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This is insanely fast, obviously a game changer over time. You should try the demo!

This seems to be using custom inference-only HW. It makes a ton of sense to use different HW for inference vs training, the requirements are different.

Nvidia, as far as I can tell, is focusing all-in on training and hoping the same HW will be used for inference.

Exciting times!

Hi there, I work for Groq. That's right. We love graphics processors for training but for inference our language processor (LPU) is by far the fastest and lowest latency. Feel free to ask me anything.

Are they only available on the cloud? Are you planning on releasing a consumer version?

Mostly available as a service via cloud API at the moment. The systems themselves are too big for consumers but we will sell systems to corporations.

What's the scale of hardware behind this demo, in terms of watts, transistors and cost?

Refuses to talk in my native language sometimes. When complies, makes basic errors in spelling and response is much shorter. Is it AI revolt?

conversation has moved to https://news.ycombinator.com/item?id=39428880