From the archive
AI hardware provides the computing power, memory and networks used to train and run artificial intelligence models. Follow news on GPUs, AI accelerators, data centres, chip design and energy demand. Read how changes in infrastructure affect performance, availability and cost, and distinguish measured results from vendor claims about what the next generation of computing will deliver.
Lead story
Durabook has announced the Z14I-DX3, a rugged Windows laptop with three built-in 14-inch touchscreens and optional NVIDIA graphics for AI work at the edge. It is less “laptop in a rucksack” and more “portable operations room with a keyboard”.
Read the report & discussion ↗TSMC Watch
Apple’s A20 Pro is the first Apple application processor made with TSMC’s N2 process, according to TechInsights. Its early analysis suggests the move to 2nm is being spent on more graphics and on-device AI capability rather than simply making the chip smaller.
Watch Desk
America’s AI expansion is running into local resistance, with roughly $130 billion in data-centre projects reportedly blocked or delayed during the first three months of 2026. The central point is not that the technology has stopped improving, but that the electricity, land and infrastructure needed to run it…
NVIDIA Watch
Apple has shown four Mac Studios working together to run a trillion-parameter model locally, putting a fresh question to Nvidia’s AI infrastructure dominance: how much inference and enterprise work might move from the cloud to desks and private servers? The immediate answer is that Nvidia’s core business still…
AWS AI Watch
Tata Elxsi says its IRIS platform uses edge computing and computer vision to spot industrial safety risks in seconds, rather than leaving operators to discover them minutes later. The important change is practical: cameras become an active warning system, while most raw video stays on site.
Watch Desk
Jared Palmer has released Kev, a family of small AI decision models that return answers such as yes/no probabilities, multiple-choice decisions and ratings instead of conversational prose. The practical point is compellingly unglamorous: developers can run these models locally for fast, repeated decisions without sending every request to…
ASML Watch
ASML is preparing larger photomasks, a second Eindhoven campus and higher EUV production as chipmakers plan increasingly large AI processors. The important point is that the next constraint on AI computing may sit in the machinery that prints chips, not only in the chips or models themselves.
Cerebras Watch
Cerebras Systems is turning surging demand for AI inference into rapid growth, but its latest figures also show why the wafer-scale chip company remains a high-risk bet. Revenue is climbing, yet losses, customer concentration and a premium valuation leave execution doing the heavy lifting.
Watch Desk
Apple is positioning its new Mac mini and Mac Studio computers as local AI machines for corporate buyers, taking aim at the cloud costs and hardware dominance of Microsoft and NVIDIA. The important shift is practical: companies could run demanding AI work on equipment they own, rather than…
TSMC Watch
TSMC is trying to expand across about 20 fabs, but a shortage of qualified construction and equipment-installation workers could slow how quickly new AI-chip capacity comes online. The constraint is not capital or ambition. It is finding enough people who can turn precision buildings, utilities and machinery into…
Watch Desk
AI sovereignty is not achieved by swapping one foreign chatbot for another, argues an O’Reilly Radar essay published on 22 September. Its central point is sharper: governments and institutions need open infrastructure across the AI stack if they want genuine control and the ability to change providers.
Watch Desk
Vast Data has announced DataEnclave, a confidential-computing environment designed to let businesses run advanced AI models on sensitive information without exposing the underlying data or intellectual property. The service is due to ship in the first quarter of 2027 as part of the company’s Vast AI Operating System,…
TSMC Watch
TSMC spent a record $15.59bn on capital expenditure in the June quarter, as the chipmaker expands capacity for an AI market that shows little sign of becoming modest overnight. The important detail is that the spending was covered by operating cash flow, while margins remained near record levels.
Watch Desk
TrendForce projects that US data centres could face a gap of more than 170GW between demand and grid-deliverable power by 2030, with serious bottlenecks emerging from around 2028. The useful point is less another giant number than the constraint it exposes: AI expansion may be limited by electricity…
Watch Desk
South Korean semiconductor-equipment maker Melcon plans a KOSDAQ listing on 15 October, aiming to raise up to 30.8 billion won for High-NA EUV development, extra production capacity and expansion into TSMC and HBM-related work. It is a useful reminder that the AI hardware race also depends on the…
Watch Desk
Compute:Arena has launched a public leaderboard and command-line tool for comparing local AI inference across models, quantisations, chips and runtimes. Its useful promise is simple: replace spec-sheet optimism with measurements tied to the exact model file and hardware combination.
TSMC Watch
TSMC says it plans to use ASML’s high-NA EUV systems in high-volume manufacturing from 2030, but the real breakthrough may be a much larger photomask. The shift from today’s 6-inch format to 12 inches is intended to solve the productivity problem that has made high-NA tools difficult to…
Watch Desk
Researchers have identified a shared geometric structure in independently trained vision and language models that could allow capabilities to be transferred in a single forward pass. The important point is not another marginal benchmark win, but a possible way to make models work together without retraining them from…
