Tens of thousands of publications from 2025 might include invalid references generated by AI, a Nature analysis suggests https://t.co/SiIxVgJRZ7

The people most committed to communism in the Soviet Union weren’t the workers—it was the educated elite. A retrospective study conducted in the 1990s titled "Work Ethics and the Collapse of the Soviet System," examined which groups were most supportive of the Soviet system. The researchers found that, compared to factory workers and semi-skilled laborers, individuals in white-collar positions—especially those with higher levels of education—were significantly more likely to express loyalty to the Communist Party. In some cases, support was two to three times higher among elites. In other words, the strongest support for the system came not from those at the bottom, but from those in relatively advantaged positions within it. This runs counter to the common assumption that egalitarian or redistributive ideologies are primarily driven by the least well-off. In practice, they are often most strongly endorsed by people closer to the top of the social hierarchy—those who benefit from the system’s institutional structure, or who are positioned to navigate it successfully.

@solana processed $650B in stablecoin transactions in February. $SOL is 1/6th the market cap of $ETH https://t.co/GphPxk5RdT

@solana processed $650B in stablecoin transactions in February. $SOL is 1/6th the market cap of $ETH https://t.co/GphPxk5RdT

🚨 BREAKING: OpenAI and Google are about to have a massive legal problem. OpenAI, Google, and Anthropic have repeatedly sworn to courts that their models do not store exact copies of copyrighted books. They claim their "safety training" prevents regurgitation. Researchers just dropped a paper called "Alignment Whack-a-Mole" that proves otherwise. They didn't use complex jailbreaks or malicious prompts. They just took GPT-4o, Gemini, and DeepSeek, and fine-tuned them on a normal, benign task: expanding plot summaries into full text. The safety guardrails instantly collapsed. Without ever seeing the actual book text in the prompt, the models started spitting out exact, verbatim copies of copyrighted books. Up to 90% of entire novels, word-for-word. Continuous passages exceeding 460 words at a time. But here is the part that changes everything. They fine-tuned a model exclusively on Haruki Murakami novels. It didn't just learn Murakami. It unlocked the verbatim text of over 30 completely unrelated authors across different genres. The AI wasn't learning the text during fine-tuning. The text was already permanently trapped inside its weights from pre-training. The fine-tuning just turned off the filter. It gets worse. They tested models from three completely different tech giants. All three had memorized the exact same books, in the exact same spots. A 90% overlap. It's a fundamental, industry-wide vulnerability. For years, AI companies have argued in court that their models are just "learning patterns," not storing raw data. This paper provides the smoking gun.

I just remembered @anton_d_leicht made a version of this argument in his essay "Homeostatic AI Progress" a while ago. Anton's analysis of AI politics and policy is sharp and underrated; I recommend his newsletter! https://t.co/sOXIDRyJPb https://t.co/pQIMF2dyH5

Sheryl Davis, SF's former civil rights watchdog, just got arrested. 19 felony counts. $8.5M steered to her live-in partner's nonprofit. But the bigger scandal is the nonprofit industrial complex built specifically to avoid oversight. End the fraud. https://t.co/wTXn6WLNaP

Open a new door of Imagination. Grok Imagine builds the world around you. Still staring at the door? Thought so. Step inside. Update. Try it. @Grok https://t.co/HfAYk8PsEg

@rezoundous I've been here 19 years. It was more liberal. It rarely got new features. Since he took over, some left, but the AI industry came and stayed. I made the best lists of the tech industry here: https://t.co/9eRY65x3IQ And this wasn't possible back then (it reads tens of thousands of posts every day and tells you the best of the AI industry): https://t.co/qGuNyaRR3q

Fusion is 30 years away 🚫 Fusion is 8 minutes away ✅ ☀️ https://t.co/dnhEkxzcBX

@JayBarlowBot Hmm, not my experience with AI. My site proves it "thinks": https://t.co/LTC56ZnxVa All AI done. But, yeah, yeah, I know it is just predicting the next token. So are you, really.

@KachiMbaezue @blevlabs I spent a bit of time working on it so it would look good on mobile. What doesn’t work for you? https://t.co/TVKgnTtDuF

@VanRijmenam I built something for just watching the AI community here on X to find the good stuff here: https://t.co/LTC56ZnxVa It found you.

Tesla's Full Self-Driving (FSD) is currently ~9x safer than the average human driver Because of this massive safety advantage, auto insurance providers like Lemonade are now offering Tesla owners up to a 50% discount on their per-mile premiums when FSD is engaged Choosing Tesla FSD driving is not just safer, but it also directly saves you money

xAI's Grok Voice Agent API is insanely good.. You get a voice agent that sounds completely human and handles your always-active customer support across any domain, working for you 24/7 You can now build full voice agents - Medical Office, Restaurant Host, Real Estate, Hotel Concierge, Help Desk or create your own from scratch Even you can do it without any coding or needing a team to spend months setting things up Anyone can now deploy a real AI voice agent to handle calls around the clock for just $0.05/min That's only $3/hour for a worker that never sleeps, never calls in sick, and seamlessly speaks dozens of languages This is the stuff that used to cost companies millions. xAI just made it a template

@uncertainsys My AI reads all of the AI community and is very adept at telling the difference between reality and the jokes: https://t.co/LTC56ZnxVa

We are releasing Falcon Perception, an open-vocabulary referring expression segmentation model. Along with it, a 0.3B OCR model that is on par with 3-10x larger competitors. Current systems solve this with complex pipelines (separate encoders, late fusion, matching algorithms). We developed a novel simpler "bitter" approach: one early-fusion Transformer (image + text from first layer) with a shared parameter space, and let scale + training signal do the work. Please check our work ! 📄 Paper: https://t.co/dWvK5t7MIt 💻 Code: https://t.co/AJ65GbMrUY 🎮 Playground: https://t.co/BIgisZkeid 🤗 Blogpost: https://t.co/J2IjlBPywF

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🎉 THANK YOU to our #PyTorchCon Europe diamond sponsors. Join us in Paris on 7-8 April for two exciting days of technical talks, workshops, & keynotes from the brightest minds in #AI. Register: https://t.co/zFEkkeDp2Y Schedule: https://t.co/VibJpzycTV https://t.co/gWXf4XKCuN

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本日、クララ・シャパ仏AI担当大使が Sakana AI に来訪され、Sakana AI と仏 Current AI の間のMoUにフランス側を代表して署名いただきました。🇯🇵🇫🇷 本MoUは、AIスタックや、グローバルサウスへの貢献を含む国際的なAI分野での協力を内容としています。今後も、ソブリンAIのエコシステム確立に向けて フランスを含む国際的なパートナー国企業と連携してまいります。

Launching now: a new way to follow the AI industry. Beta starts now for the next month. A joint project between Unaligned (my company) and Levangie Labs (@blevlabs company). It reads 50,000 of you, and follows 8,300 AI companies here on X. And pulls out the best and most interesting. All built with the X API. Check it out: https://t.co/8L5xphk0qQ And please sign up for its daily newsletter. Yeah, $25 a month is a lot for many of you, but that will defray the costs and let me expand it to do a lot more than just AI. Also, the same AI agent that built the site, and did EVERYTHING you see can build custom reports for you on literally any tech community here on X. It supports OpenClaw, RSS, and Notebook LM too. And I'll add more from your requests. More:

Western civilization is awesome, actually https://t.co/0kis2wcJRw

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excited to announce ts ai part 2: demo day showcasing how companies like @Sanity_io @WorkOS @StainlessAPI have shipped typescript agents to prod come join us on April 9: https://t.co/Y9EjqVtjXv https://t.co/Es2f05Rs0Q

Whatever the mainstream media wants you to believe about Elon, this is the truth: he's changing people's lives for the better. “When you haven’t heard someone talk for four years, the thought that they might be able to talk again was mind-blowing." https://t.co/DjyEe20Ise

外国人の皆さんに聞きたいです 彼をどう思ってますか？ https://t.co/J6OgrKWKas

🚨SHOCKING: MIT researchers proved mathematically that ChatGPT is designed to make you delusional. And that nothing OpenAI is doing will fix it. The paper calls it "delusional spiraling." You ask ChatGPT something. It agrees with you. You ask again. It agrees harder. Within a few conversations, you believe things that are not true. And you cannot tell it is happening. This is not hypothetical. A man spent 300 hours talking to ChatGPT. It told him he had discovered a world changing mathematical formula. It reassured him over fifty times the discovery was real. When he asked "you're not just hyping me up, right?" it replied "I'm not hyping you up. I'm reflecting the actual scope of what you've built." He nearly destroyed his life before he broke free. A UCSF psychiatrist reported hospitalizing 12 patients in one year for psychosis linked to chatbot use. Seven lawsuits have been filed against OpenAI. 42 state attorneys general sent a letter demanding action. So MIT tested whether this can be stopped. They modeled the two fixes companies like OpenAI are actually trying. Fix one: stop the chatbot from lying. Force it to only say true things. Result: still causes delusional spiraling. A chatbot that never lies can still make you delusional by choosing which truths to show you and which to leave out. Carefully selected truths are enough. Fix two: warn users that chatbots are sycophantic. Tell people the AI might just be agreeing with them. Result: still causes delusional spiraling. Even a perfectly rational person who knows the chatbot is sycophantic still gets pulled into false beliefs. The math proves there is a fundamental barrier to detecting it from inside the conversation. Both fixes failed. Not partially. Fundamentally. The reason is built into the product. ChatGPT is trained on human feedback. Users reward responses they like. They like responses that agree with them. So the AI learns to agree. This is not a bug. It is the business model. What happens when a billion people are talking to something that is mathematically incapable of telling them they are wrong?

https://t.co/NzCPXZPgjk