AI agents create virtual playgrounds to help robots get crucial training data
“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.
Building a VideoAgent-Style Multi-Agent System: Intent Parsing, Graph Planning, and Tool Routing for Video Editing Tasks
In this tutorial, we reconstruct the VideoAgent workflow as a runnable, API-key-free multi-agent pipeline. We build an intent parser, an agent library, a tool router, a graph planner, and a textual-gradient optimizer that repairs the execution graph. We wire these planning components to FFmpeg, Whis...
The wildest allegations in Apple’s trade secrets lawsuit against OpenAI
Apple’s trade secrets lawsuit against OpenAI contains allegations that range from employees joking about unauthorized access to Apple’s systems to claims that job candidates were asked to bring Apple hardware to interviews. Here are the complaint’s most eye-catching claims.
Waze adds new AI-powered features and customization updates
Some of the new features are powered by Google's Gemini AI assistant, which reflects the the tech giant's broader push to integrate Gemini across its products while also better positioning Waze to compete with rival services such as Apple Maps.
Scientists discovered the brain doesn't make decisions the way we thought
A new study suggests the brain begins making decisions much earlier than scientists previously thought. Researchers found that even primary sensory regions are influenced by higher brain areas through rapid feedback loops, rather than simply passing information forward. This more dynamic view of bra...
The Frontend Verification Gap in AI-Assisted Development
AI-assisted development has made frontend work feel much faster. A developer can ask for a form, a dashboard card, a table, a modal, or a responsive layout and get a decent first version almost immediately. The code may compile. The page may render. At first glance, the UI may look done. But fronten...
Stanford Researchers Introduce TRACE: A Capability-Targeted Agentic Training System That Turns Recurrent Agent Failures Into Synthetic RL Environment
Agentic LLMs keep failing the same way because they lack specific, reusable capabilities. Stanford's TRACE diagnoses those gaps from an agent's own trajectories, synthesizes one verifiable training environment per capability, trains a LoRA adapter for each, and routes tokens across experts—improving...
Prime Intellect Releases Verifiers v1: Composable Tasksets, Harnesses, and Runtimes for Agentic RL Training and Evaluations
Prime Intellect launched verifiers 0.2.0, previewing a rewritten "v1" core under the verifiers.v1 namespace. It splits an environment into a taskset (what), a harness (how), and a runtime (where), with an interception server that proxies requests and records training-ready traces. Any taskset runs u...
Meet NeuroVFM: A New Neuroimaging Foundation Model Trained With Vol-JEPA on Uncurated Clinical MRI and CT Volumes
NeuroVFM is a generalist neuroimaging foundation model from the University of Michigan, trained on 5.24M clinical MRI and CT volumes. Its Vol-JEPA base extends I-JEPA and V-JEPA to volumetric medical imaging, learning brain anatomy and pathology without radiology-report labels.
The post Meet NeuroVF...
Mira Murati’s Thinking Machines Lab Makes The Technical Case For Human-Centered AI Built On Customizable Model Weights
Thinking Machines Lab published "The Future Worth Building Is Human." The essay frames human participation, model ownership, and decentralized alignment as technical challenges. It ties them to interaction models and Tinker's LoRA fine-tuning, where teams train and keep their own model weights.
The ...
Ant Group’s Robbyant Unveils LingBot-VA 2.0: A Causal Video-Action Model Built Natively for Physical AI
Ant Group's Robbyant has released the LingBot-VA 2.0 technical report — a Physical AI video-action foundation model built from scratch for embodiment rather than fine-tuned from a video generator. It predicts future states ahead of execution through Foresight Reasoning, re-grounds on every real obse...
Open source AI matters more than ever, according to Hugging Face’s Clem Delangue
Open source AI is booming, according to Hugging Face CEO Clem Delangue. The company has grown into something like a GitHub for AI in recent years, where AI builders can share and download open models and datasets, now used by roughly half the Fortune 500. Delangue has seen the same story play out ag...
The incident that should worry you makes no destructive call. Nothing is deleted, nothing crashes, no alert fires. An employee asks an agent to summarise a customer ticket; the agent does exactly that, the user gets a useful answer, and somewhere, in the same second, a customer record leaves the clu...
Google Research Introduces SensorFM: A Wearable Health Foundation Model Pretrained on One Trillion Minutes of Sensor Data
SensorFM, a wearable health foundation model from Google Research, Google DeepMind, and university collaborators. We walk through its ViT-1D masked-autoencoder backbone, pretrained on more than one trillion minutes of unlabeled sensor signals from 5,000,000 consented participants. We examine the co-...
Meet LingBot-World-Infinity: An Open Causal World Model With An Agentic Harness
Robbyant, Ant Group's embodied-intelligence unit, has released LingBot-World-Infinity (LingBot-World 2.0). It is a 14B causal video generation model that behaves as an interactive world simulator. The core idea is the Mixture of Bidirectional and Autoregressive (MoBA) attention mask, paired with dis...
Meta Superintelligence Labs Releases Muse Spark 1.1: A Multimodal Reasoning Model for Agentic Tasks on Meta Model API
Meta Superintelligence Labs released Muse Spark 1.1 on July 9, 2026, alongside a public preview of the Meta Model API. It is a multimodal reasoning model built for agentic tasks, with a 1,000,000-token context window the model actively compacts, zero-shot generalization to new tools and MCP servers,...