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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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This is NONSENSE. The people who take photos with their books on instagram are known to be voracious readers who graciously take time to review books and recommend them to their followers. Part of their medium is to take elaborate, beautiful photos of books. Die mad, Guardian.
THEY DO READ THEM, YOU JUDGY, RACOON-PICKED TRASH BIN
If you come for Bookstagram, i will fight you.
In appreciation, here are some of my favourite bookstagrams of my books: (photos by lit_nerd37, mybookacademy, bookswrotemystory, and scorpio_books)
Beautifully read: why bookselfies are all over Instagram https://t.co/pBQA3JY0xm
— Guardian Books (@GuardianBooks) October 30, 2018
THEY DO READ THEM, YOU JUDGY, RACOON-PICKED TRASH BIN
If you come for Bookstagram, i will fight you.
In appreciation, here are some of my favourite bookstagrams of my books: (photos by lit_nerd37, mybookacademy, bookswrotemystory, and scorpio_books)
1/x Fort Detrick History
Mr. Patrick, one of the chief scientists at the Army Biological Warfare Laboratories at Fort Detrick in Frederick, Md., held five classified US patents for the process of weaponizing anthrax.
2/x
Under Mr. Patrick’s direction, scientists at Fort Detrick developed a tularemia agent that, if disseminated by airplane, could cause casualties & sickness over 1000s mi². In a 10,000 mi² range, it had 90% casualty rate & 50% fatality rate
3/x His team explored Q fever, plague, & Venezuelan equine encephalitis, testing more than 20 anthrax strains to discern most lethal variety. Fort Detrick scientists used aerosol spray systems inside fountain pens, walking sticks, light bulbs, & even in 1953 Mercury exhaust pipes
4/x After retiring in 1986, Mr. Patrick remained one of the world’s foremost specialists on biological warfare & was a consultant to the CIA, FBI, & US military. He debriefed Soviet defector Ken Alibek, the deputy chief of the Soviet biowarfare program
https://t.co/sHqSaTSqtB
5/x Back in Time
In 1949 the Army created a small team of chemists at "Camp Detrick" called Special Operations Division. Its assignment was to find military uses for toxic bacteria. The coercive use of toxins was a new field, which fascinated Allen Dulles, later head of the CIA
Mr. Patrick, one of the chief scientists at the Army Biological Warfare Laboratories at Fort Detrick in Frederick, Md., held five classified US patents for the process of weaponizing anthrax.
2/x
Under Mr. Patrick’s direction, scientists at Fort Detrick developed a tularemia agent that, if disseminated by airplane, could cause casualties & sickness over 1000s mi². In a 10,000 mi² range, it had 90% casualty rate & 50% fatality rate
3/x His team explored Q fever, plague, & Venezuelan equine encephalitis, testing more than 20 anthrax strains to discern most lethal variety. Fort Detrick scientists used aerosol spray systems inside fountain pens, walking sticks, light bulbs, & even in 1953 Mercury exhaust pipes
4/x After retiring in 1986, Mr. Patrick remained one of the world’s foremost specialists on biological warfare & was a consultant to the CIA, FBI, & US military. He debriefed Soviet defector Ken Alibek, the deputy chief of the Soviet biowarfare program
https://t.co/sHqSaTSqtB
5/x Back in Time
In 1949 the Army created a small team of chemists at "Camp Detrick" called Special Operations Division. Its assignment was to find military uses for toxic bacteria. The coercive use of toxins was a new field, which fascinated Allen Dulles, later head of the CIA