Comment by HarHarVeryFunny | Hacker News Reader

Comment by HarHarVeryFunny | Hacker News Reader

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HarHarVeryFunny

The production bottleneck in a fab isn't the human workers - the process is mostly automated. The bottleneck more derives from how many wafers per hour you can process, which comes down to the etching process and EUV throughput.

ASMLs EUV machines are literally the most complex machine that mankind has ever built, which is why no other country, including the US, has yet been able to duplicate it. It's not just the machine itself, but a global supply chain of irreplaceable components such as focusing mirrors made by Zeiss to an incomprehensible level of accuracy - differences in surface height no more than the size of a hydrogen atom (or if you scaled the mirror up to the size of the country of Germany, then surface differences in height of 0.1mm).

Robots are useful to automate things, but they are zero help when trying to build tech like this that you are incapable of building in the first place.

The US has fallen way behind in manufacturing expertise, and no swarm of robots is going to help.

You've missed a part where it's TSMC that does behavioral cloning (to build more EUV machines). The full vertical integration is a bit farther down the line.

Etching a model's weights on silicon is another way to utilize non-top-notch tech-processes, while maintaining or improving performance. (and it suits robotics well)

TSMC doesn't know how to build EUV machines - they are stuck buying them from ASML like everyone else.

Putting a model's weights in read-only memory close to the processor is certainly a way to increase token/sec generation speed, but of course does nothing to increase intelligence. Robots aren't going to help though - semiconductor manufacturing is semiconductor manufacturing regardless of whether you are etching GPUs or memory onto your wafers.

Ah, sorry, it's ASML expertise that needs to be cloned and scaled up. I don't see how it changes things, though.

Robots don't need that much intelligence. High-speed joint control, "hand-eye coordination", the higher level tasks can be delegated to external models. Distillation already works quite well for isolating the required functionality.

I'm pretty sure ASML, and their supply chain, do have plans to increase production, as do the chip fabs - they all see the demand, while at the same time being leary of boom and bust which is the historical reality of the chip business.

But, the production expansion rate of none of these companies is being limited by lack of trained personnel, and if it were it would surely be faster to hire/train more humans since robots are still very far from human dexterity, not to mention intelligence.

Robots and AI are tools of automation, a way to replace humans with machines, but not all the problems in the world are bottle-necked by lack of humans, or the cost of humans.

Investing in training a person gets you one trained person. Investing in training an ML system gets you a cloneable ML system that can be scaled on demand much faster. ROI might change quickly.

Sure, but we're simply not at the point, maybe never will be, where lack of employees is the bottleneck to chip production. A fab takes billions of dollars and multiple years to construct - there are many constraints.

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