According to Elon Musk (whose fortune now largely rests on the perceived earnings potential of robots and AI), humanoid robots that can immediately replace anyone doing manual labor is just around the proverbial corner. Emphasis added throughout.]
Speaking on Tuesday at the US-Saudi Investment Forum in Riyadh, the Tesla CEO predicted that humanoid robots could eventually number in the tens of billions, transforming the global economy.
"Everyone will want their personal robot," Musk said. "You can think of it like having your own personal C-3PO or R2-D2 — but even better," he said, referring to "Star Wars" characters.
With that scale of automation, Musk said productivity could soar and usher in what he called a "universal high income," where goods and services become so abundant that "no one wants for anything."
Musk has skin in the robot game. He called Tesla's humanoid Optimus potentially the "biggest product ever of any kind" during a launch event for its robotaxi last October.
Musk has been making this sales pitch for months now.
"You can produce any product, provide any service," Musk said of humanoid robots. "There's really no limit to the economy at that point. You can make anything."
The billionaire said that money may not carry much value by then.
"Will money even be meaningful? I don't know; it might not be," he said, adding that robots could create a "universal high-income situation" because anyone will have the ability to make as many goods and services as they want.
Musk's bullishness on humanoid robots comes as no surprise. The CEO said during an earnings call on January 29 that Tesla will begin production of "several thousand" Optimus robots by the end of 2025.
"It's one of those things where I think, long term, Optimus has the potential to be north of $10 trillion in revenue," he said during the call. "Like, it's really bananas."
He also suggested his robots could provide "quasi-infinite products and services."
On the other side, we have actual researchers (from NPR):
BRUMFIEL: I spoke to Ken Goldberg, a professor at the University of California at Berkeley. And he is pretty emphatic that AI-powered robots weren't here yet.
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KEN GOLDBERG: Robots are not going to suddenly become the science fiction dream overnight.
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BARBER: OK, so, like, tell me why because, like, AI chatbots have gotten, like, way better, super fast. So why are these robots getting stuck?
BRUMFIEL: Chatbots have a huge amount of data to learn from. They've taken basically the entire internet to train themselves how to write sentences and draw pictures. But Ken says--
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GOLDBERG: For robotics, there's nothing, right? There's no examples online of robot commands being generated in response to robot inputs.
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BRUMFIEL: And if robots really need as much training data as their virtual chatbot friends, then having humans teach them one task at a time is going to take a really long time.
BARBER: Oof.
GOLDBERG: You know, at this current rate, we're going to take 100,000 years to get that much data.
BARBER: What? OK, that's so long.
BRUMFIEL: [LAUGHS]
BARBER: Like, are there any alternatives? There must be.
BRUMFIEL: One might be to let the AI brain of the robot learn in a simulation. A researcher who's trying this is a guy named Pulkit Agrawal. He's at the Massachusetts Institute of Technology.
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PULKIT AGRAWAL: The power of simulation is that you can collect, you know, very large amounts of data. For example, in three hours', you know, worth of simulation, we can collect 100 days' worth of data.
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BARBER: Hm.
BRUMFIEL: So this is a really promising approach for some things, but it's much more of a challenge for others. So, for example, let's talk about walking. When you're just dealing with the Earth and your body, the physics of walking around, it's actually kind of simple. But if you want your robot to, say, try and pick up a mug off a desk or something, that's a lot more complicated.
BARBER: Mm, more forces.
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AGRAWAL: If you apply the wrong forces, these objects can fly away very quickly.
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BRUMFIEL: Basically, your robot will fling things across the room if it doesn't understand the weight and the size of what it's carrying. And there's more. You know, if your robot encounters anything that you haven't simulated 100% perfectly, then it won't know what to do. It'll just break.
BARBER: OK, so, Geoff, you've taken me from, like, optimist to pessimist. It's the you know, the road I take every day.
BRUMFIEL: [LAUGHS]
BARBER: I'm starting to think that AI is, like, never going to work that well in robots. Or, like, it's going to be a really long time.
BRUMFIEL: I'm sorry if I've, like, turned you into a pessimist here, Gina. And then I'm going to--
BARBER: It happens.
BRUMFIEL: --and then I'm going to have to sort of whipsaw you back. Because AI is already finding its way into robotics in ways that are really interesting. So, for example, Ken Goldberg has co-founded a package sorting company. And just this year, they started using AI image recognition to pick the best points for their robots to grab the packages.
BARBER: Ooh.
BRUMFIEL: And I think we're going to see a lot of that, AI being used for parts of the robotic problem, you know, walking, or vision, or whatever. It just may not arrive everywhere all at once.
Robotics is the future but in the foreseeable future, it's not going to be the kind of bipedal humanoid Swiss Army knife Tesla is supposed about to unveil. If there's a major breakthrough it could speed things up, but even under the best case scenario, serious people working in the field will tell you we're years, possibly decades away from the kind of functionality Elon is promising will be coming off the assembly line in six months.
So who ya gonna believe? Well, if you're an investor...