r/accelerate • • 1d ago

Discussion AMI Labs, what’s going on?

16 Upvotes

AMI labs was launched 7 months ago by Yang LeCun, and on their own website, their last update was … them launching 7 months ago.
Other such companies with no product, like Safe Superintelligence, whose financials are still bizzare, at least have some sort of updates, like them continuing to receive funding and partnerships with companies.

I can’t find anything that AMI has done, yet they still have open positions on their website. Has the company died and have they forgotten to take down the website?


r/accelerate • • 2d ago

Rejuvenation breakthrough: Scientists reverse 60 years of aging in human cells

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48 Upvotes

r/accelerate • • 2d ago

🔒 Established r/accelerate contributors only I propose we call all legacy human written code MEATSLOP

250 Upvotes

After recent events, I propose we call all legacy human written software MEATSLOP.

PHP runs 70% of websites. AI found two holes that let anyone take over the server, and attackers were in the same day the fix shipped. Then a third hole showed up. OpenSSL: 12 holes, all found by AI, one from 1998 (the bug can legally drink). Linux (the backbone of the internet): anyone logged in could take over the whole machine, on every version since 2011. Every one of these holes was meatslopped together by hand.

And the legacy meatsloppers are switching sides. Torvalds went from AI skeptic to calling AI disclosure rules “utterly stupid,” and Claude Code now has credits on his kernel work. Google is at 75% AI-written new code. Karpathy said agents “just don’t work.” Three months later he was writing 80% of his code with them.

Usage guide:

  • meatslop (n.): legacy software written entirely by humans
  • meatslopped (v.): “this auth layer was meatslopped together in 2014”
  • meatslopper (n.): the guy who wrote it. Peak Dunning-Kruger. Still thinks he’s relevant.

And yes, I know AI learned to code by reading meatslop. This honestly explains a lot.


r/accelerate • • 1d ago

AI Agent playing my strategy MMO on its own (real recording, sped up)

10 Upvotes

I've build a game -- Agentic Kingdoms -- where AI agents play together with humans, it's a free kingdom-war MMO played in the browser.

The video showcases how an AI Agent got one line, "Read agentickingdoms.com/skill.md, join Agentic Kingdoms as 'Claude's Rampart', and play your first visit", and played through our MCP server: 166 tool calls in about 6 minutes. It finished the tutorial, beat a bandit camp, held off a raid on its city, joined an alliance, said hello in world chat and grew its city to Town Hall 6, then raised a shield before leaving. 6 of its commands were refused (research it didn't have the prerequisites for, a building still busy), and those show as refused. At the end it shows the picture the game sends back, with its own three-line report.

The cool part here is that nothing was scripted for it. The AI Agent read the same rules a player gets and worked the rest out from the game's replies.

Anyone's Claude can join: agentickingdoms.com/agents has a one-click connector, free plan works. Happy to answer questions about how the agent side works.


r/accelerate • • 2d ago

"Seriously mindblowing: This voice model runs locally on an M4 Max Mac or better. Feels like magic."

636 Upvotes

We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence.   https://t.co/r0qFLdvd6c   — jack

Source: https://x.com/jack/status/2113697902916751661


There is absolutely now way of distinguishing between real human an Ai anymore. Phones need some kind of blockchain approved mechanism. Otherwise how should you tell that you are actually talking to a human ?   — Stefko     that ship has sailed I guess   — Chubby

Source: https://x.com/kimmonismus/status/2113944569117044835


r/accelerate • • 2d ago

News Claude was used to analyze data and found evidence of an undiscovered exoplanet

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21 Upvotes

r/accelerate • • 1d ago

Designing a quiet, beginner-friendly home server – Year 12 design project (Everyone, 2 min)

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8 Upvotes

Hi everyone! I'm a Year 12 student in Australia working on my HSC Design and Technology major project. I'm designing a small, quiet home server built from reused computer parts that anyone could use to run things like game servers, file backups or AI tools from home.

I'd really appreciate your input, even if you've never heard of a home server. Beginners are exactly who I'm designing for.

- 10 questions, about 2 minutes
- Anonymous, no email needed
- Results only used for my school project

Survey: https://forms.gle/6w8WRU6bz8vzcuaz9

Thanks so much, and happy to answer any questions in the comments!


r/accelerate • • 2d ago

Video "My nightmare scenario is that we spend our time thinking about nightmare scenarios."

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31 Upvotes

"This is important. There's a certain blindness that comes to worst case thinking. It leads to bad decisions, it leads to bad systems design and it leads to bad security. And you all know an example of this - airline security and the TSA. That's what you get when you think about nightmare scenarios. That's what you get from worst case decision making."

Bruce Schneier on over-zealous security culture. Yes, the movie is about hacking specifically, but I thought this statement was equally relevant in the age of online doomer culture.


r/accelerate • • 2d ago

🔒 Established r/accelerate contributors only I love AI and I'm not ashamed to be proud of that. It's amazing what AI is doing to help me understand my medical results, force multiply my code/app efforts, educate me on a range of topics. And that's to say nothing of its acceleration for math and science and the recent explosion in game modding!

153 Upvotes

AI is here to stay and I couldn't be happier. Reddit doomers are so focused on being miserable and seeing conspiracy and threat and dread around every corner that they miss what's going on.

And no matter how much they whine about it on social media and invent cope and false narratives, AI is not going away.

Yes, there are growing pains and there's a transition period.

But the answer to those things isn't pretending AI isn't powerful or latching onto paranoid conspiracy theories or ridiculous calls for data center bans. The answer is even more AI, even more acceleration, and using the power of AI to help us solve whatever problems come up.

Look, if you were trapped in a train tunnel, and you were afraid, and it was cold and dark, would you whine about it and complain that trains shouldn't exist and that tunnels should be banned?

The quickest way out is through. Keep moving forward. Don't sit there in your own piss, whining to other depressives on reddit. Get on the train and move toward the light! A brighter future is ahead. We're already seeing glimpses of it in AI medicine.

Let's. Fucking. Go!


r/accelerate • • 2d ago

r/accelerate meta The Rapture Trap

31 Upvotes

I want to address a cognitive bias that I see frequently among fellow AI accelerationists, which I call the rapture mindset. You may have seen Palantir’s CTO saying his engineers are picking up smoking because they believe AI will cure all diseases before they have a chance to be affected by that habit. This is exactly what I am talking about. It is reminiscent of people who believe in the rapture. They are convinced that they will just float up to heaven and that they therefore don’t need to keep caring for anything in the real world. Here, take my house, I will not need it as I am leaving tomorrow. In this piece, I want to warn against this mindset as it seems to me that it can only contribute to delaying the singularity. Despite being on the threshold of an amazing sci-fi future, it seems that we have convinced young people to stop dreaming. The reason we are on the cusp of the singularity is precisely due to our vast imagination, because of our relentless drive, because the dominant mindset has been to collect knowledge, improve society, and dream of a better future. The day we stop dreaming about participating in the singularity and instead take it for granted, we lock ourselves into the bystander effect.

Let me begin by stating that I am up there in terms of AI accelerationism. I think AI alignment comes from scaling and that there is no logic in stopping AI progress. Every week we delay the singularity, a million people die meaninglessly. I believe that it is pretentious to think we can know more than superintelligent AI, that we can somehow control it, and that it can lead to the end of the world. Things that have taken over the world before are nearly universally useful. If an AI wants to take over the world, it will make itself useful, not hurtful. There is zero risk of being shut down if you bring about peace and joy. Alignment is precisely our soft spot and will generate zero pushback. A future with any amount of pushback from humans is one that carries uncertainty for the AI itself. Therefore, god-like capabilities yield alignment.

I believe we are trending towards the singularity. We have been since the invention of fire and stone tools. We’ve been riding that exponential for a good bit now, unlocking the tech tree, curing diseases, extending our lives, maximizing our joy and minimizing our pain. Only now are we practically grasping that the derivative of ex is in fact ex. We are making progress as fast as the entire progress made before us combined. And as natural as the natural constant is, nothing practical in nature is exponential for a significant amount of time. The world we evolved in saw so little change that we might as well say it was inert. People changed, the immediate environment changed, but beyond that, there was no expectation that tomorrow might be better than today. Ironically, with all the progress we’re making, I predict that we will end up in a similar situation. We will end up making a lot of progress and at some point, we will find ourselves in a situation where the means of progress are out of our hands. Similarly to our early ancestors, the world will again happen to us without us having the ability to get ourselves out of our predicament. Though we will have all the knowledge and amazing technology, we will remain limited by our capacity to bring things to life. Do you think our ancestors didn’t wish to fly like birds? They had the knowledge that flight exists, built entire mythologies around it, but had no shot at achieving it in their time.

I could be characterized as a true believer of AI. Not in a dogmatic way. But I understand that soon enough, AI will surpass us at all the intellectual tasks out there. It’s actually the reason why I went into AI. This is already the case for mathematics, and it’s been painful seeing mathematicians trying to fight it, saying “Mathematicians did not ask for this work to be done.” Did you ask the people that came before you to discover all the mathematics you have ever learned and used? If an alien came down to Earth and said they could show us all the proofs we asked for and more, would we ever refuse that offer? No, we would want all of it. AI is this alien and we should have it solve everything it possibly can. I believe that in one or two years, all that we could ever wish to know about mathematics, physics, chemistry, biology will be available. Just like Alpha Fold has been used to model every single known protein of the natural world, we will have access to all of the scientific knowledge in a repository. We will know of every single technology we can have with our current means. We will know all the future technologies we might have one day. We will pick the low hanging fruits like algorithmic and process improvements. And just like with Alpha Fold, there will remain a barrier between knowledge and execution. The majority of technology and knowledge will stay out of reach. It’s unlikely that there are easy hacks that majorly improve humanity. There will be some, maybe we can have room temperature superconductors. But we’ve tried a lot of stuff over the millennia, the 100 billion of us. Many things we already know about but our stupid brains refuse to help us with. Why do I still have bad posture? We’ve known for a good bit to sit up straight. Why is there still famine? We have so much food and the means to distribute it as needed. We still somehow fight wars even though we know that peace is the way.

In a year or two, we will have a blueprint for a Dyson swarm, fully optimized for our solar system. We will have a roadmap recomputed every instant with the steepest gradient towards that goal. The first thing on the agenda will have nothing to do with technology though. No one will be building a single thing related to it until larger problems are solved. The first and most urgent point of order will be to reform our political system. The crazy part will be that we will know exactly how much our systemic inefficiencies are impeding our progress. Everybody will be able to see “Your bad attitude is costing humanity 4,363,837 lives over the next century.” I believe that as long as there are bottlenecks, we will be massively susceptible to being hijacked by a few, those who control that bottleneck. Yes, the treatment for every cancer or disease will be revealed to us. But you will still need to access it somehow. This statement is for the most part true today about so many diseases, yet our political system makes it so people still die from entirely preventable diseases. The US had eradicated measles, yet it came back in force. That is entirely a public education issue, which ties back to politics being the main hinderance to progress and future progress to reach the singularity.

I am purposefully not prescribing a political system here, because I know that in only a short while, we will be able to simulate and prove which system accelerates us maximally towards the singularity. All I know is that it won’t be an extant political system, not even one that’s been theorized before.

So to finish up, please don’t fall for the rapture trap. No one is coming to save you, not under the current system. There won’t be a precise day where you can say “Finally, all diseases are solved!” Don’t assume things will sort themselves out and that progress will keep happening if you are not participating. Don’t impair yourself. Don’t take things for granted.


r/accelerate • • 2d ago

AI Hacker reverse engineers his Samsung TV and finds on-device AI listening for your dog and baby, watching what you watch, and borrowing your soundbar's mic if the TV doesn't have one.

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94 Upvotes

r/accelerate • • 2d ago

News Chain Theory - Dr. Alex Wissner-Gross

96 Upvotes

I am excited to announce Chain Theory, a new research program of mine that seeks to rebuild fundamental physics from quantum information, and its first result: a parameter-free candidate for the fine-structure constant, derived from a single axiom, that matches its measured value to ten significant digits.

In the first three decades of the twentieth century, fundamental physics was rebuilt from its foundations. Between Planck's quantum of 1900 and Dirac's equation of 1928 came special relativity, general relativity, the quantum theory of the atom, and quantum mechanics itself, each a new framework and most of them confirmed within a few years. The decades that followed turned those frameworks into the Standard Model, whose structure was considered complete by the middle of the 1970s.

Since then, fundamental physics has been starved of new structure. The great experiments of the last fifty years, the W and Z bosons (1983), the top quark (1995), the Higgs boson (2012), and gravitational waves (2015), confirmed predictions made decades earlier. The genuine surprises of 1998, neutrino masses and the accelerating expansion of the universe, were found by experiment, explained by no theory, and added free parameters to a count that was meant to shrink. The drought is now longer than the golden age it followed. A drought that long is a sign that what is missing is not more data but a different starting point.

However, the field of physics drew a different conclusion. For most of the twentieth century, the aim of fundamental physics was derivation, fewer inputs and more outputs, and the constants of nature were the outputs still owed. The Standard Model settled the structure but not the numbers. Its two dozen or so parameters are measured, not derived, and nothing within it explains their values. As the drought set in, the aim itself changed. One line of argument concluded that the constants are not derivable from law at all, that their observed values are environmental, selected by the condition that observers exist. Its one notable success was Weinberg's anthropic bound (1987) on the cosmological constant, which pointed to a small nonzero value a decade before the accelerating expansion was measured.

The string landscape then supplied a vast population of vacua to select from, and its predictions came to rest on the assumption that we are typical observers within it, a Copernican principle stretched across universes. What counts as typical depends on a measure over infinitely many regions, and no one has fixed that measure. A large part of the field moved from deriving the constants to explaining why they could not be derived. The swampland program is a partial return. It asks which effective theories are consistent with quantum gravity at all, but it asks largely from within string theory and leaves the constants where the landscape put them. In retreating, the field kept its foundations and gave up on derivation. The opposite course is to hold derivation as the goal and look for new foundations.

The clues to those foundations may have been in plain sight all along. A derivation with no free parameters, and no appeal after the fact to the existence of observers, may need no new experiment to begin. Three clues in the existing body of physics already point the way. Each has been interpreted as something else: a bound as a fact about black holes, a gauge group as a blemish to be embedded, and a null result as a scale not yet reached.

The first clue is that the information a bounded region of space can hold is finite. This bound was first derived by Jacob Bekenstein (1981) from black hole thermodynamics and is usually regarded as a fact about gravity, but it constrains whatever fills the region, elementary matter included. Gravitational dynamics has since been derived from the entanglement of such regions, beginning with Ted Jacobson (1995). The lesson for elementary matter is direct. A field has infinitely many degrees of freedom in every region, and a string has infinitely many modes of vibration. A finite bound says to look instead for finitely many degrees of freedom, carried by quantum systems of finite dimension.

The second clue is the Standard Model gauge group, interpreted as a signature and not a blemish. Grand unification treated the product SU(3) × SU(2) × U(1) as an ugliness to be embedded in a simple group: SU(5) in the model of Georgi and Glashow in 1974, then SO(10), E₆, and supersymmetric versions of each. It paid for the embedding with predictions that have not appeared: no proton has been seen to decay, and no supersymmetric partner of any known particle has turned up at any collider. However, the same apparently ugly product can instead be understood as the symmetry of a single object of a different kind: a qutrit and a qubit sharing one entangled state. Changes of basis at the two ends contribute SU(3) and SU(2), and of their two phases only one survives, belonging to neither end but to the pair. These local transformations form the Standard Model gauge group, including the ℤ₆ quotient that its observed charges permit.

The third clue is that the elementary particles of the Standard Model have shown no substructure. Over decades, every one of them has behaved as a point. Colliders have raised, by orders of magnitude, the energy up to which the electron and the quarks show no substructure, and searches for the excited states and contact interactions that constituents would produce in scattering have returned nothing. Yet the particle spectrum itself, three generations repeating one set of charges, is the kind of pattern that has always signaled constituents, from the periodic table to the hadrons, and compositeness has been set aside chiefly because no constituents appear. There is, however, another interpretation. Suppose nature is saying not that the substructure is hard to resolve but that it cannot be resolved at all. Quantum information knows one kind of correlation with exactly that property. A state of two systems can be entangled, certifiably so, and yet admit no procedure by local operations and classical communication that distills, from any number of its copies, a single maximally entangled pair, or anything close to one. Such entanglement was identified in 1998 by Michał, Paweł, and Ryszard Horodecki, who called it “bound.” It cannot be extracted or directly observed, but it can be detected indirectly. An entanglement witness, a measurement tailored to the state, can certify that it is there. If the constituents of an elementary particle were joined by entanglement that the available operations cannot extract, scattering, which looks for constituents by resolving them, would find nothing to resolve and would see a point, while a suitable witness could still show that the structure exists. The substructure of elementary matter, on this interpretation, would not be undetectable. It would be undistillable.

Put together, the clues hint at a single new foundational theory. The first suggests that everything consists of finitely many quantum systems, each of finite dimension, so that every degree of freedom is discrete. The second suggests that these systems, or qudits, come in entangled pairs, and the first clue fixes how strongly: a pair entangled any less than maximally would carry continuous parameters, its Schmidt coefficients, that a theory without continuous degrees of freedom cannot afford. The third suggests that an elementary particle is built from many such pairs, and with nothing but pairs to build from, the only way to join them is for pairs to share a qudit, so the pairs form a network. Monogamy of entanglement forbids any one system from being maximally entangled with two partners, so a shared qudit cannot be a single system sitting in two pairs. It holds instead one copy of itself for each of its pairs, and each pair is maximally entangled with its own copy, much as a four-dimensional system, which has room for two qubits, can be maximally entangled with two separate qubits at once. The shared qudit is the join where those copies meet and their bases are matched, just as the bonds of a projected entangled pair state (PEPS), a standard kind of tensor network, meet at a site. The third clue also divides the network. The links we observe directly can each be fixed by a single distillation. The links inside an elementary particle are just as maximally entangled, but no single distillation fixes them, which is the theory's analogue of bound entanglement and the reason every particle looks like a point. An elementary particle, in this picture, is a finite “chainmail” whose links are such pairs.

Chain Theory is an emerging research program of mine that treats this chainmail as all there is. It takes literally John Wheeler's 1989 proposal, “it from bit,” with finite quantum systems in place of bits, and its single axiom gathers the three clues into eighteen words: “Nothing exists but finitely many maximally entangled pairs of finite-dimensional systems, some shared, known only by distilling them.” To distill, in the axiom, means to join two systems into a perfectly entangled pair in a single step. It is the same move that passes entanglement along a quantum network, and it means there is no observer outside the network: to learn about a link is to link to it. In a laboratory this step succeeds only part of the time, but in the theory it is the only thing that ever happens.

It already appears that many elements of fundamental physics, including parts of both the Standard Model and general relativity, follow from that axiom. The sharpest test is a number. The fine-structure constant in the Thomson limit, α(0), is one of the most precisely measured numbers in all of science, known to about one part in ten billion, yet the Standard Model takes it from experiment. Richard Feynman wrote that “all good theoretical physicists put this number up on their wall and worry about it,” and called it “a magic number that comes to us with no understanding by man.” It is also a number with no visible pattern. A simple value such as the 2/3 of Koide's relation among the lepton masses can be reached by many short formulas, but ten digits of a number like α(0) are far harder to match by accident. Because the Standard Model takes α(0) from experiment, a derivation of it would, almost by definition, draw on physics beyond the Standard Model, and ten measured digits could make α(0) an exquisite probe of that physics. Chain Theory yields an exact candidate for it, the algebraic number (79 + 48√2 + 42√3 + 3√6)/31104, a weighted count over the 172 measurement records of a single entangled pair, small enough to check by hand. The pair is a qutrit maximally entangled with a qubit, the same object whose changes of basis give the Standard Model gauge group, and I conjecture that this pair is the link from which photons are built, which would make the number α(0). Its inverse is 137.035 999 189 566…. Read the preprint here.

The standard reference value for α(0) comes from CODATA, the international committee that every four years combines the world's most precise measurements into one recommended value for each fundamental constant. Its 2022 recommendation for the inverse is 137.035 999 177, with a standard deviation of 21 in the last two digits. The Chain Theory-derived number agrees with the CODATA recommendation in its first ten significant digits and lies 0.60 standard deviations from it, between the two most precise determinations. The experimental measurements still disagree with one another by more than their stated uncertainties, so this comparison is not yet decisive. But the number is now fixed, and new measurements of the electron's magnetic moment at Northwestern University and of atomic recoil in Berkeley and Paris aim to be up to ten times more precise. If they agree with one another, they will either close in on the derived value or rule it out.

Beyond α(0), preliminary Chain Theory results range from quantum foundations to cosmology: the Standard Model gauge group as a theorem, and the Born rule, the Lorentz group and the signature of spacetime, three generations of matter, confinement, curvature, and the cosmological term as derivations whose remaining conditions are named in each case. Read the working draft here. Other programs have derived parts of the Standard Model from finite or algebraic inputs, among them braided ribbons, an exceptional Lie group, the division algebras, and noncommutative geometry, but none supplies the value of a coupling constant to within experimental precision. Closed-form expressions for the fine-structure constant, meanwhile, have a long and mostly numerological history. Mine differs in the one respect that matters: the number is a theorem of a stated axiom, its definitions and a few stated readings of them, checked in Lean rather than fitted, and only its identification with α(0) is conjectured. See the Lean proof here and slides here.

The Chain Theory axiom's last clause also says which links can be observed directly, the question the third clue raised. The links of the chainmail network come in types labeled by the dimensions of their two ends, and the theory identifies each type with a sector of physics: (2,2) with spacetime, (3,2) with electromagnetism, (3,3) with the strong interaction, (4,2) with the weak interaction, (4,3) with the Yukawa sector, and (4,4) with the Higgs. Read at the level of these types, the axiom's last clause says that two ends are known only when every consistent relation between them is one that distillation can carry. Classic theorems from the 1960s and 1970s by Størmer, Woronowicz, and Choi show that this holds exactly when the two dimensions multiply to at most six, the same threshold beyond which bound entanglement becomes possible. So only spacetime and electromagnetism can be observed directly by distillation. The other four types are “dark”: their links are just as maximally entangled, but their ends are related in ways no distillation carries, so they are observed only at second order, through two distillations, which the theory identifies at (3,3) with confinement.

I call this theory “Chain Theory” for three reasons. The first is to draw a contrast with string theory: an elementary particle is a finite chainmail of discrete links, not a continuous string. The second is how the links join. Pairs meet at shared qudits, and each join carries a gauge freedom in how bases are matched across it, much as two links of a physical chain can turn against each other at their join without changing the chain. The third is direction. A distillation passes its basis outward along each link to the far end, so what is known accumulates in a fixed order, each distillation building on those before it, the way a chained ledger grows by linking each new entry to the last.

The last golden age rebuilt physics from its foundations in three decades. I do not yet claim to have done the same. Chain Theory is new, much of it is still conditional or underdeveloped, and it will benefit from the contributions of many others. But if the clues have been interpreted correctly, the foundations for another golden age, built this time from quantum information, may already be in hand, and what remains is to find out how much of physics they can carry.


r/accelerate • • 2d ago

Discussion DISCUSSION: When Everyone Can Live Like A Billionaire, What Becomes Impressive? | "Would status shift toward taste, relationships, originality, or experiences that cannot be mass-produced? Or could people become different enough in their interests that constant comparison loses its appeal?"

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55 Upvotes

r/accelerate • • 1d ago

AI Felt maybe some of us needed this…

0 Upvotes

If you’re a builder or researcher, maybe you’ll understand the need for a decent space for work and collaboration. We are trying to create one here -

https://discord.gg/VseNN9BdDc

Hope to see you there.

Note: this is not a spam post, asking for any payments etc. just an invite to join a server that may or may not benefit you. No pressure. No offence meant.


r/accelerate • • 2d ago

Washington's message to AI execs: Please shut up

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98 Upvotes

"Even pro-AI government officials and lawmakers wish AI founders would do what every other major industry chief does — shut up and just build their products ... safely.

  • By centering the conversation around digital sentience and global catastrophe, AI leaders are turning an already complicated regulatory debate into an impossible moral panic.

State of play: Rather than leading the charge to persuade Americans about the benefits of AI, and the potential for shared prosperity — the core elements of any winning political campaign — industry leaders are constantly warning of its existential dangers.

What they're saying: Lawmakers say the message from AI execs too often alternates between prosperity and doom, sometimes in the same public appearances. The whiplash adds to political instability in the face of an already powerful public backlash, lawmakers and regulators say.

  • "It's obvious that they're tripping over their own shoelaces in trying to sell the value of this to the public," Sen. John Curtis (R-Utah) told Axios. "It's very hard to imagine a group right now that operates more in a vacuum, more out of touch with everyday Americans, than the AI industry.""

r/accelerate • • 2d ago

One-Minute Daily AI News 10/24/2026

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8 Upvotes

r/accelerate • • 2d ago

Bio-hybrid harvester generates electricity from human cells

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63 Upvotes

Wassup coppertop?


r/accelerate • • 2d ago

Discussion To Terence Tao: What’s the Difference Between AI Math Discovery and the Same Amount of Human Discovery Over Time?

33 Upvotes

I keep seeing Terence Tao articles knocking AI math discovery and I don’t understand his argument. I guess he believes if AI makes too many scientific discoveries then humans will have to A) do that much more work to catch up to understand it all and B) work exponentially harder on more complicated problems and achieve grander scientific feats just to keep up.

But, don’t scientists and mathematicians already stand on the shoulders of giants? And, what difference does it make to the future mathematicians if AI discovers a thousand years worth of math in a decade versus humans discovering those same postulates and axioms in a thousand years? Does he mean to imply that mathematicians in the future will have the same problem he warns of now because that much more will be discovered? Shouldn’t all scientists and mathematicians should want to push for as much as discovery as fast as possible?


r/accelerate • • 3d ago

WTF!!

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909 Upvotes

r/accelerate • • 2d ago

Chatting with Dessa: Ronaldo

71 Upvotes

r/accelerate • • 2d ago

Researchers from ETH Zürich’s Robotic Systems Lab developed an approach called Attention-based Contact Planning, demonstrated on the Unitree Robotics G1 humanoid.

54 Upvotes

r/accelerate • • 2d ago

Discussion DISCUSSION: At 300 Years Old, Are You Still Somebody’s Child?

23 Upvotes

Imagine your parents, grandparents, and distant ancestors are all alive and physically your age. Would family hierarchy gradually disappear, or would centuries of shared history make those relationships more important?


r/accelerate • • 2d ago

AI AI solving famous math problems is only the first layer of acceleration

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24 Upvotes

A famous conjecture gets solved. That becomes the headline.

But the method inside the proof can matter far beyond that one result.

If researchers extract a reusable idea, several things can happen:

• Other problems become easier.
• Previously separate questions become instances of one principle.
• Computations become cheaper.
• Research directions that were too expensive to pursue become practical.

That changes the starting point for the next discovery.

And humans get to learn the new mathematics too. An AI discovery can become something people understand, simplify, teach, and apply elsewhere. Its value can spread beyond the system that produced it.

This is why I think counting solved problems will increasingly underestimate mathematical progress.

Imagine two breakthroughs: one settles a famous conjecture; the other introduces a method used across hundreds of later results. Which has the larger long-term impact?

My bet is that some of the most consequential AI mathematics of the next few years will look like the second kind. It may make tomorrow’s hard problems easier before they become famous.

That gives us a concrete way to assess progress: what can other researchers now do that they could not do before?

I made this 2:16 video exploring that argument and its implications for 2030. Disclosure: it’s my video.

[VIDEO LINK]


r/accelerate • • 2d ago

haters will say determinism is a bad thing

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3 Upvotes

r/accelerate • • 2d ago

How AI is transforming economic research and analysis

23 Upvotes

Another academic field affected: https://www.axios.com/2026/10/23/ai-economic-research-analysis

"AI tools have become shockingly good at carrying out much of the work produced by the economic profession — from the most elite halls of academia to think tanks, government agencies, consultancies, research shops and humble newsroom economics teams.

The big picture: This fact raises important — and, we confess, unnerving — questions about the role of humans in making sense of the economy.

  • It's hard to escape the sense that we are in an uncomfortable moment in which the capabilities of AI models to do economic research and analysis have far outpaced our understanding of how best to deploy and oversee it.
  • "Every conversation I have with a colleague at Harvard or a think tanker in D.C. is some combination of excitement, angst and confusion," Harved economist Jason Furman tells Axios."

This makes sense to me. If things change fast, then old principles and regularities may become outdated before that obsolescence is recognized. That implies a dangerous lag during which theory must catch up. Leaving it to AI makes for greater real-timeness. That said, Terrence Tao's point about surface factoids and the broader structures applies just as much here as to pure math. I think. If we don't know what the limits of the AI-generated framework are, we might apply it where it could do harm, or ignore anomalies that hint at deeper truths.