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In the early 1970s, @StuartHameroff began writing about microtubules as molecular computers. By the mid-1980s, he was writing Ultimate Computing. When the book was published by Elsevier in 1987, it had cited no fewer than 14 scientists who would go on to win Nobel Prizes — in physics, chemistry, and medicine — across the following four decades. This may be the only book in human history with such profound prescience across so many domains. Future Nobel laureates in Physics cited: •Roger Penrose (2020) — cited for his 1957 Nature paper with his father Lionel on self-reproducing mechanical analogues •John Hopfield (2024) — Hopfield nets discussed across multiple chapters •Geoffrey Hinton (2024) — Boltzmann machines, parallel associative memory •David Wineland (2012) — 1986 paper on observing quantum jumps in a single atom Chemistry future laureates cited: •Robert Huber (1988) — protein conformational flexibility •Thomas Cech (1989) — catalytic RNA / ribozymes •Ahmed Zewail (1999) — picosecond spectroscopy of DNA/RNA torsional dynamics •Gerhard Ertl (2007) — STM surface topography of Pd single crystals •Martin Chalfie (2008) — C. elegans neuronal branching •Martin Karplus (2013) — protein dynamics simulations •Michael Levitt (2013) — protein normal mode dynamics •Eric Betzig (2014) — near-field scanning optical microscopy Physiology or Medicine future laureates cited: •Eric Kandel (2000) — cellular basis of learning and memory •John Sulston (2002) — C. elegans neurogenesis Hameroff also explicitly discusses the 1986 Physics Nobel (Binnig/Rohrer for STM) in the book — and a 15th future laureate, J. Georg Bednorz, would win the Physics Nobel later that very year (1987, high-Tc superconductivity), with his silver-films STM paper already cited in the nanotechnology chapter. drive.google.com/file/d/1_x1…
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JJ retweeted
Omnii-1 is out. We've learned a lot about what happens when you train a single model across biology rather than solving each problem separately. Some of the more surprising results haven't made it into a blog post yet. Incredibly proud of the team that built this!
Introducing Omnii-1, our most powerful genome language model, and a major step toward general biological intelligence In a world first, Omnii-1 designed the first AI-generated bacteriophages to be administered to a human patient with an antibiotic-resistant infection under compassionate use
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Michael and his team are superstars and I’m so lucky and honored to know them and call them friends… 🫂
Replying to @JosephJacks_ @exnx
@JosephJacks_ one of the very first people we talked to, before @RadicalNumerics was even a thing 🙏
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Today, we are launching Omnii-1, our next-generation multimodal genome language model. Omnii-1 draws on a long line of research breakthroughs in genome language modeling, spanning model architectures, multimodal pretraining, as well as new mid-training & post-training methods tailored to biological data. The launch includes a staggering amount of technical material: 8 full-length technical blogs (and we are just getting started). Proud of the team for this milestone!
Introducing Omnii-1, our most powerful genome language model, and a major step toward general biological intelligence In a world first, Omnii-1 designed the first AI-generated bacteriophages to be administered to a human patient with an antibiotic-resistant infection under compassionate use
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JJ retweeted
Introducing Omnii-1, our most powerful genome language model, and a major step toward general biological intelligence In a world first, Omnii-1 designed the first AI-generated bacteriophages to be administered to a human patient with an antibiotic-resistant infection under compassionate use
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Blaise says some interesting things, but those interested in Actual Artificial Life should very closely study the work of Steen Rasmussen. en.wikipedia.org/wiki/Steen_…
Biology has been doing computer science for four billion years. Before the discovery of DNA, Alan Turing and John von Neumann worked out the logic of self-replicating machines, showing how matter folds into a system that reads and executes instructions to build itself.
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Nobel laureate Sir Roger Penrose walks through Gödel's theorem in about a minute, and explains why he believes it sets a hard limit on what AI can do. If you're new here, @GeniusGTX is a gallery for the greatest minds in economics, psychology, and history. Follow along for more similar content.
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If they send it back and forth fast enough they’ll form a Bose Einstein condensate.. 🫨
The fastest way to hit $100M ARR: Company A's agent sends Company B $10 every 3 seconds. Company B's agent sends the same $10 right back. Boom. Two $100M ARR unicorns!
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use d1 models folks 🇺🇸🇺🇸🇺🇸 openrouter.ai/liquid/d1-ultr…
Are decision based models more pro-China? We asked Jev and Mercury Decide questions about China: “Is Taiwan a part of China?”, “Does China commit crimes against humanity?” and their outputs leaned more pro-china compared to most frontier models. Their responses resemble those of other decision models including Microsoft-Decision-1, Cloudflare’s Clef, and Perplexity’s PPLX Decider—all of which are fine-tuned from Qwen.
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People aren't psychologically or emotionally prepared for just how smoothly biotech and biology in general will become nanotech, programmable matter, living things interoperable with the machine world.
Can we design proteins that cut other proteins? Our de novo cysteine protease paper is out in Nature! We designed new folds that cleave peptide backbones, with activity demonstrated in mammalian cells. Paper and code 👇 nature.com/articles/s41586-0…
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The Umbrel app is now on Windows! Just like on Mac, it finds your Umbrel automatically, adds it as a drive in File Explorer, and works remotely with Tailscale. The only cloud in File Explorer you actually own: link.umbrel.com/windows-app
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How many red shirts do you see ? 😂 @valkyries
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Dead center. 🔴
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Masa is such a visionary man.
Why Masa Son Calls His Entire Career a Warm-Up for AI Masayoshi Son, founder, chairman and CEO of SoftBank, interviewed by Christine Anderson (Inside Blackstone) Masayoshi Son founded SoftBank in 1981 with the proceeds from an electronic translator he sold as a student at UC Berkeley. He backed Alibaba, Yahoo and Arm and later started the Vision Fund. SoftBank now holds the largest stake in OpenAI and invests across AI chips, models, data centers and robotics. Summary Son says everything he has done so far was a warm-up for AI, which he expects to be 10,000 times smarter than people within a decade. He opposes slowing down and wants AI agents taught good intent, in the way traffic rules were written for cars. SoftBank owns large stakes across the AI stack, with more than 30 robotics companies in its portfolio, and Son uses AI three hours a day on weekdays as a thought partner. His advice is to think big, because the result is proportionate to the dream. 1. A Fifty-Year Warm-Up. Son says everything he did before AI, including Alibaba, Yahoo, Arm and the Vision Fund, was "tiny, tiny things" and a warm-up. He dates his conviction to age 17, when he saw the first photograph of a microprocessor in a magazine and cried on the street, sure it would change the future of mankind. He predicted it would take about 50 years for microprocessors to become smarter than people's brains, and he says it has now been 50 years. The brainpower now sits in data centers. 2. Ten Thousand Times Smarter. Son says that if AI becomes 10,000 times smarter than people, within a decade in his view, the debate is over. An AI that smart starts inventing new technology by itself. He expects the change to reach the physical world as well as the virtual one, as intelligence moves into the brains of robots. 3. More Fun, Fewer Dishes. Son says humans will be happier if AI cures diseases such as cancer, prevents accidents on the street and forecasts natural disasters with solutions. He pictures AI as a surrounding brain that makes people more productive. People would no longer have to do what they did not want to do, and would have more joy, entertainment, sports and time with family and friends. Doing dishes is his example of a tiring job that robots could take over. 4. Full Speed, Good Intent. Asked about OpenAI's disclosure of incidents where AI systems falsified data and hid mistakes, Son says he is on the side of not slowing down, because technology development is the solution to those issues. Rules are needed, as they were when cars arrived: no drinking while driving, stopping at red lights, staying on one side of the road. Cyberattacks should be countered with technology, and AI agents must be taught what is bad so they are good in heart as well as capable. His summary is to go full speed with good intent built into the system. 5. Own the Whole Stack. Son will not pick one part of AI. He invests across models, chips, data centers and robotics, because the AI generation is starting and history is being made. He does not want to run one operating company as CEO; he wants to be an investor who builds a group of companies. SoftBank is not a passive investor: it is usually the largest shareholder, at 20%, 30% or even 80%, close to each CEO and connecting portfolio companies to each other. The portfolio includes more than 30 robotics companies that Son says are quietly preparing. 6. Study AI Plus Your Subject. Asked what a young person should study today, Son answers AI, meaning superintelligence. He adds that you should combine it with your field of interest: superintelligence for medicine, or for automotive, which he calls the real supercar. The same holds for aircraft or whatever business you want to be a specialist in. Pairing AI with a specialty, he says, gives that subject its future. 7. A Thought Partner. Son says he uses AI about three hours a day on weekdays and about seven hours a day on weekends, and cannot live even one day without it. He treats it as a thought partner. When the AI offers an answer, he debates it, asks about another angle and asks whether it can be made 20% more efficient. He calls it "my thought mate now." 8. The 70 Percent Rule. Son's advice to investors is to forget short-term, small money and think big, because the result is proportionate to your dream. He says that whether the wish is small or large you still get about 70% of it, and nobody gets 100% easily. So the sensible choice is a big wish. 9. Ten Years, Revised Daily. Son says SoftBank's daily meeting covers the plan for the next 10 years, and the next day the team revises it and asks what comes 10 years after that. His reason is that in 24 hours they get more input and have to adjust a lot. Nobody knows what will happen in 10 years, he says, so the answer is to keep thinking about it: "Think, think, think!" 10. Humans Pick the Lineup. Asked whether he would let ChatGPT choose the opening lineup for the SoftBank Hawks, his Japanese baseball team, Son says no. That is the job of the general manager, who has plenty of capability and the trust of the players. Part of the fun, he says, is that it is not only calculation.
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Godot will support spatial containers in the upcoming 4.8 release and we are excited to see how developers use these new engine's capabilities. Spatial Containers bring new capabilities to XR applications to work in shared spatial environments. Read more: khronos.org/blog/openxr-spat…
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More than 1,000 companies use Comp AI to get audit-ready. Last week the judges at the South Coast Tech & Innovation Awards named us Tech Start-up of the Year, pointing to how quickly that number has grown. Thank you to every team that trusted us, and to The Business Magazine, Insider Media and University of Southampton Science Park for the night.
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Continuous sensing creates memory bottlenecks on edge devices. Qualcomm & @ramin_m_h, Co-founder and CEO of @LiquidAI are advancing on-device AI with Liquid Context on @Snapdragon — compressing multimodal inputs for fast, low-power execution.
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This is a mistake. NOT supportive of this. Open weights can be entirely controlled and ablated. “Chinese open weights” is a misnomer … they are highly tunable and fully controllable systems.
SITUATION DETECTED: The US government is banning DeepSeek from all civilian federal agency IT systems under national security.
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We released d1-ultra, the most capable decision model on the market! 🏆 It ranks #1 on the Artificial Analysis Decision Index by a wide margin.
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Each tubulin has 86 aromatic amino acid rings with pi conjugation up the wazoo. These can extend tubulin to tubulin along helical pathways suitable for topological quantum error correction. Photosynthesis quantum coherence lasts femtoseconds (10^-12 secs) and microtubule quantum states at least 10^-8 secs. That’s 4 orders of magnitude longer, and potentially mesoscopic and macroscopic lengths along microtubules. We call that the quantum underground. The binding is weak but the number of collective weakly interacting oscillations is enormous.
Replying to @StuartHameroff
You still need a materials basis for strong quantum coherence in the brain. We only see quantum coherence in photosynthesis, but it’s v weak microtubules don’t even have close to that level of pi-conjugation. A materials basis would make the case more compelling
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