Imagine never having to fold laundry, wash dishes, or decipher those cryptic IKEA assembly instructions again. According to Elon Musk, that future isn't just possible—it's inevitable. And apparently, we're all going to be lining up for it.

During a May interview with CNBC journalist David Faber at Tesla headquarters, Musk painted an ambitious picture of where Optimus, the company's humanoid robot project, is headed. His prediction? Personal robots will become the most valuable product ever created.

"I think humanoid robots will be the biggest product ever," Musk told Faber. "The demand will be insatiable."

When Faber reminded him of his previous claim that "everyone's going to want one," Musk didn't back down. "It's like, basically, who wouldn't want their own personal C-3PO? R2-D2?…Everyone," he said.

The timeline Musk has in mind is characteristically aggressive: roughly one million Optimus robots rolling off production lines annually by 2030. He still considers this "a reasonable target" and frames it as the first major milestone toward what he calls "sustainable abundance."

The Training Challenge

Of course, building a million robots is one thing. Making them actually useful is another. Faber pushed Musk on this point, noting how long Tesla has been working to perfect autonomous driving in its vehicles.

"A lot," Musk conceded when asked about the training requirements. "It's going to take a lot of compute resources and it'll take time."

But here's where Musk's vision gets interesting. He believes there are specific breakthrough moments ahead that could dramatically speed up the learning process. The most critical one? When Optimus can learn new tasks simply by watching videos.

"I think there's certain threshold breakthroughs that we think we can achieve where if Optimus can watch videos — YouTube videos or how-to videos or whatever — and based on that video, just like a human can learn how to do that thing, then you really have task extensibility that is dramatic because then it can learn anything very quickly," Musk explained. "So I think we'll get there."

Learning Like a Child

Right now, Tesla's approach is fairly manual. Engineers wear motion-capture suits to teach Optimus basic movements like grasping objects or opening doors. But Musk envisions something far more sophisticated—a learning process that mirrors how children develop skills.

"Where I think it gets very interesting and very much like humans is that you want the robot to self-play," he said. "So you say, how does a child learn? Well, a child has toys. A child plays with the toys, plays with the blocks… By doing it over and over again and this — the self-play — once you have a lot of robots, you can do this self-play, which is that you just put the robot in a room with toys and have the robot play with toys."

Musk used a classic shape-sorter toy to illustrate the concept: "You're the goal of the robot is to… put the circle in the circle hole, the square in the square hole, triangle in the triangle hole and keep doing it until it works. And the reward function is succeeding."

Through repeated trial and error, the robot would learn not just specific tasks, but broader problem-solving capabilities. With enough robots in production, this self-play training could happen at massive scale, potentially accelerating the learning curve exponentially.

What's Still Missing?

When Faber asked whether fundamental AI breakthroughs are still needed to make this vision reality, Musk acknowledged the gaps.

"There are some advances needed," he replied, "but I don't think these are insurmountable."

Tesla has already demonstrated Optimus performing tasks like folding shirts, sorting objects, and walking with more natural movement than competing humanoid robots. While Musk's timelines are famously optimistic, the progress is tangible enough to make his 2030 production goal feel less like fantasy and more like an aggressive but achievable target.

If Musk is right, the era of personal humanoid robots isn't science fiction anymore. It's just a matter of time, training, and teaching machines to learn the way humans do—one YouTube video and one toy at a time.