Story time. There will be a couple crypto wallet addresses at the end of this one.
This is something that will stay up, maybe clear till the midterm election.
And it needs a significant amount of disk space, for unpacking and sorting and such.
0xc6301a7f5a750Aec37280ECabe45956405A4F92C
Nope, can't use any sort of cloud. Bare metal, encrypted drives, all that kinda stuff is required.
Nobody you know can tell you anything more about this. It's not a social media thing. At all.
So there you have it. If you know and approve of my past work, this is opportunity knocking.
More from Crypto
Short version:
The NFT token you bought either points to a URL on the internet, or an IPFS hash. In most circumstances it references an IPFS gateway on the internet run by the startup you bought the NFT from.
Oh, and that URL is not the media. That URL is a JSON metadata file
Here's an example. This artwork is by Beeple and sold via Nifty:
https://t.co/TlJKH8kAew
The NFT token is for this JSON file hosted directly on Nifty's servers:
https://t.co/GQUaCnObvX
THAT file refers to the actual media you just "bought". Which in this case is hosted via a @cloudinary CDN, served by Nifty's servers again.
So if Nifty goes bust, your token is now worthless. It refers to nothing. This can't be changed.
"But you said some use IPFS!"
Let's look at the $65m Beeple, sold by Christies. Fancy.
https://t.co/1G9nCAdetk
That NFT token refers directly to an IPFS hash (https://t.co/QUdtdgtssH). We can take that IPFS hash and fetch the JSON metadata using a public gateway:
https://t.co/CoML7psBhF
Should you invest in Polygon (Matic)?
— LearnApp (@LearnApp_co) June 12, 2021
\U0001f4a1 Here's @PrateekLearnapp's take on #Matic, as shared on @CNBCTV18News.
What are your thoughts on #Polygon (Matic)? \U0001f4ac
Read the full article here \U0001f449 https://t.co/rmLTV0WFo2#crypto #cryptocurrencies pic.twitter.com/9k1lclN7oL
ok, I lied. but strictly it's not a new graph, just a new trendline (now a quadratic on the log plot). looks um... quite a good fit. so I'd say that was interesting. pic.twitter.com/qkgyMf1ya8
— James Ward (@JamesWard73) January 27, 2021
WARNING: this is a long thread, and it’s a bit of a roller-coaster. We find some apparently strong patterns in the data, and then start to unpick them a bit. So if you start getting excited half way through you might find you’re less excited at the end. But we’ll see…
First we first have to go back a bit. @bristoliver posted a thread a few days ago explaining why, with a constant vaccination rate, a log plot of cases should show a quadratic form. In other words, it should fit an equation like: a + b.x + c.x^2
I meant to link in the model thread there - here it is
Been thinking about where we are, where we might be going, what effect vaccines might have and how to tell. This thread may not happen all at once, and will get a bit mathematical in a couple of places (sorry!), but I will put in pictures. It's yet another argument for log scales
— Oliver Johnson (@BristOliver) January 24, 2021
the quadratic coefficient – the ‘c’ in that equation – gives an estimate of the % of the population who are being newly protected by the vaccine each day. Please note ‘protected by the vaccine’, not ‘vaccinated’ – as we don't expect 100% protection after the first dose