ishaan

[ishaan @ishaans22]

I built differentially private fine-tuning for MLX so you can train local models on your private data. The full stack fits in ~600 lines and drops attacker recovery of training data from 90% to 50% 1/6

[ishaan @ishaans22]

@ishand 🚀🚀

[ishaan @ishaans22]

@josephjojoe @conviction @tkkong @philhchen @shreyanj98 🚀🚀🚀

[ishaan @ishaans22]

@jaiselsingh @Overland_AI_X @RJBtheBear 🚀

[ishaan @ishaans22]

@contextkingceo 🚀🚀

[ishaan @ishaans22]

@BhathalTanvir0 🚀

[ishaan @ishaans22]

@rishiiyer01 Yes

[underscore advait patel @_advaitpatel]

Mind has raised an additional $400M, bringing our total funding to over $1 billion. We are building dexterous, general-purpose robots and foundation models for industrial deployment, starting with the automotive industry. I’m super excited and grateful to be working on these problems with such a stellar team.

We are uniquely positioned to tackle the general-purpose robotics problem given our deep partnership with @Rivian, who is a shareholder and our pilot customer, and who is also providing us with data from production lines to add to our training mixture.

It’s still super early days, and we’re hiring across research, software, hardware, and more! (Link below)

[ishaan @ishaans22]

@_advaitpatel @k7agar @Mind_Robotics 🚀

[ishaan @ishaans22]

@thatkavish @bayesarea 🚀🚀

[Kavish Garg @thatkavish]

https://t.co/QaWAt98mFm

[ishaan @ishaans22]

@neerajprasad 🚀🚀

[ishaan @ishaans22]

@jaiselsingh etc robotics

[ishaan @ishaans22]

@rishiiyer01 @rawsh0 🚀🚀

[jaisel @jaiselsingh]

Let’s go! finally got post-physics parameter optimization working.

Shared parameters across multiple real-world trajectories, fitting the sim closer to reality instead of tuning one rollout at a time :)

[ishaan @ishaans22]

@jaiselsingh 🚀🚀🚀

[Divya Dhulipala @DivyaDhulipala]

https://t.co/Ft2gQfFAfL

[Aashay Sanghvi @aashaysanghvi_]

https://t.co/LuGVG1Yjet

[ishaan @ishaans22]

@DivyaDhulipala 🚀🚀

[ishaan @ishaans22]

@aashaysanghvi_ 🚀🚀

[ishaan @ishaans22]

@josephjojoe 🚀🚀