With US restrictions limiting its access to advanced tech, SenseTime is doubling down on open source with a new model optimized to run on Chinese-made chips. SenseTime, a Chinese AI company best known for its facial recognition technology, released a new open source model on Tuesday that it claims can both generate and interpret images far faster than top models developed by US competitors. SenseNova U1 could help the company reclaim lost ground after it slipped from its place among the leading players in China's AI development race. The model's secret sauce is its ability to "read" images without translating them to text first, speeding up the process and reducing the amount of computing power required. "The model's entire reasoning process is no longer limited to text. It can reason with images as well," Dahua Lin, cofounder and chief scientist at SenseTime, said in an interview with WIRED.

This supplementary material provides further elaboration and discussion on our work, including additional details that support our findings.

Say hello (Moto) to price hikes on all three of Motorola's latest Razr flip phones. Like clockwork, Motorola is back with a new set of Razr folding flip phones . The formula is the same as last year, with three phones differing in specs and price: the Razr Ultra, Razr+, and Razr. But alongside these models, Motorola is finally launching its first-ever book-style folding phone, the Razr Fold, which it first teased at CES 2026 . The company announced the new handsets at an event in Los Angeles, where it also revealed a new pair of Moto Buds 2 Plus wireless earbuds that look eerily like Apple's AirPods Pro, but in blue; these will retail for $150 and will be available on April 30.

We consider a non-convex constrained optimization problem, where the objective function is weakly convex and the constraint function is either convex or weakly convex. To solve this problem, we consider the classical switching subgradient method, which is an intuitive and easily implementable first-order method whose oracle complexity was only known for convex problems. This paper provides the first analysis on the oracle complexity of the switching subgradient method for finding a nearly stationary point of non-convex problems. Our results are derived separately for convex and weakly convex constraints. Compared to existing approaches, especially the double-loop methods, the switching gradient method can be applied to non-smooth problems and achieves the same complexity using only a single loop, which saves the effort on tuning the number of inner iterations.

The weaponry highlights a coastal Belgian city's longtime strategic location. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. Renovations on government buildings in the coastal Belgian town of Nieuwpoort are currently on hold after surveyors discovered an impressive archaeological trove: dozens of carefully crafted stone cannonballs dating as far back as the 14th century. However, the medieval ammunition backstock wasn't the only weaponry buried roughly 70 miles west of Brussels.

To help small aerial robots navigate in the dark and other low-visibility environments, my colleagues and I developed an ultrasound-based perception system inspired by bat echolocation. Current robots rely heavily on cameras or light detection and ranging, known as lidar, or both. But these sensors fail in visually challenging conditions, such as smoke, fog, dust, snow or complete darkness. I'm a scientific engineer who develops bio-inspired microrobots. To solve this challenge, my research team looked at nature's experts at navigating in poor visibility: bats.

However, this dance is an older male's game. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Attwater's prairie chickens live in coastal marshes. Breakthroughs, discoveries, and DIY tips sent six days a week. An exclusive dance party is raging in the coastal marshes along southern Texas--and it's coming to an end.

AI chatbots trained to be warm and friendly when interacting with users may also be more prone to inaccuracies, new research suggests. Oxford Internet Institute (OII) researchers analysed more than 400,000 responses from five AI systems which had been tweaked to communicate in a more empathetic way. Friendlier answers contained more mistakes - from giving inaccurate medical advice to reaffirming user's false beliefs, the study found. The findings raise further questions over the trustworthiness of AI models, which are often deliberately designed to be warm and human-like in order to increase engagement. Such concerns are accentuated by AI chatbots being used for support and even intimacy, as developers seek to broaden their appeal.

In this work, we consider the problem of matrix sensing over graphs (MSoG). As a general case of matrix completion and matrix sensing problems, the MSoG problem has not been analyzed in the literature and the existing results cannot be directly applied to the MSoG problem. This work provides the first theoretical results on the optimization landscape of the MSoG problem. More specifically, we propose a new condition, named the Ω-RIP condition, to characterize the optimization complexity of the problem. In addition, with an improved regularizer of the incoherence, we prove that the strict saddle property holds for the MSoG problem with high probability under the incoherence condition and the Ω-RIP condition, which guarantees the polynomial-time global convergence of saddleavoiding methods. Compared with state-of-the-art results, the bounds in this work are tight up to a constant. Besides the theoretical guarantees, we numerically illustrate the close relation between the Ω-RIP condition and the optimization complexity.