A mix of “they encourage dollar-denominated liquidity in the cryptocurrency ecosystem and discourage withdrawal of the same” and “they’re good for money laundering.”
It’s underremarked upon that stablecoins accomplish basically all of the original design goals for Bitcoin qua a transactional mechanism (instant free value transfer anywhere), but that nobody cares about this because nobody ever cared about that part of the pitch.
A mix of “they encourage dollar-denominated liquidity in the cryptocurrency ecosystem and discourage withdrawal of the same” and “they’re good for money laundering.”
This was a solved problem in traditional finance, too, mostly through the extension of credit. (It doesn’t matter how long settlement takes if there is sufficient trust to enable credit.)
More from Patrick McKenzie
If everyone was holding bitcoin on the old x86 in their parents basement, we would be finding a price bottom. The problem is the risk is all pooled at a few brokerages and a network of rotten exchanges with counter party risk that makes AIG circa 2008 look like a good credit.
— Greg Wester (@gwestr) November 25, 2018
The benign product is sovereign programmable money, which is historically a niche interest of folks with a relatively clustered set of beliefs about the state, the literary merit of Snow Crash, and the utility of gold to the modern economy.
This product has narrow appeal and, accordingly, is worth about as much as everything else on a 486 sitting in someone's basement is worth.
The other product is investment scams, which have approximately the best product market fit of anything produced by humans. In no age, in no country, in no city, at no level of sophistication do people consistently say "Actually I would prefer not to get money for nothing."
This product needs the exchanges like they need oxygen, because the value of it is directly tied to having payment rails to move real currency into the ecosystem and some jurisdictional and regulatory legerdemain to stay one step ahead of the banhammer.
On a serious note, it's interesting to observe that you can build a decent business charging $20 - $50 per month for something that any good developer can set up. This is one of those micro-saas sweet spots between "easy for me to build" and "tedious for others to build"
— Jon Yongfook (@yongfook) September 5, 2019
Every year at MicroConf I get surprised-not-surprised by the number of people I meet who are running "Does one thing reasonably well, ranks well for it, pulls down a full-time dev salary" out of a fun side project which obviates a frequent 1~5 engineer-day sprint horizontally.
"Who is the prototypical client here?"
A consulting shop delivering a $X00k engagement for an internal system, a SaaS company doing something custom for a large client or internally facing or deeply non-core to their business, etc.
(I feel like many of these businesses are good answers to the "how would you monetize OSS to make it sustainable?" fashion, since they often wrap a core OSS offering in the assorted infrastructure which makes it easily consumable.)
"But don't the customers get subscription fatigue?"
I think subscription fatigue is far more reported by people who are embarrassed to charge money for software than it is experienced by for-profit businesses, who don't seem to have gotten pay-biweekly-for-services fatigue.
More from Tech
Ok, here. Just one of the 236 mentions of Facebook in the under read but incredibly important interim report from Parliament. ht @CommonsCMS https://t.co/gfhHCrOLeU
Let’s do another, this one to Senate Intel. Question: “Were you or CEO Mark Zuckerberg aware of the hiring of Joseph Chancellor?"
Answer "Facebook has over 30,000 employees. Senior management does not participate in day-today hiring decisions."
Or to @CommonsCMS: Question: "When did Mark Zuckerberg know about Cambridge Analytica?"
Answer: "He did not become aware of allegations CA may not have deleted data about FB users obtained through Dr. Kogan's app until March of 2018, when
these issues were raised in the media."
If you prefer visuals, watch this short clip after @IanCLucas rightly expresses concern about a Facebook exec failing to disclose info.
A company as powerful as @facebook should be subject to proper scrutiny. Mike Schroepfer, its CTO, told us that the buck stops with Mark Zuckerberg on the Cambridge Analytica scandal, which is why he should come and answer our questions @DamianCollins @IanCLucas pic.twitter.com/0H4VMhtIFu
— Digital, Culture, Media and Sport Committee (@CommonsCMS) May 23, 2018
Interestingly, this thread below has been written by that.
Let me show you how it looks like. 👇🏻
Recently I just refunded all Poster's sales from Gumroad. Being that said, I decided to not using that service anymore.
— Wilbert Liu \U0001f468\U0001f3fb\u200d\U0001f3a8 (@wilbertliu) November 19, 2018
Here's a little story \U0001f447\U0001f3fb
When you see localhost up there, you should know that it's truly an experiment! 😀
It's a dead-simple thread writer that will post a series of tweets a.k.a tweetstorm. ⚡️
I've been personally wanting it myself since few months ago, but neglected it intentionally to make sure it's something that I genuinely need.
So why is that important for me? 🙂
I've been a believer of a story. I tell stories all the time, whether it's in the real world or online like this. Our society has moved by that.
If you're interested by stories that move us, read Sapiens!
One of the stories that I've told was from the launch of Poster.
It's been launched multiple times this year, and Twitter has been my go-to place to tell the world about that.
Here comes my frustration.. 😤
At the heart of this lies the most important technique in modern deep learning - transfer learning.
Let's analyze how it
THREAD: Can you start learning cutting-edge deep learning without specialized hardware? \U0001f916
— Radek Osmulski (@radekosmulski) February 11, 2021
In this thread, we will train an advanced Computer Vision model on a challenging dataset. \U0001f415\U0001f408 Training completes in 25 minutes on my 3yrs old Ryzen 5 CPU.
Let me show you how...
2/ For starters, let's look at what a neural network (NN for short) does.
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
3/ We show an image to our model.
An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.
Here is what it might look like for a black and white image
4/ The picture goes into the layer at the bottom.
Each layer performs computation on the image, transforming it and passing it upwards.
5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
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Risks of bat-borne zoonotic diseases in Western Asia
Duration: 24/10/2018-23 /10/2019
Funding: $71,500
@dgaytandzhieva
https://t.co/680CdD8uug
2. Bat Virus Database
Access to the database is limited only to those scientists participating in our ‘Bats and Coronaviruses’ project
Our intention is to eventually open up this database to the larger scientific community
https://t.co/mPn7b9HM48
3. EcoHealth Alliance & DTRA Asking for Trouble
One Health research project focused on characterizing bat diversity, bat coronavirus diversity and the risk of bat-borne zoonotic disease emergence in the region.
https://t.co/u6aUeWBGEN
4. Phelps, Olival, Epstein, Karesh - EcoHealth/DTRA
5, Methods and Expected Outcomes
(Unexpected Outcome = New Coronavirus Pandemic)