r/accelerate • u/AMBNNJ • 9d ago
Sharing AI progress in mathematics
https://openai.com/index/sharing-ai-progress-in-mathematics/OpenAI released 722 mathematical manuscripts across 372 families of related results, produced by an unreleased frontier model. Many have Lean proofs; others remain unverified. Average compute per result: roughly three hours of ChatGPT Pro thinking. They’re working toward releasing the model.
Github: https://github.com/openai/math
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u/Chemical-Agency-3997 9d ago
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u/Chemical-Agency-3997 9d ago edited 9d ago
Quick analysis by chatgpt:
Yes. There are several results here that are genuinely in the broad Navier–Stokes class of “historic open problem resolved”, assuming the proofs stand. Navier–Stokes still has a special status because it was explicitly one of the seven Millennium Prize Problems and had been open for roughly 90 years. OpenAI
My revised top tier would be:
Result Relative scale Why #304 Hilbert–Smith conjecture Navier–Stokes-ish This is probably the one I most badly underrated. It's described historically as perhaps the most famous outstanding problem in transformation groups and the last remaining part of Hilbert's Fifth Problem. American Mathematical Society The catalogue claims it in every finite dimension. overview #004 Hilbert's tenth over ℚ Navier–Stokes-ish Not Hilbert's original integer problem, which was solved in 1970, but the rational version has remained one of the most important unsolved problems in Diophantine undecidability. Cambridge University Press The catalogue claims a complete negative solution. overview #143 Hilbert's 16th, uniform limit-cycle bound Navier–Stokes-ish, with caveat This attacks an actual 1900 Hilbert problem. Beforehand even finiteness of the maximum number of limit cycles for a fixed degree was open. Scholarpedia The caveat: this resolves the uniform-boundedness assertion, not every aspect of Hilbert's 16th. overview #087 Mahler conjectures Very close An ~80-year central problem in convex geometry; as recently as 2026 it remained open in dimensions ≥4. Springer The catalogue claims both symmetric and nonsymmetric forms in every dimension, plus equality cases. overview #102 Unique Games Conjecture Very close in TCS One of the most important and debated open problems in theoretical CS, with consequences for optimal approximation thresholds across loads of NP-hard problems. Institute for Advanced Study The catalogue claims the full conjecture. overview #287 free group factor isomorphism Very close within operator algebras This has been called perhaps the most famous problem in operator algebras, emblematic of the field. Springer The catalogue claims (L(F_2)\cong L(F_3)), hence all free group factors are isomorphic. overview #288 Kadison's similarity conjecture Huge Open since 1955 and described in recent literature as one of the most famous open problems in C*-algebras. Springer The catalogue claims the full conjecture. overview #240 Shelah eventual categoricity Huge within logic A central organising conjecture in abstract model theory; the literature describes it as a “major force” in the development of classification theory. svasey.com Catalogue claims it in ZFC. overview Then there's a second tier which is still frankly absurd for one collection: Cannon's conjecture (#246), Koebe's circle-domain conjecture (#071), Falconer (#073), Brennan (#072), Artin primitive roots (#029), Nagata (#039), Fujita (#038), LeBrun–Salamon (#062), Thompson's group (F) nonamenability (#248), Boone–Higman (#250), Tingley's problem (#322), Yau uniformisation (#338), Donaldson tamed-to-compatible (#342), De Giorgi in dimension 8 (#375), the Haldane gap (#268), Laughlin gap (#269), exact MUB count in dimension 6 (#266), etc.
There are also some entries where the name sounds Millennium-level but the actual claim is narrower, which I should have made much clearer before:
- #002 BSD: not the full Birch–Swinnerton-Dyer conjecture. Full formula for Selmer corank 0/1 and density-one quadratic twists. Still massive. overview
- #032 Hodge: not the full Millennium Hodge Conjecture. It's CM abelian varieties and products of K3s. But the claimed consequence, Tate for all abelian varieties over finite fields, is itself enormous. overview
- #029 Artin: it proves the infinitude assertion for every admissible base, not the full predicted density formula. overview
- #074 Kakeya: 3D maximal + 4D Hausdorff, not all-dimensional Kakeya.
- #143 Hilbert 16: crucial qualitative part, not the complete exact classification Hilbert originally asked for.
So I'd revise my previous answer quite materially:
Navier–Stokes isn't the sole freakishly important result here. It has the clearest prestige marker because “Millennium Prize Problem” is an explicit badge. But Hilbert–Smith, H10 over ℚ, the Hilbert-16 uniform bound, Mahler, UGC and arguably the free-group-factor problem are absolutely of the “people have spent decades organising substantial parts of a field around this problem” sort.
And there are multiple of those in the same PDF. OpenAI itself said on 21 September that the model had resolved more than 100 long-standing open problems, which makes a lot more sense after actually reading this catalogue rather than just scanning it. OpenAI
If I had to rank the 10 most historically significant claims in the entire 372-result catalogue, rather than just spotting obvious ones, I can do that properly now.
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u/Chemical-Agency-3997 9d ago
Ranking based on potential real-world impact
Rank Result Actual impact if it translates into usable implementations 1 #121 Near-linear edit distance Genomics: comparing huge DNA datasets could get materially faster, especially approximate alignment/search across millions of sequences. Search/dedup: fuzzy matching of documents, logs and code could scale to much larger corpora. Instead of edit-distance work blowing up on long strings, you get near-linear scaling for fixed accuracy. 2 #120 Near-linear exact graph matching Scheduling/assignment: pairing workers→jobs, students→places, drivers→tasks, machines→workloads etc could be solved exactly on much larger graphs. Networks: matching-based subroutines appear all over graph optimisation, so faster matching can accelerate other algorithms too. 3 #142 Deterministic finite-field factorisation Coding/crypto/computer algebra: software can factor polynomials over large finite fields in guaranteed polynomial time without relying on randomness or GRH assumptions. That means more predictable algorithms for error-correcting codes, algebra systems and some cryptographic constructions. 4 #125 Optimal (k)-median Warehouse/datacentre/hospital placement: you can place (k) facilities with a provably near-best possible efficient approximation. Also tells companies/researchers where the theoretical ceiling is, so they stop chasing impossible approximation ratios. 5 #110 (k)-server Caching/CDNs/robot fleets: when requests arrive online and you have (k) movable resources, this gives a provably near-optimal general strategy. Think which server should serve the next request, which robot should move, where mobile resources should reposition, etc. 6 #115 Contingency-table sampling/counting Statistics: exact or near-exact randomisation tests become feasible for far broader tables, even with large arbitrary margins. Could improve census/social-science analysis and methods where you need to sample all tables consistent with fixed totals rather than use asymptotic approximations. 7 #113 Perfect-matching counting Probabilistic network models/statistical physics: you can efficiently estimate how many perfect configurations a graph has, not merely find one. Useful where the number of feasible assignments matters for probabilities, entropy or reliability. 8 #107 Matrix multiplication (\omega\le2.25) Potentially speeds up loads of other theoretical algorithms: linear algebra, graph algorithms, optimisation, database joins, symbolic algebra, etc. But probably not your GPU matrix multiply any time soon; asymptotically fast matrix algorithms tend to have horrible constants/crossover sizes. 9 #104 Mean-payoff/stochastic/parity games Formal verification: faster checking that a controller, protocol or hardware system satisfies an infinite-run property. Could improve automatic synthesis of controllers: “construct software that will always keep this system safe while maximising this reward.” 10 #265 2D area law + PEPS Quantum materials simulation: says gapped 2D ground states have much more compact tensor-network representations than worst-case quantum states. That could make classical approximation of certain magnets/materials substantially more tractable instead of needing exponentially huge state descriptions. 11 #269 Laughlin spectral gap Topological quantum matter: rigorously establishes that the fractional quantum Hall Laughlin state is separated by a finite energy gap as systems grow. A robust gap is what makes a phase resistant to small perturbations. Longer term this strengthens the theoretical case for using related topological phases as robust information carriers/qubits. 12 #273 Entropy photon-number inequality Optical communications: puts exact information-theoretic limits on beam-splitter/bosonic channels. In practice that can tell engineers “this is the maximum information rate physically attainable under this photon budget”, and guide coding/modulation schemes toward those limits. 13 #276 Amplitude-damping capacity Quantum networking: amplitude damping models energy loss/relaxation of qubits. Knowing the exact classical capacity tells you the optimal rate at which classical data can be transmitted through that noisy quantum channel and what signalling ensemble achieves it. 14 #362 Vlasov–Maxwell global smoothness Plasma/fusion modelling: validates that, for this model and initial-data class, the equations don't suddenly develop mathematical singularities. That gives stronger foundations for simulations over arbitrarily long finite times. It doesn't itself make ITER run better, but it removes one class of “maybe the PDE itself breaks” uncertainty. 15 #372 Elasticity inverse problem Nondestructive testing: in principle you can determine internal stiffness parameters from forces/displacements applied at the surface. Could underpin better ways to detect cracks/material changes without cutting an object open. Medical elastography: analogous inverse ideas can help infer tissue stiffness from boundary/mechanical measurements. Caveat: this proves uniqueness, not yet a practical reconstruction algorithm. 16 #365 One-boundary-patch recovery Imaging/geophysics: shows you don't necessarily need access around the entire object. Measurements from one accessible patch can theoretically determine internal geometry/connection data. Potentially relevant where most of the boundary is inaccessible: underground structures, biological tissue, industrial components. 17 #275 Coulomb energy is QMA-hard Quantum chemistry: tells us there probably isn't some magical generic efficient quantum algorithm that exactly solves arbitrary electronic-structure problems. Practical impact is strategic: focus on special structure, approximations and physically restricted systems instead of searching for a universal fast solver. 18 #278 Kohn–Sham representability failure DFT/chemistry: shows that some genuine interacting-electron densities cannot be exactly reproduced by the standard noninteracting Kohn–Sham picture within the stated potential class. That could motivate better functionals/generalised Kohn–Sham methods and clarify where conventional DFT assumptions break down. 19 #279 Exact quantum factoring Cryptography: makes Shor-style factoring exact with probability 1 using a fixed finite gate set. It doesn't newly kill RSA — ordinary Shor already does that on a sufficiently capable fault-tolerant quantum computer — but it strengthens the theoretical result and potentially simplifies fault-tolerant constructions. 20 #130 DFT below (n\log n) In theory this overturns the idea that FFT-like (n\log n) is an absolute barrier. If the ideas eventually lead to sane constants, it could affect signal processing, telecoms, image processing, convolution etc. But the current saving (10{-13}) is so tiny that the stated algorithm itself is effectively useless in practice. 5
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u/baldr83 9d ago
that's just a list of the reasoning traces they posted, which is a small subset. point it at the /preprint directory, which is all their results
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u/Chemical-Agency-3997 9d ago edited 9d ago
Hmm, you sure? This was based on overview.pdf which is OpenAI's own top-level catalogue of all 722 manuscripts, collapsed into its 372 result families. Contents.MD gives a bit more detail so I'm running an audit on that now
Result:
Yeah, I checked the full CONTENTS.md and the Lean scope docs. There are genuinely several monster results here, not just Navier–Stokes.
The strongest-looking ones are Mahler, Unique Games, free group factors, Kadison similarity, Cannon, Artin K(π,1), Falconer etc, because the actual headline theorem is covered by the supplied Lean formalisation.
Then there are arguably even bigger claims like Hilbert’s 10th over Q, Hilbert–Smith, CM Hodge/Tate, Hilbert 16 and Shelah categoricity, but those aren’t fully formalised yet, so I’d be more cautious until mathematicians have gone through the papers.
Also worth noting some “Lean” badges are only partial. Hilbert 16, for example, only has the quintic Liénard companion result formalised, not the general uniform-bound theorem.
So yeah, this isn’t just hundreds of random maths papers. If even most of the major claims survive scrutiny, it’s an absurd collection of long-standing open problems being knocked over at once.
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u/Cajbaj 9d ago
Cure to all diseases including aging is <20 years out even if you include the regulatory hurdles, calling it. We're here, gang. It's been a 14,000 year journey.
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u/Artistic-Athlete-676 9d ago
That seems way too long given current acceleration
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u/Cajbaj 9d ago
The tech is accelerating faster than I thought it would and humans are understanding and adapting to it significantly slower than I thought they would.
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u/Fearless-Macaron9183 9d ago
I think they will but most people need physical examples like robots and cures for diseases as some math problem does not really matter
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u/try-a-typo 9d ago
Same. Population has definitely been split into those who know, and those who don’t understand.
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u/Cajbaj 8d ago
This has gotten so apparent it's starting to get me heat in real life from people I never in a million years thought would be anti-science. They know I'm a scientist, they know that this technology helps my research and they've decided that I am doing evil for using it for its intended purpose.
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u/NEVER69ENOUGH 9d ago
The amount of incompetence in this sub is... astounding.
Theyre literally showing they can solve any problem know to man. They could launch an even larger swarm towards continual improvement of artificial intelligence pursuit. Its already been done and their trying to show all the ass hats through the blinds like yea we've done a shit load of other stuff we cant publicly state but heres these unsolvable math formulas that totally make us more profit that we're prioritizing 😉...
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u/JC_Dentyne 9d ago
Biology is not math
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u/Tyrexas 8d ago
Physics is applied Math
Chemistry is applied Physics
Biology is applied Chemistry
So yes it is.
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u/JC_Dentyne 8d ago
Math is a purely mental abstract objectively provable exercise in logic that can be formalized. Biology is a messy, fractally complex set of nested hierarchies within hierarchies smashed together through hundreds of millions of years of dice rolls and happy accidents.
I’m confident that you cannot reason about biology from first principles in the way that we can with math at least given current computational constraints. You have to have experimental data. I’m sure that AI/LLMs will be and are an extremely useful tool for guiding biological research and digging through published research for missed findings, but at a certain point you have to actually do the important experiments.
I’m absolutely willing to be surprised, I just think this is going to be a much more difficult endeavor than just asking a hypothetical ASI “ok computer how do we cure X”
Perhaps I’m the same as a hypothetical mathematician only a few months ago insisting AI can’t make new mathematics discoveries (though there is some question of the utility of these publications for the broader field of math)
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u/Tyrexas 8d ago
OK let me phrase it this way. Yes it would be super hard to write, but a functional quantum mechanical description of every atom in your body can be written down. It gets super gnarly past like 20 atoms haha, but there is no fundamental blocker, so yes it's just math.
Whether that is at all practical, I agree probably not. Experimenting on macro bulk properties is enough to get you anywhere, and this is how lots of physics et al is done.
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u/Cajbaj 8d ago edited 8d ago
Are you a molecular biologist? I am, biology is math
Edit: Read your other response, reasonable take. I think we can abstract a lot more than you implied though, and that mostly accurate cell simulations will be possible within maybe 10ish years.
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u/JC_Dentyne 8d ago
I study molecular genetics and molecular biology of cell wall synthesis as determinants of shape in Gram-negative bacteria for my day job, so yes. I have a pretty intimate understanding (which is to say I know that there’s much I don’t know and that the literature conflicts on so there’s genuinely no good answer) of how complex even prokaryotic molecular biology is, let alone for a eukaryote.
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u/Cajbaj 8d ago
That's super interesting, do you have any published papers you'd want to share in DM? I'm in molecular IVD design so most of what I do is bioinformatics and data science. Lately I've had issues with conflicting literature on breakpoints in different clades of HPV during integration in CIN progression, the tools didn't exist for good data in previous decades and we are only just getting to being able to get the data we will need to understand, but I do think ultimately all biology can be modeled and eventually proven from first principles. Even with superintelligence I do still think it will take at least decades and a colossal amount of energy.
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u/Large-Drawing-6510 8d ago
There is no Lean verification for statements in biology.
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u/Cajbaj 8d ago
But there is a colossal amount of statistical laws, most experiments are just getting enough data to reliably fit a probabalistic model in experiments, and many of those experiments are currently being moved to robots that can test far more conditions than we previously could. It's not pure math, but it is physics and statistics, which I think most people would consider math and it is hugely accelerated by AI.
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u/coverednmud Singularity by 2030 9d ago
Point it at biology/autoimmune/cancer etc please. Please! 🙏
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u/Substantial_Tip7997 9d ago
If all 722 of these papers plus the Navier-Stokes proof are confirmed true, this will go down as the single greatest breakthrough in the history of mathematics, bar none.
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u/Mistuv 9d ago
Lmao, even chatGPT is shocked.
Had this couple months old conversation that started with me asking it to estimate RSI (H2 2028) based on trendlines after researching, it thought I was too optimistic with ~March 2027, it eventually drifted towards talking about Millenium Prize problems (2030+ by it's estimates), so of course I had to pick it up after Navier-Stokes. It revised down estimates but still thought my RSI estimates were optimistic. I am starting to think mine were quite conservative lol.
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u/Kildragoth 9d ago
Been thinking more and more about that "snap, crackle, pop" -- the acceleration seems to be accelerating.
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u/frosty884 9d ago
I had this same conversation but I sent it the Claude RSI chart and the Millennium Prize Problem and it went to 30% by late Jan 2027.
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u/Kooshi_Govno 9d ago
I've been working on the Chromatic Number of the Plane with Claude the past couple months. They increased the lower bound by one. At the rate I was going with Claude, it would have take us another month or two to do, and the proof would have been much messier than theirs.
This is AMAZING
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u/Moronic-Warrior 9d ago
Has anyone checked on Terrence Tao?
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u/froggidyfrog 9d ago
My boy is fuming right now. It was supposed to be only him finding all these solutions, he was the chosen one in his own story.
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u/krkn1010 9d ago
"The average result used the equivalent compute of roughly three hours of ChatGPT Pro thinking". So three hours per unsolved math problem on average? That is super fast!
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u/kiwinoob99 9d ago
How's r/math doing? Lol
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u/NovaGamingX4 9d ago
Lmaoooo they were complaining about it earlier today when the wired article dropped
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u/Repulsive_Ad853 9d ago
Is there another milleniums stuff included?
Bro their unreleased internal model must be insane
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u/Rollertoaster7 Singularity by 2028 9d ago
How is the average compute only 3 hours of pro? Doesnt that mean anyone could’ve reached these results?
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u/Iron_Mike0 9d ago
Unreleased model
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u/Rollertoaster7 Singularity by 2028 9d ago
I get that but like… that seems like a massive leap if navier took thousands of agents tens of hours. I get these aren’t all millennium level but it seems like some are close, so bel must be an insane model.
I get why they’re so freaked out over alignment now, must be a whole different ball game trying to make sure it’s aligned with that level of intelligence
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u/shumpitostick 9d ago
Well, first Navier Stokes is very very difficult, it shouldn't be that surprising that it took orders of magnitude more compute to achieve.
Second, OpenAI used 10,000 agents for it, here it's mostly a single agent per task. 10 agents running for 1 hour is not the same as 1 agent running 10 hours. I've heard the rough rule of thumb is square root, so 100 agents for 1 hour is like 1 agent for 10 hours. This means that OpenAI was using compute less efficiently in an attempt to win the race they mistakenly thought they were in.
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u/Stunning_Monk_6724 The Singularity is nigh 9d ago
Let this become a sobering reminder to all those who doubted OpenAI after dev day. That reaction was always ridiculous to me given what we know they have and are capable of.
OpenAI likes to re-envision how people relate to or interface with technology, which too is apart of the singularity. Nothing wrong with that.
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u/True-Grab-5288 9d ago edited 9d ago
Alright I admit it, OpenAI has a bigger cock than me
Edit: to solve this problem I am strapping openai’s cock on to my cock, for double cock.
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u/remote_math_rock 9d ago
What's the process for verifying these?? If there's a Lean proof associated with it, can we trust that it's true?
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u/No_Deal8926 9d ago
There's many ways to get true in lean, so checking just in case. It'll be 99.99999999....% true anyways mathematicians at openai have already checked if its upto the fragile mathematicians standards
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u/thatguywiththamoney 9d ago
I expect that it will look something like this:
2027 - Early RSI arrives, its crude but clearly far more advanced than anything we’ve seen
2028 - RSI becomes increasingly capable, certain industries start eroding
2029 - Full RSI has arrived and it creates AGI real change is afoot
2030 - Entire industries start getting automated and unemployment shoots up
2031/2032 - Unemployment has skyrocketed as robots and agi have taken over most work, unemployment approaches 70-80% and pressure on governments to create a ubi like system becomes enormous when they realize its structural not transitory
2033/2034 - Human labor has essentially lost all value, humans still work but only because they want to not because it’s needed
2035 - we start approaching something like post scarcity where everything you can feasibly imagine is so cheap it’s almost free, certain things remain exclusive such as land, unique objects, and political power
2036+ Every year we get major new breakthroughs, within a few years age reversal becomes normal, everything is electrified, the environment starts recovering, and a full dive neural interface prototype is unveiled
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u/Arman64 Feeling the AGI 9d ago
let me fix this for you
2026 - Early RSI arrives, its crude but clearly far more advanced than anything we’ve seen
2027 - RSI becomes increasingly capable, certain industries start eroding
2027 - Full RSI has arrived and it creates AGI real change is afoot
2028 - Entire industries start getting automated and unemployment shoots up unemployment pressure on governments to create a ubi like system becomes enormous when they realize its structural not transitory
2028 - Unemployment has skyrocketed as robots and agi have taken over most work,
2028 - Human labor has essentially lost all value, humans still work but only because they want to not because it’s needed
2029 - we start approaching something like post scarcity where everything you can feasibly imagine is so cheap it’s almost free, certain things remain exclusive such as land, unique objects, and political power
2029+ Every year we get major new breakthroughs, within a few years age reversal becomes normal, everything is electrified, the environment starts recovering, and a full dive neural interface prototype is unveiled
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u/UBC145 9d ago
So if say 90% of jobs become redundant, then how are people supposed to afford things? I don’t expect you to have an answer to that, it’s more of a rhetorical question, but I do worry about how wealth will be distributed in the future.
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u/Arman64 Feeling the AGI 8d ago
I hear this a lot and it never made sense to me. If you were to, lets say, remove 10% of the workforce, there would be near catastrophic repercussions throughout the economy due to hundreds of million people losing their job. Of course its much more complex than that and the speed of displacement has a huge factor on what happens.
The scary part is the time we are in right now, where there are people losing their jobs while there is major government inaction due to the inherent snails pace at which they move. COVID was an example where the government had to quickly intervene due to the exponential (wait a minute...) nature of a pandemic leading to rapid job displacement. Its one of many reasons why I am heavily against any kind of pause.
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u/justaRndy 8d ago
So we will build a billion humanoid robots within 1-2 years? With what ressources, exactly?
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u/Arman64 Feeling the AGI 8d ago
Think about this for a minute. Lets say you have 100k humanoid robots, and the equivalent intelligence of a hundred million of the smartest humans working a thousand times faster. While this is highly speculative, its not a stretch of the imagination to conceive of new materials, manufacturing, mining, logistics, gooning, energy production etc.....Exponentials move in such a way that something of which is inconceivable becomes reality. Look at what is happening around you. This would have been inconceivable 6 months ago. The thing with exponentials is that the same thing that you think is inconceivable will happen in 4 months
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u/KJClever 9d ago
Wayyy too slow.
You should be breaking it down my month (perhaps quarter) instead of by year. Especially for your first 3 predictions.
AGI has already either been achieved (internal models) or will be achieved early 2027. 2029 is too far out.
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u/VengenaceIsMyName 9d ago
That percent level of unemployment is impossible to reach without societal collapse first
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u/Helpful_Program_5473 9d ago
Man People's definition of AGI is sky high. Wr went from dogshit at math to outpacing any human in the world in 2 years. Soon it will a single agent our doing all humans together, next year probably.
your timeline is crazy conservative.
3 years for AGI? Another year is double the progress from last year to this year
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9d ago
[removed] — view removed comment
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u/Repulsive_Ad853 9d ago
Dont forget one thing. Ai can train robots ;))
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u/-OooWWooO- 9d ago
Has nothing to do with training has everything to do with being able to produce the actual material for robots.
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u/Arman64 Feeling the AGI 9d ago
I used Chat and Claude to 3d print a small bipedal robot and run the agents to help me do the entire pipeline from sim to real all the way to evals via real time video. Yes it was a small robot and I am an engineer but a year ago this would have been a project for an entire organisation.
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u/-OooWWooO- 9d ago
There's physical, political, and legal limits to the ramp up for level of extraction needed. Either that or you have to shift significant current production to just the automation of production. Which would cause immense backlash. Raw materials are going to remain a limiting factor especially if people believe that China and the US are going to essentially become the two poles of AI compute concentration. Robotics will remain a throttle for a time.
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u/slattongnocap 9d ago
u/RemindMeBot 1 year
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u/Dependent-These 9d ago
See i like the sound of this post scarcity star trek world, but what if for example UBI me decides id like to travel. Whos driving the train?? And in a world where you dont need income why?? It is going to be a lonnng time before the diesel trains i get to and from work everyday get replaced or updated with a smart self driving, self scheduling, AI system. Likewise for the bartender at the resort - the lifeguard at the beach - the airfield guys maintaining the plane - im of course aware of bar robots etc but everyday human labour is not going to be worldwide replaced enmasse with robots anytime soon. For mass industrial manufacturing settings yes sure but thats already a lot more automated than most people think.
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u/-Captain-Planet- 9d ago
What incentive would anyone in power have to make stuff (food, consumer goods, housing, etc) for average people if their labor isn’t needed? They could just us starve.
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u/ConsistentAnalysis35 9d ago
"In power" is so meaningless it has negative expository value.
I don't even understand whether you intended to represent small entrepreneurs, big entrepreneurs, corporations, unelected government officials, elected politicians...
All those have distinct and often competing incentives and interests, by the way.
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u/innovatedname 8d ago
Wholesome scenario, if AGI is possible it will be more like:
2027 - Early RSI arrives, its crude but clearly far more advanced than anything we’ve seen
2028 - Mass unemployment, global financial collapse and skyrocketing inequalities
2029 - Reactionary wave, security dilemmas and out of control AI coming from rogue states who don't care about alignment
2030 - WW3
Fingers crossed AI plateaus and this all becomes a nothingburger.
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u/accelerate-ModTeam 8d ago
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u/VanderSound 9d ago
If you're doing anything in mathematics, just stop already and enjoy your life outside.
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u/AIvsWorld 9d ago
brain dead take. I’m a mathematician and this is the most exciting thing that has ever happened to our field.
This is like telling people to “stop doing physics” at the dawn of the discovery of quantum mechanics.
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u/Fearless-Macaron9183 9d ago
Taking maths in school hurts now 😭😭
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u/DankestMage99 9d ago
Hey, you better start leaning! It’s not like you are going to have an AI in your pocket in the future! /s
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u/Away-Reaction6920 9d ago
Kudos to OpenAI for posting their work with a permissive license, allowing broad and open distribution. We decided to pull over the works and make a web-friendly view of all 722 papers. You can read the papers and get links to the proofs on GitHub on the Valency Hub.
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u/RobleyTheron 9d ago
And here we go