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The Verge1 hour ago

Students who use AI generally score worse at school

According to data from a global OECD education report, students who use AI to support their studies tend to perform worse than those who do not. However, the impact is more nuanced: some forms of AI use provide a slight boost, especially for students taught to assess AI critically.

Read original· The Verge AI
Hacker News 108 hours ago

AI Has a Discovery Problem

The title suggests that AI faces challenges in discovering or uncovering new information, ideas, or capabilities. No further details are provided about the cause or scope of the problem.

Read original· miguelacevedo
Hacker News 2012 hours ago

I Resigned from Anthropic Today

The author says they resigned from Anthropic today. The headline provides no further information about the reason or context behind the decision.

Read original· yurivish
Simon Willison13 hours ago

Quoting Terence Tao

Terence Tao warns that valuable open problems are being mined in a non-renewable way, creating a risk that they will become scarce. Even rumors that someone is working on a problem can trigger massive AI-powered efforts to solve it, potentially discouraging researchers from sharing promising work.

Read original· Simon Willison
Simon Willison13 hours ago

On the Navier–Stokes Millennium Prize Problem

OpenAI reportedly used an unreleased model to produce a solution to the Navier–Stokes existence and smoothness problem, one of the seven Millennium Prize Problems carrying a one-million-dollar prize. The discovery was partly overshadowed by accusations of skulduggery from Tristan Buckmaster, an NYU mathematics professor who was collaborating on the problem with Levent Alpöge.

Read original· Simon Willison
Simon Willison14 hours ago

Introducing ChatGPT Images 2.5

OpenAI says its image-generation models have been used to create more than 3 billion images across ChatGPT Images and the GPT-Image models in the API. The new release improves multi-turn instruction following, responds faster, and better preserves subjects from reference photos. The API adds two model IDs, gpt-image-2.5-sunburst and gpt-image-2.5-flare; the author considers Sunburst the stronger option.

Read original· Simon Willison
Hacker News 2017 hours ago

OpenAI fought dirty on career-making math problem

The headline says OpenAI allegedly used unfair tactics involving a mathematics problem that could have major career significance. The article appears to focus on a dispute over how OpenAI handled or competed around the problem.

Read original· jonbaer
TechCrunch18 hours ago

Meta debuts its Muse AI agent. Will consumers trust it?

Meta’s new personal AI agent, Muse, seeks access to users’ email, calendars, payments, health services, and more. The launch is the company’s biggest consumer AI bet yet and a major test of whether people still trust Meta with their data.

Read original· TechCrunch AI
Hacker News 5418 hours ago

ChatGPT Images 2.5

The title refers to version 2.5 of ChatGPT Images. No further information about the version’s changes or features is provided.

Read original· vertigoruntime
arXiv19 hours ago

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

TANGO is a whole-body navigation framework for humanoid robots that uses language instructions and egocentric visual observations to predict 29-DoF joint-space actions. It is trained entirely in simulation using collision-free traversal behaviors generated through path planning, whole-body motion generation, obstacle-aware editing, and reinforcement learning. TANGO achieves state-of-the-art simulated vision-language navigation and is deployed zero-shot on a Unitree G1 robot for traversal in cluttered real-world scenes.

Read original· Anqi Li, Yuxin Chen, Zhaobo Li, Zhuo Cao, Junli Ren, Masayoshi Tomizuka, Dhruv Shah
arXiv19 hours ago

Learning Length-Extrapolatable Recurrent Models

The study argues that vanishing or exploding gradients alone do not determine whether recurrent models fail beyond their training horizon. It proposes Credit Stabilization through Time, which locally rescales the signal assigning future losses to earlier recurrent states while leaving the forward computation unchanged. The method improves performance beyond the training length, with gains observed at up to 128 times the training horizon.

Read original· Hanwen Jiang