Gig workers train humanoids on household chores

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**Stephanie Hughes** (0:31)
The robots are coming to do the laundry? From American Public Media, this is Marketplace Tech. I'm Stephanie Hughes.
It's Friday, time for Marketplace Tech Bytes Week in Review. Today, is your shirt folding technique good enough to train a robot how to do it? And then, could MySpace be creeping back into our browsers?
But first, the rocket ship slash satellite internet slash AI company, SpaceX, reported this week that it spent over $18 billion in capital expenditures in the second quarter, six times what it spent the same time last year. Most of that was on AI infrastructure. I talked about this with Joanna Stern at the media company New Things. I asked her what she thought of this first earnings report from SpaceX as a publicly traded company.

**Joanna Stern** (1:27)
It's good to see how much they're spending on things. I think the transparency is pretty cool. I think the big takeaway, they're spending tons of money on AI like every other company. We also get a sense of what is doing well for the company. Starlink, for instance, doing well for the company, not surprising. This is more of their consumer enterprise internet play to give people satellite internet, and that has been doing incredibly well over the last couple of years as the company forges partnerships with all kinds of companies, airlines in particular. So overall, I think the transparency is pretty cool.

**Stephanie Hughes** (2:03)
Yeah, it is nice. I mean, they have to be transparent, but like it is nice to be able to do this, to be able to see inside there. No, we weren't able to see inside their financials in this way.
One other thing that also came up a few times on the call was the moon, specifically the idea of using rockets to build manufacturing on the moon. One thing they didn't talk about was the discarded SpaceX rocket that collided with the moon this week. This was unintentional. Antoinette, do you think this is any kind of omen of what's to come with all the things that we've been sending up into space?

**Joanna Stern** (2:36)
Well, I think there's already been concern back to the Starlink and to all the satellites that have been launched. There's been a lot of concern from the scientific community around space junk. I think this is another example of, as we put more of our Earth-made contraptions into space, are we going to worry about more damages, what that does to this area that has not been tarnished by our human-made devices and technology?

**Stephanie Hughes** (3:05)
Not too tarnished, not yet, but we'll see what we can do. Let's move to our next story, which is actually your story. Tech startups pay gig workers to train robots to do chores. Joanna, you have a new story up on things where you look at startups that are having people film everyday tasks like doing laundry, loading the dishwasher in order to ultimately train robots to do that work. You actually tried doing this yourself for the startup Micro AGI. Here is a clip.

**Joanna Stern** (3:29)
Large language models like Chat GPT have been created by swallowing pretty much the entire Internet. Robot models need their own version of that. Massive amounts of data showing the physical world.
Micro AGI collects all those videos, blurs any personally identifiable details, anonymizes the videos, and AI analyzes the hand movements. Finally, all the accepted video is converted into code that can be used for training.

**Stephanie Hughes** (3:57)
Tell me, what did you take away from this reporting?

**Joanna Stern** (4:00)
So much, took away so many different things. I mean, one that, and it's something I had been reporting on previously, which is that for humanoid robots and robots in general to continue to progress in development and to get into our homes, the big thing they need is data. And so companies like this Micro AGI are so focused and so hungry for that data that they are now paying people like myself to wear these cameras on our heads and to film all of our everyday tasks. So they can start to build massive amounts of models and training data to train these models on that boring tasks.