Accurate enough for it to explain to me details of 101, 201 and 301 university courses in math or physics.
Besides, when i ask it about things like SRE, Cloud etc. its a very good starting point.
9 karma · joined December 23, 2024
Besides, when i ask it about things like SRE, Cloud etc. its a very good starting point.
LLMs do already a lot better job at this. A lot faster, accurate enough and easy to use.
I can now study something alone which i was not able to do before.
No need for Nvidia to go first to an industry standard and neither for AMD.
Personally would be great its getting backported but its so far away from an normal use case.
its nice to be aware of this but this is so fastly different from a critisism point of view that i don't think that matters.
Can't find it quickly though.
Nvidias Omniverse is one of the core things though
AI doesn't need to learn everything, our LLM Models already contain EVERYTHING. Including ways of how to find a solution step by step.
Which means, you can tell an LLM to translate whatever you want, into a logical language and use an external logic verifier. The only thing a LLM or AI needs to 'understand' at this point is to make sure that the statistical translation from left to right is high enough.
Your brain doesn't just do logic out of the box, You conclude things and formulate them.
And plenty of companies work on this. Its the same with programming, if you are able to write code and execute it, you execute it until the compiler errors are gone. Now your LLM can write valid code out of the box. Let the LLM write unit tests, now it can verify itself.
Claude for example offers you, out of the box, to write a validation script. You can give claude back the output of the script claude suggested to you.
Don't underestimate LLMs