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
AWS has published a SageMaker deployment guide for Qwen3-TTS-12Hz-1.7B-Base, allowing developers to clone a speaker’s voice from a short recording and generate new speech in ten languages. The practical shift is from model demo to managed endpoint, with the usual small print that voice identity deserves rather more…
Read the report & discussion ↗Watch Desk
Robert O’Callahan, a Google DeepMind engineer in New Zealand, has resigned after concluding that his team’s work on chip-design tools would help accelerate AI development he believes is already moving too quickly. His departure matters because it shifts the AI-safety argument away from model researchers and towards the…
Watch Desk
The AI infrastructure boom is expected to attract an estimated $10.3 trillion in investment through 2032, according to Axios’s account of new research. The crucial point is that the buildout is no longer just a technology-sector wager: it is beginning to compete with governments, businesses and households for…
ASML Watch
ASML says chipmakers are accelerating capacity plans as AI demand drives stronger orders for advanced logic and memory, while a surge in software-led upgrades is helping customers get more output from machines already on the factory floor. The company’s Q2 results point to a semiconductor bottleneck being attacked…
Microsoft AI Watch
Microsoft says it will invest more than $10bn in cloud and AI infrastructure across Kuwait, Qatar, Saudi Arabia and the UAE by 2030. The plan matters because the company is tying its regional AI expansion to local partnerships, digital resilience, skills and the unglamorous physical limits of data-centre…
TSMC Watch
TSMC’s CoWoS-L remains the dominant advanced-packaging technology for AI chips, but Samsung Electro-Mechanics and LG Innotek are preparing alternatives rather than waiting for one winner to rule the wafer. The important shift is that AI hardware competition is moving beyond chip design and fabrication into the packaging that…
ASML Watch
ASML and TSMC are backing a transition from six-inch to 12-inch EUV photomasks, with a pilot line targeted for 2031 and possible High-NA production by 2033. It is a long-range manufacturing change, but it could affect how efficiently the industry makes the denser chips demanded by AI and…
AMD Watch
AMD has crossed a US$1 trillion market value as investors pile into its AI hardware story, but the milestone is also a test: can revenue, supply and market share justify the price? The chipmaker remains far smaller than Nvidia in AI accelerators, so this is a bet on…
Watch Desk
AI infrastructure companies are borrowing billions for GPUs just as rates and investor scepticism are making that debt harder to place. The practical twist is that many large borrowers have hedged much of their floating-rate exposure, so the immediate danger is less a sudden rate shock than the…
Watch Desk
Qualcomm and Amazon are expanding their partnership to build custom AI inference chips and high-speed optical networking for Amazon Web Services data centres. The important detail is the money-shaped incentive: Amazon received a warrant for up to 25 million Qualcomm shares, with vesting tied to commercial milestones rather…
Watch Desk
Liquid AI has released an experimental draft model that it says can accelerate its LFM2.5-VL-3B vision-language model by up to 3.13 times on an Apple M5 Max. The important bit is not merely a larger benchmark number: the release brings speculative decoding to a model designed to understand…
Watch Desk
Aetina has launched industrial MXM accelerator modules built around NVIDIA RTX PRO Blackwell Embedded GPUs, bringing generative and physical AI hardware into compact systems for robots, manufacturing and medical equipment. The practical significance is edge deployment: more AI processing can happen near the machine, rather than making every…
Watch Desk
AI’s appetite for server memory has pushed the estimated value of DRAM per square millimetre above the nominal wafer price of TSMC’s leading-edge 2nm process, according to analysis from Kurnal Insight reported by BigGo Finance. The comparison is imperfect, but it captures a real shift: in the AI…
Watch Desk
A Hugging Face Community Article describes a CPU-only pipeline that turns raw genomic sequences into a structured, analysable corpus for biological AI research. The useful bit is not another grand claim about models, but the plumbing: 32.4 million records are enriched with sequence length, GC content, coding status…
Watch Desk
Minneapolis is preparing to review its data-centre rules while a local moratorium covers larger facilities, putting AI infrastructure’s appetite for electricity and water directly into a city planning debate. The useful detail is unusually concrete: one local data centre’s monthly water use rose from about 334,000 gallons to…
TSMC Watch
Siemens and TSMC are expanding a collaboration that puts AI agents into semiconductor design, including automated fixes for design-rule violations. The practical significance is not another chatbot perched beside an engineer, but software intended to inspect, reason across and improve parts of the route from chip design to…
AMD Watch
AMD has filled in much of the picture around its Zen 6-based EPYC Venice server processors, including a 256-core flagship, faster memory and a direct performance challenge to NVIDIA’s Vera CPUs. The important point is not one spectacular benchmark, but a broader platform aimed at general-purpose computing, HPC…
