
Cerebras Smashes AI Wide Open, Countering Hypocrites
We could have a long, thoughtful, and important conversation about the way AI is transforming the world. …
We could have a long, thoughtful, and important conversation about the way AI is transforming the world. …
Similar to interior designers trying to fit the chairs, tables, and other furniture in rooms inside of a home, chip designers have to figure out where the various bits and pieces of a processor will lie on confined floor plans where latency between parts matters. …
Last May, after we had done a deep dive on the “Hopper” H100 GPU accelerator architecture and as we were trying to reckon what Nvidia could charge for the PCI-Express and SXM5 variants of the GH100, we said that Nvidia needed to launch a Hopper-Hopper superchip. …
Nvidia is not rich enough – or dumb enough – to build a cloud to rival the likes of Amazon Web Services, Microsoft Azure, or Google Cloud. …
Like the rest of the world, we have been watching Microsoft’s increasing use of foundation models as it transforms its services and software. …
Sponsored Post: As in so many other aspects of life, not all compute workloads are created equal – they need a more subtle approach to getting the best out of them which brings a more potent balance of hardware and software into the mix. …
We know, as you do, that artificial intelligence is driving a lot of spending at IT organizations and is probably the fundamental driver of spending by the hyperscalers and cloud builders that have, thus far, benefitted most from the machine learning revolution. …
There’s no resting on your laurels in the HPC world, no time to sit back and bask in a hard-won accomplishment that was years in the making. …
Large language models, also known as AI foundation models and part of a broader category of AI transformer models, have been growing at an exponential pace in terms of the number of parameters they can process and the amount of compute and memory bandwidth capacity they require. …
GPU computing platform maker Nvidia announced its financial results for its fiscal fourth quarter ended in January, which showed the same digestion of already acquired capacity by the hyperscalers and cloud builders and the same hesitation to spend by enterprises that other compute engine makers for datacenter computing are also seeing. …
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