@atuntable@bindureddy I have a theory that it's already happening in a way. You see, all data used to train models ultimately originates in the human brain. All text, voice, even the imagery is produced by brains. The least path of resistance for the algos to model it is to build a brain-like entity
@atuntable@bindureddy We need to consider the overall cost of employing a brain. Then compare it to a machine doing the equivalent intellectual labor - which nowadays is a single PC for about $2K paid once and running the latest Chinese model. Same speed for math, coding, etc. But it never gets tired.
@rohanpaul_ai You might need to go as far as to basically build a complete biological cell to obtain that 100% compliant artificial neuron, so next to impossible. And what if you replace 50%, 90% of neurons? Then there's the question if what you produced isn't just a p-zombie.
@mrandersoninneo@bindureddy There is some space for improvement, it's why quantization still works. But nature seems to be going the opposite direction. It's easier for evolution to duplicate alleles and carry around junk DNA than to compress and optimize it.
@lost_in_tech With FreeCAD and Python, combined with modern AI codegen, you get a really powerful tool for free. Stuff like optimizing parts dimensions to make an assembly move in a given path; or the same with FEA to maximize rigidity.. and that's just what I did for fun.
@sippicup2@pud But I don't want to solve basic bugs, or any. I want thoughts materialized without friction. Of course I'm lazy, that's the point of, you know, technology.