Jason Ma

@JasonMa2020

Co-founder @DynaRobotics Prev: @GoogleDeepMind, @NVIDIAAI, @Penn, @Harvard.

jasonma2016.github.io

Joined August 2018

Replies Reposts Media

Jason Ma
@JasonMa2020
8h
Eureka was so ahead of its time
Wentao Zhu
@walterzhu8
11h
GPT-6 Astra test 4/n Prompt: "Implement pen spinning with a dexterous hand. Use Isaac Lab for RL training, use the Sharpa hand, and create the pen mesh yourself. Give me a trained RL policy and a visualization video. You are free to search the web and download papers or anything
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Jason Ma
@JasonMa2020
Aug 27
This is our release that I am actually most excited about because it shows and proves what truly matters. Deployment is the ultimate prize and the only reliable eval for robotics. After having worked on so many research projects and models in my career, where I saw so many new
Dyna Robotics
@DynaRobotics
Aug 27
After so many demos, models, pilots, robots are still struggling to land real deployments with real customers. Until now. Today we’re excited to share that our robots have successfully crossed the ROI threshold, and Din Tai Fung, one of the highest revenue per location
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Jason Ma
@JasonMa2020
Aug 18
I will be at #Actuate26 giving a talk on the model and infrastructure behind dyna-2. Excited to chat with everyone about scaling robot foundation models and deploying them in the real world! Please reach out if you'd like to chat!
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Jason Ma
@JasonMa2020
Aug 17
At million-hour scale, the bottleneck is not the robots or the GPUs. It's everything between the robots and GPUs. Our cracked infra team did an amazing job scaling up and revamping our ML infra to enable the dyna-2 breakthroughs! Read our new infra blog to catch a glimpse of the
Dyna Robotics
@DynaRobotics
Aug 17
When people talk about robotics, they usually talk about models, data, or hardware. Few people talk about the infrastructure that lets you iterate on all three quickly. Today we're publishing how we trained Dyna-2 on over 1,000,000 hours of egocentric video, repeatably. At this
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Jason Ma
@JasonMa2020
Aug 14
predicting the future is key for unlocking generalization, great work by Jesse and co!
Jesse Zhang
@Jesse_Y_Zhang
Aug 12
Robot WAMs typically predict future RGB latents trained for pixel reconstruction...but why stop there? We propose Flex-π, a WAM that jointly denoises multiple visual streams jointly, enabling the WAM to inherit strong 3D, object-centric, AND spatio-temporal priors for action