11 PSYCHOLOGY TRICKS YOU MUST KNOW TO HANDLE ANY SITUATION :

1. When someone answers your questions partially, wait. Don't interrupt.

The chances are high that they will complete the answer when you say nothing.
2. When you want to get something from someone, frame it as an
offer/opportunity instead of a request.

Anyone will be ready to accept an offer/opportunity.
3. When you meet people, notice their eye color while you smile at them.

Don't mention anything about it. It's a good way to make sure that you really look them in the eyes.
4. A person's name is the sweetest sound in the world to that person.

To make a person feel very special, remember and repeat their name.
5. Have zero expectations when you are first trying something new, it prevents disappointments.
6. To judge a person's character, notice the way they treat people who can't do anything for them.
7. After you state your position in a negotiation, wait for a while.

If you continue to speak, you are not speaking in your favor.
8. Chewing gum while doing nerve, cracking things calms your brain.
9. When you are learning something, teach someone about it.

You will remember it easily and explore more in the process of teaching.
10. Most people's favorite subject to talk about is themselves.

If you don't know what to talk about, or have awkward silence, just ask them questions.
11. Stand up straight. It makes you look more confident, and you will actually feel more confident.
Master your Mind. Master your Life.

Mental models are the most important ideas of each science as psychology.

• control the mind
• focus on what matters
• understand how the world works

Get started now and get the top 50 books of all time for FREE:
https://t.co/4p5tIi9y2x
That's a wrap!

If you enjoyed this thread:

1. Follow me @LeadersJunction for more of these
2. RT the tweet below to share this thread with your audience https://t.co/1yFdied1Oe

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

🧵👇(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)

You May Also Like

@EricTopol @NBA @StephenKissler @yhgrad B.1.1.7 reveals clearly that SARS-CoV-2 is reverting to its original pre-outbreak condition, i.e. adapted to transgenic hACE2 mice (either Baric's BALB/c ones or others used at WIV labs during chimeric bat coronavirus experiments aimed at developing a pan betacoronavirus vaccine)

@NBA @StephenKissler @yhgrad 1. From Day 1, SARS-COV-2 was very well adapted to humans .....and transgenic hACE2 Mice


@NBA @StephenKissler @yhgrad 2. High Probability of serial passaging in Transgenic Mice expressing hACE2 in genesis of SARS-COV-2


@NBA @StephenKissler @yhgrad B.1.1.7 has an unusually large number of genetic changes, ... found to date in mouse-adapted SARS-CoV2 and is also seen in ferret infections.
https://t.co/9Z4oJmkcKj


@NBA @StephenKissler @yhgrad We adapted a clinical isolate of SARS-CoV-2 by serial passaging in the ... Thus, this mouse-adapted strain and associated challenge model should be ... (B) SARS-CoV-2 genomic RNA loads in mouse lung homogenates at P0 to P6.
https://t.co/I90OOCJg7o