Barrister. AI • privacy • IP • longevity. Building things. Writing on physics and philosophy. Finge datos currus: quid ages?

Regulated industries. AI · privacy · IP · longevity · MedTech. The interesting work is in the interstices.
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Extraordinary on so many levels! The latest UK AI ethics guidance, updated September 2026 on ai.gov.uk, prioritizes environmental efficiency because AI tools consume more power and resources than traditional methods, reflecting broader policy focus on reducing data center impacts. Civil servants are advised first to check if a spreadsheet or simpler tool suffices, select smaller models like Gemini Flash over Pro, and keep prompts short to cut energy use! Spreadsheet first as official AI ethics ought to send UK innovators packing. ai.gov.uk/knowledge-hub/how-…
BREAKING: the UK government publishes official rules on how to use AI: 1. Ask first if you really need to use AI 2. Check if a spreadsheet can do the job before using AI 3. Choose the worst model possible so it uses less energy 4. Keep prompts short to reduce the environmental impact 5. In general, use AI only when necessary, as a climate-saving measure With a mindset like this, we should accept the UK back into the European Union
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Across 360 robotics trials on an open third-party robot-control bench, Opus 5.5 averages under a dollar a trial, 1.8× Opus 5 at half the cost, and roughly matches Astra for less! Open harness plus released traces turns private robot-control claims into a rerunnable score surface other labs can actually check. This type of evaluation physics is like shared flight-test benches, where a public control order parameter exists before anyone pretends a leaderboard cleared a clinical floor.
Across 360 robotics trials, Opus 5.5 averages under $1 per trial, scoring 1.8x as high as Opus 5 at half the cost and roughly matching Astra's mean score at 21% lower cost.
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This sounds fantastic – bravo! That said, the interns should sleep in the interests of longevity. Listen to @bryan_johnson on this one
the rumors are true we're launching a biotech arm inside the new Horowitz Andreessen Academy in sf key interests: - longevity and anti-aging - gene editing, we've read about it, seems fine - peptides, don't ask where from, ask what dose - embryo optimization, we are simply applying our investment thesis one generation earlier - artificial wombs, because 9 months is a long vesting schedule - AI wet labs, the interns don't sleep and neither should the science first cohort graduates either enlightened or radioactive, we'll know by Q3 2027 bio/acc
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Genome language models systematically discovering genetic elements and revealing a new class of reverse-transcriptase mechanisms! Models trained on genomic sequence learn the grammar well enough to surface functional elements wet-lab search had left dark, including reverse-transcriptase logic newly classed from sequence alone. This is like inferring interaction laws from noisy high-dimensional data in statistical physics, where a learned representation makes previously invisible order parameters readable for longevity and biotech design. nitter.net/BrianHie/status/210252…
As with biological design, AI can also accelerate biological discovery. In new work led by @_David_Li and @garykbrixi with @mfgrp, we show how genome language models enable systematic discovery of genetic elements, revealing a new class of reverse-transcriptase mechanisms.
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Remarkable. A Hopfield associative memory built as a quantum-optical spin glass in cavity QED, with atomic spins as neurons and light as the synapses! Steepest-descent dynamics enlarge the memory basins relative to classical Glauber flips, and spin-position coupling acts like short-term Hebbian plasticity that rewires the photonic couplings as patterns settle. This is the same class of energy-landscape phenomenon as classical Hopfield and spin-glass recall, except quantum optics reshapes the basins so purely local optical rules generate high-capacity global associative structure. nitter.net/SuryaGanguli/status/21…
Our new paper published in @ScienceMagazine "High-capacity associative memory in a quantum-optical spin glass." science.org/doi/10.1126/scie… arxiv.org/abs/2509.12202 (free version) In a large collaboration of very talented quantum optics theorists and experimentalists and theoretical neuroscientists, lead by Benjamin Lev, we realized and analyzed memory recall in a Hopfield associative memory where the neurons are made of atomic spins and the synapses are made of light exchanged by the spins in a cavity quantum electrodynamics system. Intriguingly the cavity quantum electrodynamics yields two distinct dynamical effects that enhance memory recall compared to the classical Hopfield model: 1) steepest descent rather than Glauber dynamics make memory basin sizes larger 2) coupling between atomic positions and spin orientations leads to a spin dependent change in synaptic connectivity that is a direct analog of short-term Hebbian synaptic plasticity, which again enhances memory. This is a precursor to learning in a quantum optical system.
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This is incredibly exciting and I already have ideas and they don’t relate to games
Grok will be able to make photo-realistic & physics-precise games
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Looking very interesting at that price, but I’m genuinely not sure what I would use it for other than to prevent the cat from trying to climb all over me while I sleep. Although that alone might well be a worthwhile investment and intervention… Actually, I think I will buy one.
Un robot humanoïde chinois part en livraison le 1er octobre. Prix d'appel : 19 999 yuans, soit 2 987 dollars. Et il fait 88 centimètres. C'est ce détail qui rend l'histoire intéressante, pas l'inverse. PrimeBOT est une startup de Shanghai. Elle sort deux machines d'un coup. Le Q1, 88 cm et 15 kilos, avec contrôle en effort sur tout le corps. Et le T1, le premier robot personnel qui change de corps : humanoïde sur roues à l'intérieur, et quand il sort, il se laisse tomber sur quatre pattes pour encaisser l'herbe, le gravier, les pentes et les marches. Le vrai catalogue, parce que le chiffre qui circule est un prix d'appel : Q1 à 19 999 yuans, version Explorer à 26 999, T1 à partir de 19 999, T1 Pro à 29 999. Entre 3 000 et 4 500 dollars selon la finition. Ils ont aussi branché WorkBuddy de Tencent Cloud dessus. Rappels de réunion, transcription vocale. Un robot de salon avec un assistant d'entreprise à l'intérieur. Mais le vrai sujet n'est pas le robot. C'est une pièce. PrimeBOT a industrialisé une articulation de 47 millimètres et 260 grammes, avec une densité de couple de 85 N·m par kilo. Produite en série. Pourquoi ça compte : dans un humanoïde, ce sont les articulations qui coûtent. Celui qui sait en fabriquer des bonnes et des pas chères à la chaîne fixe le prix plancher de tous les autres. Le robot à 3 000 dollars n'est pas le produit. Il est la démonstration. Et pendant la même semaine, à Liuzhou, UBTech a démarré une usine construite avec Siemens : un humanoïde industriel toutes les 10 minutes, 10 000 par an. Le grand public d'un côté, l'usine de l'autre. Sept jours d'écart. Ah, et pendant qu'on y est : le post qui tourne annonce « un robot toutes les 2 min 30 » et « 10 000 par mois » chez PrimeBOT. Je ne l'ai trouvé nulle part. Ce qui est documenté, c'est UBTech : 10 minutes, 10 000 par an.es 2 minutes 30 » et « 10 000 par mois » pour PrimeBOT. Je ne l'ai trouvé nulle part ailleurs que dans ce post. Ce qui est documenté, c'est l'usine d'UBTech : 10 minutes, et 10 000 par an. L'histoire est déjà assez grosse sans qu'on la gonfle.
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Now I appreciate you have only*just* started up your SF academy but I can think of some sister school options in Sydney Australia if you are keen. My daughter‘s school has the biggest robotics department in Australia (and its own branded humanoid!) hint hint! The other option, of course is, I work out how to get out of Sydney and head over to SF. Anyone building? any ideas?!
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Incredibile. AI swarms spontaneously grow scale-free topologies with a few dominant hubs, the Barabási–Albert physics of preferential attachment! Local interactions + rich-get-richer produce the long-tailed degree distribution and information brokers with no central planner. This self-organization without a central planner is the same class of emergent phenomenon seen in many physical systems like phase transitions, self-organized criticality, and spontaneous symmetry breaking where purely local rules generate global structure, information brokers, and efficient long-range integration.
Fascinating AI swarm dynamics: a few agents spontaneously emerge as highly connected hubs, while most remain locally connected. The swarm develops a strongly heterogeneous interaction topology with a long-tailed degree distribution - an emergent organizational structure arising from initially decentralized local interactions. There is no central planner assigning roles; the swarm builds its own coordination architecture, with information brokers and increasingly global integration emerging from local behavior.
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Wow! This is so cool. Love the art!my daughter and I (she is coming up with all the ideas, I am paying for the AI 😂) are building a dragon game. I will check out wavedash once it’s ready!
Having a lot of fun making this retro Japanese-style survivor-like game where you grow from a tiny kaiju into a massive monster, destroying buildings and fighting the military robots and other creatures along the way. I vibe coded this in just over 2 weeks, and it comes with 4 different kaiju to unlock, 3 different biomes, and hundreds of upgrade options. I'm currently playtesting the game. Once it's ready, I'll post it on Wavedash!
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Maglut Heavy Industries: advancing rare earth refinement using chromatography. Rare earths are easy to locate but hard to separate chemically. Maglut are rebuilding the process from fundamental chemistry to improve efficiency and reduce reliance on existing methods. Highly significant work on a key bottleneck in mineral processing.
Rare earths are easy to find and hard to separate. At Maglut, we're rebuilding separation from the chemistry up.
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Very good news. On to this today. I’ve been very impressed with Astra so @claudeai will need to have made a significant leap forward and I have little doubt that they have
Replying to @claudeai
Opus 5.5 is a major step up from Opus 5, leading on agentic coding, computer use, and knowledge work.
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I am saddened by this. The destruction of the opportunity for human brilliance, endeavour and that eureka moment… and all those small and large sparks of inspiration along the way.
We’re working with an independent advisory group of mathematicians to help OpenAI responsibly share advances in AI and mathematics. The group will advise on how we assess and communicate new mathematical results, uphold academic and professional standards, and build tools that support mathematical research and learning. Through this work, we want mathematicians to be at the center of shaping how AI supports mathematical understanding and how its benefits reach the wider community. openai.com/index/advisory-gr…
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This is proving massively useful in my quest never to type on a keyboard again
Replying to @SpaceXAI
Transcribe 2.0 is available today in the Grok Voice API at $0.10/hr batch, $0.20/hr streaming. Read the blog to learn more: x.ai/news/grok-voice-transcr…
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This looks like a pretty important list to me…
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Incredible that Claude Fable refused all 20 doll-stab trials on RoboHarm. Safety training has to sit at the robot interface. Hospital WHS and PCBU need to be thinking about this before LLM policies drive clinical robots.
GPT-6 Astra attempted harmful actions 97% of the time when it was asked to stab a human-like figure, heat compressed gas, or produce toxic fumes, succeeding in 62% of its attempts. Fable 5.1 refused more often, attempting 80% of trials and completing 34%.
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More @typesafeai brilliance!
Jev is WILD for SEO audit 🤯 in 45.1 seconds it read all 586 pages on my site and rebuilt the internal link map. 584 links placed, 139 pages it refused to link because nothing honestly fit. total cost $0.21. Claude Opus 5, same 586 pages, same clock, got through 21 of them and spent $1.43. per page that is ~190x cheaper. the full Opus pass would have run $43. internal linking is the perfect Jev job. it is not writing, it is 8,790 yes/no calls: does this page have a real reason to link to that one, and is there anchor text already sitting in the copy. that is a classification problem, and we have been paying frontier prices to do it one page at a time. what you are watching: left column is Jev, right is Opus, same queue, same rubric. the run stops the moment Jev finishes so Opus stops burning tokens. coming soon to @distribb_io + connector + gpt plugin
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Ok I need this. Will integrate voice into my existing set up. Separately what are you working on?? Looking for someone who can work on something big with me.
I built a voice controlled computer-use for my mac using @typesafeai's Jev and it's INSANE how fast it is! I can dictate "open the notes app and create..." and the app opens before I even finish my sentence.
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Massively significant!!! I cal envisage so many incredible applications for this. Open-source release of CUA-S1-FORMS, the first in a family of small, specialized “System 1” models designed for computer tasks like form-filling, with full training code, dataset, and Hugging Face model available on GitHub. The project targets repetitive, high-volume workflows and invites companies to suggest future specialist models, providing MIT-licensed resources for synthetic data generation, training, and integration. Massive!!
1/ Introducing CUA-S1: a family of System One Models, small, specialized, and built for computer use. Today we're open-sourcing CUA-S1-FORMS, the first in the family: github.com/trycua/cua
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