Huge thank you to the authors for the incredible resources I used to make this video 🙏 Josh Tobin: LLMOps, LLM Bootcamp Spring 2023 - fullstackdeeplearning.com/llm-bootcamp/spring-2023/llmops/ Llamaindex website - www.llamaindex.ai/ Llamaindex Github - github.com/jerryjliu/llama_index Greylock news, The Data Framework for LLMs - greylock.com/portfolio-news/the-data-framework-for-llms/ Llamaindex demo by Simon Suo, Ask Complex Queries over Multiple Documents kzfaq.info/get/bejne/fbqPf9abmN7OYaM.html Top-notch course from Cohere on LLMs - docs.cohere.com/docs/llmu Luis Serrano, What is Semantic Search? - txt.cohere.com/what-is-semantic-search/ Roie Schwaber-Cohen, What is a Vector Database? www.pinecone.io/learn/vector-database/ Jay Alammar’s notebook, Wikipedia Semantic Search with Cohere + Weaviate - github.com/cohere-ai/notebooks/blob/main/notebooks/Wikipedia_search_demo_cohere_weaviate.ipynb LangChain docs - docs.langchain.com/docs/ Lance Martin’s app, Lex GPT - github.com/rlancemartin/lex-gpt lex-gpt.vercel.app/ Harrison Chase: Agents, LLM Bootcamp Spring 2023 - fullstackdeeplearning.com/llm-bootcamp/spring-2023/chase-agents/ Richard He: Chrome GPT demo twitter.com/RealRichomie/status/1653484066010718208 Chrome GPT open source repo: github.com/richardyc/Chrome-GPT

amazing and very clear video! Thaaaaaaaaaank's

Awesome video - and thanks for the Weaviate mention :)

underated video

Good explanations and learn new things as the vector database. Going to see more and more dedicated tools, frameworks and stacks I near future.

this video can make valuable Big Picture to create advanced app with LLM, thanks a lot! 👋👋👋

Nice video, everything was well explained, and thanks for sharing all these demos! 😄 Your videos are so amazing! I would like to make a powerful chatbot, using open source models

nice intro and great links 😍😊

I have had a lot of trouble finding real world performance data comparing different self-hosted vector DB options, for example pgvector exentsion on Postgres vs ChromaDB). Do you have any recommendations?

Have you considered an RSS reader that does reprocessing?

Bookmark

great overview, but the music at 5+ minutes is way too dominant

Nice video. However, I challenge any AI influencer to accurately delineate what costs will be like in relation to anything relevant a hopeful "problem formulation" worker expects to build. If you'd like to make a big video- do it on econometrics of tokens and how much it will actually *cost* by using an example. Does no one answer the call of econometrics and parallel innovation/convergent evolution of AI builds, big or small?? Otherwise we will just keep talking about Ai while there's a big elephant in the middle of the room.