The Nvidia DGX Spark is a so-called “supercomputer” built for AI — but what does that mean, and why would you want one?

Semiconductor packaging is rapidly advancing, but how will it impact AI?

There might be movement from vendors like Nvidia and AMD, but supply issues run a whole lot deeper A few short years ago, it would have been hard to predict …

Custom inference chips could help drive down soaring costs — but Nvidia isn’t going anywhere soon While AMD and Nvidia battle for AI accelerator supremacy, hyperscalers and other major players …

AMD’s 2nm leap is real, but Nvidia’s dominance runs deeper than silicon In sum – what to know: AMD jumps to 2 nm first – The Instinct MI450 will be …

Today’s top stories focus predominantly on the big players: OpenAI, AMD, Nvidia, et al. They highlight a major trend in AI semiconductors – Nvidia is the reigning champ right now, …

With a 50 TOPS NPU and 180 TOPS unified XPU, Intel is betting on local AI inference — but does it matter? In sum – what to know: Intel’s Panther …

Intel is betting on its new 18A process and integrated AI engines to redefine the PC roadmap, while TSMC’s latest earnings show that demand for AI chips remains the industry’s …

AI hardware is entering its integration phase, where performance gains come from how chips, systems, and infrastructure fit together. From 3D design to AI mainframes, the stack is getting smarter …

It’s not all about packaging — future AI semiconductor performance gains will still come from transistor-level innovations too.