@istoica05
Professor at UC Berkeley, co-founder of Databricks, Anyscale, Arena, Conviva.
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Exo's creators say models can use runtime logs and modify and rebuild their harness while optimizing a task.
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Promoters describe SkyDiscover-built engines tailored to a Mac and model, and announce six pre-built versions.
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Evolving Agent Teams' supervisor diagnoses dead ends and draws on saved lessons and team history to restructure coding agents.
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Mirendil says Lor's agents write its code, run experiments and iterate on results for days.
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Wenhao Chai says the team built its tasks from published papers and refined them with field experts.
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Co-founder Kevin Weil says robotic labs will generate data to train AI models for science.
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Letta publishes separate model and agent-harness results for a test built around later task completion.
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The authors report faster time-to-first-token and lower peak memory across diverse tasks, without accuracy degradation.
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In the announcement, @bneyshabur places Mirendil-Base in the 100B–500B-parameter range and promises independent evaluations.
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A Google team member claims the agent ranked #1 on NVIDIA's SOL-ExecBench and reached 2× human experts on SWE-fficiency.
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The student's instructor calls the kernels “impressively fast” and asks Google DeepMind about collaborating on model architecture research.
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Arena says its index tracks unauthorized actions, false attribution and deceptive completion across 90,000-plus agent sessions and 27 models.
YouTube
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The poster says they can’t wait to see what people do with the video-generation capability.
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Arena describes a comparison of Claude Code, Codex and Pi. The researchers say harness choice had little effect on task success rate but can significantly affect cost.
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The creators say SkySynth is designed to build systems around a user's workload, hardware and requirements, bringing systems specialization to people using coding agents.
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Posts discuss a tool that runs large frontier models on consumer hardware at interactive speeds.