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Well Sam Altman finally has built a moat against Chinese open weight AI. Well done. But what will this mean for Cerebras? I remember when Tesla was building it
by LarsDu88 1mo ago
Well Sam Altman finally has built a moat against Chinese open weight AI. Well done. But what will this mean for Cerebras?
I remember when Tesla was building its own inference chips, 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. I suspect the same will be the case with OpenAI vs Cerebras + Nvidia/Groq
- brcmthrowaway 1mo ago[dead]
- Eridrus 1mo agoCerebras 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.
- porridgeraisin 1mo agoIt 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.
- Eridrus 1mo agoAFAIK You can use WSE/LPU for prefill, it's just less efficient to do so.
- porridgeraisin 1mo agoWell ya, that efficiency is why it's split. There is also the other idea where you run your attention layer on the GPU/TPU/Trainium and the FFN on the SRAM accelerator. Because KV cache is more difficult on cerebras etc, while MOE latency is easier to deal with
- KaiserPro 1mo ago> 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.
- SV_BubbleTime 1mo agoAnd 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!
- epolanski 1mo ago> 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.
- segmondy 1mo agoI 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.