Embodied AI2025
GPU-accelerated physics simulation engine for robotics and simulation research — built on NVIDIA Warp with MuJoCo Warp backend, offering differentiable simulation, OpenUSD support, and extensions for RL/embodied-AI workflows. ([github.com](https://github.com/newton-physics/newton))
AI Video2025
Real-time, streaming world model for interactive long-horizon video and scene generation — provides persistent memory across interactions, streaming inference for live scenarios, and example demos for building interactive environments.
AI Deploy2025
Turns commodity WiFi Channel State Information into spatial sensing: 17-keypoint pose estimation, presence detection, and contactless breathing/heart-rate monitoring through walls, with no camera. Runs on a mesh of ESP32-S3 nodes (~$9 each).
Embodied AI2025
Provides a unified Python interface to collect data, train visual/dynamics world models, and evaluate them with model-predictive control across many standardized environments. Includes reference baselines, planning solvers, dataset converters, and LanceDB-backed formats for reproducible experiments. Best suited for researchers benchmarking world-model algorithms.
Embodied AI2025
Detects motion from Wi‑Fi channel state information (CSI) on cheap ESP32 boards and integrates natively with Home Assistant; offers an optional on‑device ML detector that requires no calibration.
Embodied AI2025
Contains training, evaluation, and deployment code plus checkpoints for humanoid whole-body controllers (Decoupled WBC and GEAR‑SONIC). Includes C++ inference, VR teleoperation, data pipelines (Bones‑SEED) and Hugging Face checkpoints for research-to-robot workflows.
Embodied AI2026
Enables research-grade character animation with neural networks in a single NumPy/PyTorch environment — train models, run inference, and visualize results without leaving Python. Includes ECS-style architecture, mocap import (GLB/FBX/BVH), built-in renderer, and headless/standalone modes for rapid prototyping.
Embodied AI2026
Train robot reinforcement-learning agents with a heterogeneous runtime that streams CPU-parallel physics simulations (MuJoCo / Motrix) via shared memory into GPU/accelerator policy learners; provides a unified CLI, cross-platform backend support and demo checkpoints.
AI Dataset2026
Provides an annotated multimodal human-motion dataset for language-to-action and robotics research, with BVH and MuJoCo files plus recordings targeted at Unitree-G1 and NVIDIA-SOMA platforms. Covers locomotion, gestures, dance and object interaction with English annotations and 100K–1M samples.
AI Dataset2026
Transforms articulated 3D asset creation into a programmatic, LLM-driven code-generation workflow that produces objects with semantic parts, robust geometry, and physical joints. Includes CLI generation, a local viewer, and pipelines for large-scale dataset contribution.
Embodied AI2026
Reconstructs camera poses and dense 3D point clouds from video streams using a feed‑forward foundation model. Combines a Geometric Context Transformer (anchor + local window + trajectory memory) with paged KV‑cache attention to enable stable, long‑sequence streaming inference (~20 FPS at 518×378).
AI Dataset2026
Provides a large-scale multimodal embodied dataset (vision, depth, hand/arm kinematics, tactile) captured with an exoskeleton glove and egocentric sensors; organized as clip-level Zarr volumes for manipulation, imitation learning, and vision–action research. Includes both high-precision glove measurements and natural bare-hand clips; sizable storage required.