I read every annual letter Jeff Bezos published at Amazon.

It's a masterclass on strategy & leadership.

11 critical insights from a legendary leader:

1/ Move Fast

Bezos understood the importance of moving quickly.

Especially as Amazon grew.

To survive as a large company, you have to move at the pace of a startup.

If not, you'll die.
2/ Don't Sweat Reversible Decisions

Some problems require long thought and deliberation.

But many don't.

If a decision is easily reversible, Bezos thought they should be made quickly by "high judgement individuals or small groups."
3/ Stay Terrified... Of Your Customers

In the 1998 letter, Bezos remarked that it was Amazon's customers and not competition that should be feared.

He understood that Amazon was providing a service.

Amazon to this day has unmatched service to their customers.
4/ Focus On Inputs

Amazon constantly focused on things that they had input on.

-# of products available
-# of items available for Prime shipping

The focus on the inputs (what Amazon could control) led to the outputs Wall Street looked for.
5/ Long Term Mindset

In the 1st letter on the 1st page, long term mindset is mentioned.

It would remain a theme throughout and something the company stuck to.

Even forgoing profitability to invest back into the company for long term results.
6/ Plant Seeds and Wait

Many companies have shiny new object syndrome.

Amazon isn't different.

But they knew for seeds to grow, it took patience.

Amazon fulfillment center and AWS were both started as seed projects at Amazon.
7/ Talent Is King

The 3 questions before making a hiring decision for an employee at Amazon:

-Will you admire this person?

-Will this person raise the average level of effectiveness of the group they’re entering?

-Along what dimension might this person be a superstar?
8/ Be Customer Centric

In the early days, many vendors wondered why Amazon would allow customers to publish negative reviews.

Simply, Amazon knew it would improve the customer experience.

Better products would ultimately end up in the customers hands.
9/ Ownership MentalityBe

Bezos knew that if he wanted the company to focus on long-term results, ownership mentality was key.

Autonomy is given at Amazon to ensure that employees feel some sense of ownership.

It is the only way to remove the bias of short term results.
10/ In Lean Times, Build A Cash Moat

May be relevant very soon as fears raise around the risk of recession.

Amazon was able to weather the dot com bubble by building cash reserves.

A tight cash conversion cycle was critical in 2000 & 2001.
11/ Wandering is a Counterbalance to Efficiency

Many businesses are great at executing set plans.

But that is not where innovation is sparked.

Ideas are sparked by wanderers.

Amazon aimed to be a see-saw with wandering on one end and efficiency on the other.
I highly recommend reading the Amazon letters.

You can find them on Google and total there are only about 80 pages.

I'm currently reading Berkshire and that's around 900 pages.
TL;DR

1/ Move Fast
2/ Don't Sweat Reversible Decisions
3/ Stay Terrified of Customers
4/ Focus On Inputs
5/ Long-Term Mindset
6/ Plant Seeds & Wait
7/ Talent Is King
8/ Be Customer Centric
9/ Owner's Mentality
10/ Build A Cash Moat
11/ Wander but Be Efficient
If you enjoyed this thread, I'd appreciate a RT so others may find it as well.

And give me a follow @chrisxmunn if you deem me worthy of blabbering my insights onto your timeline! https://t.co/fVfhozHnBC

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🌺श्री गरुड़ पुराण - संक्षिप्त वर्णन🌺

हिन्दु धर्म के 18 पुराणों में से एक गरुड़ पुराण का हिन्दु धर्म में बड़ा महत्व है। गरुड़ पुराण में मृत्यु के बाद सद्गती की व्याख्या मिलती है। इस पुराण के अधिष्ठातृ देव भगवान विष्णु हैं, इसलिए ये वैष्णव पुराण है।


गरुड़ पुराण के अनुसार हमारे कर्मों का फल हमें हमारे जीवन-काल में तो मिलता ही है परंतु मृत्यु के बाद भी अच्छे बुरे कार्यों का उनके अनुसार फल मिलता है। इस कारण इस पुराण में निहित ज्ञान को प्राप्त करने के लिए घर के किसी सदस्य की मृत्यु के बाद का समय निर्धारित किया गया है...

..ताकि उस समय हम जीवन-मरण से जुड़े सभी सत्य जान सकें और मृत्यु के कारण बिछडने वाले सदस्य का दुख कम हो सके।
गरुड़ पुराण में विष्णु की भक्ति व अवतारों का विस्तार से उसी प्रकार वर्णन मिलता है जिस प्रकार भगवत पुराण में।आरम्भ में मनु से सृष्टि की उत्पत्ति,ध्रुव चरित्र की कथा मिलती है।


तदुपरांत सुर्य व चंद्र ग्रहों के मंत्र, शिव-पार्वती मंत्र,इन्द्र सम्बंधित मंत्र,सरस्वती मंत्र और नौ शक्तियों के बारे में विस्तार से बताया गया है।
इस पुराण में उन्नीस हज़ार श्लोक बताए जाते हैं और इसे दो भागों में कहा जाता है।
प्रथम भाग में विष्णुभक्ति और पूजा विधियों का उल्लेख है।

मृत्यु के उपरांत गरुड़ पुराण के श्रवण का प्रावधान है ।
पुराण के द्वितीय भाग में 'प्रेतकल्प' का विस्तार से वर्णन और नरकों में जीव के पड़ने का वृत्तांत मिलता है। मरने के बाद मनुष्य की क्या गति होती है, उसका किस प्रकार की योनियों में जन्म होता है, प्रेत योनि से मुक्ति के उपाय...
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
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)

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