We can all talk until we are blue in the face about how weird it is for so much money to be spent on servers during the GenAI boom, but after reviewing the latest market report from IDC – which is one again but sporadically giving out some stats to the public – we thought that to feel the full impact of this change, we should draw you a picture of the past 26 years of server revenues by quarter so you can take it all in. …
We are still mulling over all of the new HPC-AI supercomputer systems that were announced in recent months before and during the SC25 supercomputing conference in St Louis, particularly how the slew of new machines announced by the HPC national labs will be advancing not just the state of the art, but also pushing down the cost of the FP64 floating point operations that still drives a lot of HPC simulation and modeling work. …
Nvidia may have cornered the market for the compute engines and networks that link them to train GenAI models, and the company has a very large share of the platforms that do inference, too. …
It is one thing for the market researchers of the world to make prognostications about hardware, software, and services spending relating to the GenAI boom. …
Every OEM in the world has two choices.
Choice One: Sell the Nvidia AI hardware and software stack and boost the top line while diluting operating income in their systems businesses. …
Unsurprisingly, the main topic of conversation at the recent Dell Technologies World 2025 event in Las Vegas was AI, and a central theme that wove through many of the messages we heard there was that adopting the emerging technology is much easier now than it was even a year ago. …
Back in February, Dell, the world’s largest server maker, told Wall Street that it was planning on selling and delivering $15 billion in AI servers in its fiscal 2026, when will end in early November. …
For much of the two-plus years since ChatGPT hit the market and kicked off the generative AI frenzy, the market tilted toward well-resourced hyperscalers like Google, Amazon Web Services, and Microsoft as well as Tier 2 cloud service providers, with powerful – and expensive – accelerators and massive large language models like Meta’s Llama with 405 billion parameters. …
It is funny how companies can find money – lots of money – when they think IT infrastructure spending can save them money, make them money, or do both at the same time. …
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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