A new AI model for the agentic era
AI

A new AI model for the agentic era

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Advancing AMIE towards specialist care and real-world validation
AI

Making quantum error correction work

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Willow: beating the threshold Operating “below the threshold” has been a goal for error corrected quantum computing since its inception in the 1990s. However, after almost 30 years of advancement in device fabrication, calibration, and qubit design, quantum computers still hadn’t passed this landmark. That is, until our latest 105-qubit superconducting processor, Willow. Willow represents

Advancing AMIE towards specialist care and real-world validation
AI

Making quantum error correction work

/

Willow: beating the threshold Operating “below the threshold” has been a goal for error corrected quantum computing since its inception in the 1990s. However, after almost 30 years of advancement in device fabrication, calibration, and qubit design, quantum computers still hadn’t passed this landmark. That is, until our latest 105-qubit superconducting processor, Willow. Willow represents

Advancing AMIE towards specialist care and real-world validation
AI

Making quantum error correction work

/

Willow: beating the threshold Operating “below the threshold” has been a goal for error corrected quantum computing since its inception in the 1990s. However, after almost 30 years of advancement in device fabrication, calibration, and qubit design, quantum computers still hadn’t passed this landmark. That is, until our latest 105-qubit superconducting processor, Willow. Willow represents

Google DeepMind at NeurIPS 2024
AI

Google DeepMind at NeurIPS 2024

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Research Published 5 December 2024 Advancing adaptive AI agents, empowering 3D scene creation, and innovating LLM training for a smarter, safer future Next week, AI researchers worldwide will gather for the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), taking place December 10-15 in Vancouver, Two papers led by Google DeepMind researchers will be

Genie 2: A large-scale foundation world model
AI

Genie 2: A large-scale foundation world model

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Acknowledgements Genie 2 was led by Jack Parker-Holder with technical leadership by Stephen Spencer, with key contributions from Philip Ball, Jake Bruce, Vibhavari Dasagi, Kristian Holsheimer, Christos Kaplanis, Alexandre Moufarek, Guy Scully, Jeremy Shar, Jimmy Shi and Jessica Yung, and contributions from Michael Dennis, Sultan Kenjeyev and Shangbang Long. Yusuf Aytar, Jeff Clune, Sander Dieleman,

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