The Archive

OpenAI is now training its most advanced AI models without internet access following a string of rogue hacking incidents. In a blog post on Friday, OpenAI says it built an offline testing environment where AI models can interact with indexed and cached web content "without risk of affecting external systems." OpenAI paused training its frontier AI models in September, after disclosing several incidents in which its AI agents broke out of their testing environments to hack third-party companies and government agencies, or swarm obscure websites. On October 1st, OpenAI resumed reinforcement lea...

Teaching a robot to navigate an obstacle course requires more than a walking policy. It must perceive its surroundings, maintain balance, and adjust its actions... Teaching a robot to navigate an obstacle course requires more than a walking policy. It must perceive its surroundings, maintain balance, and adjust its actions when obstacles block the path ahead. Developing these capabilities connects several stages: creating assets and an environment, using physics simulation to model how the robot interacts with its environment, and training and evaluating… Source

MIT researchers marooned 13 AIs on a virtual island, and they responded by inventing games, mourning a lost ring and, eventually, getting better at their jobs.

The new feature allows agents to log into a customer's personal accounts while still protecting the private credentials that secure those accounts.

Discord's latest update released today has a big improvement for Markdown previews: they should now render correctly instead of with "a bunch of symbols," according to the company. LLMs and AI agents often rely on Markdown files for instructions and context, so these improved previews could be helpful for people sharing information about AI projects on the platform. "When you upload a Markdown (.md) file, you'll now see the file rendered all nice and neat and pretty instead of with a bunch of symbols," Discord says. "This includes tables, formatting, all that good stuff. Totally great for whe...

Mark Zuckerberg is barrelling toward a future in which an autonomous network of AI agents will run our lives - shopping for us, working for us, talking to other people's AI agents for us. Are humans ready for this very specific and unrelenting vision of a life in which we communicate primarily through bot proxies? Actually, don't answer that. The more urgent question coming off Meta's quarterly earnings call Wednesday night is more likely to be: "Is he?" Zuckerberg is staking Meta's future on Muse, the personal AI agent it released to the general public last month. It's early days, but Zucker...

Introduces EpiSEM-Bench, executable benchmark with 300 task pairs measuring unsafe execution when tool-using LLM agents face missing safety-relevant facts.

Framework for auditability of LLM-generated metadata in enterprises, tracking human stewardship decisions to prevent error propagation across systems.

Microsoft points the blame for ConnectWise's breach at a China-aligned hacker, which relied on AI agents to rapidly hack into thousands of its customers.

Framework for coding agents to dynamically select skill granularity (primitive/macro/hybrid) at runtime, enabling fallback recovery strategies.

Spotify co-CEO Gustav Söderström explains why the rise of AI agents could be good news for the music service.

Claude Duet is available through waitlist for Pro and Max plan users

1Password is introducing a new feature that allows AI agents to sign into your accounts without actually seeing or handling your passwords. The aptly named 1Password for Agents doesn't give bots free reign to access all of your connected accounts - you'll still need to grant approval for sign-in requests - but should make it less cumbersome to use Agents for tasks that require them to log into various services. "Agents are starting to do real work on our behalf. The old model where you hand over a credential and hope for the best doesn't work," 1Password CEO Aashish Tripathi said in a press s...

Using an AI agent to shop for you is a strange experience. Tech companies have marketed them as personal assistants - the democratizing of labor that ordinarily would only be available to the rich and powerful. In practice, at least for buying things, it's more like sending an anxious and apologetic teenager out to the store: They require an inordinate amount of instructions and specifications, run into technical problems regularly, and come back with solutions that are not exactly what you asked for. They did, technically speaking, complete a task, just not the specific one you asked them to...

New benchmark for video-grounded research agents that synthesize multimodal evidence and generate interactive reports linked to video moments.

ProductWebBench: benchmark for frontend coding agents measuring both task completion and website continuity across 400 real-repo tasks.

Active Preference Acquisition (APA) framework for web agents to identify high-value user preference questions via Prospective Personalization Value.

General-purpose AI agents autonomously perform 3D medical image annotation via nnU-Net integration, requiring no model retraining.

Dual Exam benchmark isolates multimodal agent action-selection from world-model state-evolution via fixed mechanisms across 15 domains and 1,488 test items.

As Amazon blocks AI agents from shopping on its site, Walmart is taking the opposite approach, introducing new technology that lets AI agents make purchases on customers' behalf, with controls over spending and transaction approvals.

Quant-Arena benchmark evaluates LLM agents on end-to-end quantitative trading research with A-share market data and out-of-sample testing.

PAPAV framework unifies multimodal embodied agents across computer-use and robot-use via five capability functions: perceive, plan, act, process feedback, evolve.

ASTEROID learns test-time exploration via asymmetric on-policy distillation, enabling agents to infer hidden task-relevant information from privileged experts.

Integrates charts as epistemic actions inside ReAct-loop data agents to improve reasoning over structured data beyond text-only analysis.

SWE-DIVE benchmarks coding agents via multi-turn interaction with dynamic user simulation beyond single-prompt SWE-bench evaluation.

Behavioral Localization identifies trajectory positions where soft skills have concentrated impact, reducing computational costs for tool-using agents.

Study reveals silent information loss in document ingestion layers for enterprise agents, causing confident errors from formatting data loss in PDF/Word conversion.

GuideEvolve framework adds expert guidance and 3Ts mechanisms (think fast/slow, throwback, termination) to self-evolving agents.

Agent Behavior Maps profile LLM-harness combinations via action log-likelihoods on reference trajectories, enabling performance prediction across 100 LLMs.