[JimmyRuska]

Anyone know how milvus, quickwit, pinecone compares?

I've been thinking about seeing if there's consulting opportunities for local businesses for LLMs, finetuning/vector search, chat bots. Also making tools to make it easier to drag and drop files and get personalized inference. Recently I saw this one pop into my linkedin feed, https://gpt-trainer.com/ . There's been a few others for documents I've found

https://www.explainpaper.com/

https://www.konjer.xyz/

Nope nope, wouldn't want to compete with that on pricing. Local open source LLMs on a 3090 would also be a cool service, but wouldn't have any scalability.

Are there any other finetuning or vector search context startups you've seen?

[tikkun]

Pinecone and Milvus would be alternatives for their use of FAISS for the vector store and search component. I think more of the embeddings difference would be noticed by what’s used for creating the embeddings (eg the ones here https://news.ycombinator.com/item?id=36649579 instead of the OpenAI embeddings API they used), rather than noticing differences from the embedding store/search alternatives which I can’t think of what the difference would be other than maybe performance at a large scale and cost and personal preference / developer experience.

Hadn’t heard of Quickwit but from a quick glance at their site it doesn’t look like a vector store, seems perhaps unrelated.

For tools for making custom ChatGPTs see my list: https://llm-utils.org/List+of+tools+for+making+a+%22ChatGPT+...

Fine tuning as a service there’s Lamini AI, aimed at enterprises.

Other embeddings startups there’s Weaviate.

[sdan]

I am working on a simple vector db just with numpy: https://github.com/sdan/vlite

I think milvus, quickwit, and pinecone are geared more towards enterprise and are hard to use.

[eddieweng]

qdrant is better in my opinion