The AI boom has been very, very good to Taiwan Semiconductor Manufacturing Co, which is positioned to do well if Nvidia continues with its hegemony over AI training and inference or if the rebel alliance forms behind AMD or if the hyperscalers and cloud builders dedicate a substantial portion of their capital budgets to etching and packaging homegrown compute engines. …
As part of the pre-briefings ahead of the Google Cloud Next 2025 conference last week and then during the keynote address, the top brass at Google kept comparing a pod of “Ironwood” TPU v7p systems to the “El Capitan” supercomputer at Lawrence Livermore National Laboratory. …
Making a graphics card for gamers is one thing, but manufacturing a rackscale supercomputer with over 600,000 components that burns 120 kilowatts of power, that has over 5,000 copper cables for an all-to-all interconnect mesh for 72 dual-chip compute engines, and that weighs over 3,000 pounds is another thing entirely. …
Beleaguered chip maker Intel has been looking for ways to capitalize on non-core, not large, but profitable parts of its business to raise funds for its ambitious plans to revitalize Intel Foundry and to also invest heavily in the Intel Products group. …
SPONSORED FEATURE: Back before there were AI factories, there were two generations of the AI Bridging Cloud Infrastructure supercomputer, built by the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. …
The HPC centers of the world like fast networks and compute, but they are also always working under budget constraints unlike their AI peers out there in the enterprise, where money seems to be unlimited to what sometimes looks like an irrationally exuberant extent. …
SPONSORED CONTENT When it comes to artificial intelligence, context is everything. …
If you want to be a leading in supplying AI models and AI applications, as well as AI infrastructure to run it, to the world, it is also helpful to have a business that needs a lot of AI that can underwrite the development of homegrown infrastructure that can be sold side-by-side with the standard in the industry. …
Compute engine makers can do all they want to bring the performance of their devices on par or even reasonably close to that of Nvidia’s various GPU accelerators, but until they have something akin to the NVLink and NVSwitch memory fabric that Nvidia uses to leverage the performance of many GPUs at bandwidths that dwarf PCI-Express switches and latencies that dwarf Ethernet interconnects, they can never catch up. …
Spending on AI systems in 2024 just utterly blew by the expectations of the major market researchers and those who dabble in metrics like we do. …
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