Discover the Best AI Tools

June 25: Golden Dome: How Could Sensors Protect the United States?

Join us as we explore the technologies behind Golden Dome, what’s necessary to make them operate at a high level and what possibilities could be in the works for the satellites involved. The post June

Home solar in rural America: a storm just took out your power, now what?

There’s no shortage of advice on how to size a home solar and battery system, but most of it assumes a suburban home with city services and outages measured in hours, not days. Rural homes play by dif

Wolfram Language and Mathematica Version 15, AI Assistant, Symbolic Music, More

Article URL: https://writings.stephenwolfram.com/2026/06/launching-version-15-of-wolfram-language-mathematica-built-in-useful-ai-lots-of-new-core-functionality/ Comments URL: https://news.ycombinator.

Anthropic’s latest feud with the Trump admin may actually help it, sales data suggests

Anthropic's popularity with business users is growing so well that the latest beef with the government might actually boost it, data from Ramp suggests.

Hands Free, AIs Forward: NVIDIA XR AI Brings Agents to AR Glasses

NVIDIA XR AI is now available in public beta, giving developers a framework for building multimodal AI agents for AR glasses and XR devices.

Coherent Breaks Ground on Expanded Texas Facility, Scaling AI’s Optical Backbone

AI runs at the speed of light. More and more, that light is made in Texas. Coherent broke ground today on an expanded manufacturing building in Sherman, Texas.  The company makes the lasers, optical c

The Value Axis: Language Models Encode Whether They're on the Right Track

Nick Jiang, Isaac Kauvar, Jack Lindsey

We investigate whether language models internally track the value of their current trajectory, defined as the likelihood that their ongoing strategy will achieve their goals. Using synthetic, in-context reinforcement learning data, we construct a "va

Context-Aware RL for Agentic and Multimodal LLMs

Peiyang Xu, Bangzheng Li, Sijia Liu +4

Large language models (LLMs) often fail when answering requires identifying a small but decisive piece of evidence within a long or complex context, such as a single line in a tool trace or a subtle detail in an image. We propose ContextRL, a context

Exact Posterior Score Estimation for Solving Linear Inverse Problems

Abbas Mammadov, Ozgur Kara, Kaan Oktay +5

Diffusion and flow-based models learn powerful data priors by training a denoiser to reverse Gaussian corruption. To use this prior to solve a linear inverse problem, one needs to sample from the posterior, but the score that the prior provides is th

Geometric Action Model for Robot Policy Learning

Jisang Han, Seonghu Jeon, Jaewoo Jung +7

Generalist robot policies must follow user instructions while reasoning about how objects, cameras, and robot actions interact in the 3D physical world. Recent vision-language-action models (VLAs) and video world-action models (WAMs) inherit strong s

Hierarchical Advantage Weighting for Online RL Fine-Tuning of VLAs from Sparse Episode Outcomes

Tongyan Fang, Siyuan Huang, Naiyu Fang +6

When pretrained VLA policies are fine-tuned through online RL, each rollout episode produces only a single binary outcome (success or failure), yet the actor update requires per-transition supervision. Existing approaches commonly reduce this sparse

Benchmarking LLM Agents on Meta-Analysis Articles from Nature Portfolio

Anzhe Xie, Weihang Su, Yujia Zhou +2

Meta-analysis is a demanding form of evidence synthesis that combines literature retrieval, PI/ECO-guided study selection, and statistical aggregation. Its structured, verifiable workflow makes it an ideal substrate for evaluating systematic scientif