An excerpt has surfaced from the AI2027 podcast with siskind and the ex AI researcher, where the dear doctor makes the case for how an AGI could build an army of terminators in a year if it wanted.

It goes something like: OpenAI is worth as much as all US car companies (except tesla) combined, so it could buy up every car factory and convert it to a murderbot factory, because that’s kind of like what the US gov did in WW2 to build bombers, reaching peak capacity in three years, and AGI would obviously be more efficient than a US wartime gov so let’s say one year, generally a completely unassailable syllogism from very serious people.

Even /r/ssc commenters are calling him out about the whole AI doomer thing getting more noticeably culty than usual edit: The thread even features a rare heavily downvoted siskind post, -10 at the time of this edit.

The latter part of the clip is the interviewer pointing out that there might be technological bottlenecks that could require upending our entire economic model before stuff like curing cancer could be achieved, positing that if we somehow had AGI-like tech in the 1960s it would probably have to use its limited means to invent the entire tech tree that leads to late 2020s GPUs out of thin air, international supply chains and all, before starting on the road to becoming really useful.

Siskind then goes “nuh-uh!” and ultimately proceeds to give Elon’s metaphorical asshole a tongue bath of unprecedented depth and rigor, all but claiming that what’s keeping modern technology down is the inability to extract more man hours from Grimes’ ex, and that’s how we should view the eventual AGI-LLMs, like wittle Elons that don’t need sleep. And didn’t you know, having non-experts micromanage everything in a project is cool and awesome actually.

  • humanspiral@lemmy.ca
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    22 hours ago
    1. No need to buy car companies to get a head start on manufacturing. Car automation is a bit specialized, but multi DOF robot arms, and 3d/cnc machines, are going to be more precise at manufacturing than humanoid robots.

    2. Programming for humanoid robots is exponentially harder, and at best, can replicate some human labour tasks. 100% quality replication is very hard. Even if you can replicate $1/hour labour quality, there is still a limit to usefulness, as that labour capacity exists already. Military applications though can “tolerate” high mistake level.

    3. There is no user software platform that exists. It is much simpler to get a LLM/AI interface to 3d printing/CAD/CNC model generation than humanoid steps, even if environmental implementation/obstacles are handled in software/AI, and its unclear that there is success in 3d manufacturing realm. The software almost needs to come first, even in a simulated environment, before humanoid robots are practical. Military applications somewhat excepted.

    4. OpenAI is not particularly ahead at anything. Their military/Empire supremacism lobbying focus is not a manufacturing focus. Military vehicles that are wheeled or airborne are easier to program to shoot at all the things, and easier to get paid $Ms per unit, and remote control is both much easier and still worth $Ms, until exponential production capacity.

    So, while adapting humanoid manufacturing/task robots to military is extremely attractive, the money is in military, and other vehicles are much easier, and OpenAI is not ahead on anything even if they have the most paper wealth. The paper wealth has many more immediate military opportunities to cash in on.