Parler has been hacked and user data has been downloaded. The following thread contains information from /u/BlueMountainDace on Reddit:

"so a group of developers latched onto the Press Release that Twilio put out at midnight last night. In that Press Release, Twilio

I did more research into the Parler dump. What probably happened was not so much a "hack", but this: When Twilio/Okta shut them down, they just disabled email/phone verification to create an account. This means anyone could directly create huge amounts of accounts via their API.

Someone also found out that fetching Parler posts could be done by enumerating IDs (e.g 1, 2, 3) instead of random IDs that can't be guessed. Unclear if this was via the ordinary API endpoint, or that they found a separate one by monitoring app network traffic.

So you combine these two things and you can create a script to scrape all the posts on the entire platform, using a lot of different accounts to avoid suspicion. Anyone could download and run this script to spread it out over many IP addresses as well.

What I'm still not sure about is whether deleted (meaning flagged as deleted, it's common that services never actually delete data) posts could be fetched without any special handling.

The verdict: The people who wrote Parler are fucking amateurs.

I sympathize with mid-size companies seeking to acquire a premium domain name. Even if they stretch to make the maximum possible offer, it often still can't compete with what a larger company can offer. Their desired domain name remains always out of reach. /1

From the broker:

"The prospective buyer responded and explained that their absolute maximum amount they can spend is $100,000 USD. They are accountants and explained this is an extraordinary amount of money for them." /2

The distribution of how much a domain name is worth to a particular company may look approximately like the right half of a bell curve, with values increasing along the X-axis and the # of companies for which the domain name has that value on the y-axis. /3

Since each domain name is unique, a domain owner wishing to maximize the value of that asset will often wait for an offer in the (light green) rightmost tail of the distribution, from that small percentage of companies for whom the domain name will deliver the most value and /4

as a result can justify making the highest value offers for the domain name. But that means that the domain name will remain out of reach for the vast majority of companies that would benefit from owning the domain name. For even a company at the 80th percentile, in the /5

Here's an overview of key adoption metrics for deep learning frameworks over 2020: downloads, developer surveys, job posts, scientific publications, Colab usage, Kaggle notebooks usage, GitHub data.

TensorFlow/Keras = #1 deep learning solution.

Note that we benchmark adoption vs Facebook's PyTorch because it is the only TF alternative that registers on the scale. Another option would have been sklearn, which has massive adoption, but it isn't really a TF alternative. In the future, I hope we can add JAX.

TensorFlow has seen 115M downloads in 2020, which nearly doubles its lifetime downloads. Note that this does *not* include downloads for all TF-adjacent packages, like tf-nightly, the old tensorflow-gpu, etc.

Also note that most of these downloads aren't from humans, but are automated downloads from CI systems (but none are from Google's systems, as Google doesn't use PyPI).

In a way, this metric reflects usage in production.

There were two worldwide developer surveys in 2020 that measured adoption of various frameworks: the one from StackOverflow, targeting all developers, and the one from Kaggle.