Our paper, "An evidence review of face masks against COVID-19", written by a cross-disciplinary team of 19 international experts, was published in the Proceedings of the National Academy of Sciences today.

No time for the paper? Then read this thread!
pnas.org/content/118/4/…
The paper, which includes 141 references (yes, I read every one of them!) argues that we should increase focus on a previously overlooked aspect of mask usage: mask wearing by infectious people ("source control"), rather than only mask wearing by susceptible people ("PPE") Image
Masks have been used to help control respiratory pandemics for at least 600 years. Wu Lien-Teh (the "Plague Fighter") showed the world the importance of masks nearly 100 years ago, doing detailed studies over many years.

Sadly, his work became largely forgotten in the west Image
Unfortunately, it's impossible to study the impact of masks as source control using the gold standard: a "randomized controlled trial". That's because you can't really tell whether a mask wearer infects others or not. So we developed a new framework to study this topic Image
There are a number of very strong multivariate population-levels studies that are strongly suggestive of the impact of mask wearing. Particularly that of @ChrisLefflerMD et al
ajtmh.org/content/journa… Image
We were lucky enough to have one of the world's top aerosol scientists, Prof Vladimir Zdimal, on our team, who helped explain how masks can block infectious particles, and the impact of aerosols Image
Personally, the studies I found most compelling are those that simply physically showed that masks literally block the ejection of respiratory particles Image
We were lucky enough to have @zeynep and @HeleneMarivdW on the team, who explained the sociological considerations around mask wearing, including looking at risk compensation behavior Image
We wrote the first version of this paper back in April, and it became the most viewed paper of all time on any topic, on preprints.org.

One key section we've added since that time is "Further Research" - that's a lot we still don't (but need to!) know Image
We should all wear a mask.

pnas.org/content/118/4/… Image
Thanks too all my great co-authors, @arimoin, @larrychu, @zeynep, @lexfridman, @austinvhuang, @Hernandez_Danny, @ArneDelft, @HeleneMarivdW, @AmyPricePhD, @reshamas, Z. Li, C. Ramirez, L. Tang, V. Zdimal, C. Bax, G. Watson & V. Tang

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More from @jeremyphoward

6 Jan
IIUC this "new technique" from Facebook is actually just a slight repackaging of bits of @wightmanr's brilliant timm library.

Great they wrote a paper that documented how well it works, but they should at *minimum* have cited timm, and really should have made him senior author
I've read thru their code, and it's basically calling out to timm (which is based on years of research from @wightmanr), along with a standard Pytorch training loop and data munging.
github.com/facebookresear…
There are clearly some pretty deeply rooted issues surfaced here regarding how @facebookai works with the open source community.

Hopefully this turns out to be a productive learning experience.
Read 6 tweets
18 Dec 20
Excited to launch "ghapi" today in partnership with @GitHub. ghapi provides complete access to the entire GitHub API, using a consistent interface with many nice touches.

See thread below for a demo and summary, or read the post for details: 1/
github.blog/2020-12-18-lea…
ghapi has both a Python and a CLI interface. The operations and parameters of them are identical, so once you know one, you know them both! Here's a demo of the CLI interface, which includes help for all API operations and tab-completion.
Here's a demo of ghapi's Python interface, which even includes links to the official @GitHub documentation for every endpoint.
Read 11 tweets
29 Oct 20
NumFOCUS found I violated their Code of Conduct (CoC) at JupyterCon because my talk was not “kind”, because I said @joelgrus was “wrong”.

This sets a bad precedent.

Joel was not involved in NumFOCUS’s action, was not told about it, and did not support it
fast.ai/2020/10/28/cod…
The process has left me shattered, and I won't be accepting any more speaking invitations.

See the post above for details on what happened, including the full finding.

I've re-recorded my talk - you can decide for yourself if it merited such an action.
I'm doing something I've never done before, which is to restrict replies to this thread. I encourage open discussion, but I am left without the emotional energy to cope at this time, I'm sorry.
Read 6 tweets
20 Sep 20
Wow this turned into a nice rabbit hole! Turns out I wasn't, by any means, the first person to notice this. There's some great apps and deep dives built on this idea. See thread below for details.
"The Google ‘vs’ Trick
How ego graphs can help you learn about AI, play chess, eat healthier, buy a dog and find love"

Really nicely done article.
medium.com/applied-data-s…
A really pretty app that shows this functionality
anvaka.github.io/vs/?query=powe…
Read 4 tweets
20 Sep 20
Folks, do you have any suggestions for what the simplest, clearest, most solid Python implementation of basic web app session management with cookies is? e.g. it should handle stuff like opening a second independent tab. And it should be small enough a student can understand it
So for instance, something that only works within Django wouldn't be great, since it requires understanding all the Django stuff too. I'm looking for something that's as standalone/decoupled as possible.
BTW, I'm referring to server-side session management - ideally something using just sqlite or text files or similar
Read 7 tweets
16 Sep 20
:really-very-sad-face:

I was so excited about Codespaces. But there's no free tier!?! And no small instances!?! And the cost is so high!

Somehow pricing always seems to be the bit @github mess up. (e.g: LFS bandwidth pricing)
docs.github.com/en/github/deve… Image
Codespaces looks like it really could be a game changer. But not like this.

Thankfully, there's still time to fix it before it launches officially...

Pricing should look more like this (from @HelloPaperspace). Image
To compare: AWS provides 750 hours of t3.micro for free. GCP gives you an amazing $300 credit for anything you want!

GitHub themselves gives you as much Actions time as you like (as long as it's a public repo)!
Read 8 tweets

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