Key TakeawaysNavitas Semiconductor fell 15% today, along with STMicroelectronics and onsemi, as AI chip stocks extended their post-midterm slide. Navitas had no news of its own, and its third-quarter revenue rose 33% from the second quarter.
US stock markets face a massive selloff as AI and technology stocks plunge, wiping out earlier market gains. The Nasdaq hits its lowest level since April 2025, while fears grow over a possible data center moratorium following the Democrats' election victory.
At the end of 2025, its debt-to-equity ratio was approximately 0.2x, and its current ratio was 2.5x. TSMC generated roughly $32 billion in free cash flow during the year, despite investing more than $40 billion in capital expenditures.
By Noel Randewich and Utkarsh Hathi Nov 5 (Reuters) - The Nasdaq Composite tumbled on Thursday, on track for its deepest one-day drop in 19 months and set to confirm it was in a correction, as chipmakers sank on fears of tougher AI regulation after Democrats won control of the US Congress.
Kimi K3.1 Pro is an open-weight, natively multimodal agentic model, and our most capable 3T-class model to date. Post-trained from Kimi K3 with large-scale joint reinforcement learning across hundreds of downstream domains, it is the first model in the K3.1 series. With a…
Web Answer on Amazon Bedrock AgentCore returns a synthesized, source-cited answer to a natural-language question in a single tool call, with no search, retrieve, synthesize, and citation pipeline to build. Learn how it works and how to add it to an AgentCore Gateway and call it…
Benchmarking is an increasingly critical part of research in machine learning and the domains where it is applied, including healthcare. Yet, despite the steady development of new ultrasound foundation models in recent years, the development of well-designed benchmarks to…
Reinforcement learning with verifiable rewards (RLVR) supervises mathematical reasoning through final-answer correctness, but provides little guidance on individual tokens. On-policy distillation (OPD) supplies dense feedback on student-generated responses, yet teacher…
Role-playing agents based on large language models have been widely applied in areas such as personalized assistance and social simulation. Recent RL methods typically train on a fixed scenario pool collected before learning begins. This creates a distributional bottleneck: as…
We study the application of large language models (LLMs) to the visual exploration of textual corpora. We introduce zero-shot visualization (ZSV), a task in which users specify concepts in natural language and documents are mapped onto the corresponding concept axes for…