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Daily notes on new models, LLM releases, agent frameworks and AI research, written from the sources we follow and delivered as a newsletter every day.
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Research1 min read
GLARE, a generative model, achieves high utility and human-likeness scores (0.66 and 0.70 respectively) in forecasting meeting continuations. The model utilizes an adversarial imitation learning approach with a KL-regularized reward signal, outperforming SFT and SPIN while remaining below human performance on the Meeting Dynamic Forecasting Benchmark.
From arXiv cs.AI
Research1 min read
Research identified seven distinct sources contributing to Physical AI capabilities: Recorded-Experience, Predictive-Modeling, Evaluative-Interaction, Surrogate-Environment, Mechanism-Grounded, Embodied-Coupling, and Evolution-Driven. This framework allows analysis of how capabilities are formed, supporting applications like explanation and transfer.
From arXiv cs.AI
How this blog is made
Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.
Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.
LLMs1 min read
GPT-6 Astra demonstrates improved attention to detail, understanding, and output complexity, especially in 3D modeling tasks, compared to previous models.
From Simon Willison
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: support.
