I find MacOS terrible (any version) and wish my employer would not force Mac upon me. I hope one day we will be able to use Linux on Mac hardware (in enterprise setting).
Something like it but with (large) in-memory computation would be a welcome addition. Ability to run LLMs on edge platforms needs to be addressed. The question is: will it take 1 or 10 years.
Sadly the coral was already outdated when released.
I can definitely write better code with copilot due to faster iterations and much better code coverage. I believe we are a paper away before this can start improve of existing code itcluding the code of itself.
How would it know what a better version of itself were? Seems like that's a particularly human instinct. It requires a certain level of introspection and purpose, coupled with desire, ambition, a goal etc.
> Create a list of test cases by which you can benchmark yourself against
> Create an architecture for an LLM that passes 99%+ of those test cases
Then use an evolutionary algorithm based on those <1% of cases to create the next batch of tests. Keep a running record of all created tests and make sure the new model can still pass all of them. Add some randomness/branching into those tests and I think you’d have a recipe for an effective AI. I think Deepmind did something like that with AlphaStar and their tournament system.
I haven't looked too deeply into it, but as I understand it you would basically create branching tests (like an evolutionary tree) where the AI would need to solve all of those tests in order to move on to the next level of tests
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