com/videos/test/unlock-profitable-potential-with-barrier-reverse-convertibles-navigating-risks-rewarding-returns Unlock Profitable Potential with Barrier Reverse Convertibles: Navigating Risks & Rewarding Returns https://i.ytimg.com/vi/3ReM5VeaHuY/maxresdefault.jpg Unlock Profitable Potential with Barrier Reverse Convertibles: Navigating Risks & Rewarding Returns Beyond Conventional Investments: Unveiling the Potential of Barrier Reverse Convertibles (BRCs) In the world of finance, investors often seek sophisticated instruments that offer the potential for higher returns while also providing protection against market volatility. Barrier Reverse Convertibles (BRCs) stand out as a complex yet intriguing option that blends the characteristics of bonds and derivatives. Unlocking the Synergy of Bonds and Derivatives At its core, a BRC encompasses two key elements: Bond-like Structure: BRCs resemble bonds in that they offer a fixed interest payment, known as a coupon, typically higher than traditional bonds. Derivative Component: BRCs incorporate a derivative linked to an underlying asset, such as stocks, indices, currencies, or commodities. The Role of the Barrier: A Shield Against Downside Risk The defining feature of BRCs is the 'barrier level.' This pre-determined price point acts as a protective mechanism. If the underlying asset's price breaches the barrier level during the investment period, specific outcomes unfold. Conversion into Underlying Assets: Investors receive the underlying asset at a reduced price, potentially mitigating losses. Option to Sell Back to Issuer: Investors can sell the BRC back to the issuer at the strike price, ensuring a fixed return despite the underlying asset's performance. Navigating the Benefits and Risks of BRCs BRCs hold the potential for appealing returns: Higher Yields: The combination of coupon payments and the potential for capital appreciation offers enhanced returns. Downside Protection: If the barrier is breached, downside risk is minimized. However, investors should exercise caution: Complexity: BRCs are complex instruments that require careful consideration and understanding of the underlying assets and risks. Illiquidity: BRCs may be less liquid than traditional bonds, making it challenging to sell them quickly. B https://www.youtube.com/embed/3ReM5VeaHuY 334 2024-02-24T23:00:02.000Z monthly 0.5 https://img.denu5.com/videos/test/how-to-improve-your-performance-with-brcs-swissquote How to improve your performance with BRCs | Swissquote https://i.ytimg.com/vi/0PoC96SVVek/maxresdefault.jpg This webinar will introduce you to the basics of barrier reverse convertibles, a type of structured product that can be used to generate income or participate in the upside of a stock while limiting your downside risk. Francois Bloch, an expert in structured products, will explain how barrier reverse convertibles work, the different types available, and how to choose the right one for your investment goals. Speakers: Ludovica Scotto di Perta - Senior Structured Product Specialist at Swissquote François Bloch - Investment Strategist _____ Learn the fundamentals of trading at your own pace with Swissquote's Education Center. Discover our online courses, webinars and eBooks: https://swq.ch/wr _____ Discover our brand and philosophy: https://swq.ch/wq Learn more about our employees: https://swq.ch/d5 _____ Let's stay connected: LinkedIn: https://swq.ch/cH https://www.youtube.com/embed/0PoC96SVVek 1932 2023-11-09T11:54:21.000Z monthly 0.5 https://img.denu5.com/videos/test/are-structured-products-good-investments Are Structured Products Good Investments? https://i.ytimg.com/vi/fVRPF1rHzVo/maxresdefault.jpg Structured notes are complex investment products with returns linked to an underlying asset. They are often marketed based on high coupon yields, downside protection, or some combination. The payoffs of structured notes can seem like a free lunch, but banks are not selling them to you because they’re your friend. When you’re having dinner with lions you have to make sure you’re at the table, not on the menu. ------------------ Follow Ben Felix on - Twitter: https://twitter.com/benjaminwfelix Visit Rational Reminder: https://rationalreminder.ca/ Join the Rational Reminder Community: https://community.rationalreminder.ca/ Follow the Rational Reminder on: - Twitter: https://www.twitter.com/RationalRemind - Instagram: https://www.instagram.com/rationalreminder/ Visit PWL Capital: https://www.pwlcapital.com/ Follow PWL Capital on: - Twitter: https://twitter.com/PWLCapital - Facebook: https://www.facebook.com/PWLCapital - LinkedIn: https://www.linkedin.com/company/pwl-capital/ You can find the Rational Reminder podcast on Google Podcasts: https://www.google.com/podcasts?feed=aHR0cHM6Ly9yYXRpb25hbHJlbWluZGVyLmxpYnN5bi5jb20vcnNz Apple Podcasts: https://itunes.apple.com/ca/podcast/the-rational-reminder-podcast/id1426530582?mt=2 Spotify Podcasts: https://open.spotify.com/show/6RHWTH9iW7hdnA7eAg7ukO?si=hjZNfLKuSjSeWX38GPqhVA ------------------ Sources: Cochrane, J. H. (2022). Portfolios for long-term investors. Review of Finance, 26(1), 1–42. https://doi.org/10.1093/rof/rfab038 Gabaix, X., & Laibson, D. (2006). Shrouded attributes, consumer myopia, and information suppression in competitive markets. The Quarterly Journal of Economics, 121(2), 505–540. https://doi.org/10.1162/qjec.2006.121.2.505 Carlin, B. I. (2009). Strategic price complexity in retail financial markets☆. Journal of Financial Economics, 91(3), 278–287. https://doi.org/10.1016/j.jfineco.2008.05.002 Henderson, B. J., & Pearson, N. D. (2011). The dark side of financial innovation: A case study of the pricing of a retail financial product☆. Journal https://www.youtube.com/embed/fVRPF1rHzVo 452 2023-08-03T20:11:51.000Z monthly 0.5 https://img.denu5.com/videos/test/was-sind-brcs-bx-swiss-tv Was sind BRCs? | BX Swiss TV https://i.ytimg.com/vi/xcYiPEaBepc/maxresdefault.jpg Barrier Reverse Convertibles, abgekürzt BRCs, sind strukturierte Finanzprodukte. Sie kombinieren eine festverzinsliche Komponente mit einer Option auf ein oder mehrere Basiswerte. Im Rahmen eines Experteninterviews mit David Kunz, COO der BX Swiss, gibt Manuel Dürr, Head of Public Solutions, Leonteq AG einen Einblick auf den Schweizer BRC Markt. In welcher Marktphase funktionieren sie am besten und wie sieht es mit dem Risiko aus, diese und weitere Fragen beantwortet Manuel Dürr. Kapitel: 00:00 Was sind BRCs? | BX Swiss TV 00:51 Wie lange läuft ein BRC? 01:05 In welcher Marktphase funktioniert ein BRC? 02:00 Verschiedene Barriere Mechanismen 02:20 Was ist in der Schweiz verbreiteter? 02:43 Mehrere Underlyings? 03:28 Wie hoch wird das Risiko ausbezahlt? 04:00 Mehr Single oder Multi? ► Folgt uns auch bei Instagram: https://www.instagram.com/bxswiss ► Aktuelle Kurse auf unserer Homepage: https://www.bxswiss.com/ __________________________________________________________________________________ ► Rechtliche Hinweise und Angaben zu möglichen Interessenkonflikten: https://www.bxswiss.com/disclaimer https://www.youtube.com/embed/xcYiPEaBepc 291 2023-07-07T07:00:25.000Z monthly 0.5 https://img.denu5.com/videos/test/wie-funktioniert-der-hebel-bei-unlimited-turbo-optionsscheinen-licht-an Wie funktioniert der Hebel bei Unlimited Turbo Optionsscheinen? - Licht an https://i.ytimg.com/vi/oByP7iwLhTU/maxresdefault.jpg Der Hebel bzw. das Hebelverhältnis ist ein Bestandteil des Chancen- und Risiken-Profils eines Investments. So bedeutet ein Hebel von 10 etwa, dass ein Unlimited Turbo Long Optionsschein um zehn Prozent steigt, wenn der zugrundeliegende Basiswert um einen Prozent zulegt. Genauso fällt der Unlimited Turbo Long Optionsschein aber auch um 10 Prozent, wenn der Basiswert lediglich um zehn Prozent an Wert verliert. Eine ausführlichere Erklärung zu Unlimited Turbo Optionsscheinen und den relevanten Kennzahlen finden Sie hier. https://derivate.bnpparibas.com/service/produktwissen/handbuch-fuer-trader/unlimited-turbo-optionsscheine-produktvarianten2/ Zu den Unlimited Turbo Optionsscheinen https://derivate.bnpparibas.com/knockouts/receiveSearch/?search=eyJsaXN0LWFza05vdEVxdWFsVG9aZXJvIjoidHJ1ZSIsImRlcml2YXRpdmVUeXBlSWQiOiI2Nyw2OCJ9 Wichtige rechtliche Hinweise https://derivate.bnpparibas.com/service/produktwissen/ https://www.youtube.com/embed/oByP7iwLhTU 116 2022-10-10T14:00:12.000Z monthly 0.5 https://img.denu5.com/videos/test/yield-boosters-barrier-reverse-convertibles-swissquote Yield Boosters - Barrier Reverse Convertibles | Swissquote https://i.ytimg.com/vi/EE0Ks2uYoNU/maxresdefault.jpg Barrier Reverse Convertibles are accessible structured products designed to enhance your portfolio’s yield in sideways markets with a controlled risk level. Simple and transparent pre-packaged investment, ideal as a first foray into structured products Enhanced-rate coupon independently of the performance of the underlying Mitigated risk of loss compared to direct investments in the underlying #swissquote #barrierreversecomvertibles #structuredproducts #brc #yieldboosters _____ Learn the fundamentals of trading at your own pace with Swissquote's Education Center. Discover our online courses, webinars, and eBooks: https://swq.ch/wr _____ Discover our brand and philosophy: https://swq.ch/wq Learn more about our employees: https://swq.ch/d5 _____ Let's stay connected: LinkedIn: https://swq.ch/cH https://www.youtube.com/embed/EE0Ks2uYoNU 287 2022-06-10T11:26:27.000Z monthly 0.5 https://img.denu5.com/videos/test/an-introduction-to-structured-products An introduction to structured products https://i.ytimg.com/vi/2GLPMgrdV8g/maxresdefault.jpg Abdel Hamidouche gives you an introduction to structured products in a highly volatile environment with a special focus on BRC, Barrier Reverse Convertibles. https://www.youtube.com/embed/2GLPMgrdV8g 259 2022-03-22T14:18:45.000Z monthly 0.5 https://img.denu5.com/videos/test/knockout-zertifikate-richtig-verstehen-und-anwenden-am-beispiel-von-trade-republic Knockout Zertifikate richtig verstehen und anwenden am Beispiel von Trade Republic https://i.ytimg.com/vi/O55AEdQcXfk/maxresdefault.jpg Du hast keine Ahnung wie Knockout Zertifikate funktionieren. Dann bist du hier in diesem Video genau richtig denn ich möchte dir heute zeigen was Knockout Zertifikate sind wie funktionieren und berechnet werden. Danach zeige ich dir Schritt für Schritt wie ich an die Sache heran gehe von Anfang der Analyse mit Tradingview bis hin zum Kauf bei Trade Republic. Ich hoffe das du nach dem Video keine Fehler mehr machst beim heraus suchen von Turbo Zertifikaten oder Mini Futures. Bei den Zertifikaten kann man sowohl auf fallende (short) oder steigende (long) kurse wetten. Egal ob es der Dax oder Nasdaq ist. Auch auf Währungen, Rohstoffe oder Aktien kann man sich Knock-out Zertifikate kaufen. Wenn du Fragen hast dann schreib sie doch gerne in die Kommentare und ich versuche sie so schnell wie möglich zu benatworten. Wenn dir das Video gefallen hat würde ich mich natürlich sehr über ein Like oder Abo freuen. RISIKOHINWEIS: Alle Inhalte entsprechen meiner persönlichen Meinung. Das oben gezeigte Video stellt keine Aufforderung zum Verkauf oder Kauf eines Finanzproduktes dar. Dies ist KEINE Anlageempfehlung. Dieses Video ist nur als Informationsvideo zu betrachten. #knockout #zertifikate #erklären https://www.youtube.com/embed/O55AEdQcXfk 845 2021-08-01T10:27:15.000Z monthly 0.5 https://img.denu5.com/videos/test/reverse-convertible-lohnt-sich-wirklich-ein-kauf Reverse Convertible - Lohnt sich wirklich ein Kauf? https://i.ytimg.com/vi/-ORQdTAS584/maxresdefault.jpg Die Reverse Convertibles sind wohl das beliebteste Anlageprodukt in der Schweiz. Erklärvideo über die Risiken und Funktionen der Rev Conv mit Preisgestaltung und Empfehlungen für jeden Schweizer Investor. https://www.youtube.com/embed/-ORQdTAS584 1069 2021-04-25T15:58:31.000Z monthly 0.5 https://img.denu5.com/videos/test/structured-products-explained Structured Products Explained https://i.ytimg.com/vi/yUd1JAjHzes/maxresdefault.jpg Structured Products Explained https://www.youtube.com/embed/yUd1JAjHzes 485 2020-09-24T17:07:43.000Z monthly 0.5 https://img.denu5.com/videos/test/the-derivative-league-reverse-convertibles The Derivative League: Reverse Convertibles https://i.ytimg.com/vi/Z2CyR5CFwWA/sddefault.jpg The derivative league: Reverse Convertibles Have you ever wondered what to do with your money better then placing it at a bank? Especially in times of almost 0% interest. Or are you already familiar with stocks looking for opportunities to diversify your portfolio? Then This series is for you. The derivative league is an introduction to the world of certificates. It's purpose is to educate people about the financial world nowadays. https://www.youtube.com/embed/Z2CyR5CFwWA 157 2019-07-22T10:10:18.000Z monthly 0.5 https://img.denu5.com/videos/test/what-are-structured-products What are Structured Products? https://i.ytimg.com/vi/cLLVyRG7vmI/maxresdefault.jpg Today we will learn what structured products are. These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0 Check out our website http://www.onfinance.org/ Follow Patrick on twitter here: https://twitter.com/PatrickEBoyle Patreon Page: https://www.patreon.com/PatrickBoyleOnFinance A structured product, also known as a market-linked investment, is a pre-packaged investment strategy based on a single security, a basket of securities, options, indices, commodities, debt issuance or foreign currencies, and to a lesser extent, derivatives. The variety of products just described demonstrates that there is no single, uniform definition of a structured product. A feature of some structured products is a "principal guarantee" function, which offers protection of principal if held to maturity. For example, an investor invests $100, the issuer simply invests in a risk-free bond that has sufficient interest to grow to $100 after the five-year period. This bond might cost $80 today and after five years it will grow to $100. With the leftover funds the issuer purchases the derivatives needed to perform whatever the investment strategy calls for. Theoretically an investor can just do this themselves, but the cost and transaction volume requirements of many derivatives are beyond many individual investors. Structured products are designed to facilitate highly customized risk-return objectives. This is accomplished by taking a traditional security, such as a conventional investment-grade bond, and replacing the usual payment features (e.g. periodic coupons and final principal) with non-traditional payoffs derived not from the issuer's own cash flow, but from the performance of one or more underlying assets. Structured products were created to meet specific needs that cannot be met from the standardized financial instruments available in the markets. Structured products can be used as an alternative to a direct investment, as part of the ass https://www.youtube.com/embed/cLLVyRG7vmI 714 2019-05-28T11:00:07.000Z monthly 0.5 https://img.denu5.com/videos/test/svsp-the-benefits-of-barriere-reverse-convertibles SVSP - The Benefits of Barriere Reverse Convertibles https://i.ytimg.com/vi/wbUQzllgugQ/maxresdefault.jpg Financial Investments with Structured Products https://www.youtube.com/embed/wbUQzllgugQ 61 2019-01-21T08:39:46.000Z monthly 0.5 https://img.denu5.com/videos/test/new-sp-portfolio-optimizer-features-filmed-use-cases-show-targeted-applications New «SP Portfolio Optimizer» features: Filmed use cases show targeted applications https://i.ytimg.com/vi/sgFxfx27f9M/maxresdefault.jpg Filmed use cases for participation products, yield optimisation products and capital protection products illustrate how different products can generate portfolio benefits. Portfolios also can now be replicated with individual stocks, facilitating an even more accurate simulation. https://www.youtube.com/embed/sgFxfx27f9M 285 2018-03-01T08:33:50.000Z monthly 0.5 https://img.denu5.com/videos/test/reverse-convertibles Reverse Convertibles https://i.ytimg.com/vi/LfE4wZakLPc/maxresdefault.jpg This video provides a basic introduction to the terminology and structure of these often misunderstood securities. The presentation describes how reverse convertibles belong in the category of structured notes (debt instruments whose returns are a function of an embedded derivative) known as enhanced yield structured notes. The source of the high coupon rate and the type of embedded option (knock-in put) that results in the complexity of the securities are discussed. The similarities and differences with regular convertible bonds are also covered. InsidersGuideToFinance.com facebook.com/insidersguidetofinance https://www.youtube.com/embed/LfE4wZakLPc 706 2017-08-08T13:56:34.000Z monthly 0.5 https://img.denu5.com/videos/test/andreas-bl-mke-rediscovering-swiss-stocks-04-04-2017 Andreas Blümke: «Rediscovering Swiss Stocks» (04.04.2017) https://i.ytimg.com/vi/hIbNIL2neQw/maxresdefault.jpg Why are investors rediscovering Swiss stocks, and what role do structured products play? Andreas Blümke, Executive Director, Vontobel Private Banking. https://www.youtube.com/embed/hIbNIL2neQw 300 2017-04-07T13:46:46.000Z monthly 0.5 https://img.denu5.com/videos/test/funktionsweise-barrier-reverse-convertible Funktionsweise Barrier Reverse Convertible https://i.ytimg.com/vi/Di_qVmSJliU/maxresdefault.jpg Funktionsweise, Payoff und steuerliche Behandlung von Reverse Convertibles https://www.youtube.com/embed/Di_qVmSJliU 836 2017-03-19T14:46:10.000Z monthly 0.5 https://img.denu5.com/videos/test/finance-im-alltag-funktionsweise-eines-reverse-convertibles Finance im Alltag - Funktionsweise eines Reverse Convertibles https://i.ytimg.com/vi/7Q187pMsfAE/maxresdefault.jpg Dieses Video ist Teil des Massive Open Online Course "Das liebe Geld - Finance im Alltag". Sie finden den ganzen Online Kurs unter: www.coursera.org/learn/finanzen Expertinnen und Experten des Instituts für Banking und Finance der Universität Zürich vermitteln ein Basiswissen für bewusste und korrekte finanzielle Entscheidungen im Alltag. Ausserdem erhält man Einblick in verschiedene neueste Forschungserkenntnisse der Finance. Weitere Infos: www.bf.uzh.ch/mooc2017 https://www.youtube.com/embed/7Q187pMsfAE 336 2017-03-13T09:01:04.000Z monthly 0.5 https://img.denu5.com/videos/test/what-is-a-structured-product What is a Structured Product? https://i.ytimg.com/vi/gvl95OS6_4o/maxresdefault.jpg Much maligned structured products are back on the investor's radar as we seek post-retirement solutions that pay a sustainable income. But should they be avoided? Morningstar Guest: Rosie Bullard, Portfolio Manager for james Hambro & Partners http://www.morningstar.co.uk -~-~~-~~~-~~-~- Please watch: "Should You Be Worried About the Economy?" https://www.youtube.com/watch?v=WUzqTPeI9IM -~-~~-~~~-~~-~- https://www.youtube.com/embed/gvl95OS6_4o 308 2015-03-30T10:17:06.000Z monthly 0.5 https://img.denu5.com/videos/test/svsp-wissensfilm-3 SVSP Wissensfilm 3 https://i.ytimg.com/vi/jeQ3DcFHa3Y/maxresdefault.jpg Was sind die gängigsten Strukturierten Produkte? https://www.youtube.com/embed/jeQ3DcFHa3Y 770 2013-06-19T12:10:37.000Z monthly 0.5 https://img.denu5.com/videos/test/was-ist-ein-open-end-turbo Was ist ein Open End Turbo? https://i.ytimg.com/vi/2Mo65Zt0uh4/hqdefault.jpg Open End Turbos sind eine Weiterentwicklung der klassischen Turbo-Zertifikate. Auch hier wird auf ein Stop-Loss-Level verzichtet, zusätzlich ist die Laufzeit jedoch offen und theoretisch unbeschränkt. Was diese offene Laufzeit aber für das Finanzierungslevel bedeutet, legen wir Ihnen im Video dar. https://www.youtube.com/embed/2Mo65Zt0uh4 134 2012-09-19T12:50:37.000Z monthly 0.5 https://img.denu5.com/videos/test/why-you-should-avoid-structured-products-moneyweek-investment-tutorials Why you should avoid structured products - MoneyWeek Investment Tutorials https://i.ytimg.com/vi/jIajAJRFIV4/maxresdefault.jpg Tim Bennett evaluates structured products as an investment, using clear concise wording and easy to understand analysis. Don't miss out on Tim Bennett's video tutorials -- get the latest video sent straight to your inbox each week, before it's released on YouTube: http://bit.ly/TimBSubscribe To receive Tim's 50 FREE MoneyWeek Basics emails: http://bit.ly/mwk-basics Watch over 100 of Tim's videos for free: http://MoneyWeek.com/tutorials Or download them to your mobile device: http://bit.ly/TimBpodcast For the most important financial stories and how to profit from them: http://MoneyWeek.com http://Facebook.com/pages/MoneyWeek/110326662354766 http://Twitter.com/moneyweek Video series by CFA UK Highly Commended journalist Tim Bennett. http://twitter.com/TimMoneyweek https://www.youtube.com/embed/jIajAJRFIV4 850 2011-02-24T17:10:07.000Z monthly 0.5