TorqueAGI Site

Humanoids Summit Interview

In this Humanoids Summit interview, Ian Khan speaks with Ashutosh Saxena, Founder & CEO at TorqueAGI, about the innovations and leadership shaping humanoid robotics and AI solutions. Ashutosh shares insights into entrepreneurial strategy, scaling cutting-edge robotics technologies, and translating research into practical, real-world applications.

From Models to Machines: Building AI That Actually Delivers with Ash Saxena

Ash Saxena, Founder & Chief AI Officer of TorqueAGI, has dedicated decades to merging research and entrepreneurship in AI. His current focus is on enabling robots to perform meaningful tasks in the real world.

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Scaling Robotics Episode 4: Ashutosh Saxena (Founder, CEO @TorqueAGI)

In Episode 4, we speak with ⁠Ashutosh Saxena,⁠ CEO and Founder of ⁠Torque AGI⁠. Torque builds robotic foundation models for Fortune 100 companies like ⁠John Deere⁠.

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Humanoids Summit Interview

In this Humanoids Summit interview, Ian Khan speaks with Ashutosh Saxena, Founder & CEO at TorqueAGI, about the innovations and leadership shaping humanoid robotics and AI solutions. Ashutosh shares insights into entrepreneurial strategy, scaling cutting-edge robotics technologies, and translating research into practical, real-world applications.

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Your Home Can Be A Robot

In this episode of the Control Alt Podcast, we sit down with AI pioneer Dr. Ashutosh Saxena, the CEO and founder of Torque AGI. Dr. Saxena, who has worked with the likes of Andrew Ng at Stanford University, is at the forefront of the robotics revolution, building robots that can think and do things autonomously.

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TorqueFlow for end-to-end, from perception to placement

TorqueFlow classifies bags and selects grasp poses simultaneously. The orange overlay evaluates positions, ensuring informed decisions. Designed for mixed SKU pick-and-sort, it tackles logistics challenges with seamless object recognition and classification.

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NVIDIA GTC 2026 TorqueAGI Presentation

Dr. Ashutosh Saxena, Founder and CEO of TorqueAGI, takes the stage at NVIDIA GTC 2026 to present how TorqueAGI and NVIDIA technology work together to bring physical AI to enterprise-grade robotics.

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What package handling teaches us about Physical AI

Every warehouse is different. Conventional AI fails. Physical AI reasons. Robotic failure compounds but when logistics works, it unlocks global systems: freight, medicine, e-commerce. TorqueAGI is building that frontier.

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Long-horizon Robotic Tasks

Making ice cream is easy for humans. For robots, it exposes a hard problem. Long-horizon tasks require memory, planning, and coordination across many steps, not just perception and control.

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AI Models Concept Learning with Robert Scoble on Unaligned Podcast

Cross-embodiment learning shifts robotics from memorizing robot-specific datasets to learning transferable physical abstractions. The result: orders of magnitude less data and far faster deployment across different machines.

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Edge Foundation Model for Drones

This video shows TorqueAGI’s edge native foundation model running fully on device, operating in real time with no data sent off platform. The model runs live, observing the environment, reasoning over it, and triggering behavior under real world constraints

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Robobrain Cross-embodiment Learning

Cross-embodiment learning lets robots build on each other’s experience instead of starting over every time, unlocking their true potential. No retraining. No custom scripting. This was the idea behind Robobrain and the foundation that TorqueAGI is built on.

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Physical AI Foundation Model for Humanoids

At TorqueAGI, we are building the Physical AI foundation model that enables this structured decision-making. It lets humanoids handle complex workflows in warehouses, manufacturing, and logistics in the real world today.

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Graph Physical AI: Real-Time on Edge GPUs

VLAs can generalize in the cloud. Robots need real-time on the edge. The only architecture that works puts the entire intelligence pipeline on the GPU. Three steps make this possible.

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