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Deepak Pathak

@pathak2206 • 28,460 subscribers

Co-Founder & CEO @SkildAI, Faculty @CarnegieMellon. PhD @UCBerkeley; BTech @IITKanpur I study topics in AI (robotics, machine learning & computer vision).

Shorts

Incredible news. Neural MP has won the Best Student Paper award at IROS 2025!! Congratulations to Murtaza Dalal & Jiahui(Jim) Yang for leading the project along with Russell Mendonca, youssef, Russ Salakhutdinov. Neural MP is a major step in making motion planning end-to-end, fast & reactive.

Incredible news. Neural MP has won the Best Student Paper award at IROS 2025!! Congratulations to Murtaza Dalal & Jiahui(Jim) Yang for leading the project along with Russell Mendonca, youssef, Russ Salakhutdinov. Neural MP is a major step in making motion planning end-to-end, fast & reactive.

40,424 views

Seeing ≠ feeling in robotics🤖. Collecting data without force feedback is not only frustrating but also doesn’t work for contact-rich tasks. Introducing FACTR: a low-cost teleop that lets users feel what the robot feels + a simple algo to integrate force into autonomous policies. Video doesn't do justice, but feels magical in person!🚀 Also removes the need for gravity compensation strings.

Seeing ≠ feeling in robotics🤖. Collecting data without force feedback is not only frustrating but also doesn’t work for contact-rich tasks. Introducing FACTR: a low-cost teleop that lets users feel what the robot feels + a simple algo to integrate force into autonomous policies. Video doesn't do justice, but feels magical in person!🚀 Also removes the need for gravity compensation strings.

33,573 views

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We hosted Prof. Alyosha Efros (UC Berkeley) at Skild AI! He didn't believe that robots could actually cook eggs reliably. :) Tested back-to-back 5times without fail! One batch of scrambled eggs every ~2.5mins nonstop. The same model assembles a GPU on a server rack too.

We hosted Prof. Alyosha Efros (UC Berkeley) at Skild AI! He didn't believe that robots could actually cook eggs reliably. :) Tested back-to-back 5times without fail! One batch of scrambled eggs every ~2.5mins nonstop. The same model assembles a GPU on a server rack too.

171,419 views • 2 months ago

Excited to announce that Skild AI has completed the acquisition of Zebra Technologies’ robotics arm (formerly Fetch Robotics). By combining Zebra's human-robot orchestration platform with omnibodied Skild Brain, we plan to turn warehouses everywhere into hubs of hyper-efficiency. Imagine a single platform, single brain optimizing every movement of robots as well as human workers in warehouses. Many of us in the robotics community have used Fetch Robots in the past and have rooted for them over the years, so this acquisition is special for us in many ways.

Excited to announce that Skild AI has completed the acquisition of Zebra Technologies’ robotics arm (formerly Fetch Robotics). By combining Zebra's human-robot orchestration platform with omnibodied Skild Brain, we plan to turn warehouses everywhere into hubs of hyper-efficiency. Imagine a single platform, single brain optimizing every movement of robots as well as human workers in warehouses. Many of us in the robotics community have used Fetch Robots in the past and have rooted for them over the years, so this acquisition is special for us in many ways.

78,880 views • 1 month ago

At Skild AI, we’ve raised $1.4B, bringing our valuation to over $14B. We’re on a generational mission, and I’m grateful to be working alongside an exceptional team. Thanks to our investors for the long-term conviction towards omni-bodied intelligence 🚀

At Skild AI, we’ve raised $1.4B, bringing our valuation to over $14B. We’re on a generational mission, and I’m grateful to be working alongside an exceptional team. Thanks to our investors for the long-term conviction towards omni-bodied intelligence 🚀

159,376 views • 4 months ago

Robots assembling robot brain -- imagine this kind of robustness on every precision manufacturing line! Live demo of GPU rack assembly at #NVIDIAGTC: - end-to-end neural network (Skild Brain) finetuned with little data - memory to perform long horizon task (placing jigs, 16 screwes, removing jigs) - robust to disturbances and fast to set up - no fancy sensors, just off-the-shelf arms and cameras

Robots assembling robot brain -- imagine this kind of robustness on every precision manufacturing line! Live demo of GPU rack assembly at #NVIDIAGTC: - end-to-end neural network (Skild Brain) finetuned with little data - memory to perform long horizon task (placing jigs, 16 screwes, removing jigs) - robust to disturbances and fast to set up - no fancy sensors, just off-the-shelf arms and cameras

45,564 views • 2 months ago

Even after 4yrs of locomotion research, we keep getting surprised by how far we can push the limits of legged robots! We report a major update 🚀🤖 Extreme Parkour: extremely long & high jumps, ramp, handstand, etc. all with a single neural net! 🧵(1/n)

Even after 4yrs of locomotion research, we keep getting surprised by how far we can push the limits of legged robots! We report a major update 🚀🤖 Extreme Parkour: extremely long & high jumps, ramp, handstand, etc. all with a single neural net! 🧵(1/n)

260,141 views • 2 years ago

Introducing ManipGen: a sim2real agent for zero-shot manipulation. ManipGen handles complex tasks in the real world like organizing shelves, tidying cluttered tables, and more – all from text input and with on human demonstrations!

Introducing ManipGen: a sim2real agent for zero-shot manipulation. ManipGen handles complex tasks in the real world like organizing shelves, tidying cluttered tables, and more – all from text input and with on human demonstrations!

57,936 views • 1 year ago

Motion planning in complex tasks is hard and still done via slow, explicit, traditional planners. We present a generalist Neural Motion Planner -- a single neural network that plans complex dynamic motions quickly and accurately at test time. Building upon our lab's sim2real efforts, the key idea is to create many complex scenes in simulation and then distill classical motion planner trajectories into a single reactive neural network policy. More details in the thread below! 👇 Open-sourced:

Motion planning in complex tasks is hard and still done via slow, explicit, traditional planners. We present a generalist Neural Motion Planner -- a single neural network that plans complex dynamic motions quickly and accurately at test time. Building upon our lab's sim2real efforts, the key idea is to create many complex scenes in simulation and then distill classical motion planner trajectories into a single reactive neural network policy. More details in the thread below! 👇 Open-sourced:

28,642 views • 1 year ago

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