Christofer Sjögren @deephacks

Academics write for each other, not for people. Steven Pinker has spent over four decades doing the opposite, and thinks current academic writing is "enormous wasted effort." "There's an awful lot of brilliant work, really smart people in academia. Why are they doing it? Just to entertain each other? Taxpayers pay for it. It should be accessible. Why should I have to read a paragraph five or six times? It gets under my skin when academics devote so much brainpower into the scholarship and then just blow off the essential task of letting the world know what you've done."

I use the words physical hygiene and emotional hygiene. We should pay equally important attention to the hygiene of our emotions. Physical hygiene keeps us physically fit — but full of anger, what use is that? Real hygiene is emotional: peaceful, compassionate emotion. That is the real inner hygiene.

This is biblical. A woman in her eighties. Ten years into Alzheimer's. Hadn't spoken a full sentence in five years. Takes one, 5 gram dose of psilocybin. She slept 19 hours and woke up and spoke for hours about her life, recognized family and held real conversations. She regained bladder control after five years, walked on her own. and dressed herself. Gains held for weeks.

A good example of predictive AI from the Waymo Driver: in a split second, it predicted an initial crash of human-driven cars in the next lane, anticipated a secondary collision, and proactively shifted lanes — all while  managing its distance from the vehicles around it.

Friends !!! We are going to space !!! « The companies are also reportedly in talks to try to build orbital data centers — a major component of SpaceX’s future plans. »

Le monde qui a enfanté @ylecun n’est pas celui d’Albert Einstein. Einstein n’avait pas la revue par les pairs ni la National Science Foundation et ses mécanismes de financement bureaucratiques. Dans la première moitié du XXᵉ siècle et jusqu’à la fin des années 1960, la plupart des percées fondamentales sont venues d’environnements relativement autonomes, souvent des laboratoires industriels ou de chercheurs individuels : - Relativité restreinte (Albert Einstein, 1905) : rédigée alors qu’il était simple employé au bureau des brevets à Berne. - Mécanique quantique : développée presque entièrement par des chercheurs individuels ou de très petites équipes dans des universités européennes modestes. Planck (1900), Einstein (1905 et 1917, alors au bureau des brevets), Bohr (1913), Heisenberg (1925), Schrödinger (1926) et Dirac (1928). Pas de gros financements d’État ni de comités de pairs centralisés. Transistor (John Bardeen, Walter Brattain et William Shockley aux Bell Labs, 1947). - Circuit intégré (Jack Kilby chez Texas Instruments en 1958 ; Robert Noyce chez Fairchild Semiconductor en 1959). - Laser (Theodore Maiman chez Hughes Research Laboratories, mai 1960). Son principe fondamental remonte à l’article d’Einstein sur l’émission stimulée de la lumière publié en 1917. L’informatique moderne suit exactement la même dynamique. Alan Turing pose les bases théoriques des ordinateurs universels en 1936 alors qu’il est chercheur à Cambridge (travail individuel). Claude Shannon établit les fondements mathématiques de l’information aux Bell Labs en 1948. Les ordinateurs deviennent réellement pratiques grâce au transistor inventé aux Bell Labs en 1947, puis au circuit intégré développé dans des entreprises privées à la fin des années 1950. Même Unix, qui influencera profondément toute l’informatique moderne, est créé aux Bell Labs à la toute fin des années 1960 par Ken Thompson et Dennis Ritchie. À compter des années 1970, l’Occident a émulé le modèle soviétique de planification centralisée et de bureaucratie scientifique (revue par les pairs généralisée, panels de financement, cycles de subventions). Une longue stagnation dans les percées fondamentales a suivi. En ce sens, @elonmusk s’inscrit dans une longue tradition d’ingénieurs visionnaires qui ont osé l’impossible et transformé le monde malgré les sceptiques. Les frères Wright ont conquis les airs quand tout le monde affirmait que c’était impossible. James Watt a rendu la machine à vapeur efficace et a lancé la Révolution industrielle. Les pionniers du moteur à combustion interne, de Lenoir à Benz et Daimler, ont changé la mobilité pour toujours. Comme eux, Musk ne se contente pas de rêver : il construit, itère et livre. LeCun se limite au modèle linéaire de l’innovation : la recherche fondamentale, bien financée par l’État et les agences, produirait mécaniquement le progrès technologique. C’est un modèle simpliste et indéfendable, construit à compter des années 50 pour justifier le financement public massif, et largement démenti par l’histoire. x.com/lemire/status/…

Brivael Le Pogam @brivael

5 days ago

Yann LeCun décrit un monde qui l'a enfanté, et ce monde est en train de mourir. Le modèle qu'il défend est celui du XXe siècle. La recherche fondamentale d'un côté (universités, PhD, papiers), l'application industrielle de l'autre, des décennies plus tard. Une chaîne longue,

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Many people are saying.

Alps @alpaysh

5 days ago

i still think about this

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The car that used to be in my garage is currently in an Earth-Mars elliptical orbit and will be there for at least 10 million years

DogeDesigner @cb_doge

5 days ago

Elon Musk sending a Tesla into space remains one of the most iconic and entertaining moments in SpaceX history. 🚀😂

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The creator of Linux just publicly called out the AI hype. Word for word. Linus Torvalds took the stage at Open Source Summit 2026 and said this: "When I see people saying 99% of our code is written by AI, I literally get angry. Because those same people — I can pretty much guarantee — 100% of their code is written by compilers. But they never say that." He is not anti AI. The Linux kernel saw a 20% jump in submissions this release because of AI tools. He uses it. He gets it. His point is something most people are too afraid to say. AI is a productivity tool exactly like compilers were. Compilers boosted programming by 1000x. AI adds another 10x on top. Enormous. But nobody says "the compiler wrote my code." So why are we saying AI wrote it? He also flagged something nobody is talking about. AI is flooding small open source projects with drive-by bug reports. Someone runs a prompt, files a report and disappears when asked for a patch. Maintainers with one or two people are drowning trying to keep up. "Sometimes AI reports a bug and when you ask for more information the person has done that drive-by and does not even answer your question. That is the real burnout issue." And his final warning was the sharpest of all. "People who do not understand the complexity of systems will prompt systems and write processes that will fail." The AI hype crowd is very loud right now. Linus has been building real systems for 35 years. When he talks, engineers listen. Full interview here: thenewstack.io/torvalds-ai-pr…

🎯 Andrej Karpathy on how to learn.

“This is the first time ever that I can remember that technology costs the same as people” Technology / compute and computers used to cost a LOT more than people up to the 1960s. Utilizing machines 100% was thus extremely important back then - hence eg the time sharing model

Deirdre Bosa @dee_bosa

2 weeks ago

"This is the first time ever that I can remember that technology costs the same as people, and you're making that comparison: choose tech or people”-@jainarvind

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I can’t sleep at night because my mind races with all the cool shit I could be building. AI has turned my workdays into 24 hour grind sessions. I code until I literally collapse from exhaustion 7 days a week.

The thing nobody tells you about exponential change is that it feels like nothing is happening right up until the moment everything happens at once.

The problem with maintaining AI skills is that the incoming bugs come with a synopsis like "SKILL ISSUE: ..."

Human immortality just around the corner? youtube.com/watch?v=4IM866…

I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem. As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)! I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work. It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results? 88ms => 1.5ms 150K allocs => ~500 allocs Incredible right? Nope. My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path. This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput. The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity. Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.

"... The proof came from a new general-purpose reasoning model, rather than from a system trained specifically for mathematics ..." openai.com/index/model-di… Bitter lesson!

My current experience with coding models.

🚨: Japanese scientists made history by becoming the first nation to successfully generate electricity in space and beam it wirelessly back to Earth

It really feels like the pandemic broke society. Everything from city sports leagues to bars are still a shell of what they were before 2020

vo @vanillaopinions

3 weeks ago

the post covid years have truly been so awful

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