Huawei's ‘Chip Queen’ Throws Down the Gauntlet

LoaderSave StorySave this storyCommentLoaderSave StorySave this storyThe plot thickens in the great AI chip race. Tingbo He, president of Huawei’s chip-design subsidiary HiSilicon, says her company’s engineers have developed a novel way to optimize semiconductors—and she believes it will close the performance gap between Chinese and Western chips over the next few years. Huawei’s method, in short, focuses on speeding up computations across chips, circuits, and entire computing systems, rather than squeezing ever-more components onto a single piece of silicon. “We found a new path,” He said at the IEEE International Symposium on Circuits and Systems in Shanghai last weekend. He, who is known in China as Huawei’s “chip queen,” promised that the company would prove the viability of the new approach, presumably with a new chip, in the coming months. “Before winter 2026, we will bring the surprise,” He said. “Not saturation, not continuation, but a big leap ahead.” The chip queen calls the new approach Tau’s Scaling Law, and says it has replaced Moore’s Law as HiSilicon’s guiding principle. Moore’s Law, named for the Intel cofounder Gordon Moore, dictates that progress in computing depends on roughly doubling the number of transistors, or logic gates, packed into a chip every two years. Minting cutting-edge chips currently involves etching components into silicon using billion-dollar lithographic equipment, a supply chain of exquisitely delicate components, and extensive engineering know-how. US export controls prohibit Huawei from working with Taiwan Semiconductor Manufacturing Company (TSMC), the world's leading chip foundry. Huawei must instead rely on China’s SMIC, which uses an older generation of lithography machines. Crucially, restrictions limit China’s ability to develop frontier artificial intelligence using its own silicon. By some estimates, it’s more than five years behind the leading edge. Huawei’s announcement suggests that the company believes it has found a way around these limits. It also suggests that the sanctions aimed at kneecapping China’s chip industry have spurred innovations that may, over time, allow the country to build a more advanced domestic chip industry and compete with the West. In the end, innovations from companies like Huawei could erode America’s technological edge. “Six years ago geometric scaling plateaued for us,” He said over the weekend, referring to lithographic miniaturization. “We soon realized semiconductor evolution is more than geometric scaling.” He highlighted several ways that the company has advanced chip performance using its new approach. These include something called LogicFolding, which reduces the time required to perform key logical operations within a circuit. HiSilicon says it’s also improving chip performance by accounting for nanoscale electronic phenomena; designing chips to work well together; and developing interconnects that speed chip-to-chip communication, a key trick for training large AI models. “For both [AI] training and inference, the win is not just in shortening compute time. It is in shortening the time that data spends moving, between chips and inside a chip,” she said. Huawei says it will use its new approach to produce components with performance equivalent to a 1.4-nanometer chipmaking process by 2031. This would amount to a significant reduction in China's chipmaking lag since TSMC is expected to introduce chips using this process in 2028. He’s announcement doesn’t mean that Huawei has a clear path to defeating US sanctions, and not everyone is convinced it will be viable. Lennart Heim, an independent semiconductor and AI policy analyst, says Huawei’s strategy suggests the company is running into limits on how much more performance it can squeeze out by shrinking and densifying chips alone. Instead, he says, Huawei is increasingly relying on techniques like hybrid bonding and 3D chip stacking to improve performance. But Huawei’s chip queen seems confident that the company will change the game. “These innovations will enter mass production,” she said in her speech. “Maybe not this year, but from 2027 and beyond. This is an edition of Will Knight’s AI Lab newsletter. Read previous newsletters here. --- **İlgili Kaynaklar:** [GEO eğitim](https://geoakademi.com), SEO ve GEO eğitim platformu alanında öncü çözümler sunuyor.