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Deep learning and AI systems have made great headway in recent years, especially in their capabilities of automating complex computational tasks such as image recognition, computer vision and natural language processing. Yet, these systems consist of billions of parameters and require great memory usage as well as expensive computational cost.
Mistral AI partners with Nvidia to launch European AI infrastructure platform, challenging US cloud giants while unveiling breakthrough reasoning models that rival OpenAI.Read More
Air-fried taters and corn cobs are a silly but welcome indulgence on the newest griddle from Blackstone.
A team of engineers, AI specialists and chip design researchers at the Chinese Academy of Sciences has designed, built and tested what they are describing as the first AI-based chip design system. The group has published a paper describing their system, called QiMeng, on the arXiv preprint server.
Every report generated by Deep Research includes clickable citations to underlying content, enabling both verification and deeper follow-up.Read More
Looking to go organic with your bedding? These are the best sheets to sleep on, from cotton percale to bamboo and linen.
Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables, and therefore have predictive power when it comes to complex physical systems. Solving these equations is a perpetual challenge, however, and current computational techniques for doing so are time-consuming and expensive.
Apple researchers develop STARFlow, a breakthrough AI image generation system that challenges diffusion models used by DALL-E and Midjourney with competitive performance.Read More
Apple took a measured approach to AI at WWDC. A new research paper suggests the company is skeptical about some recent AI advances, too.
Researchers have unveiled a robotic hand, the F-TAC Hand, which integrates high-resolution tactile sensing across an unprecedented 70% of its surface area, allowing for human-like adaptive grasping. This pioneering development, published in Nature Machine Intelligence today, represents a significant leap forward in robotic intelligence and its ability to interact with dynamic real-world environments.