What comes after ChatGPT? Vector Databases - the Simple and powerful future of ML? - Erik Bamberg

What comes after ChatGPT? Vector Databases - the Simple and powerful future of ML? - Erik Bamberg

  • What comes after ChatGPT? Vector database projects like Weaviate, Pinecone, and Chroma recently got millions of dollars of funding for their projects. But what are vector databases? And why will they be so important in the future?Let us see how Vector Databases can help you define and run your machine learning business use cases. We will explore some real-world use cases and try to understand the potential of vectors and vector databases. A brief hands-on demonstration just using open source will give you an idea, of how to use the new generation of databases in praxis.We will also cover how vector databases can work together with chatGPT and helps you to overcome some limitations of chatGPT.

  • Ref: https://www.youtube.com/watch?v=qifmEICIaQE&list=PL03Lrmd9CiGey6VY_mGu_N8uI10FrTtXZ&index=10
  • Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

    Episoder(144)

    The 7 Skills You Need to Build AI Agents

    The 7 Skills You Need to Build AI Agents

    As AI agents become more capable, the skills needed for AI jobs are shifting. Bri Kopecki breaks down the 7 skills you need to move from prompt engineering to full agent engineering, including system ...

    11 Aug 19min

    What is LangChain?

    What is LangChain?

    LangChain became immensely popular when it was launched in 2022, but how can it impact your development and application of AI models, Large Language Models (LLM) in particular. In this video Martin Ke...

    5 Aug 20min

    LangChain vs LangGraph

    LangChain vs LangGraph

    Get ready for a showdown between LangChain and LangGraph, two powerful frameworks for building applications with large language models (LLMs.) Master Inventor Martin Keen compares the two, taking a lo...

    30 Jul 16min

    RAG vs Agentic AI

    RAG vs Agentic AI

    Agentic AI and RAG are redefining how LLMs think and act 🤖. Live from TechXchange in Orlando, Martin Keen & Cedric Clyburn unpack how vector databases, data integration, and context engineering enabl...

    23 Jul 21min

    RAG's Evolution

    RAG's Evolution

    How did search evolve into agentic AI? Sam Anthony explains RAG's evolution, from simple retrieval to adaptive systems powered by LLMs. Learn how semantic search, hybrid retrieval, and AI agents enabl...

    16 Jul 13min

    AI Agent Skills

    AI Agent Skills

    We're all using AI agents, but they still lack the procedural knowledge real work needs. Martin Keen explains how agent skills, LLMs, RAG, and MCP help agents follow workflows, automate tasks, and mak...

    9 Jul 24min

    MCP vs. RAG

    MCP vs. RAG

    How do AI agents learn and take action? Live from TechXchange in Orlando, Melissa Hadley breaks down how MCP and RAG help large language models connect to data — one to retrieve knowledge, the other t...

    2 Jul 20min

    RAG vs Fine-Tuning vs Prompt Engineering

    RAG vs Fine-Tuning vs Prompt Engineering

    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 t...

    25 Jun 20min

    Populært innen Fakta

    fastlegen
    dine-penger-pengeradet
    relasjonspodden-med-dora-thorhallsdottir-kjersti-idem
    foreldreradet
    treningspodden
    jakt-og-fiskepodden
    rss-kunsten-a-leve
    rss-strid-de-norske-borgerkrigene
    mikkels-paskenotter
    hverdagspsyken
    sinnsyn
    fryktlos
    gravid-uke-for-uke
    rss-var-forste-kaffe
    rss-sarbar-med-lotte-erik
    laringsmiljo-i-skole-og-barnehage-uis-podkast
    rss-orjasater
    rss-impressions-2
    kvallm
    lrerrommet