- SEO
- Web design
- Email marketing
Those are just a few examples.
The big idea is choosing a "high-ROI" skill.
In other words, a skill that makes other companies a lot of money.
Running Cost: $0
Start Earning Online With Just $100
(Thread)
- SEO
- Web design
- Email marketing
Those are just a few examples.
The big idea is choosing a "high-ROI" skill.
In other words, a skill that makes other companies a lot of money.
Running Cost: $0
- CrossFit gyms
- Wellness ecom stores
- Digital marketing agencies
Again, a few examples out of many.
Once you decide, do a ton of market research.
Find out what they need, then use it for step #4.
Running Cost: $0
Buy your domain, then add on G Suite.
After that, warm up the domain so you don't land in spam.
You can take care of the next couple steps while it warms up.
Running Cost: $30
Affiliate link for warming software:
https://t.co/rwYVHT7RFy
Basic questions to answer...
- What will you deliver?
- What is the value of it?
- How much will you charge?
Some examples...
- Website design for $1500
- SEO services for $2500/mo
- Email marketing for $3000/mo
Running Cost: $30
Settle on your preferred builder (Carrd is a solid, cheap option).
Explain your offer, use social proof, make the CTA scheduling a call.
Alternatively, you can forward the domain to your LinkedIn and make the LP later.
Running Cost: $50
There are a lot of ways to do this.
Scraping with Snov on LinkedIn is my favorite.
Buy the cheapest package to get started.
Running Cost: $90
Affiliate link:
https://t.co/t77pF6gop4
LinkedIn works.
Cold email works.
Basically every social media platform works.
Choose one, then send them personalized outreach messages.
For this thread, we'll use your leftover Snov credits to send emails too.
Running Cost: $90
Messages turn into discovery calls.
Discovery calls turn into sales calls.
You can use Calendly to schedule them.
Then, you'll build rapport, ask qualifying questions, and sell.
Running Cost: $100
Once you close the sale, you'll get paid and start delivering your service.
So, the basic process is:
- Learn for free
- Create an offer
- Buy some software
- 10-50x your investment
That's a lot of upside for so little risk.
Pretty cool, right?
1. Daily content
2. Weekly newsletter
3. Free 10-day email course
So, follow me if you aren't already, then click below 👇
https://t.co/Xpg2S4KjSE
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)
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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1/12
RT-PCR corona (test) scam
Symptomatic people are tested for one and only one respiratory virus. This means that other acute respiratory infections are reclassified as
2/12
It is tested exquisitely with a hypersensitive non-specific RT-PCR test / Ct >35 (>30 is nonsense, >35 is madness), without considering Ct and clinical context. This means that more acute respiratory infections are reclassified as
3/12
The Drosten RT-PCR test is fabricated in a way that each country and laboratory perform it differently at too high Ct and that the high rate of false positives increases massively due to cross-reaction with other (corona) viruses in the "flu
4/12
Even asymptomatic, previously called healthy, people are tested (en masse) in this way, although there is no epidemiologically relevant asymptomatic transmission. This means that even healthy people are declared as COVID
5/12
Deaths within 28 days after a positive RT-PCR test from whatever cause are designated as deaths WITH COVID. This means that other causes of death are reclassified as
RT-PCR corona (test) scam
Symptomatic people are tested for one and only one respiratory virus. This means that other acute respiratory infections are reclassified as
4/10
— Dr. Thomas Binder, MD (@Thomas_Binder) October 22, 2020
...indication, first of all that testing for a (single) respiratory virus is done outside of surveillance systems or need for specific therapy, but even so the lack of consideration of Ct, symptoms and clinical findings when interpreting its result. https://t.co/gHH6kwRdZG
2/12
It is tested exquisitely with a hypersensitive non-specific RT-PCR test / Ct >35 (>30 is nonsense, >35 is madness), without considering Ct and clinical context. This means that more acute respiratory infections are reclassified as
6/10
— Dr. Thomas Binder, MD (@Thomas_Binder) October 22, 2020
The neither validated nor standardised hypersensitive RT-PCR test / Ct 35-45 for SARS-CoV-2 is abused to mislabel (also) other diseases, especially influenza, as COVID-19.https://t.co/AkFIfTCTkS
3/12
The Drosten RT-PCR test is fabricated in a way that each country and laboratory perform it differently at too high Ct and that the high rate of false positives increases massively due to cross-reaction with other (corona) viruses in the "flu
External peer review of the RTPCR test to detect SARS-CoV-2 reveals 10 major scientific flaws at the molecular and methodological level: consequences for false positive results.https://t.co/mbNY8bdw1p pic.twitter.com/OQBD4grMth
— Dr. Thomas Binder, MD (@Thomas_Binder) November 29, 2020
4/12
Even asymptomatic, previously called healthy, people are tested (en masse) in this way, although there is no epidemiologically relevant asymptomatic transmission. This means that even healthy people are declared as COVID
Thread web\u2b06\ufe0f\u2b07\ufe0f
— Dr. Thomas Binder, MD (@Thomas_Binder) December 16, 2020
The fabrication of the "asymptomatic (super) spreader" is the coronation of the total nons(ci)ense in the belief system of #CoronasWitnesses.
Asymptomatic transmission 0.7%; 95% CI 0%-4.9% - could well be 0%!https://t.co/VeZTzxXfvT
5/12
Deaths within 28 days after a positive RT-PCR test from whatever cause are designated as deaths WITH COVID. This means that other causes of death are reclassified as
8/8
— Dr. Thomas Binder, MD (@Thomas_Binder) March 24, 2020
By the way, who the f*** created this obviously (almost) worldwide definition of #CoronaDeath?
This is not only medical malpractice, this is utterly insane!https://t.co/FFsTx4L2mw
1/ Some initial thoughts on personal moats:
Like company moats, your personal moat should be a competitive advantage that is not only durable—it should also compound over time.
Characteristics of a personal moat below:
2/ Like a company moat, you want to build career capital while you sleep.
As Andrew Chen noted:
3/ You don’t want to build a competitive advantage that is fleeting or that will get commoditized
Things that might get commoditized over time (some longer than
4/ Before the arrival of recorded music, what used to be scarce was the actual music itself — required an in-person artist.
After recorded music, the music itself became abundant and what became scarce was curation, distribution, and self space.
5/ Similarly, in careers, what used to be (more) scarce were things like ideas, money, and exclusive relationships.
In the internet economy, what has become scarce are things like specific knowledge, rare & valuable skills, and great reputations.
Like company moats, your personal moat should be a competitive advantage that is not only durable—it should also compound over time.
Characteristics of a personal moat below:
I'm increasingly interested in the idea of "personal moats" in the context of careers.
— Erik Torenberg (@eriktorenberg) November 22, 2018
Moats should be:
- Hard to learn and hard to do (but perhaps easier for you)
- Skills that are rare and valuable
- Legible
- Compounding over time
- Unique to your own talents & interests https://t.co/bB3k1YcH5b
2/ Like a company moat, you want to build career capital while you sleep.
As Andrew Chen noted:
People talk about \u201cpassive income\u201d a lot but not about \u201cpassive social capital\u201d or \u201cpassive networking\u201d or \u201cpassive knowledge gaining\u201d but that\u2019s what you can architect if you have a thing and it grows over time without intensive constant effort to sustain it
— Andrew Chen (@andrewchen) November 22, 2018
3/ You don’t want to build a competitive advantage that is fleeting or that will get commoditized
Things that might get commoditized over time (some longer than
Things that look like moats but likely aren\u2019t or may fade:
— Erik Torenberg (@eriktorenberg) November 22, 2018
- Proprietary networks
- Being something other than one of the best at any tournament style-game
- Many "awards"
- Twitter followers or general reach without "respect"
- Anything that depends on information asymmetry https://t.co/abjxesVIh9
4/ Before the arrival of recorded music, what used to be scarce was the actual music itself — required an in-person artist.
After recorded music, the music itself became abundant and what became scarce was curation, distribution, and self space.
5/ Similarly, in careers, what used to be (more) scarce were things like ideas, money, and exclusive relationships.
In the internet economy, what has become scarce are things like specific knowledge, rare & valuable skills, and great reputations.
