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  • Hacker News
  • Dario likes this timeline. Good for the IPO valuation.
    by 12as79
  • I'm probably going to be downvoted for this, but this makes this whole industry look like a bunch of snake oil salesmen and charlatans.
    by heyts
  • So often people shy away from making predictions, which is a shame. I always love when people make the attempt and use their imagination.
    by bibimsz
  • > 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.

    by 27183
  • > Hacker News Guidelines

    > Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.

    by Mond_
  • One 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.
    by mcbuilder
  • Anthropic documented even more proof of that yesterday:

    https://www.anthropic.com/threat-intelligence-report-septemb...

    by adt
  • Biased 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.

    by Rover222
  • Fun 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.
    by waffletower
  • >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.

    by glenstein
  • Kimi K3 isn’t cheaper.
    by applicative
  • I 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.

    by alephnerd
  • Interesting 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.

    by api
  • Mom said it was my turn to post this
    by Topology1
  • My 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

    by AlexErrant
  • Room temperature superconductivity, developed by AI

    Poulsen treatment for the rich (https://hyperioncantos.fandom.com/wiki/Poulsen_treatments)

    The race is for things that does not exist today.

    by mf2hd
  • I think the idea is that AI itself is going to massively accelerate its own development, and AI with real-world competence is coming very soon. At the rate things are going, it wouldn't suprise me at all if we had mass production of AI-designed systems in the next six months, actually.
    by AlexCoventry
  • I have much more faith that AI would come up with a way to bioengineer ordinary mosquitoes than have any chance at a tiny insect sized robot
    by nancyminusone
  • > 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.

    by pizza234
  • https://isaiprofitable.com/

    I like this one better

    by firemelt
  • This 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.
    by reducesuffering
  • On the other hand, people said this about Amazon, Google, Meta/Facebook, and loads of other huge tech things that are now wildly profitable.

    It hasn't been a reliable predictive metric so far. All runaway growth tech sectors and businesses tend to look economically insane until they're not.

    by api
  • You almost have hope for them from the total number until you realize the vast majority of that green is made up of NVIDIA
    by ofjcihen
  • I don’t understand how they track these figures.

    For example: META made a bit more than $5 bn revenue since 2022?

    by baxtr
  • The accounting is pretty iffy there though. Like the top line implies Amazon lost $334bn on AI but they aren't really an AI company and made a $16bn profit last quarter at AWS up 64% on the previous year. Also a larger profit as a company as a whole.
    by tim333
  • AI is more like an ongoing research project than it is a product. GPUs are currently the product that is profitable and Nvidia will keep funding labs to keep buying GPUs.
    by 10xDev
  • Oh look, the answer is the same when I looked a couple months ago. Interesting
    by ealready_value
  • Funny how they include nvidia, micron, and AMD revenue as “AI revenue” and that it represents that majority of industry revenue but presumably a big chunk of everyone else’s spend. Almost might as well include electric utility revenue as AI Revenue by that metric
    by andy99