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For decades, automakers enjoyed a luxury that had nothing to do with the softest leather or the smoothest engines. Their luxury was time, with some popular cars and trucks enduring for a decade or longer before they received a full redesign. The clock is ticking faster now, thank...
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A walkthrough of the LeRobot integration in Strands Robots - one agent loop, from a Hub dataset to a physical robot, with sim-to-real datasets in the same on-disk format and policies you swap with a string. You have a robot, a folder of demonstration data on the Hugging Face Hub,...
We're introducing GLM-5.2, our latest flagship model for long-horizon tasks. It marks a substantial leap in long-horizon task capability over its predecessor GLM-5.1 and, for the first time, delivers that capability on a solid 1M-token context. GLM-5.2's new capabilities include:...
June 11, 2026 Responsibility & Safety Google DeepMind, Schmidt Sciences, the Cooperative AI Foundation, ARIA and Google.org For the past decade, we’ve focused on making individual AI models more capable, helpful and safe. Today, Google DeepMind — together with Schmidt Sciences, t...
June 16, 2026 Responsibility & Safety Around the world, Governments are exploring how AI can deliver better public services, faster. The UK is working to build 1.5 million new homes by 2029, but local planning authorities are often slowed down by dense paperwork and administrativ...
OpenAI’s fourth large language model (LLM), GPT-4, took an estimated 50 gigawatt-hours to train, or the equivalent of 5,000 American homes’ yearly power consumption. That was in 2023. Since then, the computational resources used to train frontier LLMs have only increased, though...
For more than a decade, artificial intelligence has been touted as a way to dramatically accelerate drug discovery. Yet despite billions of dollars in investment, relatively few AI-designed medicines have made it to patients. That’s partially because the timelines for careful dru...
This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore. As robots advance in terms of dexterity and other physical capabilities, it becomes more likely that humans may find themselves working alongside them. If that happens, how will robot...
Understanding the behavior of complex machine learning systems, particularly Large Language Models (LLMs), is a critical challenge in modern artificial intelligence. Interpretability research aims to make the...
GRASP is a new gradient-based planner for learned dynamics (a world model) that makes long-horizon planning practical by lifting trajectories into virtual states, stochastic state iterates for exploration, and gradient reshaping so action signals stay clean.
What if a reasoning model could decide for itself when to decompose and parallelize independent subtasks, how many concurrent threads to spawn, and how to coordinate them based on the problem at hand? We provide a detailed analysis of recent progress in the field of parallel reas...
arXiv:2606.17266v1 Announce Type: new Abstract: Production planning increasingly has to treat workforce capability as a decision variable: certifications lapse when skills are not maintained, new products require skills the current workforce does not hold, and reskilling compete...
arXiv:2606.17220v1 Announce Type: new Abstract: Legal case retrieval remains challenging due to the complexity of legal language and the need for precise lexical alignment between queries and relevant cases. Although dense retrieval models have achieved notable progress, empiric...
arXiv:2606.17209v1 Announce Type: new Abstract: Test-time scaling for agentic search typically increases depth (i.e., more turns and tokens per trajectory) or breadth (i.e., more parallel rollouts). Here we focus on breadth scaling, showing that standard parallel sampling yields...
Skip to content AI did my homework Pentagon also claims 1.5 million personnel are using generative AI...
Move originally planned for Monday would have heavily increased power users' costs.
The Trump administration is trying to help Elon Musk’s xAI Corp. beat a Clean Air Act lawsuit filed by the National Association for the Advancement of Colored People (NAACP). The US said the NAACP lawsuit...
Despite advances in machine vision, processing visual data requires substantial computing resources and energy, limiting deployment in edge devices. Now, researchers from Japan have developed a self-powered artificial synapse that distinguishes colors with high resolution across...
Human-AI interactions are well understood in terms of trust and companionship. However, the role of attachment and experiences in such relationships is not entirely clear. In a new breakthrough, researchers from Waseda University have devised a novel self-report scale and highlig...
The effects of artificial intelligence on adolescents are nuanced and complex, according to a new report that calls on developers to prioritize features that protect young people from exploitation, manipulation and the erosion of real-world relationships.
The carbon footprint of computing is a key sustainability challenge. It is driven by two major sources: operational carbon reflects emissions from energy consumed during use, and embodied carbon encompasses...
More than half of adults use the Internet for health information, and one-third turn to artificial intelligence (AI). However, access to information does not mean that it is easy to understand or correctly...
We developed a high-resolution deep learning framework to reveal fine-scale ecological features, like hedgerows and copses, that are typically invisible to standard satellite detection. This precise vector...
The concept of AI self-improvement has been a hot topic in recent research circles, with a flurry of papers emerging and prominent figures like OpenAI CEO Sam Altman weighing in on the future of self-evolving intelligent systems. Now, a new paper from MIT, titled "Self-Adapting L...
The increasing integration of robots across various sectors, from industrial manufacturing to daily life, highlights a growing need for advanced navigation systems. However, contemporary robot navigation systems face significant challenges in diverse and complex indoor environmen...
Share My Research is Synced’s column that welcomes scholars to share their own research breakthroughs with over 1.5M global AI enthusiasts. Beyond technological advances, Share My Research also calls for interesting stories behind the research and exciting research ideas. Contact...
Back to Articles The building-block economy comes for multimedia Every Space is a building block, via agents.md The worked example: Paris monuments → splats Two prompts, a whole new gallery Why this...
Back to Articles In the first part of this series "Profiling in PyTorch", we used torch.add(torch.matmul(x, w), b) to learn how to read PyTorch profiler traces. We also discussed several...
Back to Articles 💻 Code: https://github.com/allenai/olmo-eval While you're building an LLM, you evaluate it over and over across many interventions. Every adjustment to its data, architecture, or...
In an effort to address this, Google DeepMind—which made agent-based tools a centerpiece of Google I/O last month—has teamed up with several other organizations to announce a $10 million funding pot for...
Essays (5)
Research
In traditional software, a unit test either passes or fails. In AI, evaluation is a probabilistic art. As models have become smarter, they have saturated traditional benchmarks like MMLU, making it nearly impossible to distinguish between a "state-of-the-art" model and a slightly tuned competitor. This crisis in evaluation has led to a reliance on "Vibes" (subjective human feel) and dynamic arenas, undermining scientific rigor.
Research
"Alignment" is the subfield of AI research dedicated to ensuring that artificial systems behave according to human intent and values. It is not just about preventing "Terminator" scenarios; it is about solving the immediate problem of how to make a system that optimizes for a goal (like "cure cancer") without causing unintended side effects (like "kill all humans to stop cell division")—a classic optimization trap known as "Specification Gaming."