I want to explain what happened to tumblr overnight. And why Twitter as reached it's dream (or have come ever so close to it)

Yahoo, who bought Tumblr years ago, used to have a huge adult presence on the early net. They allowed adult groups and what not.
However, people and bots (just like now) misused the service, and Yahoo were forced to make a choice. They made private the groups (and later closed them down and sold some of it to other companies) and then ended their chatrooms on yahoo messenger...
after a incident with one of the chatrooms vid cams. The damage was done, Yahoo Messenger lost a lot of people - and with the closing of the groups - backpage and Craigslist came more important.
Now backpage is no more and Craigslist is slowly passing away. Tumblr had a semi strong community, but once 2014 came around and both porn, and political bots exploded the quality started to go down,
Apple finds out damaging information about the Tumblr App, which just a reskin of the main website, Apple takes it down. Verizon, the owners of Oath, who owns Tumblr, went holy roller on the site. Most of the artist pages and other work from anime and animation were wiped.
Now we find out that TUMBLR had a secret filter data base...with the FBI and others. Yall should know the reasons why. Not only they know who the bad men are, the fact Tumblr didnt tell local agencies about this and who doing dark shit is a red fucking flag.
That not the worst thing. The worst thing is that Tumblr took down legit shit too that wasnt even close to bad shit. This has become a problem, and now with most of the stuff people want to see gone, only leaving the toxic nature of the conversation left... Tumblr is done.
But that leaves something important. It deals with Twitter. For years the dream of many of these now mega Silicon Valley CEO's was to Copy the power and ease of use somewhat of 2Channel, or more known as 2Chan.
4Chan was made some years later - but there were competition between other boards. 4Chan was the freest space (or at least one of it) on the net for a while...
Until Poole betrayed the base. Now he works as Google as it were, but he has made a mess of things there as well. 4Chan is about to split up last I heard between a 4Channel sfw and the 4Chan nsfw...
Even with 4Chan being the bad guy of the internet - full of dark dank memes and what not - aspects of it these SV CEO's and VC's love. This is where twitter comes to play and dont you realize that the dream is about to come true?
With 4Chan diminished, Tumblr finally on its death throes, Mastodon not ready for Prime Time as of yet. Gab not sure if its going to be for free speech or not... the only one left is Twitter. Twitter wants to become bigger than 2Channel ever was and it might yet do so.
Think about how Twitter Looks and How 2Chan operates. The ideas are nearly the same even if the constrictions are there.
And guess who gets all the straggerlers from Backpage, Creiglist, Tumblr and other places.
Twitter. Twitter becomes the world wide version of 2Chan.
That was the goal.
There nearly there.
And it was all because of sex and sex in abundance.

More from Tech

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/
THREAD: How is it possible to train a well-performing, advanced Computer Vision model 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗣𝗨? 🤔

At the heart of this lies the most important technique in modern deep learning - transfer learning.

Let's analyze how it


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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First update to https://t.co/lDdqjtKTZL since the challenge ended – Medium links!! Go add your Medium profile now 👀📝 (thanks @diannamallen for the suggestion 😁)


Just added Telegram links to
https://t.co/lDdqjtKTZL too! Now you can provide a nice easy way for people to message you :)


Less than 1 hour since I started adding stuff to https://t.co/lDdqjtKTZL again, and profile pages are now responsive!!! 🥳 Check it out -> https://t.co/fVkEL4fu0L


Accounts page is now also responsive!! 📱✨


💪 I managed to make the whole site responsive in about an hour. On my roadmap I had it down as 4-5 hours!!! 🤘🤠🤘