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Study: AI models that consider user’s feeling are more likely to make errors

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In human-to-human communication, the desire to be empathetic or polite often conflicts with the need to be truthful—hence terms like “being brutally honest” for situations where you value the truth over sparing someone’s feelings. Now, new research suggests that large language models can sometimes show a similar tendency when specifically trained to present a “warmer” […]

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Meta will use employee-tracking software to help train AI agents: Report

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Meta will begin tracking the mouse movements, clicks, and keystrokes of its US employees to generate high-quality training data for future AI agents, Reuters reports. The news organization cites internal memos posted by the Meta Superintelligence Labs team in reporting on the new Model Capability Initiative employee-tracking software. That software will operate on specific work-related

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From folding boxes to fixing vacuums, GEN-1 robotics model hits 99% reliability

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Robotic machine learning company Generalist has announced GEN-1, a new physical AI system that it says “crosses into production-level success rates” on “a broad range of physical skills” that used to require the dexterity and muscle memory of human hands. Generalist is also touting the new model’s ability to respond to disruptions by improvising new

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Figuring out why AIs get flummoxed by some games

ai, AI (Artificial Intelligence), Artificial Intelligence, chess, Computer Science, Games, math, NIM, Science, training

With its Alpha series of game-playing AIs, Google’s DeepMind group seemed to have found a way for its AIs to tackle any game, mastering games like chess and Go by repeatedly playing itself during training. But then some odd things happened as people started identifying Go positions that would lose against relative newcomers to the

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Large genome model: Open source AI trained on trillions of bases

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Late in 2025, we covered the development of an AI system called Evo that was trained on massive numbers of bacterial genomes. So many that, when prompted with sequences from a cluster of related genes, it could correctly identify the next one or suggest a completely novel protein. That system worked because bacteria tend to

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Anthropic: Claude faces ‘industrial-scale’ AI model distillation

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Anthropic has detailed three “industrial-scale” AI model distillation campaigns by overseas labs designed to extract abilities from Claude. These competitors generated over 16 million exchanges using approximately 24,000 deceptive accounts. Their goal was to acquire proprietary logic to improve their competing platforms. The extraction technique, known as distillation, involves training a weaker system on the

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