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How can we use language supervision to learn better visual representations for robotics?
Introducing Voltron: Language-Driven Representation Learning for Robotics!
Paper: https://t.co/gIsRPtSjKz
Models: https://t.co/NOB3cpATYG
Evaluation: https://t.co/aOzQu95J8z
🧵👇(1 / 12)
Videos of humans performing everyday tasks (Something-Something-v2, Ego4D) offer a rich and diverse resource for learning representations for robotic manipulation.
Yet, an underused part of these datasets are the rich, natural language annotations accompanying each video. (2/12)
The Voltron framework offers a simple way to use language supervision to shape representation learning, building off of prior work in representations for robotics like MVP (https://t.co/Pb0mk9hb4i) and R3M (https://t.co/o2Fkc3fP0e).
The secret is *balance* (3/12)
Starting with a masked autoencoder over frames from these video clips, make a choice:
1) Condition on language and improve our ability to reconstruct the scene.
2) Generate language given the visual representation and improve our ability to describe what's happening. (4/12)
By trading off *conditioning* and *generation* we show that we can learn 1) better representations than prior methods, and 2) explicitly shape the balance of low and high-level features captured.
Why is the ability to shape this balance important? (5/12)
Introducing Voltron: Language-Driven Representation Learning for Robotics!
Paper: https://t.co/gIsRPtSjKz
Models: https://t.co/NOB3cpATYG
Evaluation: https://t.co/aOzQu95J8z
🧵👇(1 / 12)

Videos of humans performing everyday tasks (Something-Something-v2, Ego4D) offer a rich and diverse resource for learning representations for robotic manipulation.
Yet, an underused part of these datasets are the rich, natural language annotations accompanying each video. (2/12)
The Voltron framework offers a simple way to use language supervision to shape representation learning, building off of prior work in representations for robotics like MVP (https://t.co/Pb0mk9hb4i) and R3M (https://t.co/o2Fkc3fP0e).
The secret is *balance* (3/12)
Starting with a masked autoencoder over frames from these video clips, make a choice:
1) Condition on language and improve our ability to reconstruct the scene.
2) Generate language given the visual representation and improve our ability to describe what's happening. (4/12)
By trading off *conditioning* and *generation* we show that we can learn 1) better representations than prior methods, and 2) explicitly shape the balance of low and high-level features captured.
Why is the ability to shape this balance important? (5/12)
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And here they are...
THE WINNERS OF THE 24 HOUR STARTUP CHALLENGE
Remember, this money is just fun. If you launched a product (or even attempted a launch) - you did something worth MUCH more than $1,000.
#24hrstartup
The winners 👇
#10
Lattes For Change - Skip a latte and save a life.
https://t.co/M75RAirZzs
@frantzfries built a platform where you can see how skipping your morning latte could do for the world.
A great product for a great cause.
Congrats Chris on winning $250!
#9
Instaland - Create amazing landing pages for your followers.
https://t.co/5KkveJTAsy
A team project! @bpmct and @BaileyPumfleet built a tool for social media influencers to create simple "swipe up" landing pages for followers.
Really impressive for 24 hours. Congrats!
#8
SayHenlo - Chat without distractions
https://t.co/og0B7gmkW6
Built by @DaltonEdwards, it's a platform for combatting conversation overload. This product was also coded exclusively from an iPad 😲
Dalton is a beast. I'm so excited he placed in the top 10.
#7
CoderStory - Learn to code from developers across the globe!
https://t.co/86Ay6nF4AY
Built by @jesswallaceuk, the project is focused on highlighting the experience of developers and people learning to code.
I wish this existed when I learned to code! Congrats on $250!!
THE WINNERS OF THE 24 HOUR STARTUP CHALLENGE
Remember, this money is just fun. If you launched a product (or even attempted a launch) - you did something worth MUCH more than $1,000.
#24hrstartup
The winners 👇
#10
Lattes For Change - Skip a latte and save a life.
https://t.co/M75RAirZzs
@frantzfries built a platform where you can see how skipping your morning latte could do for the world.
A great product for a great cause.
Congrats Chris on winning $250!

#9
Instaland - Create amazing landing pages for your followers.
https://t.co/5KkveJTAsy
A team project! @bpmct and @BaileyPumfleet built a tool for social media influencers to create simple "swipe up" landing pages for followers.
Really impressive for 24 hours. Congrats!

#8
SayHenlo - Chat without distractions
https://t.co/og0B7gmkW6
Built by @DaltonEdwards, it's a platform for combatting conversation overload. This product was also coded exclusively from an iPad 😲
Dalton is a beast. I'm so excited he placed in the top 10.

#7
CoderStory - Learn to code from developers across the globe!
https://t.co/86Ay6nF4AY
Built by @jesswallaceuk, the project is focused on highlighting the experience of developers and people learning to code.
I wish this existed when I learned to code! Congrats on $250!!
