One only need look at the incredible revenues and profits of the datacenter business at Nvidia to know that the world’s biggest compute customers – the hyperscalers, the cloud builders, and now the biggest model builders – need to bend the price/performance curve to boost their own profits. …
Big Blue may have missed the boat on being one of the big AI model builders, but its IBM Research division has built its own enterprise-grade family of models and its server and research divisions have plenty of experience building accelerators and supercomputers. …
“If you build it, they will come,” as we all learned from watching Field of Dreams two and a half decades ago. …
Rather than measure the funding rounds and valuations of AI startups building foundation models in US dollars, perhaps we should just convert that right into GPU-hours rented to train models, since this accounts for the vast majority of spending that OpenAI, Anthropic, and a handful of others do in their day to day operations. …
If Amazon is going to make you pay for the custom AI advantage that it wants to build over rivals Google and Microsoft, then it needs to have the best models possible running on its homegrown accelerators. …
If Microsoft has the half of OpenAI that didn’t leave, then Amazon and its Amazon Web Services cloud division needs the half of OpenAI that did leave – meaning Anthropic. …
It is a strange time in the generative AI revolution, with things changing on so many vectors so quickly it is hard to figure out what all of this hardware and software and people-hours costs and what it might be worth when it comes to transforming, well, just about everything. …
It takes big money as well as big ideas to compete in the generative AI space. …
We read a fairly large number of technical papers here at The Next Platform, and it is a rare thing indeed when we can recommend that everyone – or damned near everyone – should read a paper. …
All Content Copyright The Next Platform