TL;DR
For me, AI is everywhere. Everyone wants to do AI.
But sometimes, it is hard to know which tools to master to implement AI feature...
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Normally, people like me can just use an API and get most of the AI features lol. That's great but we are definitely not AI developers. The ones truly involved in prompt engineering are the ones in control. Anyway, great work :)
Haha, Yes, APIfication of AI and deep learning in general is a recent phenomenon. That's good in some ways. Thanks.
we need some standard on how to talk to llms and make then interchangeable, kind of like TCP for LLMS
If you're looking for a an open source and privacy first AI infrastructure, you could give TrustGraph a try. TrustGraph supports and Ollama and Llamafiles for fully private deployments. Container orchestration through Docker or Kubernetes. Native GraphRAG with either Cassandra or Neo4j as your graph store.
github.com/trustgraph-ai/trustgraph
these tools are great, but the real problem starts when you try to move an GenAI app in production. I have very little experience on that part, but would love some guidance on such area where we can expect reliability and consistency from GenAI app.
That's true but it also depends on what kind of GenAI app we are talking about. And GenAI apps are in its infancy, so it might take some time.
Nice list, will take a look at it!
Thank you, Prashant,
Good. Very useful.
Glad you found it helpful.
Nice list of resources, thanks for sharing.
Thank you.
Why is everyone obsessed with listing repositories on DEV? I quite dont get it