DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks. Alongside these gains, the model reduces task execution time and output length, enabling users to complete…
Figma introduces Figma Specs, code layers in open beta, MCP integrations, and Payload CMS features to help AI agents adhere to brand design system rules.
Elon Musk's comments during SpaceX's Q3 earnings call about rapidly expanding AI computing capacity sparked a premarket rally in chip stocks including NVIDIA, Intel, and SanDisk. Musk expects to increase SpaceX's AI compute power to 2.5-3 gigawatts by year-end and add up to 13 gigawatts in 2027, signaling strong future demand for AI chips. Despite this, the rally's sustainability remains uncertain as Musk leases compute capacity on spot market rates without long-term contracts. The market will…
Many companies cannot say what their AI agents did yesterday. Two former Doppel engineers built an open-source tool that records what agents do, and a Wall Street trading firm discovered them while testing it on its own machines. Asymptote Labs just raised $5.5M to turn that record into real-time defense.
SpaceX just told investors its AI compute pays back faster than almost anyone expected, and now Michael Burry is betting that confidence will crack. Two earnings reports in the coming weeks will decide who is right.
One quote from Elon Musk sent chip stocks surging in premarket trading, but whether that momentum signals a real turning point or just a brief relief rally is what the rest of October will decide.
People adapt how they talk to the person in front of them. However, chat models tend to respond in Standard English regardless of the dialect used by the user. A uniform answer can hide whether training treats these users alike, and output audits cannot tell as well. We trace…
Human mobility data are fundamental to Web-based location services and broader urban applications, and mobility generation provides synthetic trajectories when real data are costly or inaccessible. Although recent mobility generators have incorporated collective mobility…
Joint-Embedding Predictive Architectures (JEPA) offer an appealing approach to self-supervised learning, but are typically prone to representation collapse. LeJEPA resolves this by introducing a theoretically grounded distribution-matching objective that drives the embedding…
General-purpose multimodal models have shown promise as direct robot action policies, yet whether they grasp the physics underlying real-world interactions and can apply that understanding to guide action remains underexplored. We investigate this question using contact-rich…