Viable Alternative of CUDA Moat, NVIDIA scared and working nights & weekends, Jensen’s Counter Submission, Kimi K3, Muse ...

We’ve since written multiple update notes to our Datacenter Industry Model subscribers showing off all the sites that can ...

There are now five companies besides OpenAI that have models that can beat GPT-3.5 in a variety of benchmarks: Mistral Mixtral, Inflection-2, Anthropic Claude 2, Google Gemini Pro, and X.AI Grok. More ...

The performance of the network connecting your GPUs together is often the gating factor for performance and as such, it is the highest cost aspect of the AI buildout after the accelerators themselves.

Subscription plans are still the primary way consumers and small businesses pay for AI. These plans are highly subsidized—as we previously explained in June—but can still make economic sense as ...

Huawei is making waves with its new AI accelerator and rack scale architecture. Meet China’s newest and most powerful Chinese domestic solution, the CloudMatrix 384 built using the Ascend 910C. This ...

Nvidia’s GB200 brings significant advances in performance via superior hardware architecture, but the deployment complexities rise dramatically. While on the face of it, Nvidia has released a standard ...

Not a week goes without another piece of datacenter FUD. We’ve already debunked in depth why moratoriums aren’t as impactful as one may think. Despite that, many still misunderstand the pace of the ...

The past two months have been a breakout period for open source AI. Yes, there was the “DeepSeek moment” back in January 2025, but no one actually used R1 to do any economically valuable work. In ...

When we published our first AMD software article, we gave AMD a 0% chance of closing the gap with Nvidia in AI accelerators. Software was broken, progress was unexciting, and we were the top bug ...