Julien @serializers

Yellow Magic Orchestra with Throbbing Gristle.

Do you know how deeply broken a culture has to be to ship this product and let the CEO walk around like this?

Remember when Musk challenged the World Food Program to explain how he could solve world hunger with just $6 billion, they did, and he just completely ignored them?

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DiscussingFilm @DiscussingFilm

a week ago

Elon Musk has become the first trillionaire in history.

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NEW: malware developers added nuclear & biological weapons text to to their spyware. Goal? To trigger LLM safety refusals... so that their spyware wouldn't be analyzed by an AI security scanner. Cleanest practical example I can think of for why over-indexing on first order safety alignment is risky. When closed (and open) models ship with aggressive refusals, they will be sprinkled with second-order blindspots that attackers will discover...and exploit. We are only in the earliest days of attackers leveraging these features, and it wouldn't surprise me if users systems that need to handle complex cybersecurity issues demand that models be less safety-blunted. In the weeds: @SocketSecurity's post also shows why intention matters in how you design a malware analysis pipeline to avoid prompt manipulation. H/T to colleagues that shared this with me socket.dev/blog/mini-shai…

You have noticed it. ChatGPT feels dumber than it used to. Your prompts that worked six months ago produce worse results now. The writing sounds flatter. The ideas sound safer. The internet itself feels like it is shrinking. Every article reads the same. Every email sounds the same. Every answer sounds like it was written by the same voice. You thought it was you. It is not you. Researchers at Oxford and Cambridge published a paper in Nature proving what is happening. They call it Model Collapse. Here is the mechanism in one sentence. AI trained on AI-generated data gets dumber every generation until it forgets what real human data looked like. The internet is filling with AI-generated content. Blog posts. Articles. Reviews. Comments. Social media. AI companies scrape the internet to train the next generation of models. Which means the next generation of AI is being trained on the output of the current generation. Each cycle loses information. Not randomly. It loses the rarest, most unusual, most creative parts first. The researchers call these the "tails of the distribution." The weird ideas. The unexpected perspectives. The things that made the internet feel human. Those disappear first. What remains is the average. The safe. The expected. The bland. Then the next generation trains on that. And loses more. And the next generation trains on that. And loses more. The researchers proved this is not a slow decline. Major degradation happens within just a few iterations. Even when some of the original human data is preserved. They tested it on large language models. On image generators. On statistical models. The pattern was the same every time. The output converges toward a narrow, flattened version of reality that looks nothing like the original data. The lead researcher put it plainly. "Large language models are like fire. A useful tool. But one that pollutes the environment." The pollution is invisible. You cannot see which sentence on the internet was written by a human and which was written by AI. Neither can the AI that is about to train on it. And once the tails are gone, they do not come back. The damage is irreversible. This is not a prediction anymore. It is a diagnosis. The internet you grew up on was built by humans writing things no algorithm would have written. Strange, personal, imperfect, alive. That internet is being diluted. One generation of AI at a time. And the models trained on what remains are learning a smaller and smaller version of the world. Model Collapse is not a technical problem. It is a cultural one. The thing that made the internet worth reading is the thing that disappears first.

I admire Fabrice Bellard. He is almost certainly a better overall programmer than I am.

Spencer Baggins @bigaiguy

2 weeks ago

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

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a reminder that branding matters.

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This is the tough lesson that a lot of people are learning the hard way AI might have made building apps a lot easier, but it also set the barrier to entry at zero Because anyone can do it, there is no moat left The only edge left in the future will be sales and marketing

Hollywood’s favorite story: the broke outsider who self-financed an $80k movie on credit cards. The receipts: a ~$1M elite education, $330k+ in grants on her prior film, and a father - a Chinese real-estate and equity investor - credited as an executive producer. I call it “poorface.” New piece: open.substack.com/pub/hollywoodg…

bad graphic design > ai design

team call

Please pay a graphic designer and stop using chat gpt for your event flyers 😭

AI is doing [X thing] It should be doing [Y thing that is better] Introducing [name you got from Claude], the first [AI thing] that actually [does thing]. 👇

Sue @suekhim

3 weeks ago

AI is making kids dumber. It should be making them geniuses. Introducing Koji, the first AI tutor that gets kids to actually think. 👇

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Nutopia Cyberlounge. Covent Garden, London, 1999-2004.

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“Read, read, read, read, read, read, read, read…” — Werner Herzog

Day @Daywrotethis

3 weeks ago

A man who reads old books cannot be fully captured by modern stupidity. He has dead kings, prophets, poets, killers, saints, drunks, generals, and madmen whispering in his bloodstream. The feed has no chance against this.

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