The industry needs a unified intelligence infrastructure that any robot, any model, and any workflow can plug into. We call this an intelligence grid. Infrastructure that makes intelligence composable, deployable, and continuously adapting. Every connected robot evolves as the platform advances.

From simulation to a live multi-agent detection dashboard with GRID’s cloud-native unified stack for simulation, vision inferencing and telemetry.

For decades, the pursuit of general-purpose robotics has swung between brittle pipelines and large monolithic foundation models. Hand-engineered pipelines deliver reliable performance in narrow domains but are difficult to adapt or reuse.

It's easy to think these robots can now do almost anything. After all, humans master basic tasks before moving on to complex skills like kung-fu. But robots don't learn like us. Today, we're excited to introduce DreamControl, a workflow for building core skills for humanoid robots that can be useful, today.

At General Robotics, our mission is bold - build general-purpose intelligence for every robot—across any form, task or environment.

Signal Temporal Logic (STL) provides a precise formal language for specifying desired robotic system behavior, grounded in a well-developed theoretical foundation of logic.

Today, we’re thrilled to announce the integration of NVIDIA Isaac Sim, a reference application for robot simulation built on the NVIDIA Omniverse platform, into GRID, our General Robot Intelligence Development platform.

A pivotal step forward in the evolution of simulation technology, expanding the possibilities for AI and robotics development.

Combining the speed of State Space Models (SSMs) like Mamba2 with the adaptability of Matryoshka-style learning.

A private GRID experience that is scalable, customizable, and deeply integrated into your development pipeline.

Language is the most intuitive way for us to express how we feel and what we want.

Simulation is playing an increasingly major role in the development of safe and robust autonomous systems, especially given the advent of deep learning techniques.

Recent advances in machine learning architectures have induced a paradigm shift from task-specific models towards large general-purpose networks.

The General Robot Intelligence Development (GRID) platform combines foundation models, simulation, and large language models for rapid prototyping

We released a platform for creating intelligent and safe robots using foundation models, large language models, and simulation.

I ran the autonomous systems and robotics research effort at Microsoft for nearly a decade and here are our biggest learnings.

We are announcing SMART, a generalized pretraining framework for a wide variety of control tasks.

We introduce Perception Action Signal Temporal Logic Transformer (PASTEL), a deep machine learning architecture to control robots safely.

We extended the capabilities of ChatGPT to robotics, and controlled multiple platforms such as robot arms, drones, and home assistant robots intuitively with language.

We’re opening the waitlist for our General Robot Intelligence Development (GRID) platform. GRID is an open and free cloud-based IDE for robotics, requiring zero setup. GRID accelerates robot AI development with seamless access to foundation models, simulation and AI infrastructure.