I started a business that has generated almost $10M in revenue.

And I got the idea from Reddit.

But only a few people know the power of Reddit to fuel entrepreneurship.

Here are 9 under-the-radar subreddits that will help you build a million dollar business:

Thread 🧵👇

r/sweatystartup (65K+ members)

The subreddit started by our own Twitter fam @sweatystartup

It's still an active subreddit, with most people talking about their local businesses.

Lots of great idea swapping and community.

https://t.co/3ivzATZ8Tw
@sweatystartup r/EntrepreneurRideAlong (200K+ members)

The subreddit where I found out about the biz model that would eventually become @MaidThis . I spent a ton of time in here.

Solid community. Originally founded by the godfather @rohangilkes

https://t.co/1ZkQFsYzVG
@sweatystartup @MaidThis @rohangilkes r/AdvancedEntrepreneur (22K members)

Good amount of case studies and people sharing their progress reports.

Quality of the posts is high here, even if the quantity isn't as much as other subreddits.

https://t.co/9Ajx5nNoZB
@sweatystartup @MaidThis @rohangilkes r/smallbusiness (800K+ members)

This active subreddit was created to share knowledge on the nuts-and-bolts of starting a small business.

Topics range from how to file an LLC to case studies on successful SMBs.

A worthy subscribe.

https://t.co/gy4eHpoiqZ
@sweatystartup @MaidThis @rohangilkes r/Entrepreneur (1M+ members)

The most active business-related subreddit with over a million subscribers.

People share advice on everything from side hustles and small businesses to venture-backed startups and lemonade stands.

A good jumping point.

https://t.co/E7Ndt2pSzv
@sweatystartup @MaidThis @rohangilkes r/Startups (1M+ members)

A subreddit focused on high-scale startups.

Topics range from minimum-viable-product help to co-founder issues to celebrations about VC funding.

Great for the entrepreneur getting into the tech industry.

https://t.co/M7gWtw78bb
@sweatystartup @MaidThis @rohangilkes r/sidehustle (150K+ members)

Fantastic subreddit for idea inspiration.

The range of topics is huge - everything from rental property side hustles to affiliate sites.

It's full of people looking for start a side hustle and trading ideas.

https://t.co/THPQEacZ1J
@sweatystartup @MaidThis @rohangilkes r/juststart (110K+ members)

A community around affiliate marketing, search engine optimization and related topics.

A good place to troubleshoot any issues you're currently experiencing with your digital asset.

https://t.co/mExshPdkJF
@sweatystartup @MaidThis @rohangilkes r/PersonalFinance (16M+ members)

While this is not entrepreneur specific, the advice in this subreddit will help you save and make a ton of money.

Strong, active community with great insights into investing, budgeting, retirement planning, and more.

https://t.co/61OCwOrfX5

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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The YouTube algorithm that I helped build in 2011 still recommends the flat earth theory by the *hundreds of millions*. This investigation by @RawStory shows some of the real-life consequences of this badly designed AI.


This spring at SxSW, @SusanWojcicki promised "Wikipedia snippets" on debated videos. But they didn't put them on flat earth videos, and instead @YouTube is promoting merchandising such as "NASA lies - Never Trust a Snake". 2/


A few example of flat earth videos that were promoted by YouTube #today:
https://t.co/TumQiX2tlj 3/

https://t.co/uAORIJ5BYX 4/

https://t.co/yOGZ0pLfHG 5/
1/“What would need to be true for you to….X”

Why is this the most powerful question you can ask when attempting to reach an agreement with another human being or organization?

A thread, co-written by @deanmbrody:


2/ First, “X” could be lots of things. Examples: What would need to be true for you to

- “Feel it's in our best interest for me to be CMO"
- “Feel that we’re in a good place as a company”
- “Feel that we’re on the same page”
- “Feel that we both got what we wanted from this deal

3/ Normally, we aren’t that direct. Example from startup/VC land:

Founders leave VC meetings thinking that every VC will invest, but they rarely do.

Worse over, the founders don’t know what they need to do in order to be fundable.

4/ So why should you ask the magic Q?

To get clarity.

You want to know where you stand, and what it takes to get what you want in a way that also gets them what they want.

It also holds them (mentally) accountable once the thing they need becomes true.

5/ Staying in the context of soliciting investors, the question is “what would need to be true for you to want to invest (or partner with us on this journey, etc)?”

Multiple responses to this question are likely to deliver a positive result.