Harness VLA extends frozen VLAs beyond their training distribution, improving strongest relevant baselines by 38.6 and 25.4 percentage points on LIBERO-Pro and RoboCasa365, reaching 58.4% on RoboTwin C2R.

NEO learns a latent world model without action labels, using VQ-VAE to build an action codebook so it can train directly from video and select actions at inference.

Semantic Anchoring for Robotic Action Representations anchors action representations to a semantic manifold and yields up to +18.7% on real-world in-distribution tasks and +21.5% on out-of-distribution generalization.

GigaWorld-Policy-0.5 preserves future visual dynamics training while achieving 85 ms inference latency on a local RTX 4090 setup for action-only robot control.

REAL-Bench spans 241 tasks; trained agents outperform leading commercial closed-source VLMs on interactive tasks with a 56.9% success rate and reach 78.3% end-to-end on 60 real-world episodes.

Kepler-Encoder-v0.1 fuses vision, proprioception, and force/torque into a shared latent, recovering force above raw frozen-ViT features and reaching AUROC 0.90 on out-of-range states.

PhysClaw-0 matches teleoperation episode success on a real-robot desktop-clearing testbed while reducing human working time to 16% and raising average single-attempt success from 12.5% to 47.5%.

EgoHTR introduces 55 scene-aligned 4D human motion sequences and over 150k frames, demonstrating state-of-the-art accuracy against motion-capture ground truth for human motion analysis and synthesis.

HELP achieves 80%–95% success rates and improves task throughput by 1.7×–4.2× over the base model across four real-world manipulation tasks.

Latent Policy Steering for robotic manipulation removes alpha-based regularization by optimizing a frozen flow-matching policy in latent noise space, improving robustness on physical robots.

Robot learning pipelines still mostly use 2D camera observations, even though manipulation problems often require 3D information about reachability, occlusion, and collision risk.

π*0.6 + RECAP turns robot deployment into continuous learning, using rollouts, failures, rewards, and human interventions to improve a VLA policy over time.

Pulkit’s RSS keynote framed generally useful robots as requiring both force intelligence and interactive intelligence, plus a deployment-to-learning loop for continuous improvement.

I’ve been working on a small open-source project called **LeRobot 3D** — a 3D-grounded teleoperation stack for the SO101 robot. Most accessible robo…

Kepler fuses robot sensors into one latent and, when given vision only, predicts force better than raw vision features on every robot with a force sensor.

Robotics Learning Packet RLP-001 contains subgoal trees, failure recovery branches, instruction variants, success/reward criteria, and XES traces; it covers tabletop tasks across 12 domains.

NVIDIA Gear Lab’s robottt scales robot context to 8,000 timesteps, or about 5 minutes of memory, a 1,000x jump from under 0.1 seconds.

Picture this: you ask an AI to "launch a new feature," and instead of one chatbot guessing what you mean, a whole team shows up-one agent asks clarif…

Markets don't move for one reason. They move [because thousands of signals](https://dev3lop.com/analyzing-data-on-the-use-of-transportation-services)…

Software development has always been about leverage: better languages, better tools, better frameworks, better automation. AI agents are the next lev…

We didn't adopt [offline LLMs](https://www.reddit.com/r/AnalyticsAutomation/comments/1rcsrpz/offline_llms_your_healthcare_teams_silent_hipaa) because…

## *Embedding MOGOPS v5.0 Coherence Architecture into Everyday Computing* ** [Blueprint](https://codeberg.org/TaoishTechy/EatherText/src/branch/main…

Explore LingBot World V2 14B Causal Fast, an interactive video model built for long sequences, character control, and real-time generation.

Angela Jiang and Katelyn Lesse explain why enterprise AI depends on layered architecture, token strategy, and reliable execution, not just better mod…

Inside the machines that dream in physics — and why they may finally drag AI out of the datacenter and onto the device on your desk.

Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal…