Transcript

Title text: This is how you all fucking sound

[A smug tech bro wearing a sideways cap, watch, chain around his neck stands in front of a data center by a lake with dead fish. A smoke stack blows pollution into the air]

Tech bro: AI is already here, there’s no going back.

[A smug man in a suit with cigarette in hand stands in a restaurant while two disgruntled diners cough from the smoke]

Suit: Smoking indoors is already here, there’s no going back.

[A smug man in a top hat and suit stands in a factory with two sad and dirty children]

Hat: Child labor is already here, there’s no going back.

[A smug plantation owner stands in front of a field with with two angry slaves]

Plantation owner: The Atlantic Slave trade is already here, there’s no going back.

Still Vreni on Bluesky

  • dual_sport_dork 🐧🗡️@lemmy.worldEnglish
    0·
    10 hours ago

    Yes, but at least at the end of the day you can use nukes to blow stuff up. Presumably your enemies.

    If your enemies win the generative AI “arms” race they can use it to, uh…

    ???

    (Yes, I am aware there are military/governmental applications for neural net learning technologies but they’re the types of pattern recognition and signals analysis stuff we already do without needing to build a football stadium sized datacenter every 50 miles and burn the entire nation’s GDP on electricity generation. Most of the other applications appear to revolve around a regime using it solely to shoot themselves in the foot, e.g. powering a fantasy army of likely to be highly defective murder robots or using it to propagandize at and spy upon their own population in order to ensure a ready supply of destabilizing internal dissent always exists.)

    • 9point6@lemmy.world
      0·
      9 hours ago

      Making a better LLM isn’t the point of all this, it’s taking what they have and building on it until they create a true AGI.

      Whoever gets there first, makes basically everything else obsolete in an instant.

      In a world where the organisations that are blazing the trail are in private hands, this is very bad news for everyone who isn’t in the winning organisation.

      That’s essentially the arms race: who gets to be king of the world.

      The slim chance of it not being monumentally detrimental to humanity is basically tied to us abandoning capitalism wholesale and uniting the world, so I’m not holding my breath.

      • dual_sport_dork 🐧🗡️@lemmy.worldEnglish
        0·
        9 hours ago

        But LLMs are not the path to the final state of AI, either. And that’s assuming only if — and this is a very big “if” — a true general artificial intelligence can even be created using traditional silicon computing methods in the first place. Blithely assuming that it can be is really rather asking past the sale.

        • Dagnet@lemmy.world
          0·
          9 hours ago

          Yep, by design LLM cannot become ‘inteligent’, you can only make it more believable but it’s still copying humans not really thinking by itself. No amount of development or money invested will change that, it’s not a pokemon it won’t just evolve into something different one day.

          • dual_sport_dork 🐧🗡️@lemmy.worldEnglish
            0·
            8 hours ago

            And it’s worth reiterating, the current crop of generative “AI” is incapable of producing anything new or novel. All it can do is reassemble existing strings, tokens, and patterns in slightly different ways. Innovation can never come from such a machine. That will have to come from a human.

            The current push is the notion that “hyperscaling,” i.e. throwing even more hardware and space and power and money at the same concept, will magically make it something it isn’t. Obviously that’s not going to work. It’ll allow grifters to make a ton of money over it, though!

              • dual_sport_dork 🐧🗡️@lemmy.worldEnglish
                0·
                2 hours ago

                From TFA:

                The AI did not prove that its approach is the best anyone can do, though. In fact, mathematician Will Sawin has already improved upon the AI’s grid.

                OpenAI privately contacted Litt, Sawin, Gowers and a number of other mathematicians to verify the LLM’s proof. Together (and without the company’s direct involvement), they wrote up their individual takeaways. (No external experts have seen the AI’s original output, however—just an edited version of its train of thought.)

                What stood out, they said, was the AI’s preternatural patience and focus.

                …

                “AIs have an edge: It’s not just that they can try all known methods,” says Jacob Tsimerman, a mathematician at the University of Toronto, who was not involved in the work but was part of the companion paper solicited by OpenAI. “They can play for longer and in more treacherous waters than mathematicians without getting overwhelmed.”

                …

                The mathematical tools the AI used here are not novel, although their application in this domain appears to be. “The model did not invent something fundamentally new that nobody saw coming,” says Sébastien Bubeck, a mathematician leading OpenAI’s mathematical explorations. “It just executed like an amazing mathematician.”

                So, it’s a monkeys-on-typewriters situation with the computer able to try and reject the hammering of who knows how many square pegs into round holes until it finally arrives at a workable conclusion, which a human has already bested. And we’re not allowed to see its homework.

                This is categorically failing to set the world on fire, except possibly in the literal sense.