Foundry leader Taiwan Semiconductor Manufacturing Company (TSMC) grew 37% year to date — and still lost four percentage points of the sub-sector's revenue share, because the other 26 manufacturers grew more than twice as fast.

Thirty-eight of 43 companies grew year to date at a median rate of 28.7% — the highest of any semiconductor sub-sector — with test handlers, sockets and probe cards recurring across company filings.

High-voltage direct current (HVDC) is currently one of the hottest areas of technology and product development for AI data centers. It is not only the first layer of what Nvidia CEO Jensen Huang has described as the industry's "five-layer cake," but also a concrete manifestation of the idea that computing power ultimately depends on electrical power.

The sub-sector's dominant supplier grew 37.9% year to date and still ranks only seventh of 20, while the other 19 companies grew 56.9% between them.

Tsinghua Unigroup's former "chip-to-cloud" expansion strategy unraveled after a debt crisis in 2020 and subsequent bankruptcy restructuring. Several projects originating in the group's earlier era have since entered disposal proceedings, and one of the former group's largest planned investments has now reached a formal end.

The two largest silicon wafer companies are the sector's slowest growers on a cumulative basis. Everything running fast sits downstream of them.

Scale and growth have decoupled. TSMC still supplies more than half the sector's monthly sales, but the growth table now belongs to DRAM, NOR flash and controller names.

Ardentec credits a new fab entering volume production for the sharpest monthly jump in the sub-sector; ELASER's revenue nearly doubled year on year on customer demand.

On February 20, 2026, Canadian AI chip startup Taalas unveiled its HC1 inference chip. Taalas said the chip ran the Llama 3.1 8B model at a single-user inference speed of 16,960 tokens per second, roughly 48 times the inference speed of an Nvidia B200 in the company's testing.

Around 2019, a friend working at a large cloud services provider excitedly shared that his team had trained a CNN model for document text recognition with good results, but the computing cost was too high to deploy directly. They then used distillation to train a smaller model for service, and it turned out to be highly effective.

Amid global supply chain restructuring and geopolitical rivalry, precious metals are no longer merely financial hedging tools but have become core assets supporting high-tech manufacturing and strategic material reserves.

As physical AI and robotics draw unprecedented market attention, a key bottleneck is clogging the deployment pipeline: quality, real-world physical data. To move applications from the lab to real-world deployment, companies are getting creative in overcoming this obstacle while balancing affordability, stability, and data volumes.

Chinese humanoid robot maker Unitree Robotics has drawn significant market attention with its IPO. Based on DIGITIMES' review of the company's three-hour IPO roadshow and Q&A session on August 7, chairman Xingxing Wang and the management team provided further details on humanoid robot commercialization, embodied intelligence, and its supply chain strategy.

Ken Phua, former Arm China co-CEO, spent 25 years abroad building someone else's business model. He came home to Singapore to build his own.

The speed of AI data center deployment is raising the bar for power and cooling suppliers. Chipmakers such as Nvidia and AMD are refreshing platforms annually, with each generation bringing sharp increases in power density and thermal requirements. Suppliers that cannot match that pace in R&D or capacity deployment risk missing the next design cycle.