I have been a Substack and Patreon user for a few years now. And though more than one social media giant has, in recent months, expressed the desire to help writers and journalists monetise their audience, there are very good reasons to take these SOPs with a pinch of salt.

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.

1/ @werat asked about whether the debugger was using the C# compiler or language service in VS 2002. It was not. The debugger has a component called an ‘expression evaluator’ that is provided per language and is responsible for parsing and evaluating expressions when stopped at a

2/ breakpoint. For example, if you type into the immediate window, hover over a variable, type into the watch window, etc. the expression evaluator is involved. The debugger and the language service are actually deeply integrated in a number of scenarios in VS, which may

3/ initially seem surprising. I may talk about more of these scenarios in the future, but to give a flavor, when you set a breakpoint at design time the language service is involved, when you are using Edit and Continue the LS is involved, the range of what is being evaluated

4/ when you get a debugger data tip, completion lists when typing in the data windows or immediate window, etc. Prior to VS 2002, there were distinct debug environments tailored to each target customer (VB/VBA, C++, VJ, VBScript, TSQL, FoxPro, Fortran, etc.). The goals of the

5/ VS 2002 debugger included unifying the debugger backend components and providing a single UI stack that would enable new scenarios (for example, a callstack across languages). Expression evaluators are the architecture that separate the language specific pieces from the

Dear journalists, venture capitalists, TikTok teens and other ThinkFluencers: before hot-taking on how to regulate online speech, please consider reading some of the foundational work in this area.

Start with @Klonick's groundbreaking

Follow with @daphnehk on the overall regulatory structure of online

Read @jkosseff's book before ever typing 2-3-0 on your

Read @evelyndouek on the risks of coordinated

Pre-order @jilliancyork to understand the global human-rights

I'm going to tell you a little bit how we work on features at GitHub. It's simple, but very powerful in my opinion. At GitHub we have a high performance culture.

We are deploying changes almost all the time while keeping the service running and the deployment failure ratio needs to be super low! We are constantly working on new medium/big features, we have frequent deploys and required peer reviews.

How do we know that big features are not conflicting with each other in functionality and in version control. How do we merge the work done in these non-trivial features? How do we do prevent peer reviews slow down our productivity?

With basically two things: split the work in small batches and feature flags. We don't have long-lived feature branches. We do very small changes all the time and deploy them.

We could split a feature in tens or hundreds of PRs, but until it is beta or GA, we don't expose it to users by using feature flags.

Company
Permanent suspension of @realDonaldTrump
By Twitter Inc.
Friday, 8 January 2021
After close review of recent Tweets from the @realDonaldTrump account and the context around them — specifically how they are being received and interpreted on and off Twitter —

we have permanently suspended the account due to the risk of further incitement of violence. 

In the context of horrific events this week, we made it clear on Wednesday that additional violations of the Twitter Rules would potentially result in this very course of action.

Our public interest framework exists to enable the public to hear from elected officials and world leaders directly. It is built on a principle that the people have a right to hold power to account in the open. 

However, we made it clear going back years that these accounts are

not above our rules entirely and cannot use Twitter to incite violence, among other things. We will continue to be transparent around our policies and their enforcement. 

The below is a comprehensive analysis of our policy enforcement approach in this case.

Overview

On January 8, 2021, President Donald J. Trump Tweeted:

“The 75,000,000 great American Patriots who voted for me, AMERICA FIRST, and MAKE AMERICA GREAT AGAIN, will have a GIANT VOICE long into the future. They will not be disrespected or treated unfairly in any way, shape or form