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…
One of the most effective ways to protect the environment is to make markets work for environmental goals rather than against them, using tools such as tradable permits and payments for ecosystem services. But doing that requires measurements and data: How much of a resource…
Chinese AI start-up DeepSeek has announced the open-sourcing of its internal inference framework, DeepInfer, to help software developers and enterprises optimize throughput and latency for large-scale inference, lowering compute costs and energy consumption, the company said in an article released via its WeChat account on Tuesday.
Despite recent volatility in the Kospi, major brokerages remain bullish on Korean chip stocks Samsung and SK hynix, citing an ongoing AI-driven memory boom that is expected to ensure strong demand and pricing power through 2028.
XRlabs has raised $8.4 million in seed funding led by Playground Global to develop and deploy an AI platform that analyzes surgical data in real time while working with equipment already used in operating rooms.
Long-term assistants must follow unfinished tasks across days as information and circumstances change. Finding information or starting an action, however, does not ensure that the task gets completed. We introduce OptionWorld, a benchmark that traces information acquisition,…
Online scene change detection requires integrating incoming observations to determine which regions have changed relative to a reference scene. We update change beliefs as new images arrive using generalised Bayesian evidence fusion. However, the prior probability of change and…
Looped Transformers increase effective depth by repeatedly applying shared layers, offering a way to scale computation without increasing parameter count. However, full-stack looping places context construction and iterative state refinement within the same recurrent…
We introduce a two-stage data-driven neural framework for discovering dynamically admissible extreme scenarios. Rather than assuming prior knowledge of the governing equations, the first stage infers the effective dynamical constraints directly from observational data. When the…