It has been becoming increasingly clear – anecdotally at least – just how expensive it is to train large language models and recommender systems, which are arguably the two most important workloads driving AI into the enterprise. …
Changing the compute paradigm in the datacenter, or even extending it or augmenting it in some fashion, is no easy task. …
Sponsored Feature: It’s a decade and a half since researchers dazzled the tech world by demonstrating that GPUs could be used to dramatically accelerate key AI operations. …
Sponsored Feature: Humans have wanted to know what the weather is going to do since first we understood how the forces of nature determined our expectations of survival. …
While AI training dims the lights at hyperscalers and cloud builders and costs billions of dollars a year, in the long run, there will be a whole lot more aggregate processing done on AI inference than on AI training. …
Big Blue was one of the system designers that caught the accelerator bug early and declared rather emphatically that, over the long haul, all kinds of high performance computing would have some sort of acceleration. …
It seems like we have been talking about Google’s TPUv4 machine learning accelerators for a long time, and that is because we have been. …
Beijing-based hyperscale giant, ByteDance, owners of TikTok among other popular applications, have found that general purpose, open source recommendation engines fall far short of what is required for on-point real-time suggestions. …
Like everyone else on planet Earth, we were expecting for the next generation of graphics cards based on the “Ada Lovelace” architecture to be announced at the GTC fall 2022 conference this week, but we did not expect for the company to deliver a passively cooled, datacenter server friendly variant of the GeForce RTX 6000 series quite so fast. …
You can’t be certain about a lot of things in the world these days, but one thing you can count on is the voracious appetite for parallel compute, high bandwidth memory, and high bandwidth networking for AI training workloads. …
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