Nuvacore, a six-month-old San Jose chip startup with no product yet, is raising hundreds of millions of dollars at a valuation of about $2.5bn, Reuters reported on Friday. The round has not closed and the company declined to comment.
Ting-Wei Sun, the contractor prosecutors call a fixer, has pleaded guilty to four counts in the case over about $2.5bn of Nvidia-powered servers sent to China. Super Micro's co-founder, charged in March, has pleaded not guilty.
The maker of the lasers that move data between AI servers says it cannot build enough to meet demand until early 2029. In March the date was the end of 2027. New factories take years, and its customers are now helping to pay for them.
GlobalFoundries will make silicon interposers, the slabs that AI processors and their memory sit on, for TSMC at its plant in upstate New York. The $2bn agreement gives GlobalFoundries a part in the AI packaging bottleneck, though volume production does not start ramping until 2028.
Blaize, the AI chip company that listed through a SPAC last year, says it booked about $0.5m of revenue in the third quarter and cut its outlook again. The full-year number now depends on a customer that has paid $0.2m of a $13.3m bill due in September, and on inventory the company needs cash to buy.
Micron will pay Netlist $600m over five years to end every case between them, six days after Netlist asked the ITC to block Micron's high-bandwidth memory and named Nvidia, Broadcom and Google as respondents.
A projection putting the data-centre AI chip market at $860bn in 2030 has travelled a long way since Sunday morning. It has an author, the research arm of Korea's export credit agency; a policy conclusion it was written to support; and a base year two years stale. Nvidia booked more data-centre revenue in six months than the forecast's entire starting market.
Micron reports on 30 September with a gross margin of 84.6 per cent already on the record and $18bn of customer cash deposits committed behind it. Almost none of the gain came from making more; it came from charging more. Whether a Chinese supply wave can break that is the argument, and the answer is in a filing rather than an interview.
Nvidia's outlook for the quarter now ending books no data-centre compute revenue from China at all. That is the company's own sentence, not an inference — and it turns the largest market it is barred from into something closer to a free option than a hole.
Claude Opus 5.5 quietly declines to do kernel work for certain machine-learning accelerators, and independent testers say Huawei's and Amazon's are among them. What Anthropic has actually written down is a classifier in a help article, not a term in a contract.
At SEMICON India, the pitch was not cost or scale. It was that supply chains are being weaponised and India is the destination that will not do the weaponising.
Semiconductor revenue reached $425bn in three months, a record 31.4% rise on the previous quarter. Memory and price, not volume, did most of the work.
Justice Department reviewers are looking at whether a $20bn arrangement was designed to deliver an acquisition's effect without triggering an acquisition's review.
A domestic supplier now sells into chipmaking equipment and has passed DRAM certification. The crucible that grows the ingot still comes from one town in North Carolina.
A forecast taking AI-related chip revenue from $2.6bn to $230bn in six years describes a supply chain, not a product cycle — and the supply has already been bought.
A memory supply agreement is widening toward foundry work, and the number attached to it — 900,000 DRAM wafer starts a month — is the part worth holding on to.
The largest purchasers of AI accelerators are now shipping their own silicon at volume, which changes the negotiation more than the benchmark.
The rulemaking has slowed while the penalties have grown. The policy is now being made in settlement agreements rather than in the register.
Packaging capacity, memory, and power components are the constraints that now shape delivery schedules more than leading-edge logic.
Capable local models are shifting latency-sensitive and private workloads onto consumer hardware, with consequences for chipmakers and cloud bills alike.