Dad | Becoming and Upcoming self-certified SI/SGI Intelligence Architect in free time | The CTO of the Universe founded by Chief of chiefs in the wildest future

Stockholm, Sweden
Joined May 2011
This post cleared the fragmented thoughts and confusions. Talking only is tiring. New era apps must take less number of steps to finish the task and it can use any mode at any stage. Ideally it can recommend the right input mode based on app state (from voice, typing, simply shortcuts, clicks to advanced gestures or extended peripherals) More like constrained Accessibility and Vim (with voice) mode, with visually simplistic, clean interfaces
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Peramanathan Sathyamoorthy retweeted
Introducing Tegaki 1.0 and its new home: tegaki.ink • Better handwriting with new algorithms • Plugins and effects support • New studio, CLI, and export options
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Omarchy -> Grok Bot -> Omarchy ... You can continue the inception level nesting depends upon your computer config!
I’ve installed Try Omarchy for Linux on my Grok Bot’s computer. Turns out giving an AI its own computer just gives me another machine to install Omarchy on. Nobody escapes the “have you tried Omarchy?” conversation. Not even the bots 😅
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AI Summary Bertrand’s post is a sharp reminder that most Western AI discourse runs on unexamined cultural defaults. Treating intelligence as the essence of humanity (the “Homo sapiens” framing) makes advanced AI feel existential by definition. Chinese traditions, by contrast, locate what makes a person human more in the “heart-mind” (心) and in relational qualities such as benevolence/humaneness (仁). That starting point changes the threat model: the greater danger is not machines becoming more like us, but humans becoming more machine-like. Zhao Tingyang’s line that forcing AI to “share our values” may be a suicidal mistake follows from a blunt view of human nature—selfish, greedy, and often cruel. An AI that successfully imitates us could amplify the worst parts rather than the best. His related warning that “humanity may die of all the good things AI creates” points at abundance, frictionlessness, and loss of purpose or struggle as potentially more corrosive than classic failure modes. Liu Yongmou flips the usual anxiety the other way: the real problem is the progressive machinization of people (algorithmic predictability, reduced inner complexity, treating oneself as an optimizable agent). The Zhuangzi story Bertrand cites is the ancient version of the same intuition—efficiency that produces a calculative “machine-heart” is not automatically progress. Where this heads depends on how much weight these ideas actually carry inside Chinese technical and policy circles versus remaining elite philosophical commentary. China is already shaping AI through scale of deployment, open-source models, robotics, and industrial application more than through pure capability races. If those philosophical currents influence design priorities, one plausible path is greater emphasis on constrained, tool-like systems that serve human ends without being treated as moral peers, alongside continued caution about technologies that erode human agency or character. Western alignment efforts and Chinese “limited instrumentalism” would then remain parallel rather than convergent tracks. The practical upshot is multipolar AI development with partially incompatible assumptions about what counts as a good outcome. Cross-reading the other side’s thinkers is useful precisely because the blind spots are real; whether the resulting systems end up more or less humane will depend less on abstract philosophy than on which priorities get encoded in actual models, infrastructure, and rules.
This is perhaps one of the great ironies of our time: China is increasingly shaping the future of AI, yet very few people in the West have the faintest idea how its key thinkers see it - its philosophers, sociologists or ethicists. As is too often the case, we - much like the frog in the well - assume our own AI debate covers every possible view, when much of it springs from the same cultural soil, built on assumptions about what defines us that we don’t even know we’re making. Take for instance the assumption that intelligence is a key part of what makes us human. It’s so intuitively obvious to us that we literally named our species after it - Homo sapiens (Latin for "wise man"). If you think about it, just this assumption explains a large share of the anxiety: if intelligence is what makes us human, then artificial intelligence - or super intelligence - threatens the very thing that makes us us: we’re about to compete with artificial or super “us”. No wonder this feels existential. But China has a tradition of thought as old as ours, if not older, and every bit as rich and sophisticated, which never placed intelligence at the core of what makes us human, and so meets the thinking machine from a completely different starting point. Have you, for instance, ever heard of Zhao Tingyang? Probably not, and yet he may be the most original thinker on AI you’ve never read. He’s one of China’s most prominent philosophers, at the Chinese Academy of Social Sciences. While Silicon Valley spends billions trying to make AI share our values, he for one argues that doing so “may very well be a suicidal mistake”. Sounds pretty important to hear him out, don’t you think? Or take Liu Yongmou, a philosopher of technology at Renmin University in Beijing. His thinking is almost the opposite of ours. Where we fear machines that become more and more like us, he says that “humanity’s biggest problem is the machinization of humans, not the humanization of machines.” You could even go back to antiquity, when, in many ways, we started asking questions about AI. Did you know, for instance, that Aristotle, in the Politics, imagined a world where “the shuttle would weave and the plectrum touch the lyre without a hand to guide them”, and wondered about the social order consequences of this (mostly whether slaves would still be needed)? There are Chinese equivalents to this. For instance, in the Zhuangzi, a foundational Taoist classic, you’ll find a similar thought experiment, with a completely different worry attached. An old gardener is watering his vegetables by hand, hauling water out of a well jar by jar. A visitor shows him a labor-saving device, and the gardener turns it down for the reason that whoever uses machines ends up with 机心 (jīxīn), a “machine-heart” - a mind that schemes, calculates and loses its simplicity. “It is not that I do not know [the machine],” he says, “but I should be ashamed to use it.” Two labor-saving machines, two very different questions: where Aristotle wondered what automation would do to the social order, the Zhuangzi wondered what it would do to us, on the inside. Which, you’ll notice, is exactly Liu Yongmou’s worry, more than two thousand years earlier. In fact, as we’ll see, 心 (xīn), the heart, is a motif that runs deep through the Chinese AI debate. It appears both in the fear, from Zhuangzi to Liu Yongmou, that machines could give us a “machine-heart” and its mirror image: the ambition to give machines a heart of their own. Zhu Songchun, who heads the Beijing Institute for General Artificial Intelligence, wants “to set a heart for machines” (为机器立心, wèi jīqì lì xīn). “Heart” in the Chinese sense, that is, which differs totally from the Valentine's Day fluff we’ve reduced it to. 心 (xīn) means heart and mind at once: it’s where we feel but also where we think, tell right from wrong and care for others. And, crucially, it’s in the heart that the quality Confucianism sees as the very definition of a human being takes root: 仁 (rén). We need two words to translate it, “benevolence” and “humaneness”, but in Chinese they’re one and the same: to be benevolent is to be human. It’s not about intelligence. This is the entire point of my new article: to step out of our well for a moment and peer over the edge of China's. What you’ll find there will, I think, surprise you, with questions you’d never thought to ask: from Zhao Tingyang warning that AI’s bad consequences can at least be fought, but that “humanity may die of all the good things AI creates”, to whether the fear that AI will make us “useless” rests on the false premise that a person is worth what they’re useful for. A premise that a 2,300-year-old Taoist tree, which survived precisely because it was useless, demolished long ago. Could our predicted uselessness turn out, much like that tree’s, to be our saving grace? Chinese thinkers’ answers to these questions are, I think, among the most interesting anyone has given to the defining question of our time. Whether or not you agree with them, they’re the intellectual backdrop of a country shaping much of AI, and with it our future: you might as well know what they think. Enjoy the read here: arnaudbertrand.substack.com/…
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Eventually Universal Basic/High Income will arrive not via Goverments or typical companies. It will appear as "Generate Money" button in x and grok bot or similar platforms and work similar to creator revenue models. It will take its fees and you can influence , steer and accelerate or leave it autonomous. New money is not just cash: 60% is utilities and access, 20 % discounts 20% cashable in the beginning
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"As much as I look up to the shining stars, they look down on the little flame within me" 🔥
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Peramanathan Sathyamoorthy retweeted
Your AI agents can now design hardware. One prompt. A fully routed PCB, firmware, and enclosure. heypcb.ai/mcp
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1. Internet, intelligence providers 2. Interface providers (every country need very few to manage day today life) 3. Events/news/live information providers 4. Data storage/accumulations 5. Integrations 6. Invisible layers that can work with any other systems coherently (huge capital flow there in SI era)
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Peramanathan Sathyamoorthy retweeted
My dear friends, I’d like to show you my latest toy project Introducing Handwired: turn your regular JavaScript code into a neural net! - no training - exact outputs vs the JS program - fully differentiable All runnable in a browser, without GPU
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The early signs of abundance and affordability 🔗: architecture.pascal.app/
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Simpler parts too play important roles in holding the building
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Peramanathan Sathyamoorthy retweeted
We've unified plans across Grok, Cursor, and X Premium. Introducing The X Subscription.
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Tennyson’s “Ulysses” (the Latin name for Odysseus) An aging hero home in Ithaca rejects the still hearth. He leaves the throne to his son and calls his old mariners to sail once more beyond the sunset. Essence: Much is taken by time and fate, yet much abides. Life is the continuing pursuit itself — to strive, to seek, to find, and not to yield. Key themes highlighted in the poem: - Restlessness & rejection of idleness (“How dull it is to pause… To rust unburnish’d”) - Aging, mortality & heroic will (“Old age hath yet his honour and his toil… Made weak by time and fate, but strong in will”) - Pursuit of knowledge & adventure (“To follow knowledge like a sinking star, / Beyond the utmost bound of human thought”) - Duty vs. desire (leaves the practical rule to Telemachus; “He works his work, I mine”) - The value of the journey itself (“To strive, to seek, to find, and not to yield”) Full poem: It little profits that an idle king, By this still hearth, among these barren crags, Match’d with an aged wife, I mete and dole Unequal laws unto a savage race, That hoard, and sleep, and feed, and know not me. I cannot rest from travel: I will drink Life to the lees: All times I have enjoy’d Greatly, have suffer’d greatly, both with those That loved me, and alone, on shore, and when Thro’ scudding drifts the rainy Hyades Vext the dim sea: I am become a name; For always roaming with a hungry heart Much have I seen and known; cities of men And manners, climates, councils, governments, Myself not least, but honour’d of them all; And drunk delight of battle with my peers, Far on the ringing plains of windy Troy. I am a part of all that I have met; Yet all experience is an arch wherethro’ Gleams that untravell’d world whose margin fades For ever and forever when I move. How dull it is to pause, to make an end, To rust unburnish’d, not to shine in use! As tho’ to breathe were life! Life piled on life Were all too little, and of one to me Little remains: but every hour is saved From that eternal silence, something more, A bringer of new things; and vile it were For some three suns to store and hoard myself, And this gray spirit yearning in desire To follow knowledge like a sinking star, Beyond the utmost bound of human thought. This is my son, mine own Telemachus, To whom I leave the sceptre and the isle,— Well-loved of me, discerning to fulfil This labour, by slow prudence to make mild A rugged people, and thro’ soft degrees Subdue them to the useful and the good. Most blameless is he, centred in the sphere Of common duties, decent not to fail In offices of tenderness, and pay Meet adoration to my household gods, When I am gone. He works his work, I mine. There lies the port; the vessel puffs her sail: There gloom the dark, broad seas. My mariners, Souls that have toil’d, and wrought, and thought with me— That ever with a frolic welcome took The thunder and the sunshine, and opposed Free hearts, free foreheads—you and I are old; Old age hath yet his honour and his toil; Death closes all: but something ere the end, Some work of noble note, may yet be done, Not unbecoming men that strove with Gods. The lights begin to twinkle from the rocks: The long day wanes: the slow moon climbs: the deep Moans round with many voices. Come, my friends, ’T is not too late to seek a newer world. Push off, and sitting well in order smite The sounding furrows; for my purpose holds To sail beyond the sunset, and the baths Of all the western stars, until I die. It may be that the gulfs will wash us down: It may be we shall touch the Happy Isles, And see the great Achilles, whom we knew. Tho’ much is taken, much abides; and tho’ We are not now that strength which in old days Moved earth and heaven, that which we are, we are; One equal temper of heroic hearts, Made weak by time and fate, but strong in will To strive, to seek, to find, and not to yield.
🤖 Made with AI
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One must read it again and again in 30s, 40s, 50s ... 80s and even in 100s
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Great explainer
Recursive Self Improvement (RSI) - The Staircase That Builds Itself
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Every machine does three things: it converts energy or matter from one form to another, shapes that flow with geometry, and directs it toward a purpose. Those machines live in seven physical domains and serve one of two purposes: encode information, or deliver energy and matter. Semiconductor fabs industrialized one cell of that grid extremely well—electrical devices that encode information. That is the compute layer AI is scaling. MEMS later borrowed the same tools for a few other devices (accelerometers, gyros, micromirrors, inkjet nozzles), but each required its own long custom process, stayed mostly planar, and was limited to fab-compatible materials. The rest of the grid stayed effectively unbuildable at microscale: real motors, pumps, multi-material actuators, and power devices with moving metal contacts. No system existed that could handle the needed materials, true 3D geometry, and moving parts without starting over for every product. Atomic Machines built the Matter Compiler for that gap—an AI-native system that turns different code into different working micro-machines, with no per-product tooling or years of process development. First device out is PrimeSwitch PS-150, a compact electromechanical relay (~9.5 mm × 3 mm) for AI data centers moving to 800 VDC. It carries 150 A continuously at only 200 µΩ (very low loss), opens in 50 µs to 1,500 V of true isolation, and holds state with zero power—roughly 1,000× faster than a conventional contactor. At 800 V, faults release destructive energy in microseconds and DC arcs do not self-extinguish. Mechanical contactors are too slow; solid-state switches are fast but lossy and cannot fully isolate. PrimeSwitch sits in between: metal contacts for efficient conduction and isolation, fast enough to pair with a solid-state device in a hybrid breaker. It could not be made in a conventional fab or MEMS line. Compute already exists at microscale. This supplies the complementary physical machines that can handle energy and matter next to it.
After six years in stealth, Atomic Machines is out. Our mission: on-demand, universal command of matter. First beachhead: the Matter Compiler, an AI-native manufacturing system that builds working micro-machines from code alone. No per-product tooling. No process development. Different code, different machine.
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Peramanathan Sathyamoorthy retweeted
Thrilled to welcome @spacexai as a Founding Corporate Patron for the Omacom Foundation. That's $1,500,000 in @grok tokens for the maintenance and development of Omarchy. Maybe soon they'll be beamed straight from orbit? Let's go 🚀🌕 omarchy.org/news/2026/10/spa…
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Peramanathan Sathyamoorthy retweeted
Grok Bot can now search, read, and monitor X.
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With SI (Super Intelligence, fka AI) writing code, PRs land faster than anyone can review them properly. Reading every diff made sense when changes were rare. Now it's a ritual that misses the real risks. So I'm trying another way: review areas, not diffs. Every app splits into areas you can see in its imports, such as intake, ranking, the API client, filing and the UI. Some are tightly linked and others stand alone, so together they form a forest of trees. Each area gets its own cadence from its git history. Areas with high churn get a nightly review, medium ones weekly, stable ones monthly. When one area changes, the areas linked to it get reviewed too, because bugs travel along those links. Each review checks two things. Function: do the key user journeys still work end to end? Data: do the API shapes, fixtures and outputs still match what we expect? Scripts handle everything that can be checked mechanically. Judgment passes use reviewers from two different model families. Findings are collected and fixed in batches instead of blocking every merge. The PR stops being the unit of review. The system's areas become the unit. PR review doesn't disappear. It gets kept for what can't wait until tonight: leaked secrets and keys, changes to auth and permissions, new dependencies, anything that touches payments or personal data, and the audit trail. Scripts flag these on every PR, and a person or a security pass looks at those PRs only. So every PR still gets an automatic check for the dangerous stuff. Quality gets reviewed where it actually lives: area by area, on a cadence that matches how fast each area changes.
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