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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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Research2 min read
Research indicates that recall failures, not encoding limitations, are the primary cause of factual errors in advanced LLMs like Gemini-3 and GPT-5. The new knowledge profiling framework highlights this issue and suggests inference-time methods as a key area for improvement.
From Google Research blog
LLMs1 min read
NVIDIA’s Nemotron 3.5 Lightning, a 30 billion parameter open model, is now accessible on Ollama for local agent execution. Optimized for multi-step tasks and long context windows, it offers 4x higher throughput and faster task completion compared to similar models.
From Ollama blog
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.
Research1 min read
Google DeepMind and A24 have initiated a research partnership focused on developing advanced AI agents. The collaboration aims to explore the use of large language models in creative workflows, specifically for scriptwriting.
From Google DeepMind blog
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.
