@omarsar0
Building and measuring frontier intelligence @dair_ai • Prev: Meta AI | Galactica LLM | Papers with Code | Elastic | PhD
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Rohan Paul says Emma’s face, voice and conversational reactions come from recordings made with an actress.
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His early-access testing favored one agent for coding projects, but clear goals and human oversight still mattered.
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The reported workflow pairs brokerage explanations with text messages asking users to approve suggested trades.
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Steve is reportedly designed to record what went wrong and simulate the outcome of a decision before acting.
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Private datasets now carry 45% of the index’s weight, up from 25% in the first version.
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Drex reportedly assigns probabilities to fixed-choice answers instead of generating text.
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The benchmark tests agents' research methods and software use; every model reportedly scored zero on its end-to-end research track.
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Aina says the ring uses context from devices and routines to suggest actions users can accept or dismiss.
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Atmee v2 uses one image and 10 seconds of audio to create a character for live video conversations.
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TwIL-8B's open-source release drew praise from a commentator who sees locally run models aiding scientific discovery.
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Aether's extra credits cost $0.10 for 12 minutes on a small machine, with idle time free, a user says.
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Nvidia's tests put Opus 4.5 at 70.2 with compaction after every action versus 70.0 with full history on SWE-bench Verified.
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The Stacks Project spans hundreds of chapters and tens of thousands of results; AxiomMathAI's version is reportedly open and machine-checked.
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Living Brain is described as keeping context in a separate store that agents can access through MCP or an API.
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Skill++'s authors report that it selected every required skill for 76.3% of queries, versus 36.4% with original metadata.
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The managed inference product is pitched for spiky search, OCR and agentic workloads, with a $500 launch-credit offer.
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Traversal says its software finds the root cause of production incidents and helps prevent future ones.
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Its reported matched-compute comparisons favor Locus over selected baselines and AI agents, with detail on property prediction.
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In the authors' tests, changing opening tokens mainly helped models add or restyle information, not consistently leave it out.
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Revolut says its GLM bill is roughly a tenth of what it paid OpenAI and Anthropic.