Dominique Dumont

[paji.eth @paji_a]

AI時代に起きる最大の悲劇は《仕事を奪われること》じゃなく、【20年間追いかけてきた夢が、たった20分で叶ってしまうこと】なんよな、これを勝手に《夢の即死問題》と呼んでいるんだけど、例えば「いつか自分のゲームを作りたい」と思っていた会社員が、Claude Codeに話しかけたら30分後には遊べるゲームができてしまう、「いつか小説家になりたい」と思っていた人が、ChatGPTと週末に一冊書き上げてしまう、Sunoで作曲家になり、Soraで映画監督になり、Cursorで起業家になる、もちろん《プロ品質》や《商業的成功》とは別の話だけど、これまで人類は「才能がないからできない」「時間がないから挑戦できない」「技術がないから形にできない」という《3大言い訳》に守られてきたとも言える、それがAIによって一気に剥がされると、恐ろしいことに【夢を叶えたのに、別に楽しくない】という人が大量に現れるかもしれない、つまり人間が欲しかったのは《作品》なのか、《作る行為》なのか、それとも「いつかすごい自分になれる」という《未来の自分への期待》だったのかが、いきなり試されるんよな、これまでの社会は《才能の証明》に10年かかったから、その10年間を“夢”として生きられた、でもAIがその期間を10分の1、100分の1に圧縮すると、夢の賞味期限まで短くなってしまう、そこで始まるのが、これも勝手に名付けた《夢のデフレ》で、映画を作れることも、アプリを公開できることも、会社を立ち上げられることも、それ自体はどんどん珍しくなくなる、すると逆に価値が上がるのが【誰にも頼まれていないのに、なぜか作り続けてしまう人間】なんよな、100本のゲームを作れる人より、101本目をどうしても作りたくなる人、100曲生成できる人より、たった1曲のサビが気になって朝まで直してしまう人、AIが《能力の格差》を縮めるほど、《執着の格差》がむき出しになっていく、これは《情熱資本主義》とでも呼べる変化で、学歴でも職歴でも資格でもなく、何に異常なほど夢中になれるかが、その人の競争力になっていく、皮肉だけど、人類が何千年もかけて《できないこと》を減らしてきた結果、最後に残る問いが「で、あなたは何をしたいの？」という、子どもに聞くような質問に戻ってくる、そしてもっと面白いのは、そこで初めて自分の《本当の好き》を発見する人が大量に出てくる可能性で、AIが人間から奪うのは仕事だけじゃなく、“やらなかった人生への言い訳”なのかもしれない、でもその先には、誰もが何度でも自分の人生を試作できる【人生のプロトタイプ時代】が待っていると思うと、ちょっとワクワクするんよな…

[Oliver Prompts @oliviscusAI]

"I don't have a GPU" is officially dead 🤯

You can now run 70B model on a single 4GB GPU and it even scales up to the colossal Llama 3.1 405B on just 8GB of VRAM.

AirLLM uses "Layer-wise Inference." Instead of loading the whole model, it loads, computes, and flushes one layer at a time

→ No quantization needed by default
→ Supports Llama, Qwen, and Mistral
→ Works on Linux, Windows, and macOS

100% Open Source.

[Alex St. Louis @AlexStLouis10]

Unreal Engine 5, meet WebGPU.

Want to bring a UE game to the web? Then try Strata, our CI/CD distribution tool. Just a single prompt into Claude or Codex, and your UE game will be in WebGPU. Link here:

https://t.co/8ilRSZbzCN @alightinastorm

[Dominique Dumont @DomDumont]

Je n’en reviens pas. Je croyais que les mathématiciens étaient les rares chercheurs totalement désintéressés. Tout faux. Ce sont des humains plein d’ego eux aussi. C’est rassurant quelque part

[Noah Smith 🐇🇺🇸🇺🇦🇹🇼 @Noahpinion]

*Mathematicians did not ask for this work to be done"

WTF?!! Since when was math something that was only done at the request of professional mathematicians?!!

Mathematicians don't own mathematics! This is crazy!!

[Dominique Dumont @DomDumont]

Google down.

[Guillermo Rauch @rauchg]

At this rate AI will get us GTA 7 before GTA 6

[Evan Jenkins @ejenk]

Mathematicians are like women. They ask questions, and then they get angry when you answer them.

[bioshok⏸️ @bioshok3]

→過去3年間のすべての主要な数学発見の81%が、今日、OpenAIによって公開されました。数学的特異点は本質的に今日達成されたことになります。つまり、人間の知能が追いつく可能性は二度とないということです。すべての科学分野が最終的にこのような状況に直面するでしょう！

[VraserX e/acc @VraserX]

This is why I’m an accelerationist.

OpenAI just released 722 mathematical manuscripts across 372 families, largely produced by an unreleased AI model tackling open research problems.

Think about what that trajectory means.

Today it’s mathematics. Tomorrow it’s drug discovery, aging, materials science, fusion, physics and engineering.

The most important property of advanced AI isn’t that it can write emails or generate videos. It’s that it can potentially compress years of human scientific work into hours.

Slowing AI down isn’t automatically the cautious position. There is a cost to not accelerating too: discoveries delayed, diseases untreated and technologies that arrive years later than they could have.

We should manage the risks. But we should be racing toward systems capable of accelerating science itself.

Humanity has spent centuries wishing we had more Einsteins, von Neumanns and Curies. We may be building millions of them.

[Dominique Dumont @DomDumont]

Euh … doucement quand même

[Superman @thesupermannx]

Google Deepmind just broke chemistry..

They open-sourced a model that can invent completely new biology from scratch.

It’s called “AlphaProtein Novo”

It's an AI pipeline that designs brand new enzymes for "new-to-nature" chemical reactions that have never existed in any living organism.

to put this in perspective..

standard protein ai models (like alphafold) answer the question "what shape will this protein have?". ap novo answers the question "can i make a protein that does this specific chemistry?".

the results from the paper are actually terrifyingly good:

the ai designed an enzyme to synthesize piperidines, which are a critical building block used in pharmaceuticals and materials.

this designed enzyme inverted natural biases to achieve near-perfect regioselectivity.

it produced the chemical building block 99x more often than the competing natural product.

it also designed an enzyme to hydrolyze DEHP, which is a pervasive plastic environmental toxin.

this plastic-eating ai enzyme was 14-fold more active at 90°C than at room temperature, and survived in 75% acetonitrile.

meanwhile, natural enzymes completely failed and were entirely inactive under those exact same extreme conditions.

these new ai-generated designs are up to 60% smaller than natural equivalents.

because they are smaller, they have a much higher mass density of active sites.

i am speechless.. this is the holy grail of synthetic biology.

we don't have to wait millions of years for microbes to evolve enzymes that eat our pollution or build our drugs.. we can just compute them on a gpu today. the ai's success rate in finding functional designs actually matches or surpasses traditional natural sequence screening.

and deepmind open-sourced the whole thing on github.

[Chubby♨️ @kimmonismus]

Ok so I took a closer look at the results, and OpenAIs AI-generated mathematics manuscripts are *even more* significant than I initially thought.

I spent the morning going through it. Some thoughts.

The list is absurd. A zero-free half-plane for the zeta function (Re s > 7/8), which is the first result of its kind in over a century. Hilbert's tenth problem over the rationals. The Hodge conjecture for CM abelian varieties. Irrationality of Catalan's constant. Dozens more.

Any one of these would normally be a career.

But the number that many arent seeing is the following: It's 3. That's the average hours of ChatGPT Pro compute per result. A month ago, Navier–Stokes took them around 10,000 agents and 88 hours. That efficency gain within just a few weeks.

Also OpenAI claims to have solved the quasi-Riemann hypothesis. That alone would be a historic breakthrough in mathematics.

This is a weaker version of the famous Riemann hypothesis, which concerns how prime numbers are distributed. The full hypothesis remains unsolved, but the claimed advance would be enormous in its own right.

Math twitter obviously is shocked. Again: this is literally the intelligence explosion happening right now. 2027 will be the year of Superintelligence. Im now convinced by that.

[Dominique Dumont @DomDumont]

Non mais les maths c’est comme les échecs,le go et la littérature, ça demande une véritable intelligence humaine … ou pas …

[Frenchie @Frenchie_]

Voir des mathématiciens peter un plomb sur les résultats de OpenAI

C’est mieux que l’UFC

[Daniel Leach @danielkleach]

Nobody talks about the psychological damage of watching something you spent 15 years learning become a button.

[Kevin Picchi @KevinPicchi]

This guy re-created all the adobe apps with opus-5.5, ported them to rust, and opensourced them

something really cool is happening

[Eric S. Raymond @esrtweet]

This is the doom I predicted a few days ago, coming for Photoshop. A clean-room open-source reimplementation.

No prizes for guessing that they decompiled Photoshop to source code, processed that to some kind of non-code specification language, then fed the spec to an LLM with an instruction to generate Rust.

Adobe just got nuked. And closed source is dead, dead, dead.

https://t.co/0sxtGNaPtq

[套利豪仔🗽 @pritipatelor]

英伟达刚刚放出了一个很有意思的新工具：随意一张图片，就能生成一个可以自由探索的 3D 世界

而且项目还是 100% 开源 🔥

模型已经上线 Hugging Face
UI 代码已经开源到 GitHub

这个名为 Lyra 2.0 的模型，可以把普通图片直接变成可交互的 3D 场景

你不仅可以在里面自由行走、转身探索，甚至还能把机器人放进生成的世界里进行模拟训练

简单来说就是：一张图 → 一个可以走进去的 3D 世界

[liam. @liambraus]

HOY UNA INDUSTRIA ENTERA DEJÓ DE TENER SENTIDO

alguien subió a GitHub un repo que coge cualquier foto y te devuelve un mundo 3d explorable: mallas con físicas, splat del fondo, audio ambiente. todo.

entra una imagen.

sale un mundo. cinco minutos.

la gente que lleva diez años aprendiendo Blender se ha pasado el día mirando esto en silencio.

se llama image-blaster.

os dejo el repo abajo.

[Dominique Dumont @DomDumont]

@AndroidBlogger Zelda and Switch games also

[Dominique Dumont @DomDumont]

@AndroidBlogger @valigo Ok

[Dominique Dumont @DomDumont]

@AndroidBlogger @valigo Oui je pensais bien à ça mais je croyais que c’était du script