
Deepak Pathak
@deepakpathak • 29,177 subscribers
Co-Founder & CEO @SkildAI, Faculty @CarnegieMellon. PhD @UCBerkeley; BTech @IITKanpur I study topics in AI (robotics, machine learning & computer vision).
Videos

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.
Deepak Pathak177,547 Aufrufe • vor 3 Monaten

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.
Deepak Pathak79,343 Aufrufe • vor 3 Monaten

Force is arguably the most overlooked ingredient in modern robot learning. Introducing FACTR 2: it turns *any* commodity robot into a force-aware system with no force sensors required. Train a tiny force network in <1min with <10mins of data and drop it into any existing teleop pipelines: ✅ Free force sensing for both the robot and the operator arm ✅ Makes demos higher-quality → fewer of them needed. ✅ A new force-aware learning algorithm (FIRST) uses those recovered forces to figure out which parts of a demo actually matter, making learning data-efficient. ✅ Strong performance on complex tasks with fewer demos and even no pretraining! More details below.
Deepak Pathak38,967 Aufrufe • vor 1 Monat

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
Deepak Pathak45,984 Aufrufe • vor 4 Monaten
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