A theme snaking its way through conversations these days about generative AI is the need for open source models, open platforms, and industry standards as ways to make the emerging technology more accessible and widely adopted by enterprises. There is a growing number of open source models – or models …
Three years ago, thanks in part to competitive pressures as Microsoft Azure, Google Cloud, and others started giving Amazon Web Services a run for the cloud money, the growth rate in quarterly spending on cloud services was slowing. In the last few quarters, the rate of spending has begun accelerating …
With new generations of GPUs and other kinds of AI accelerators either shipping or soon to start shipping and new CPUs also soon to be available from Intel and AMD, and sales already at a historical high level at Supermicro, you might not be expecting for sales to bust through …
It is not a coincidence that the companies that got the most “Hopper” H100 allocations from Nvidia in 2023 were also the hyperscalers and cloud builders, who in many cases wear both hats and who are as interested in renting out their GPU capacity for others to build AI models …
A few years ago, it was hard to imagine how AMD would have survived without re-entering the datacenter with its CPU and GPU compute engines. And now, it is hard to imagine how the chip maker could have possibly thrived without a revitalized GPU compute engine business. Intel knows a …
When it comes to solving data analytics problems at scale, it is tough to beat the hyperscalers. And that is why a combination of technologies that were originally developed at Facebook (now Meta Platforms) and Netflix could end up being the perfect pairing to create a “lakehouse” underpinning AI training …
It would be hard to pick a worse time to not have an XPU offload engine that can do lots of matrix math at mixed precision and that can ship in volume. But this is precisely where Intel finds itself as there is a server recession in the datacenter. And …
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The energy sector is undergoing a monumental shift as the power grid struggles to accommodate growing demand and the complexity of modern energy systems. A major driver of this change is the increasing use of distributed renewable energy sources such as wind, solar and geothermal. These have very different location …
Commissioned: Thanks to recent technological advancements, there are many different sources of electricity available which can help organizations address our growing demand for energy from power hungry devices such as electric vehicles while reducing their reliance on fossil fuels like petroleum, coal, and gas. It’s a diversity that also presents …
It has been quite a week for Hashi Corp, the company behind the open source Hashi Stack of systems software for creating and running modern, distributed applications. First, on Monday the company was in the middle of transforming is business model with the Hashi Stack, and had a big event …
Not many devices in the datacenter have been etched with the Intel 4 process, which is the chip maker’s spin on 7 nanometer extreme ultraviolet immersion lithography. But Intel’s Loihi 2 neuromorphic processor is one of them, and Sandia National Laboratories is firing up a supercomputer with 1,152 of them …
Here is a paradox for you: Spending on infrastructure to support generative AI is apparently booming, as clearly evidenced by the skyrocketing revenues and profits of Nvidia. But spending on datacenter hardware is not changing all that much, and where spending is now forecast to be higher, it is in …
With large language models, bigger is better (and faster) but better is also better. And one of the key insights that the Meta AI research team had with the Llama family of models is that you want to optimize for the lowest cost, highest performance AI inference with any model …
Everyone is in a big hurry to get the latest and greatest GPU accelerators to build generative AI platforms. Those who can’t get GPUs, or have custom devices that are better suited to their workloads than GPUs, deploy other kinds of accelerators. The companies designing these AI compute engines have …
We have a long-standing joke that dates from the early 2000s, when the hyperscalers – there were not yet cloud builders as we now know them – started having hundreds of millions of users and millions of servers and storage arrays to run applications for them at the same time …
More than a decade ago, executives at Arm Ltd saw the energy costs in datacenters soaring and sensed an opportunity to extend the low-power architecture of its eponymous systems-on-a-chip that has dominated the mobile phone markets from the get-go and took over the embedded device market from PowerPC into enterprise …
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