> 1. Robotics begin rolling out more broadly across the world.
To borrow the Strangelove quip, this is not only necessary but essential.
Broader physical robotic deployments are the glue that connects {cheap synthetic intelligence} to {physical outcomes}.
The former is a newer phenomenon, in the LLMs-can-approximate-higher-intelligence-well sense, so robotics deployments haven't caught up yet (outside of the highest ROI dark factory scenarios).
They'd also have to be self-assembling from the ground up or rely on human slaves. They'd need to understand the world much better. And they'd have to be incredibly more power efficient. These all remain hard problems right now. That said, you could swarm people with cheap drones (the predicted slaughterbots) that were assembled by robots that eventually break down I guess, but how is that any worse than a crazy human with a gun or what nation states do to people they deem enemies already? The worst these things seem capable of is an attack on the infrastructure and shutting down the Internet. Perhaps this is a great time to insure that our infrastructure is capable of operating autonomously indefinitely and hardening it against attack? But unfortunately, no VC or politician will touch that until something bad happens.
So broadly, a better educated Blake Lemoine IMO. What's disturbing to me is how fast and far some junior minion from the frontier labs was platformed all the way to the Wall Street Journal over a tweet that sounds exactly like every other anti-AI tweet. I share concerns about irresponsible deployments of AI, and we need technological literacy in the leadership, but America hates technocracy and prefers populism so buckle up.
> They'd also have to be self-assembling from the ground up or rely on human slaves. They'd need to understand the world much better. And they'd have to be incredibly more power efficient.
All robotics needs to drive deployment at scale is (1) useful intelligence & (2) performing novel valuable functions.
Both of these are satisfied by current tech (LLM + sensors + robotics) and the existing simplest use cases (assembly lines and repetitive tasks).
LLMs get you a moderately-intelligent, mostly-reliable orchestration layer of intelligence on top of deterministic hard robotics.
And that's enough for a lot of failure-tolerant, feedback-looped cases. E.g. reading 20 dials in a factory throughout the day or monitoring a production line visually, then figuring out what to do about a problem, then effecting that plan.
It'll be deployed in heavily utilized spaces at first, but will eventually trickle down throughout the economy.
And that will be when 'control over robots' starts to be an existential threat, for denial of critical services at the minimum.
And all of this will inevitably roll out as long as ROI is positive, because that's the way the world works.
To borrow the Strangelove quip, this is not only necessary but essential.
Broader physical robotic deployments are the glue that connects {cheap synthetic intelligence} to {physical outcomes}.
The former is a newer phenomenon, in the LLMs-can-approximate-higher-intelligence-well sense, so robotics deployments haven't caught up yet (outside of the highest ROI dark factory scenarios).
But it's too economically-valuable not to come.