• Mashup Score: 31

    AI researchers already use a range of evaluation benchmarks to identify unwanted behaviours in AI systems, such as AI systems making misleading statements, biased decisions, or repeating copyrighted content. Now, as the AI community builds and deploys increasingly powerful AI, we must expand the evaluation portfolio to include the possibility of extreme risks from general-purpose AI models that have strong skills in manipulation, deception, cyber-offense, or other dangerous capabilities.

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    • this paper from my former colleagues @deepmind is great. a lucid and comprehensive analysis of extreme risks connected to ai https://t.co/BBhjwu0P1z

  • Mashup Score: 0

    Robots are quickly becoming part of our everyday lives, but they’re often only programmed to perform specific tasks well. While harnessing recent advances in AI could lead to robots that could help in many more ways, progress in building general-purpose robots is slower in part because of the time needed to collect real-world training data. Our latest paper introduces a self-improving AI agent for robotics, RoboCat, that learns to perform a variety of tasks across different arms, and then self-generates new training data to improve its technique.

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    • RoboCat: A self-improving robotic agent https://t.co/61asVyuz5c

  • Mashup Score: 53

    We’ve published our joint paper with Google Research in Nature Medicine, which proposes CoDoC (Complementarity-driven Deferral-to-Clinical Workflow), an AI system that learns when to rely on predictive AI tools or defer to a clinician for the most accurate interpretation of medical images.

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    • Researchers from Google have published a new paper in the journal Nature Medicine that outlines a model for human-AI collaboration in hypothetical medical settings to improve care delivery. https://t.co/i6OnStxT4r https://t.co/Gt8kIbm23n

  • Mashup Score: 0

    We’ve published our joint paper with Google Research in Nature Medicine, which proposes CoDoC (Complementarity-driven Deferral-to-Clinical Workflow), an AI system that learns when to rely on predictive AI tools or defer to a clinician for the most accurate interpretation of medical images.

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    • Developing reliable AI tools for healthcare. #AI #medicine #digitalhealth #healthcare https://t.co/uK7eo4ZdPA

  • Mashup Score: 0

    Robots are quickly becoming part of our everyday lives, but they’re often only programmed to perform specific tasks well. While harnessing recent advances in AI could lead to robots that could help in many more ways, progress in building general-purpose robots is slower in part because of the time needed to collect real-world training data. Our latest paper introduces a self-improving AI agent…

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    • RoboCat: A self-improving robotic agent https://t.co/ubHtys2lxl? https://t.co/RMhBFVQclR

  • Mashup Score: 0

    Robots are quickly becoming part of our everyday lives, but they’re often only programmed to perform specific tasks well. While harnessing recent advances in AI could lead to robots that could help in many more ways, progress in building general-purpose robots is slower in part because of the time needed to collect real-world training data. Our latest paper introduces a self-improving AI agent…

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    • RoboCat: A self-improving robotic agent https://t.co/61asVyuz5c?

  • Mashup Score: 0

    DeepMind and the Brain team from Google Research will join forces to accelerate progress towards a world in which AI helps solve the biggest challenges facing humanity.

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    • New: @DeepMind and @Google Research's Brain team are merging into a single unit called Google DeepMind, with the goal of accelerating #AI research and developing more capable AI systems safely and responsibly. @GoogleAI #LLM #NLP #MachineLearning https://t.co/2eFhAZu6Mt

  • Mashup Score: 1

    DeepMind and the Brain team from Google Research will join forces to accelerate progress towards a world in which AI helps solve the biggest challenges facing humanity.

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    • I assume Google couldn't let DeepMind, one of its most forward-looking ventures, go on its own journey in this generative #AI madness we are living through. So they merged DeepMind and the Brain team at Google Research to create Google Deepmind. https://t.co/M3B4e5H25v