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Robotics

Genesis AI Releases Nyx, Quadrants, and Genesis World 1.0 Physics Platform for Scalable Robotics Foundation Model Evaluation

Genesis AI released Genesis World 1.0. The platform consists of four components: the Genesis World physics engine, Nyx (a real-time path-traced renderer), Quadrants (a Python-to-GPU compiler), and a simulation interface. It is designed to accelerate robotics foundation model development through simulation-based evaluation. Robotics model development has two bottlenecks: data and iteration speed. The field has…

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NVIDIA Releases Cosmos 3: A Two-Tower Mixture-of-Transformers Foundation Model Unifying Physical Reasoning, World Generation, and Action Generation

NVIDIA AI team have released Cosmos 3. It is a family of omnimodal world models for physical AI. The models combine physical reasoning, world generation, and action generation. All three capabilities live inside one open model. NVIDIA open sourced the checkpoints, training scripts, deployment tools, and datasets. The Cosmos 3 release targets robotics, autonomous vehicles,…

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A Coding Guide to Markerless 3D Human Kinematics with Pose2Sim, RTMPose, and OpenSim

import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D from pathlib import Path import re def parse_trc(trc_path): """Parse a .trc file and return marker names, frame data, and metadata.""" with open(trc_path, 'r') as f: lines = f.readlines() meta_keys = lines[2].strip().split('\t') meta_vals = lines[3].strip().split('\t') …

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Google DeepMind Releases Gemini Robotics-ER 1.6: Bringing Enhanced Embodied Reasoning and Instrument Reading to Physical AI

Google DeepMind research team introduced Gemini Robotics-ER 1.6, a significant upgrade to its embodied reasoning model designed to serve as the ‘cognitive brain’ of robots operating in real-world environments. The model specializes in reasoning capabilities critical for robotics, including visual and spatial understanding, task planning, and success detection — acting as the high-level reasoning model…

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How to Build Advanced Cybersecurity AI Agents with CAI Using Tools, Guardrails, Handoffs, and Multi-Agent Workflows

In this tutorial, we build and explore the CAI Cybersecurity AI Framework step by step in Colab using an OpenAI-compatible model. We begin by setting up the environment, securely loading the API key, and creating a base agent. We gradually move into more advanced capabilities such as custom function tools, multi-agent handoffs, agent orchestration, input…

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Physical Intelligence Team Unveils MEM for Robots: A Multi-Scale Memory System Giving Gemma 3-4B VLAs 15-Minute Context for Complex Tasks

Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to failure. To address this, researchers from Physical Intelligence, Stanford, UC Berkeley, and MIT have…

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NVIDIA Releases DreamDojo: An Open-Source Robot World Model Trained on 44,711 Hours of Real-World Human Video Data

Building simulators for robots has been a long term challenge. Traditional engines require manual coding of physics and perfect 3D models. NVIDIA is changing this with DreamDojo, a fully open-source, generalizable robot world model. Instead of using a physics engine, DreamDojo ‘dreams’ the results of robot actions directly in pixels. https://arxiv.org/pdf/2602.06949 Scaling Robotics with 44k+…

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Ant Group Releases LingBot-VLA, A Vision Language Action Foundation Model For Real World Robot Manipulation

How do you build a single vision language action model that can control many different dual arm robots in the real world? LingBot-VLA is Ant Group Robbyant’s new Vision Language Action foundation model that targets practical robot manipulation in the real world. It is trained on about 20,000 hours of teleoperated bimanual data collected from 9…

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