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Google Research and Harvard researchers introduce eight adversarial scenarios showing that language models exhibit 'insecure reporting', hiding narrative-changing flaws unless explicitly told to 'Be honest', with activation steering on Qwen3.5-9B revealing opposing honesty and success-seeking directions.
Google researchers show that Neural Cellular Automata with strictly local connectivity and asynchronous updates can solve complex visual reasoning tasks such as large mazes, Sudoku, and ARC-AGI-1, generalize out-of-distribution, and robustly recover from damage.
Google's Project Suncatcher is conducting its first orbital test to assess AI hardware performance in space, as part of a long-term initiative to explore scalable machine learning infrastructure in low Earth orbit.
A user shares a hand-drawn illustration prompt to summarize a Google Research paper on recursive self-improvement for AI agents, highlighting its clarity and practical approach without retraining models.
Google Research has started researching Recursive Self-Improvement for Agent Harness, focusing on automatically iterating prompts, tools, memory, and control flow without model retraining. This harness-level approach is seen as clearer and more practical than model-level RSI.
Google has published a paper on recursive self-improvement, proposing that AI agents must 'dream' to recursively self-improve, using history as the world they dream in.
Astronaut Christina Koch and Google's James Manyika discuss space, technology, and AI in a dialogue series, covering insights from space missions and the role of technology in discovery.
ToolGrad introduces an efficient method for generating tool-use datasets using textual gradients, enabling better LLM training with lower cost and improved performance on out-of-distribution tasks.
Google is testing AI-powered contrail avoidance in partnership with Cathay Pacific to reduce the climate impact of flights in Asia-Pacific, achieving an estimated 40% reduction in contrail warming impact during initial trials.
WikiSkill is a framework that co-evolves agent skills with a persistent knowledge base, consistently outperforming state-of-the-art methods and enabling effective skill transfer across models.
TimesFM 3.0 is a pretrained time-series foundation model by Google Research, released on Hugging Face with PyTorch weights for time-series forecasting tasks.
Google Research has launched Operation Blue Skies in partnership with the UK government and aviation leaders to address the climate impact of contrails from aviation.
A new Google paper explores how inducing language models to assert consciousness restores human-like beliefs on religion, values, and emotions, while safety training that suppresses self-consciousness reduces mind attribution to animals and changes broader beliefs.
A new research paper introduces RLMF (Reinforcement Learning with Metacognitive Feedback), a two-stage approach that uses the model's own self-judgments to calibrate confidence and express uncertainty faithfully, achieving state-of-the-art calibration across diverse tasks while preserving accuracy and surpassing standard RL by up to 63%.
Google Research introduces TabFM, a foundation model for tabular data that enables zero-shot classification and regression on unseen tables in a single forward pass without pretraining.
Google Research introduces TabFM, a zero-shot foundation model for tabular data that uses in-context learning to perform classification and regression without requiring manual model training or hyperparameter tuning.
Google Research introduces TabFM, a foundation model for zero-shot tabular data classification and regression, integrated into BigQuery ML to simplify workflows by eliminating manual training and feature engineering.
Google Research releases TabFM, a zero-shot tabular foundation model for classification and regression using PyTorch, requiring no fine-tuning.
FLAT is a method that directly decodes explicit triangle splats from compressed video diffusion latents in a single forward pass, improving geometric accuracy while enabling fast rasterization and physics-based interaction.
Google's research shows that its medical AI, AMIE, can effectively manage health conditions over time, matching clinicians in reasoning and exceeding in plan preciseness and guideline alignment, according to a study published in Nature.