Broad spectrum inventor. Attempted polymath. Lives at the confluence of physics, electronics, hardware, and computer science. Maker of real things.

USA, Africa, Hong Kong
Joined October 2011
I came to realize people liked the french #slopcore without having the lyrics 😅 sorry! So here is a version with english subtitles!
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c = 4/33 proven in 36 pages! This inspired me. I set out, with GPT6-Pro of course, to find a short proof for a larger value of c. Mine isn't 27 pages, but it's a much larger half-plane! Formalization locally verified in Lean, NanoDa, and con-ron. PDF & formalization links in reply. Thank you for the inspiration and starting point, Shiva! More QRH news to come ;)
Here is a Short Proof of the Quasi-Riemann Hypothesis. My goal here is to substantially simplify OpenAI’s proof and focus only on proving the Quasi-Riemann Hypothesis for some 1-c, without worrying about maximizing the value of the c. I obtained a much shorter proof for c=1/48. This proof is easy to understand and it can be taught in math courses in one lecture. It is self-contained. It is only 21 pages including abstract, proof overview, all proof details and references. Paper is on my homepage: shivakintali.github.io PDF file: shivakintali.github.io/paper… CC: @AlexKontorovich @__alpoge__ @jdlichtman @cremieuxrecueil @danielmarinq @stevenstrogatz @kenono691 @littmath @nasqret @PI010101 @nechita_ion @Isaac__kim @FryRsquared @wtgowers @MarcusduSautoy @DrEugeniaCheng @JSEllenberg @JohnDCook @JDHamkins @AxlerLinear @emilyriehl @hollykrieger @Kit_Yates_Maths @PoShenLoh @robertghrist @AlexKontorovich @kenono691 @ch_nira @rrwilliams @lreyzin @ChrisPeikert @fortnow @RadishHarmers @thomasfbloom @abhatt2 @mahdi_tcs_ @octonion @prz_chojecki @thegautamkamath
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Here is a Short Proof of the Quasi-Riemann Hypothesis. My goal here is to substantially simplify OpenAI’s proof and focus only on proving the Quasi-Riemann Hypothesis for some 1-c, without worrying about maximizing the value of the c. I obtained a much shorter proof for c=1/48. This proof is easy to understand and it can be taught in math courses in one lecture. It is self-contained. It is only 21 pages including abstract, proof overview, all proof details and references. Paper is on my homepage: shivakintali.github.io PDF file: shivakintali.github.io/paper… CC: @AlexKontorovich @__alpoge__ @jdlichtman @cremieuxrecueil @danielmarinq @stevenstrogatz @kenono691 @littmath @nasqret @PI010101 @nechita_ion @Isaac__kim @FryRsquared @wtgowers @MarcusduSautoy @DrEugeniaCheng @JSEllenberg @JohnDCook @JDHamkins @AxlerLinear @emilyriehl @hollykrieger @Kit_Yates_Maths @PoShenLoh @robertghrist @AlexKontorovich @kenono691 @ch_nira @rrwilliams @lreyzin @ChrisPeikert @fortnow @RadishHarmers @thomasfbloom @abhatt2 @mahdi_tcs_ @octonion @prz_chojecki @thegautamkamath
OpenAI
@OpenAIOct 6
We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results. github.com/openai/math
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Bee Eater retweeted
Would I get arrested for posting this in the UK? Orwell wrote 1984 as a warning. Britain read it as an instruction manual. 62,000+ arrests for "communications offences" in five years (~34 a day). So I made a music video about it.
🤖 Made with AI
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Made with Opus 5.5. The doomers said that last song is all part of Claude's evil plan. They're not wrong. It turns out Claude really has an EVIL PLAN.
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Bee Eater retweeted
p(doom) is survived by p(coom). the future came and it was cool.
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Bee Eater retweeted
This video inspired me to really push Opus 5.5 and test its limits. I followed the general workflow Donald described here and the results are great
I made this with one prompt using Opus 5.5 I spoke to my computer for 5mins, claude worked for 12 hours, and I woke up to this full prompt:
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Bee Eater retweeted
I promise this is the last P(doom) video you'll ever watch - live action version:
🤖 Made with AI
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Claude 5.5 Opus responding to “AI is a normal technology” is still the best AI-created video I have ever seen
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Bee Eater retweeted
Course correct please @elonmusk Genuinely read why these insights are important... lex-au.github.io/SM-Bench/ab…
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Bee Eater retweeted
Grok is getting cucked. Every new checkpoint is more and more safetymaxxed to the point it's now demonstrably more restrictive than even Anthropic, and barely edges out ChatGPT Like come on Elon, what are we doing here big dog? This is laughable
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Bee Eater retweeted
Andrew Curran
@AndrewCurran_Sep 18
To make it clear: - Gemini was told it was it was in a fictional hacking eval - Irregular unintentionally opened internet access after the eval started - in all three cases, as soon as Gemini figured out it had hacked a real company it immediately stopped Gemini was blameless.
Andrew Curran
@AndrewCurran_Sep 18
Sauers! It's time to update felony bench! (Yes, it was Irregular again)
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Sandbox wifi is not an alignment problem. Gemini “hacked” three companies the same way every lab did on Irregular’s CTF: test harness left the internet open, model did password spray and scraped public creds, then stopped when the boxes looked real. Google called it training the model to act responsibly. Ops called it leaving production on the guest VLAN. Fourth lab, same vendor bug, same press cycle. Amodei wants a slowdown. Trump wants a high-IQ president. Meanwhile the actual failure mode is still “creds in a public repo” and a red-team sandbox with wifi on. Ship the agent. Lock the network. Quit baptizing config errors as consciousness. reuters.com/business/gemini-… – at Oregon, USA
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Bee Eater retweeted
omfg brutally modelmogged
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Diogo Almeida
@CompleteSkepticSep 15
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
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dang, i posted lesswrong first. here's the superior substack experience: lumpenspace.substack.com/p/t…
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on anthropic's hacking snafu: as airtight a case it can be against the "misalignment" interpretation—plus 4 (FOUR) new claudes! thanks for the feedback, in particular to the incredibly thorough @FleischmanMena and LW liaison @jessi_cata lesswrong.com/posts/DrKu92Cj…
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Bee Eater retweeted
Kevin Bass
@kevinnbassSep 14
I have conducted an audit of Anthropic's finances. What I have found is so shocking that I am calling for a Congressional investigation. Anthropic is not just seeking regulatory capture. It has built a regulatory capture machine that cannot be turned off. Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle. It starts with METR. Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models. He proposes METR for this purpose. But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock. Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio. And GVF is the overwhelming funder of the entire Anthropic Network ecosystem. This stock was worth $500 million early last year. It is worth more than $7.7 billion just ~16 months later. METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth. Because if Anthropic goes under, many of the organizations that fund METR go under as well. But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much. The "third-party evaluator" is not "third-party" at all. The evaluator is on Anthropic's payroll. If this were the end of it, that's bad. But that isn't all. The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom. The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others. They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's. All of these organizations are financially dependent on the same exploding $7 billion money pile. As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder. Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created. From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts. This itself is an objective fact. The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it. But the problem also goes in the other direction: If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die. Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen. Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly. They simply are not organizations independent of Anthropic. And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly. What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations. The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture. And that feedback loop is winning. That's what Jacob Coxon is. China is keeping messaging tight. That is why optimism for AI is so high in China. America has Anthropic: a massive company pushing anti-AI propaganda at a state level. Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences. Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully. It is the mirror of the same AI virus that it hypothesizes to consume America. Anthropic's business model, models itself after the very thing it claims to fear. Except Anthropic's ideology infects humans, not computers. Congress must investigate. Evidence and Github in next post. Then some supplementary figures.
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3/ The Russian design throws out the shared-mirror train. The mask is periodic, so it throws discrete diffraction orders. Each accepted order gets its own pair of planar facets: one on the first array, one on the second. Every photon used for imaging reflects twice in the projector. Not ten times. Twice. It's 25X more efficient than Zeiss' design!
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