The boundary for adopting external capacity is changing, as workloads that previously needed memory offload because of insufficient high-bandwidth memory (HBM) can now run directly on next-generation GPUs. As a result, demand for external capacity is shifting toward scenarios with higher memory requirements and deployments designed to extend the usable life of existing GPUs.
Elon Musk has moved to quell uncertainty over Intel's position in the Terafab chip project, stressing that his companies will build and operate the planned semiconductor complex themselves while limiting any potential TSMC involvement to subleasing part of the site.
Largan Precision will hold its earnings call on October 8, when the optical lens maker is due to report third-quarter results and outline its fourth-quarter outlook. With September revenue recovering and the company stepping up property acquisitions, investors are likely to focus on three issues: progress in co-packaged optics (CPO), capacity expansion and the pace of fourth-quarter customer orders.
The ferocious push toward artificial intelligence is gathering momentum amid growing industry demand for higher AI inference and increasingly compute-intensive models.
The recent summit between US President Donald Trump and Chinese President Xi Jinping concluded without progress on automotive issues—namely, whether Chinese automakers might enter the US market or build manufacturing plants on American soil. While the prospect had previously sparked anxiety among American, European, and Japanese carmakers, the topic yielded no tangible breakthrough during the talks.
China's National Day holidays have opened one of the fourth quarter's most important promotional windows for consumer electronics. For smartphones, the timing is especially significant: Apple, Xiaomi, Vivo, Oppo and Honor have all launched new models since September, while Huawei introduced its Mate 90 series on October 1.
As Elon Musk's Terafab ambitions advance, the realities of modern silicon manufacturing become increasingly apparent, prompting Musk to enter talks with industry mainstays like Intel and TSMC for assistance.
Singapore is building a semiconductor R&D hub by attracting both multinational investment and overseas research talent. Dr Yu-chieh Chien, a Taiwanese scientist at the Agency for Science, Technology and Research's Institute of Microelectronics (A*STAR IME), is one example.
As the number of AI computing transistors integrated within a single CoWoS package rises rapidly, DIGITIMES observes that moving massive volumes of data to compute chips fast enough is becoming increasingly critical to fully utilizing available computing power.
This excerpt from DIGITIMES analyst Luke Lin's podcast looks at TSMC's rumored Texas expansion, Intel's 14A and 18A process debate, and Qualcomm's high bandwidth compute (HBC) push as AI workloads drive demand for hybrid bonding and advanced packaging.
The rapid iteration of AI-capable hardware, following an industry-wide push toward integrating AI-processing capabilities into PCs, is bringing renewed attention to what AI could offer as its presence extends further into the notebook market. But beneath the expanding promise of these machines lies a less straightforward question: what is actually compelling buyers to bring them into their businesses and homes?
Data center AI accelerator package power has climbed from about 500W in the A100 generation to roughly 3,500–4,000W for Rubin Ultra-class products expected in 2027, pushing supply current into the thousands of amperes. In conventional frontside power delivery, current must cross the full metal interconnect stack before reaching the transistors, while power and signal lines compete for routing resources. Intel Foundry estimates that raising a single compute package from 1kW to 5kW increases power delivery network I²R losses from 89W to 2,222W, cutting the share of input power reaching the transistors from 66.0% to 41.8%.
When the underlying economics of infrastructure commitments meet the financing muscle of the companies supplying foundational compute, the traditional boundary between supplier and customer begins to blur.
New AI models arrive every few weeks, and the question of which is better often comes down to the leaderboard. Behind those rankings, evaluation can look like an academic exercise in setting rules, running tests, and assigning scores. However, public benchmarks—and strong placement on them—have long been tied to a lucrative business, with money flowing to different players in different eras.
Advanced Micro Devices (AMD) has agreed to acquire World Labs in an all-stock transaction valued at approximately US$8.2 billion. Following the closing, World Labs will operate as a dedicated frontier research organization for large language models (LLMs) and spatial intelligence, with founder Fei-Fei Li joining AMD as executive vice president and chief scientist, reporting directly to Chair and CEO Lisa Su.
