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AI 2027 (2025)
- heyts 16d agoI'm probably going to be downvoted for this, but this makes this whole industry look like a bunch of snake oil salesmen and charlatans.
- 27183 16d ago> It’s informed by trend extrapolations, wargames, expert feedback, experience at OpenAI, and previous forecasting successes. In other words: bias. Tons and tons of self-congratulatory, glue sniffing bias.
- Mond_ 16d ago> Hacker News Guidelines > Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.
- faraday2211 16d ago[dead]
- 27183 15d agoThat wasn't a shallow dismissal. It's literally the sentence that renders the rest of the article not credible.
- sigalor 16d agoI wonder when the people will get that intelligence is not only directed at the external, but only really starts when you look at the internal (joy, pleasure, traumas, taboos, awkwardness, abuse etc.). Look up the word "interoception".
- glenstein 16d ago>Agent-2, more so than previous models, is effectively “online learning,” in that it’s built to never really finish training. Every day, the weights get updated to the latest version, trained on more data generated by the previous version the previous day. That seems to me to be a natural progression, from discrete models to models that are just continuously improved. Maybe we'll end up with different models with different rates of improvement rather than static differences in performance, and methodologies for that improvement will be the thing we care about. Maybe over time, even benchmark tests will be primarily concerned with that kind of efficiency. I think a huge debate right now is the relative value of the "frontier" models from Western companies at the cutting edge, vs distilled versions of those models that are good enough and exponentially cheaper coming from China. But a paradigm of 'always training' means an always active, always advancing frontier, which is a stronger moat than a one-off model that's more advanced for a few months.
- applicative 15d agoKimi K3 isn’t cheaper.
- glenstein 15d agoThen don't take my comment as directed toward that example. Charitable interpretation for the win.
- Topology1 16d agoMom said it was my turn to post this
- Ydarbleoj 16d agoSorry, but the notion that creative writing and robotaxi's exist as proof of anything is like saying my child can drive and write; and while true, the measure of that ability is not at the level of the best humans. It's average at best.
- Rover222 16d agoSo you've never tried FSD.
- Ydarbleoj 16d agoThe one that requires full-attention from the driver? No.
- Rover222 16d agosounds about right
- qwerpy 16d agoDepends what your definitions of "requires" and "full" are. On mine there's some nagging on the scale of once every tens to hundreds of seconds if it thinks I'm not paying attention. You're willingly living a more stressful and unsafe life if you're still manually driving your car in 2026.
- Ydarbleoj 16d agoSounds less stressful.
- rpdillon 16d agoAll of the early data shows that self-driving cars from Waymo are safer than the average attentive driver. This is not the average driver, since of the 36,000 deaths a year from accidents in the US, about 12,000 of them are due to alcohol or impaired driving. https://publichealth.jhu.edu/2026/the-safety-data-on-autonomous-vehicles https://publichealth.jhu.edu/2026/the-safety-data-on-autonom... As for writing: AI is not nearly as good as the average professional writer, but they are definitely better than the average citizen of the United States, considering that 21% of adults are not functionally literate in the US. AI has no problem writing at the undergrad level.
- weezing 16d agoAt which point do we get to fight in the anti clanker uprising?
- firemelt 16d agohttps://isaiprofitable.com/ https://isaiprofitable.com/ I like this one better
- ealready_value 16d agoOh look, the answer is the same when I looked a couple months ago. Interesting
- reducesuffering 16d agoThis is exactly how Cloud Computing looked in 2012-2018. Dumping huge $ into computing buildout that wasn't profitable yet. All those co's: Amazon, GCP, Azure paid off immensely and are ridiculously profitable.
- simianwords 16d agothe same type of people will eventually hate it when AI actually starts profiting at which point they will ask for redistribution. damned if you do. damned if you don't.
- skulk 16d agoif all of humanity's knowledge was redistributed to AI labs to sell back to us, it's only fair that some of the profits get redistributed back.
- marcosdumay 16d agoNo, it wasn't. Cloud computing was almost immediately profitable. And Amazon was famously "unprofitable" for their first 9 years because they were investing all their very real profits into a form of capital that the US tax code didn't recognize.
- reducesuffering 16d agoGCP reported its first quarterly operating profit in Q1 2023, roughly 15 years after Google began offering cloud computing. Frontier labs are also reinvesting their tens of billions of revenue back into infra scaleout, sounds like Amazon. If 2 of 3 were like this, and Azure numbers were never split out, want to take a guess what the economics of the third was like too?
- AlexErrant 16d agoMy main issue with this timeline is that AI still has trouble transitioning to the real world. It predicts for 2029: > There are swarms of insect-sized drones that can poison human infantry before they are even noticed; flocks of bird-sized drones to hunt the insects; new ICBM interceptors, and new, harder-to-intercept ICBMs. The rest of the world watches the buildup in horror, but it seems to have a momentum of its own. Does anyone really predict insect drones _in production_ 3 years from now, to the degree that we need bird drones to hunt the insect drones? How the hell are these things powered? Lean/math/millenienium prizes are "grindable" [0]. Wake me up when AI is making order-of-magnitude improvements in ungrindable real world tasks like batteries, hypersonic engine manufacturing, and stealth/silent motors that you can't hear. [0]: https://www.dwarkesh.com/p/the-next-paradigm https://www.dwarkesh.com/p/the-next-paradigm
- pizza234 16d ago> Does anyone really predict insect drones _in production_ 3 years from now The industrial expansion timelinen as described in AI 2027 is way too compressed; I don't think any AI doomer believes that. The dynamics are plausible though, even without China stealing the weights.
- AlexErrant 16d agoLiterally 2 days ago, from a former Anthropic researcher: > The people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. https://x.com/hilbertspaess/status/2097476203863224394 https://x.com/hilbertspaess/status/2097476203863224394 > The dynamics are plausible Please elaborate: what dynamics? This is rather vague. My point is that AI can't grind real world physics/chemistry/engineering. What dynamics are in play here?
- mf2hd 16d agoSolve the grinding then: https://www.nature.com/articles/s41524-026-01964-8 https://www.nature.com/articles/s41524-026-01964-8
- api 16d agoInteresting but it degenerates into sci-fi tropes if you look at the extrapolations. Reminds me of 90s writing about what the Internet was going to do. The Internet ended up being both more incredible and more mundane than predicted.
- waffletower 16d agoFun to read this again and see actual parallels. The 2030 Takeover section is such a ludicrous leap, however. None of the supply chain infrastructure, energy, or Moravec's Paradox realities are ever addressed. Turn the page and suddenly humanity is largely annihilated with a Corgi-esque human breed kept as pets. How did these robots emerge from utter rhetorical nothingness? Robocalypse impossible? Perhaps not. By 2030? an intellectually embarrassing farce worthy of a facepalm.
- 12as79 16d agoDario likes this timeline. Good for the IPO valuation.
- mcbuilder 16d agoOne of the most biased claims IMO in AI 2027 is that a huge portion of the geopolitical and existential risk argument is hinged on the notion that China just steals the US frontier weights.
- Rover222 16d agoBiased how? China has a long history of corporate espionage. Everyone knows the Chinese are capable of whatever they put their minds to. But stealing IP to skip some steps is part of the system.
- ramon156 16d agogood thing US is completely clean
- Rover222 16d agoOf course it's a spectrum that all advanced countries exist on, but if you think China and the US are on the same end of the spectrum, that's strange.
- sterlind 16d agoThe US/China divide is one thing, but if I'm asked whether I trust OpenAI or Deepseek, as companies, more, I'm not sure how I'd answer. I suppose my default is to distrust whoever is in the lead, since the lead is power, and power corrupts.
- Rover222 16d agoYeah Sam Altman doesn't inspire trust. Dario and Musk are a bit better in this regard. I think they both say what they really think. Altman... no way.
- mcbuilder 16d agoLook what's coming out of China, they are catching up on performance and surpassing the US in efficiency. They're on a different level when it comes to open releases of weights. I don't, to me the entire premise is a bit flawed at it's core (ASI), and I read it like bad science fiction with China playing the bad guy just a narrative crux so we get to the acceleration timeline and warring nation states.
- hmokiguess 16d agoNow that's some load-bearing seam if I ever seen one
- alephnerd 16d agoI am an AI booster and have visibility into a number of these models, and this is ridiculous. They underestimate AI's existing impact on some job markers and overestimate it's impact in such short a timeframe.
- bibimsz 16d agoSo often people shy away from making predictions, which is a shame. I always love when people make the attempt and use their imagination.
- aadyachinubhai 16d agoI don't like grandiose claims about AI.
- luisln 16d agoHow do you know if you are sticking your head in the sand versus being reasonable?
- aadyachinubhai 16d agoOne of the first things I learned in ML is that the model can only learn from the information in X. If X doesn't contain enough information to determine y, no amount of compute can fully recover it. That's why I'm skeptical of grand claims about AI. Scaling can make models much better, but it can't create information that isn't there. An AI system can be extremely useful without becoming superhuman.
- sambapa 16d agoAnd what do you think about recent developments, for example Navier-Stokes? I always thought the same but now I have doubts, but maybe it is just psyops from openai.
- aadyachinubhai 15d agoIt is speculated that there was context leak from a NYU Professor's chat I think? I contribute to SciPy heavily and I've seen AI shit the bed a few times now. So 13 million lines of lean? Hell no dude!