When you're starting with your business idea, you will be looking at how successful businesses have accomplished their success. You will see a lot of different sizes, markets, and business models. But they all have one thing in common: they've built a system that works.

Their long-term and short-term goals may have changed through the years, but the system that has kept them running never has. That system is the core of every business.
A sustainable bootstrapped business is successful when you have found a repeatable, reliable, and resilient system to continuously provide a value-producing product to paying customers at a profit.
Since "system" is such an abstract term: look at it as a set of rules and guidelines, like a recipe. To make a tasty omelet, you will need to mix the right ingredients and cook them for the right time, at the right temperature, using a specific technique. A business is the same.
Having a recipe in place will make the transition from the Preparation Stage into the Survival Stage less chaotic. But, it's still important to think of the core growth engine of your business before you start selling your product to your audience.
A business without goals is an aimless venture. But goals are reached and exceeded. New goals arrive in their place, and they often change shape mid-operation. A goal is meant to become obsolete. A system is intended to endure and allow you to reach your goals in the first place.

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)

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Oh my Goodness!!!

I might have a panic attack due to excitement!!

Read this thread to the end...I just had an epiphany and my mind is blown. Actually, more than blown. More like OBLITERATED! This is the thing! This is the thing that will blow the entire thing out of the water!


Has this man been concealing his true identity?

Is this man a supposed 'dead' Seal Team Six soldier?

Witness protection to be kept safe until the right moment when all will be revealed?!

Who ELSE is alive that may have faked their death/gone into witness protection?


Were "golden tickets" inside the envelopes??


Are these "golden tickets" going to lead to their ultimate undoing?

Review crumbs on the board re: 'gold'.


#SEALTeam6 Trump re-tweeted this.