Shotwell.

Make the most of your robotics data.

[Shotwell. @ShotwellSt]

Shotwell works with robotics companies scaling their robotics data operations by providing annotations and quality checks.

It's been the biggest unlock for our customers, enabling them to make the most of their data

[Farhan Khan @farhunky]

Today, we're introducing @shotwellst.

We're solving the hardest problem in robotics: understanding your data

There’s no point collecting robotics data if you don't understand whats happening in it, but your options are limited. If you need dense, accurate labels with precise subtask boundaries, VLMs don't cut it, an in-house annotation army is a huge operational sink, and today's vendors charge an arm and a leg for low quality work

Shotwell combines the best of both worlds by training our own annotation models and letting humans deal with the ugly edge cases.

Its the ONLY way to consistently guarantee 100% quality in a scalable way. Humans are inconsistent, and models are inaccurate.

[Shotwell. @ShotwellSt]

@xdof * @xdofai! their ABC-130K is a huge open-source contribution, learn more about it here: https://t.co/pLRLmi9h7j

[XDOF @xdofai]

Read more and access the data here:

https://t.co/JAx21wwiL6

[Shotwell. @ShotwellSt]

Today, we are releasing over 415 hrs of annotations on top of the expansive ABC 130K data set from @xdof. We took 5 tasks and ran them through the Shotwell engine, and here are the results: https://t.co/5zVQ0BAVH5

[ali @si3luwa]

Automated temporal segmentation, dense descriptions of the segments, and scene descriptions of the data, with a bar for quality only humans can hit. Play around here: https://t.co/WYMhkiBkdE

[Farhan Khan @farhunky]

“Annotations” are a loaded term. Every company has different needs, different techniques, different strategies. And it’s difficult to have conversations that arent grounded in data. That’s why we’re sharing these annotations.

Play around with the demo here: https://t.co/jJprFZT8MO

[Varun Nair @_varunnair]

@ShotwellSt x @Ultraroboticsco just turned teleop data into reliable training data through dense annotation

Process is simple:
1. Define SOP - task definition, event definition, success criteria
2. Manual Annotation & Schema Alignment
3. Model Training + Human in the Loop

[zöda @zodattack]

this is huge actually

if they can effectively and accurately clip and annotate robotics data were at the cusp of the robotic Cambrian explosion.

huge congrats to the team, looking forward to seeing more.

[Ali Abid @anotheraliabid]

Just wrapped up my time at @huggingface building @Gradio a couple months ago. Still chasing the high of building ML tools - now in robotics! If you've got robotics data and need annotations, reach out and see how we can help!

[nour e @neldien_]

One of the biggest learnings from @ShotwellSt is that defining what good quality looks like is extremely difficult and vastly inconsistent.
It really takes a comprehensive cross industry view + going very deep to understand every customers use case

[Farhan Khan @farhunky]

In a few months, we helped @Ultraroboticsco 6x their operations, without having to scale up their team to match.

Take a look: https://t.co/ofKTUQlWJJ

[Farhan Khan @farhunky]

Today, we're introducing @shotwellst.

We're solving the hardest problem in robotics: understanding your data

There’s no point collecting robotics data if you don't understand whats happening in it, but your options are limited. If you need dense, accurate labels with precise subtask boundaries, VLMs don't cut it, an in-house annotation army is a huge operational sink, and today's vendors charge an arm and a leg for low quality work

Shotwell combines the best of both worlds by training our own annotation models and letting humans deal with the ugly edge cases.

Its the ONLY way to consistently guarantee 100% quality in a scalable way. Humans are inconsistent, and models are inaccurate.

[ali @si3luwa]

I left @huggingface a few months ago, and working there was a blast! Learned so much from everyone, especially the @Gradio team who were the smartest people i’ve ever worked with❤️

Will share soon what I’m working on now! 

pic is missing @abidlabs and @_akhaliq and so am I 😔

[Farhan Khan @farhunky]

Some personal news: I wrapped up my time at @sundayrobotics a few months ago, after an amazing year💛💛 (guess Monday is a fitting day for that announcement!)