A list of cool websites you might now know about

A thread 🧵

1) Learn Anything - Search tools for knowledge discovery that helps you understand any topic through the most efficient path

https://t.co/k3sGW1m1d6
2) Grad Speeches - Discover the best commencement speeches.

This website is made by me šŸ™ˆ

https://t.co/inO0Uig6NQ
3) What does the Internet Think - Find out what the internet thinks about anything

https://t.co/Bf1Ph0xxYv
4) https://t.co/vuhT6jVItx - Send notes that will self-destruct after being read.
5) https://t.co/8v2AlVlDr5 - Buy cool gifts and gadgets for almost no money
6) https://t.co/XDEXddER0O - Website that makes it sounds like it's raining outside. It's amazing if you need to concentrate on studying
7) Free Online MBA - Get 20+ curated resources to learn what you would in an MBA

Made by Me and @PinglrHQ

https://t.co/kEP8EnvKqO
8) https://t.co/DvcalRqpDd - For those times you need a throwaway email address. The email address will enable you to get confirmation then self destruct in 10 minutes
9) https://t.co/VGPYr81JhQ - Do you spend all your Netflix time trying to figure out which movie to watch? Problem solved
10) https://t.co/jdPejcTVDz - you'll find courses from top universities like Harvard, Stanford, etc., for free in an organized format.

Made by @Prajwxl and @krishnalohiaaa
11) https://t.co/AuXv5ErL8t - Watch documentaries for free
12) https://t.co/9B2ITMa4GU - The Useless Web is a website that's somewhat similar, except that its only goal is to show you the most pointless websites that exist on the internet.
13) https://t.co/M4lvi1D4co - If you need to know just how good or bad your internet connection is, Ookla’s Speedtest can tell you
14) https://t.co/kB63siJe3e - Enter a book you like and the site will analyze our huge database of real readers' favorite books to provide book recommendations and suggestions for what to read next.
15) https://t.co/yTRdvdUSQU - Find the technology stack of any website.
16) https://t.co/j2lBJJXvuj - Learn skills that college doesn't teach you

Made by @1997harkirat
17) https://t.co/HTtJqFbrwb

Timeless articles from the belly of the internet. Served 5 at a time

Creator: @louispereira
18) Learn to code online for free
https://t.co/hNSO1hOmoY

Thank you @prannesh_54 for suggesting!
@prannesh_54 19) Relax and focus with live lofi stations

one of my fav website

https://t.co/5ZR0tvr26b
20) https://t.co/P2apelwYxU - one of the coolest web page to hear random songs on random stations across the globe.

Thanks @RK_382922 for suggesting!
@RK_382922 21) A site that will search for any word you type, in many different languages, and show you YouTube clips where the word was said so you can learn the pronunciation and context in which it is used.

https://t.co/Pi9Dpjo8A9
@RK_382922 22) https://t.co/aYtsDEMYqm - This website will self destruct
23) https://t.co/4NTsB4OzQn - A website that takes you on a drive through a city while listening to local radio stations

one of my fav website
24) https://t.co/XQuhe3aYk2 - Millions of songs on Spotify have been forgotten. Let’s give them new life in new ears – yours.
If you found this thread helpful, please like and RT so others can find it šŸ‘‡
https://t.co/gM20ZVT4lS
Some more cool websites. https://t.co/92xICD17ll

More from All

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

šŸ§µšŸ‘‡(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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