Quite complex algorithms are used to compensate and tune for pattern clarity and focus in high end semiconductor production.

Its a field that has used neutral networks before. (As people pushed down the size pre-EUV, apparently alot of wierd techniques were layered to produce features at or smaller than the wavelength)

But mistral just makes llms. There is no reason to believe experts in llm would be at all competent at quantom scale physics simulation and prediction.

It feels more logical to invest on the existing researchers and companies in the nanotechnology design field to adapt newer AI techniques.

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sroussey 6 days ago | parent [-]

Multi patterning to get effective smaller wavelengths has been around a while. It’s cheaper to reuse machines you already own, but slows down production.

OpenAI does more than LLMs, they have bio ML research etc. and Google has AlphaFold. It would not surprise me if Mistral had an ML team on physics related to work that ASML could use.

	▲	aDyslecticCrow 6 days ago \| parent [-]
		I suppose, but i don't feel like that makes mistral special enough to excuse this amount of funding. They would need clever researchers with resources to do research. The kind of AI we're talking about would likely not benefit from data-center scale training either. So why the 1.7B euro? That amount of money could fund multiple small dedicated research labs for exactly the domain ASML is interested in. I don't think it adds up if this is truly for multi-patterning or pattern exposure correction technology. As others mention it could be for entering and grabbing some value from down-stream technologies (actual investment expecting return of some sort) but it's odd how they skip over like 200 steps between their industry and the industry they invest in. Its like iron ore mine investing in precision screws. Its down the value added chain but such a massive leap that it makes me scratch my head.