Here's a thread for PARENTS with some of the most useful FREE resources for YOU (breath!) and your kids in lockdown. None of these links require you to sign up for stuff. You've got this 💪
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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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Trading view scanner process -
1 - open trading view in your browser and select stock scanner in left corner down side .
2 - touch the percentage% gain change ( and u can see higest gainer of today)
3. Then, start with 6% gainer to 20% gainer and look charts of everyone in daily Timeframe . (For fno selection u can choose 1% to 4% )
4. Then manually select the stocks which are going to give all time high BO or 52 high BO or already given.
5. U can also select those stocks which are going to give range breakout or already given range BO
6 . If in 15 min chart📊 any stock sustaing near BO zone or after BO then select it on your watchlist
7 . Now next day if any stock show momentum u can take trade in it with RM
This looks very easy & simple but,
U will amazed to see it's result if you follow proper risk management.
I did 4x my capital by trading in only momentum stocks.
I will keep sharing such learning thread 🧵 for you 🙏💞🙏
Keep learning / keep sharing 🙏
@AdityaTodmal
1 - open trading view in your browser and select stock scanner in left corner down side .
2 - touch the percentage% gain change ( and u can see higest gainer of today)
Making thread \U0001f9f5 on trading view scanner by which you can select intraday and btst stocks .
— Vikrant (@Trading0secrets) October 22, 2021
In just few hours (Without any watchlist)
Some manual efforts u have to put on it.
Soon going to share the process with u whenever it will be ready .
"How's the josh?"guys \U0001f57a\U0001f3b7\U0001f483
3. Then, start with 6% gainer to 20% gainer and look charts of everyone in daily Timeframe . (For fno selection u can choose 1% to 4% )
4. Then manually select the stocks which are going to give all time high BO or 52 high BO or already given.
5. U can also select those stocks which are going to give range breakout or already given range BO
6 . If in 15 min chart📊 any stock sustaing near BO zone or after BO then select it on your watchlist
7 . Now next day if any stock show momentum u can take trade in it with RM
This looks very easy & simple but,
U will amazed to see it's result if you follow proper risk management.
I did 4x my capital by trading in only momentum stocks.
I will keep sharing such learning thread 🧵 for you 🙏💞🙏
Keep learning / keep sharing 🙏
@AdityaTodmal