Comment by Marha01
15 days ago
> Aren't we still like a decade away from an Argon model being able to run on battery power for any reasonable amount of time that would fit on a robot that isn't the size of a school bus?
Sooner or later, the models will stop improving. After that happens, the best models will be etched into model-specific ASICs with weights fixed in mask ROM (like Taalas is already doing), which will result in massive, at least order of magnitude inference efficiency increase.
They said the same thing for transistor density in new chip nodes. It took 40 years of doubling every 2 years to finally hit a wall.
And although the industry hit a wall in density/area, they switched to scaling in 3D or glueing chiplets together. Moore's Law is still working if you change the definition to transistors/integrated circuit.
Transistors doubled for so long, but pretty much no other technology has come close, so it’s not like going to improve for very long, which is far more common. Transistors only did it due to a quirk in physics, that of electrons being long lasting, super tiny, and fairly controllable. We’re out of such particles to make another set of leaps.
For data bound things, there’s also fundamental laws of information theory, far stronger than physics theories, since they’re theorems about math. And LLMs can only compress knowledge so far, and we’re about at it now.
That doesn’t help the RAM situation