In a Hindu home, the main door is extremely important. It is adorned with toran and other religiously significant items. It represents the divide between the inner and outside worlds.
#Thread
· Pumpkin & Horseshoe
· In some regions, a face (mask) with protruding eyes, a big mustache, and a tongue is kept on the front door.
More from Sriram 🇮🇳
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Margatha Natarajar murthi - Uthirakosamangai temple near Ramanathapuram,TN
#ArudraDarisanam
Unique Natarajar made of emerlad is abt 6 feet tall.
It is always covered with sandal paste.Only on Thriuvadhirai Star in month Margazhi-Nataraja can be worshipped without sandal paste.
After removing the sandal paste,day long rituals & various abhishekam will be https://t.co/e1Ye8DrNWb day Maragatha Nataraja sannandhi will be closed after anointing the murthi with fresh sandal paste.Maragatha Natarajar is covered with sandal paste throughout the year
as Emerald has scientific property of its molecules getting disturbed when exposed to light/water/sound.This is an ancient Shiva temple considered to be 3000 years old -believed to be where Bhagwan Shiva gave Veda gyaana to Parvati Devi.This temple has some stunning sculptures.
#ArudraDarisanam
Unique Natarajar made of emerlad is abt 6 feet tall.
It is always covered with sandal paste.Only on Thriuvadhirai Star in month Margazhi-Nataraja can be worshipped without sandal paste.
After removing the sandal paste,day long rituals & various abhishekam will be https://t.co/e1Ye8DrNWb day Maragatha Nataraja sannandhi will be closed after anointing the murthi with fresh sandal paste.Maragatha Natarajar is covered with sandal paste throughout the year
as Emerald has scientific property of its molecules getting disturbed when exposed to light/water/sound.This is an ancient Shiva temple considered to be 3000 years old -believed to be where Bhagwan Shiva gave Veda gyaana to Parvati Devi.This temple has some stunning sculptures.
APIs in general are so powerful.
Best 5 public APIs you can use to build your next project:
1. Number Verification API
A RESTful JSON API for national and international phone number validation.
🔗 https://t.co/fzBmCMFdIj
2. OpenAI API
ChatGPT is an outstanding tool. Build your own API applications with OpenAI API.
🔗 https://t.co/TVnTciMpML
3. Currency Data API
Currency Data API provides a simple REST API with real-time and historical exchange rates for 168 world currencies
🔗 https://t.co/TRj35IUUec
4. Weather API
Real-Time & historical world weather data API.
Retrieve instant, accurate weather information for
any location in the world in lightweight JSON format.
🔗 https://t.co/DCY8kXqVIK
Best 5 public APIs you can use to build your next project:
1. Number Verification API
A RESTful JSON API for national and international phone number validation.
🔗 https://t.co/fzBmCMFdIj
2. OpenAI API
ChatGPT is an outstanding tool. Build your own API applications with OpenAI API.
🔗 https://t.co/TVnTciMpML
3. Currency Data API
Currency Data API provides a simple REST API with real-time and historical exchange rates for 168 world currencies
🔗 https://t.co/TRj35IUUec
4. Weather API
Real-Time & historical world weather data API.
Retrieve instant, accurate weather information for
any location in the world in lightweight JSON format.
🔗 https://t.co/DCY8kXqVIK
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)