Krishnan Srinivasan

[Chuning Zhu @chuning_zhu]

Can we get robots to think before they act? In Latent Memory Palace, we achieve this through a classic principle: variational inference. (1/8)

[Murtaza Dalal @mihdalal]

Handy

[Russ Tedrake @RussTedrake]

TRI's latest Large Behavior Model (LBM) paper landed on arxiv last night! Check out our project website: https://t.co/AV2cmfeX40

One of our main goals for this paper was to put out a very careful and thorough study on the topic to help people understand the state of the technology, and to share a lot of details for how we're achieving it.

https://t.co/EVFLJAY6Zu

[Krishnan Srinivasan @krishpopdesu]

Want your dexterous allegro hand to pick up a novel object, but don't know where to start? Check out our work "Get a Grip" at #corl2024, and grab our diverse grasping dataset and model for dexterous grasps :)

[Albert Li @albert_h_li]

There have been many recent big grasping datasets, but few demos of real-world grasping using generative models. How do we achieve this?

Introducing: Get a Grip (#corl2024)!

We show that instead of generative models, discriminative models can attain sim2real transfer!

👀🧵👇

[Zipeng Fu @zipengfu]

Introduce HumanPlus - Shadowing part

Humanoids are born for using human data. We build a real-time shadowing system using a single RGB camera and a whole-body policy for cloning human motion. Examples:
- boxing🥊
- playing the piano🎹/ping pong
- tossing
- typing

Open-sourced!

[Ignat Georgiev @imgeorgiev]

We have a new ICML paper! Adaptive Horizon Actor Critic (AHAC). Joint work with @krishpopdesu @xujie7979 @eric_heiden @animesh_garg

AHAC is a first-order model-based RL algorithm that learns high-dimensional tasks in minutes and outperforms PPO by 40%.
🧵(1/4)

[Cheng Chi @chichengcc]

We made a step-by-step video tutorial for building the UMI gripper! Please leave comments on @YouTube if you have any question
https://t.co/UptjPrRaEq

[Andrej Karpathy @karpathy]

# on technical accessibility

One interesting observation I think back to often:
- when I first published the micrograd repo, it got some traction on GitHub but then somewhat stagnated and it didn't seem that people cared much.
- then I made the video building it from scratch, and the repo immediately went through hockey stick growth and became a verty often cited reference for people learning backpropagation.

This was interesting because the micrograd code itself didn't change at all and it was up on GitHub for many months before, stagnating. The code made sense to me (because I wrote it), it was only ~200 lines of code, it was extensively commented in the .py files and in the Readme, so I thought surely it was clear and/or self-explanatory. I was very happy with myself about how minimal the code was for explaining backprop - it strips away a ton of complexity and just gets to the very heart of an autograd engine on one page of code. But others didn't seem to think so, so I just kind of brushed it off and moved on.

Except it turned out that what stood in its way was "just" a matter of accessibility. When I made the video that built it and walked through it, it suddenly almost 100X'd the overall interest and engagement with that exact same piece of code. Not only from beginners in the field who needed the full intro and explanation, but even from more technical/expert friends, who I think could have understood it if they looked at it long enough, but were deterred by a barrier to entry.

I think as technical people we have a strong bias to put up code or papers or the final thing and feel like things are mostly self-explanatory. It's there, and also it's commented, there is a Readme, so all is well, and if people don't engage then it's just because the thing is not good enough. But the reality is that there is still a large barrier to engage with your thing (even for other experts who might not feel like spending time/effort!), and you might be leaving somewhere 10-100X of the potential of that exact same piece of work on the table just because you haven't made it sufficiently accessible.

TLDR: Step 1 build the thing. Step 2 build the ramp. 📈
Some voice in your head will tell you that this is not necessary, but it is wrong.

[Krishnan Srinivasan @krishpopdesu]

Foundational moment in robotics! Huge props to @QuanVng and @KarlPertsch for coordinating such a massive project

[Karl Pertsch @KarlPertsch]

Very excited to release the Open X-Embodiment Dataset today — the largest robot dataset to date with 1M+ trajectories! Robotics needs more data & this is a big step!
https://t.co/wokjrOO2jg

There’s lots to unpack here, so let’s do a deep dive into the dataset!

🧵1/15

[Krishnan Srinivasan @krishpopdesu]

It's been great experience working with the team on this, with much more to come!

[Tesla Optimus @Tesla_Optimus]

Optimus can now sort objects autonomously 🤖

Its neural network is trained fully end-to-end: video in, controls out.

Come join to help develop Optimus (& improve its yoga routine 🧘)

→ https://t.co/dBhQqg1qya

[Siddharth Karamcheti @siddkaramcheti]

Check out the Robotics section (§2.3), discussing opportunities in applying #foundationmodels across the robotics pipeline.

Challenges await! Collecting the right data, ensuring safety are crucial. But tackling these problems now – *before* building models – is key!

[Dorsa Sadigh @DorsaSadigh]

Making assistive teleoperation intuitive, easy to operate, and precise! The journal version of our work on the framework of learned latent actions + shared autonomy + personalization is out. We also have new studies with users with disability.
Paper: https://t.co/KXomKMMhvV

[Ashwin Balakrishna @ashwinb96]

Safe learning is critical for using RL to learn tasks in the real world. We introduce Recovery RL: https://t.co/N68B3UQ0Th in collaboration with @brthananjeyan, @SurajNair_1, Michael Luo, @krishpopdesu, @MinhoHwang6, @mejoeyg, @julianibarz, @chelseabfinn, @ken_goldberg 👇(1/8)

[Krishnan Srinivasan @krishpopdesu]

Today’s one of those days where if I suddenly woke up from a coma after >= 7mo and you explained everything that’s going on and why the sky turned completely orange, I’d demand to be put back into another coma

[Anthony Castrio @AnthonyCastrio]

The latest issue Out-Of-Pocket from @nikillinit is so so on point.

https://t.co/nqtPbYPjA1

[Winnie Xu @winniethexu]

I want naan, not NaN.

[ACLU @ACLU]

BREAKING: The Trump administration just agreed to rescind its harmful policy that would've barred international students who attend universities or colleges that are fully online this upcoming semester.

This is what victory looks like.

Keep speaking out. Keep fighting back.

[Jeannette Bohg @leto__jean]

Code now available at https://t.co/EWqkUSGcAp

[Krishnan Srinivasan @krishpopdesu]

@NAChristakis @threadreaderapp unroll

[Stanford AI Lab @StanfordAILab]

The International Conference on Robotics and Automation (ICRA) 2020 is being hosted virtually from May 31 – Jun 4.

We’re excited to share all the work from SAIL and Stanford that’s being presented in our new blog post:

https://t.co/fF5GpGSA73