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MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation1h◆Counterfactual Model Testing Under Distribution Shift1h◆Centralized Critics for N-Agent Ad Hoc Teamwork1h◆Where and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning1h◆Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction1h◆Numina Fuse: Interactive Autoformalization in Lean 41h◆On the Limits of Sparse Linear Model with Shuffled Differential Privacy1h◆Video World Models Need Predictable Latents1h◆AutoPRL: Automated Path Representation Learning via a Learnable View Generator1h◆Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models1h◆Latent Goal Prediction from Language for Model-Based Planning1h◆Rectified Language Flow1h◆Trainable Boundary-Keeping Where No Formal Answer Exists: A Controlled Knock-In Study of Reward Training in Evidence-Sufficiency Judgment1h◆Intrinsic Goals for Autonomous Agents: Hierarchical Exploration Captures Future Volitional Action in Drosophila1h◆Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights1h◆Intervention-Certified Amplification: A Validity Gate for $\sigma$-Weighted Post-Training1h◆Single-Cycle Battery Remaining Useful Life Prediction with Compressed Continuous Wavelet Features and Deep Neural Networks1h◆DoubleFree:Exploiting Exploration History for Rollout-Free Multi-Task LLMs Training1h◆Unbiased Alignment for Large Language Models with Noisy Preferences1h◆ExCal: Optimization-Free Multivariate Time Series Anomaly Detection via Excess Calibration1h◆MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation1h◆Counterfactual Model Testing Under Distribution Shift1h◆Centralized Critics for N-Agent Ad Hoc Teamwork1h◆Where and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning1h◆Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction1h◆Numina Fuse: Interactive Autoformalization in Lean 41h◆On the Limits of Sparse Linear Model with Shuffled Differential Privacy1h◆Video World Models Need Predictable Latents1h◆AutoPRL: Automated Path Representation Learning via a Learnable View Generator1h◆Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models1h◆Latent Goal Prediction from Language for Model-Based Planning1h◆Rectified Language Flow1h◆Trainable Boundary-Keeping Where No Formal Answer Exists: A Controlled Knock-In Study of Reward Training in Evidence-Sufficiency Judgment1h◆Intrinsic Goals for Autonomous Agents: Hierarchical Exploration Captures Future Volitional Action in Drosophila1h◆Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights1h◆Intervention-Certified Amplification: A Validity Gate for $\sigma$-Weighted Post-Training1h◆Single-Cycle Battery Remaining Useful Life Prediction with Compressed Continuous Wavelet Features and Deep Neural Networks1h◆DoubleFree:Exploiting Exploration History for Rollout-Free Multi-Task LLMs Training1h◆Unbiased Alignment for Large Language Models with Noisy Preferences1h◆ExCal: Optimization-Free Multivariate Time Series Anomaly Detection via Excess Calibration1h◆
News/Watch astronaut Christina Koch and Google’s James Manyika discuss space, technology, and discovery.
google
PublishedSeptember 14, 2026 at 7:00 PM
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Watch astronaut Christina Koch and Google’s James Manyika discuss space, technology, and discovery.

Watch astronaut Christina Koch and Google’s James Manyika discuss space, technology, and discovery.
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<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/Dialogues_Christina-Koch_social.max-600x600.format-webp.webp">Christina Koch sits down with James Manyika, Google’s Senior Vice President of Research, Labs, Technology & Society.

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