ℙ𝔸⚡𝕂𝕐

Knowledge Hoarding Syndrome and Chronical Irreverence sufferer. / Sufridor del Síndrome de Diógenes del Conocimiento e Irreverencia Crónica.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

“The opposite of a trivial truth is a falsehood.

The opposite of a profound truth may well be another profound truth.”

Niels Bohr.

If the opposite is stupid, the statement was obvious; if it is another deep idea (God exists/does not exist), you’re dealing with a profound truth

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@Dan_Jeffries1 Excuse me for being nitpicking, but I guess you mean 7.6 billion people who aren't American.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@slashdot Still waiting all cryptos to reach it's deserved zero value, as stated by @nntaleb

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

Poetic justice

[Anne Applebaum @anneapplebaum]

Amazing: KPMG wrote a report describing the successful use of AI by businesses. But the case studies turned out to be AI hallucinations.
https://t.co/s3LE8vedNi

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@psantacl @rdomenechv @JosephEStiglitz @PikettyWIL @jasonhickel @guardian It’s just a matter of empiricism: “you should follow me because MY degrowth is a success case” vs. “I want YOU not to grow because I guess it’s good”.

Practice vs. theory.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@elonmusk @iam_smx *Trollioniare 😅

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@random_walker I'd like to add the expert user is trending to use the new superpowers to avoid technical debt, doing "what it should have been done if we had the chance to get the right resources".

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@fchollet Agents are supposed to do “Ora et labora”.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@RocketLab @NASASpaceflight Are the iron lungs back?

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@karpathy How about ARC-AGI-3 @fchollet ?

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@JesusFerna7026 Serious question: have you considered a scenario where offspring can be generated in a factory of artificial wombs (like in "A brave new world")?

It seems it has been achieved with chickens: https://t.co/BDPFtES4Bx

Sure thing it's not as enjoyable as natural process, by the way

[Spencer Baggins @bigaiguy]

A French engineer who lives quietly in Paris has spent 30 years writing software that the entire internet now runs on without knowing his name.

He wrote the code that streams every YouTube video, every Netflix show, every TikTok clip. He wrote the code that runs the virtual servers underneath AWS, Google Cloud, and Microsoft Azure. He calculated more digits of pi than anyone in history. He has no Twitter. He has no marketing. He just keeps shipping.

His name is Fabrice Bellard.

Here is the story, because almost nobody outside the systems programming world knows what one man has built.

Fabrice was born in 1972 in Grenoble, France. He studied at École Polytechnique, the top French engineering school. He never went to Silicon Valley. He never built a startup empire. He just wrote code.

In 2000 he started a project called FFmpeg, an open-source multimedia framework for encoding, decoding, and streaming video. He was 28. The project did one thing nobody else had done well. It handled every video and audio format that existed, in one library, on every operating system. He led it himself for years.

Today FFmpeg is the invisible engine of the internet. YouTube uses it. Netflix uses it. VLC uses it. Chrome and Firefox use parts of it. Every Android phone, every iPhone, every smart TV, every video editing tool you have ever touched runs FFmpeg somewhere underneath. If you have watched a video on a screen in the last 20 years, Fabrice's code processed it.

He was not done.

In 2003 he started QEMU, a machine emulator and virtualizer. He wrote it solo until version 0.7.1 in 2005. QEMU lets you run any operating system on any other operating system. It became the foundation of modern virtualization. KVM, the Linux kernel hypervisor, runs on top of QEMU. Every major cloud provider, AWS, Google Cloud, Microsoft Azure, IBM Cloud, runs virtual machines on infrastructure built around it. The Quick Emulator is the most cited piece of cloud infrastructure code on Earth.

He kept going.

In 2001 he won the International Obfuscated C Code Contest with a small C compiler that grew into TCC, the Tiny C Compiler. TCC can compile and boot a Linux kernel from source in under 15 seconds. In 2004 he calculated the most digits of pi ever computed at the time, using a personal desktop computer and an algorithm he derived himself called Bellard's formula. In 2011 he wrote a complete PC emulator in pure JavaScript that runs Linux in your browser, a project called JSLinux that engineers still cannot believe is real.

In 2019 he released QuickJS, a small but complete JavaScript engine that fits where V8 cannot. In 2021 he released NNCP, a neural network based lossless data compressor that immediately took the lead on the Large Text Compression Benchmark.

Then he turned his attention to large language models. He built TextSynth Server, a web server with a REST API for running LLMs locally. He released ts_zip and ts_sms, compression utilities that use language models to compress text and short messages at ratios traditional algorithms cannot reach. He released TSAC, a very low bitrate audio compression system. In December 2025 he released Micro QuickJS, a new JavaScript engine for microcontrollers, separate from QuickJS, designed for environments with almost no memory.

Fabrice co-founded a telecom company called Amarisoft in 2012, where he serves as CTO. Amarisoft builds 4G and 5G base station software used by carriers and labs around the world. He has been running it for over a decade while continuing to ship personal projects from his own home page at bellard dot org

He has no Twitter. He has no Instagram. He gives almost no interviews. His personal website is a flat list of projects with no styling, no fonts, no marketing copy. Just titles and links.

A quiet French engineer who never moved to Silicon Valley wrote the code that quietly runs the internet.

He is still shipping.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@rdomenechv @yndurain No, no hay círculo alguno. La IA requiere de un volumen masivo de datos con cálculos tensoriales relativamente simples, y la computación cuántica maneja pocos datos cubriendo infinidad de cálculos por superposición.
Al contrario, el deep learning come terreno a la comp. cuántica.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@atmoio This guy is doomed: https://t.co/qlarGAk3pX 😅

[Noah Smith 🐇🇺🇸🇺🇦🇹🇼 @Noahpinion]

Maybe demand for consumer software is just saturated.

https://t.co/v1s9ZOSLxG

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@ylecun

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@skdh Bohmian Rapsody
🎵Mamaaaa... just killed a wave...🎶

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@paulg If the ONLY companies who can make a net return on LLMs are infrastructure providers (HW + Cloud), there's not too much to expect but wishful thinking.

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@chemadepablo

[ℙ𝔸⚡𝕂𝕐 @rogerpasky]

@stephen_wolfram Syndrome anticipated it:

[Oded Rechavi @OdedRechavi]

Most experiments fail, and negative results rarely get published. This means LLMs are unaware of the outcomes of most experiments.