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最新模型

Compile by Training Compiles Natural-Language Specifications into Reusable Offline Neural Functions

A new method first uses a teacher model to synthesize task data, then fine-tunes adapters for a small interpreter, packaging text specifications as versionable `.paw` functions. It achieves 83.6% semantic accuracy on difficult, ambiguous text tasks, but compilation requires an external model and roughly 40GB of accelerator memory, and it cannot provide the formal guarantees of conventional programs.

代理工具

Prime Agent 0.9.2 Persists Trace Upload Progress with an On-Disk Cursor and Resumes Unfinished Work After Restart

The new release turns agent trace uploads into a persistent outbox. Processes no longer wait for network transfers when exiting, and can resume uploads from a byte cursor after restarting. It also begins recording semantic edges across sub-agents, but there is currently no corresponding delivery endpoint, so this should not be considered a complete distributed tracing capability.

應用研究

WeatherNext 3 Directly Ingests Satellite Observations, Relaunching Global Probabilistic Weather Forecasts Every Hour

Google DeepMind’s new model no longer merely imitates reanalysis data produced every six hours; it incorporates low-latency satellite imagery into forecast initial conditions. It improves precipitation and station-level predictions, but evaluations in mountainous and polar regions and for heavy rainfall still expose limitations caused by sparse data and imperfect metrics.