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blibblelast Sunday at 6:15 PM7 repliesview on HN

I don't see how nvidia come out of this stronger

their huge customers will be able to produce ASICs hat will be faster and cheaper to operate than their GPUs

jensen has to be the luckiest man in the world, first crypto, now "AI"


Replies

jonas21last Sunday at 9:19 PM

> their huge customers will be able to produce ASICs hat will be faster and cheaper to operate than their GPUs

Why? NVIDIA is better positioned to produce faster and more efficient ML ASICs any of their huge customers (except possibly Google). And on top of that, the fact that there is a huge library of CUDA code that will run out of the box on NVIDIA hardware is a big advantage.

Arguably, this shift has already happened. Modern NVIDIA datacenter GPUs, like the H100, only bear a passing resemblance to a GPU -- most of the silicon is dedicated to accelerating ML workloads.

throw234234234last Sunday at 10:32 PM

I think this is what the "circular financing" is all about actually. While you are in the 'picks and shovels' phase you want to use your high margins to buy up the value chain and become more vertically integrated. Effectively investing when the sun shines to diversify the company.

As a possibility for example I can see them transforming from a GPU based corp into a parent company for many full or partially owned "subsidiaries". They still manufacture chips to be "vertically integrated" but that becomes bread and butter as an enablement rather than the main story (e.g. Google TPU's). As their margins go down the value accrues to what they are owning (the business units/product areas).

vb-8448last Sunday at 6:23 PM

Nvidia is the Cisco of .com ... cisco still exists, and it's doing pretty well.

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pataponglast Sunday at 7:17 PM

> their huge customers will be able to produce ASICs hat will be faster and cheaper to operate than their GPUs

Are we sure this will be the case? Perhaps the sweet spot for hardware that can train/run language models is the GPU already, especially with the years of head start Nvidia has?

tim333last Sunday at 11:43 PM

They were working on adapting GPUs for machine learning back in 2005. The getting lucky with AI was preceded by a lot of preparation.

malux85last Sunday at 7:29 PM

Gaming, then crypto, then AI - all GPU hungry!

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