*)Traditional historians believe that he lived between 544-496 B.C.
*) He grew up with an education focusing on military affairs and politics.
*)Currently ,he is one of the East Asia’s most important historical figures.
*)His work was used by Napoleon, Mao Zedong, Fidel Castro, Joseph Stalin & Douglas Macarthur etc.
*)Originally Kautilya was a teacher at the ancient university of Takshashila which is considered as one of the first universities of the world.
*)Chanakya assisted Chandragupta Maurya in his rise to power.
*)Chanakya served as the chief advisor to both Emperor Chandragupta and his son Bindusara.
*) While Arthashastra Basically deals with Economics, NeetiShastra deals with Morals, Foreign Relations, War Statergies etc.
*)Their basic concept of fighting resemble each other as whole.
*)Both were very calculative and had great respect towards enemies.
*)Both had believed that war should be profitable if ever committed.
*)While Sun Tzu had focused on basically the military strategies, Chanakya had focused on all(Like Economics, Society etc).
*)Sun Tzu's philosophies are basically influenced by invading and conquering other states while Kautilya +
*) While China is using Sun Tzu's Philosophy in foreign policy and going on to become powerful nation, India is not using Chanakya Neeti and Arthashastra to become "Vishwaguru" or Worlds Leader/Philosopher.
As a gift to readers I am Sharing 3 books links
1) Arthashastra Pdf
https://t.co/nXiR97AwL6
2) Chanakya Neeti Pdf
https://t.co/VXiNIpJE9w
3) Sun Tzu "The Art of War" Pdf
https://t.co/vNVdkUkVg2
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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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First update to https://t.co/lDdqjtKTZL since the challenge ended – Medium links!! Go add your Medium profile now 👀📝 (thanks @diannamallen for the suggestion 😁)
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Less than 1 hour since I started adding stuff to https://t.co/lDdqjtKTZL again, and profile pages are now responsive!!! 🥳 Check it out -> https://t.co/fVkEL4fu0L
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Just added Telegram links to https://t.co/lDdqjtKTZL too! Now you can provide a nice easy way for people to message you :)
Less than 1 hour since I started adding stuff to https://t.co/lDdqjtKTZL again, and profile pages are now responsive!!! 🥳 Check it out -> https://t.co/fVkEL4fu0L
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his name might sound familiar because the new cortellucci vaughan hospital at mackenzie health, the one doug ford has been touting lately as a covid-centric facility, is named after him and his family
but his name also pops up in a LOT of other ford projects. for instance - he controls the long term lease on big parts of toronto's portlands... where doug ford once proposed building an nfl stadium and monorail... https://t.co/weOMJ51bVF
cortellucci, who is a developer, also owns a large chunk of the greenbelt. doug ford's desire to develop the greenbelt has been
and late last year he rolled back the mandate of conservation authorities there, prompting the resignations of several members of the greenbelt advisory
his name might sound familiar because the new cortellucci vaughan hospital at mackenzie health, the one doug ford has been touting lately as a covid-centric facility, is named after him and his family
but his name also pops up in a LOT of other ford projects. for instance - he controls the long term lease on big parts of toronto's portlands... where doug ford once proposed building an nfl stadium and monorail... https://t.co/weOMJ51bVF
cortellucci, who is a developer, also owns a large chunk of the greenbelt. doug ford's desire to develop the greenbelt has been
and late last year he rolled back the mandate of conservation authorities there, prompting the resignations of several members of the greenbelt advisory