Micrographia is a new YouTube channel that studies interesting objects under a microscope. In this video it's an old Intel 8086 CPU:

Good introduction [https://nakabonne.dev/posts/understanding-how-aes-encryption-works/] to how a common encryption algorithm works, described by Ryo Nakao.

Researchers at Google applied GANs to crude sketches of imaginary creatures and managed to render them in rich detail. From their post [https://ai.googleblog.com/2020/11/using-gans-to-create-fantastical.html]on the Google AI Blog: > Today, we present Chimera Painter, a trained machine

There have been many accounts about what it was like to work at Bell Labs, here's [https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1657810] another short one by speech-processing researcher Man Mohan Sondhi. Two notable quotes, emphasis mine: > The department

At some point I'll get around to reading the paper [https://arxiv.org/abs/2005.14165], but meanwhile Jay Alammar has managed to explain how GPT-3 works in a short Twitter thread [https://twitter.com/JayAlammar/status/1285498971960598529]. It doesn't

A bit of light fun: 1SecondPainting [https://1secondpainting.com/]uses a neural network to generate abstract paintings. Some of them are quite good: Generated by 1SecondPainting [https://1secondpainting.com/]Generated by 1SecondPainting [https://1secondpainting.com/]Generated by 1SecondPainting [https://1secondpainting.com/]

Using neural networks to generate realistic, animated faces from portraits. Not all of them are compelling but the Mona Lisa one is very believable.

Probably the world's most interesting operating system. Some quotes from the CodersNotes blog [http://www.codersnotes.com/notes/a-constructive-look-at-templeos/]on the OS: > TempleOS is somewhat of a legend in the operating system community. Its sole author, Terry A. Davis, has spent

'Dying since 1995', that's apparently the unofficial slogan for PHP. This year it turned 25, and it's more popular than ever. The JetBrains folks (developers of the PhpStorm IDE), have put together a timeline [https://www.jetbrains.com/

Rodney Brooks on the state of the peer review process [rodneybrooks.com/peer-review/] for scientific papers: > My three most cited papers were either rejected under peer review or accepted with no peer review.  So I am not exactly a poster child for peer

Searching for root causes can often be misguided, because complex systems rarely have a single root cause. This [https://www.kitchensoap.com/2012/02/10/each-necessary-but-only-jointly-sufficient/] article discussed some of the problems with the 'single root cause' idea: > Again, this tendency

This [https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg]YouTube channel has summaries and demos for computer science papers, usually from artificial intelligence and computer graphics. Here's one [https://www.youtube.com/watch?v=4J0cpdR7qec]on making Mona Lisa speak.

TIL that many large banks, airlines, insurance companies, and government agencies are still using IBM mainframes, a ~50 year old computing platform. In fact mainframes still seem to be in active development: IBM announced [https://fuse.wikichip.org/news/2659/ibm-introduces-next-gen-z-mainframe-the-z15-wider-cores-more-cores-more-cache-still-5-2-ghz/] its new z15

A short 1-page overview [https://robertovitillo.com/what-every-developer-should-know-about-tcp/]of TCP for developers.

This [https://dl.acm.org/doi/10.1145/114669.114686]1991 paper discusses the author's experience with building two early time-sharing systems, and his learnings on managing reliability of such large software projects. To be honest, I paid less attention to the

An explanation [http://fabiensanglard.net/floating_point_visually_explained/index.html]of the IEEE 754 floating point standard that appeals to the intuition.

A set of interviews [https://staffeng.com/stories] with senior engineers at tech companies.

Some solid advice [https://blog.nelhage.com/post/systems-that-defy-understanding/] on how to debug and in general make sense of complex distributed systems. Deductive reasoning is unlikely to work; we need to rely on empirical methods instead.

Vanevar Bush's vision [https://blog.acolyer.org/2018/02/23/as-we-may-think/] of machines that would augment human knowledge.

This article [https://fermatslibrary.com/s/douglas-carl-engelbart-developing-the-underlying-concepts-for-contemporary-computing] discusses the life and work of Douglas Engelbart, who played a major role in modern computing – he invented the mouse, hyperlinks, and text and graphics editing, among other things. He demonstrated all of these inventions in a