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Cerebras is targeting a distinctly different point on the cost/latency curve. They are betting that there will be some high value applications where latency and not just throughput is super important.

by porridgeraisin8 hours ago|

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It is being used as part of a combined system. For example AWS is pushing for Trainium + WSE 3. The WSE 3 does the decode and the Trainium does the prefill.

Even in nvidia land rubin + LPU does a similar thing.

It has its downsides of course - if your traffic swings prefill heavy to decode heavy, you can't suddenly use your lpu for prefill. With GPUs they're totally interchangeable. Tradeoffs.

by Eridrus6 hours ago|

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AFAIK You can use WSE/LPU for prefill, it's just less efficient to do so.

by KaiserPro8 hours ago|

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> Well Sam Altman finally has built a moat against Chinese open weight AI

Hes got a press release.

The issue is, baking something to silicon requires discipline and about 2 years.

This isn't something you can just change your mind on halfway through. Trust me, I know. You need a clear vision of what you want to support, why and what bits of a chip you need to achieve that.

by SV_BubbleTime6 hours ago|

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And yet, the top comment is about “hardcoding” weights into the silicon.

Man, if only someone made like, chips that could lots of different calculations all at the same time!

by segmondy6 hours ago|

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I think the Chinese are going to be building their own chips aided with AI. DeepSeek, z.AI, MiniMax, Moonshot, etc, it's a race. The take off has really started.

by epolanski8 hours ago|

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> and after about 2 years and billions spent, the whole effort was scuttled b/c they simply could not keep up with the iteration and R&D cycles of dedicated chip companies

That sounds quite like...nonsense?

Chip companies work on years-long cycles. They know today what are they launching 4-5 years from now.

by brcmthrowaway9 hours ago|

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