we have been trying to make it so that people dont have to reinvent the wheel, over and over and over again, and have a very straight forward all batteries included that can scale to many millions of documents, combining the best of RAG with traditional search and parametric search,
https://docs.mindsdb.com/mindsdb_sql/knowledge_bases/overvie...
Would love your feedback.
So, casually trying to make LLaMA achieve consciousness (as one does on a Tuesday), when I stumbled upon something hilarious. Turns out, you can make these language models "reason" with about as much code as it takes to write a "Hello World" program. No, really!
Here's the philosophical crisis I'm having now: When you ask an LLM to code something vs. asking it to reason about something... are we basically watching the same neural spaghetti being twirled around?
The real question is: If one can make an AI model "think" with 5 lines of code, does this mean:
a) An LLM should be able to write its own reasoning code
b) We've been overthinking AI?
c) The simulation is running low on RAM
d) All of the above
Would love to hear your thoughts, preferably in the form of recursive functions or philosophical paradoxes.
P.S. No LLAMAs were harmed in the making of this experiment, though several did ask for a raise.
great question, i think rather than smaller inputs, you should be able to have as much context as needed in. Its more aboue smaller outputs, that are well typed and allow you to control workflow via standard coding mechanics. Therefore getting the best of both worlds, llms power of understanding unstructured info (which python sucks at) and being able to control things which python is great at.
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