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Do you ever like when you were edited, when you had an editor, when you worked at a real publication? Yeah. Did you ever put stuff in a story that you knew was bad just so your editor would cut that and not the thing that you actually wanted to stay in? No. And thank God I never worked somewhere where I had to think like that because like trying to play the
nine-dimensional chess and like how do I get something past my editor when it's ridden me out of this business? I call this my green M&M strategy where I like I put something that's like horrible in the story and I just like leave it there and then there's something like three paragraphs below that that I know they're gonna want to cut but that I really want them to leave in. Kevin will just be like admittedly some have asked whether 9-11 actually happened. And the editor says you know what I know how we can save one paragraph worth of space.
I'm Kevin Roos. I'm a tech columnist at the New York Times. I'm Casey Newton from Platformer. And you're listening to Heart Fork. This week on the show, X marks the spot where Twitter died. Plus, why iris scanning orbs may be coming to a city near you. And we visit Google's robotics lab where they are putting AI inside the machine's brain. We'll tell you how many have escaped the lab.
All right, Casey, I have been dying to talk to you about what the hell is going on at the company formerly known as Twitter. Well, Twitter doesn't exist anymore, Kevin. We have to stop using that word. It's no longer an active concern. Right. So...
Let's just do some chronology up top, because I think it's useful for people to understand how quickly and kind of erratically all of this happened. Right. So Saturday night, Elon Musk tweets at about nine o'clock Pacific time. Soon we shall bid adieu to the Twitter brand and gradually all the birds. Now,
Now, we have known for some time that Elon Musk has wanted to rebrand Twitter. He started a couple holding companies for Twitter called X Holdings. So we kind of knew that something was afoot. But talk to me about how sort of chaotically and quickly this all happened. Well...
As you noted, it was all done in a very haphazard way. On Sunday night, they projected a giant X onto Twitter's headquarters on Market Street. And then Monday, a crane showed up and started to take down the Twitter sign. Right. And actually got stopped by San Francisco police before they could finish. So at least for a little while, the sign on the Twitter building just had a
an E-R left. It just was er. Er. Yeah, just er. Which really does capture, I think, a lot of people's feelings about the whole city. It is, what did Elon Musk
So anyway, by that point, of course, the product had begun to transform. And so if you opened up the app, all of a sudden where you used to see the bird, you now saw an X. Yeah. And at most companies, like a rebranding is something that takes many months. It involves lots of, you know, consultants and designers and focus groups. Paying people to do things for you. Exactly. This was like, you know, let's just throw it up and see what happens. Exactly.
And not only was the product sort of renamed, but actually people started going around inside Twitter's headquarters and like pulling the bird logos off the walls and renaming the conference rooms. So my colleagues at the New York Times reported on Monday that the company's conference rooms have been changed to words and phrases with the letter X in them, like exposure, exalt, and
sexy with a three instead of an E? I'm so excited to get laid off in the sexy room. That's got to take the sting out of it. Frankly, any room you're in is the sexy room. But I just like... I think it's really strange. And actually...
I had a moment this week where, you know, I was opening up my computer to start my work day like normal. So it's roughly noon. Are we talking? Come on now. So I wake up, I pull up my Chrome. I instinctively go to Twitter. And instead of the like blue bird in my like little browser tab, there's this like black X. And
And that was the moment for me where it clicked. Like, oh, this is not Twitter anymore. Yeah. Like, the thing, like, I don't know why that was the moment for me. But, like, until now, if you didn't really, like, think about it too hard, you could kind of just squint and pretend that Twitter was still the old Twitter. And lots of people have been doing that, basically. Just trying to pretend all the Elon stuff is noise and I'm just going to keep tweeting like I've always been tweeting. Right.
Right, and you could kind of fool yourself because some of your friends were still there. The site and the app looked roughly the same. But for me, that little black X in the browser bar was the moment where I was like, oh, it's gone. I'm not using Twitter anymore. This is a site that's owned by Elon Musk who probably does not want me on it. And it just was a moment where it went from feeling like,
A thing that I have been doing for like more than a decade at this point when I opened my browser is no longer a thing that feels good to me. Absolutely. And look, I think Twitter has died a lot of deaths since October when Elon Musk walked in with that sink. And in fact, I think that day was probably the first of those deaths. I think it died again when he got rid of three quarters of the staff.
I think it died as he gradually replaced the old content moderation policies with sort of more of an anything-goes ethos. But the moment when the website actually just redirects to another name and the app itself has another logo, yeah, Twitter is no more. So I want to talk about why this is all happening because it seems like
totally incomprehensible to me. And let's talk first about the official explanation, which is the one that Twitter CEO Linda Iaccarino gave. And it's so beautiful. This is some of the best writing that you'll ever hear. And Kevin, I hope you do it justice when you read it. Okay, let's do a dramatic reading of her tweet. X is the future state of unlimited interactivity.
centered in audio, video, messaging, payments slash banking, creating a global marketplace for ideas, goods, services, and opportunities. I mean, what doesn't X do, you know? Right. So what is the official explanation that the company is giving for why they are changing the name of the service? Well, going back to before Elon completed the transition, he talked about wanting to make
Twitter into a super app, right? So in China, you have WeChat, this app that is your entire digital life. You shop with it, you post on its sort of internal social network, it's your pass on the train, right? And
that's a huge opportunity, right? It's essentially, it's like, well, if one app on your phone constituted all of the economic activity that you did, Elon Musk would make a lot of money. So that's what he wanted to do. It will not be possible for him in the United States for a bunch of reasons, but that is the goal, is that X is essentially going to be your one-stop shopping app for everything. Right. So that's the official explanation that we're getting, is that Twitter is becoming this like
huge super app that's going to do everything from handling your banking information to getting you onto the subway to paying you for your banger tweets or zits or whatever we're calling them now. Yeah. By the way, have you uploaded all your banking information to x.com yet?
I saw the activity over the weekend and just the thoughtfulness of the new X rollout. And I thought, I would like to give that man my social security number and routing number. I called up Wells Fargo and I said, it's over between the two of us. I'm taking my business to a man that gets me. Okay. So you have a different explanation for why all this is happening.
What is your take on why Elon Musk is doing this? So, you know, the way that I have described what he's doing is cultural vandalism, right? I see this as very much a political project and specifically a reactionary political project. And we've talked about that a bit on the show in the past.
the way that Elon Musk was really aggrieved by what he saw as a growing sense of entitlement among tech workers in general, but specifically at Twitter. Twitter had endorsed a lot of liberal values and causes like Black Lives Matter. And, you know, I'll just never forget when after he took over, he opened a closet and he found a bunch of T-shirts that the old Twitter had made that said, stay woke on them, which sort of recognized the company's role as a part of the Black
Lives Matter movement, right? And to Elon, I mean, he just could not stop making fun of this. Like, this was just so funny to him that, you know, essentially anyone would support the Black Lives Matter movement. But it was the way that he was preening for the camera when he talked about this that sort of let me know, this is the project. This is the point. It is to go into this important cultural institution and to tear it down from the inside and to say, these values no longer apply.
I am going to wipe this thing off the face of the earth. And we eventually got there, and it didn't even take that long. So you think this is basically like a kamikaze mission, right? He is trying to run Twitter into the ground. My theory about what is happening here is partly what you said, is partly that there's this sort of cultural vandalism happening. But I also wonder if, like,
He just is starting to feel like Twitter is too boring and too small to command his attention. Like, he is clearly obsessed with Twitter, the service, but I think as time has gone on, you know, it's been almost a year since he acquired it now. And
I think that he is just kind of out of ideas. He tried subscriptions. He tried sharing revenue with creators. He tried longer videos and bringing back the people who'd been banned, like all these ideas. And nothing has really kind of moved the needle in the direction that he wants it to go. And so this to me feels like kind of an act of surrender. Like he's just kind of saying, well, I can't fix Twitter, so I'm just going to rename it and fold it into something bigger. And maybe you'll forget about how disastrous the past year has been.
Well, look, in the run-up to him acquiring it, a lot of folks said, you know, he's probably going to get bored of this, right? Because it's actually hell to run a social network. You do spend most of your time having to weigh in on these very difficult questions about content moderation, the business models of challenge. And I think a lot of folks thought, this guy's got a lot of other things on his plate. He's just not going to want to stick with it for the long haul. He, of course, famously tried to get out of the acquisition, was eventually compelled to buy the thing by a court. And so then he's in charge of it. And as you point out, he tries some things and they don't work.
I do think that it is reasonable to assume that in the aftermath of the failure of his original set of ideas for Twitter, he's now beginning to think like, well, what else could I do? I guess I could go dust off this idea that I had in the 90s for a payments app and just hope that the people who are still using Twitter will come along for that ride.
Right. But let's just say, that's a terrible idea. It's a very bad idea. It's like if you've acquired the user base of Coke and then you're saying like, and now we're going to sell them mortgages. It's like, well, you can try to do it, but you went about it in the worst way imaginable.
Right. It does not inspire confidence that one would need to, like, hand over your finances to this man. Right. So let's talk about these Twitter alternatives. Yeah. Because, you know, a few weeks ago, we had our special episode with Adam Masseri, the head of Instagram, right as they launched Threads.
And just to sort of remind everybody what happened, we did a podcast when Threads launched, and within the first week, it had 100 million signups. So we're calling that the hard fork bump. And it could have worked for your product launch too. Get in touch. Yeah, we don't promise 100 million users for every product, but maybe 50 million. The forker army is strong out there. So Threads has now been in existence for three weeks. How's it going? What's your impression of...
whether this is actually the social media app that can replace Twitter. So there's two ways of looking at it. One is you can look at how engagement has been on the app since it launched. And that is a chart that has basically been going down over time.
A lot of people opened up the app, they browsed a bit, they saw a lot of posts from brands, they didn't see their friends, they thought this feels like a shopping mall, and they bounced. Some folks who were frankly predisposed to saying, "This thing is never going to work, it's just a copycat app from a company that I hate," they've been doing some victory laps lately saying, "This thing does not have the juice and it's going to flop." Right. There is some data to support this. SimilarWeb, which is a company that measures for the popularity of various websites,
estimated that threads usage has dropped by about 60% compared to its initial kind of surge of interest. So, you know, a bunch of people rushed to sign up. Maybe they saw it on their Instagram. Maybe they heard about it on a hard fork or somewhere else. They sign up, they go, they maybe post a few things, read a few things, and then they drop off. And that seems to be happening for a lot of people. That's not just like an I hate meta thing. This is like, it does actually appear to be losing popularity.
Yeah. So, I mean, I think that that is true. I also think that that is true of most social networks when they launch. There's this initial rush of attention, and then most users churn away, and then it's up to the makers of that social network to figure out, okay, how do we build this thing so that people keep coming back time after time? And that is maybe the thing with which Meta has had the most practice over the years, as it has built Facebook, as it has built Instagram, as it has built WhatsApp, right? So I'm not particularly bothered by all that.
The more optimistic framing of what's happening at Threads is they launched a bare-bones copycat of Twitter. There was so much demand for something like Twitter in the world that they got 100 million users within a few days. And now they have to do the hard work of building out the rest of the features.
And so the game is how quickly can they ship the features that will not just make it what Twitter used to be, but actually better than what Twitter ever was. And I think they're well on their way, right? So this week, they shipped something that people like us have been asking for since they launched, which is you can now see a feed, a post just from the users themselves.
that you follow, right? For the most part, when you open up Twitter, for most of its existence, you would just see stuff from people you follow. That's what made it very useful. Threads opened up to this algorithmic timeline, much more TikTok-like. It would just sort of show you things that thought you might be interested in. Which are mostly like Wendy's, from my experience, or like brands. Who doesn't love a cold frosty on a summer's day, Kevin? But you know...
So, you know, it still has a lot of levers that it can pull to grow the thing. And I would say that within a couple of weeks, it has just become far and away the most likely thing to replace Twitter in the popular imagination. There are alternatives, but this is the one that I just think has the most momentum. Yeah, I'm going to take the other side of this. And partly that's because I'm one of these people who like,
opened threads and used it a bunch for the first couple days. And then ever since, it just hasn't been that interesting or compelling to me as a product. And so I've basically churned off at this point. But it's also just like, it is worth reminding people of why Meta has the reputation that it had, why people are skeptical of this company. There was a period of many years where
meta slash Facebook was just pursuing growth at all costs. You know, a lot of that resulted in real concrete harms. There was a genocide in Myanmar. There was ethnic violence in Sri Lanka. That was a direct result of Facebook's decision to grow into those regions without having the infrastructure that they need to support. And now we know all of this in part because people
kept leaving Facebook and saying, we knew about this at the time. We knew that these harms were present and we didn't do anything about them because growth was more important. And so I think when I see something like threads and I see all the Facebook executives, you know, celebrating the growth of this new app that they've built,
What I'm thinking is like, what are we going to learn 12 or 18 or 24 months from now about what's going on actually under the hood at Threads? And so that's what makes it feel a little bit less fun for me because I actually still remember the period from like 2014 to 2020 where Facebook just was causing real harm all over the world because of this appetite for growth.
I think these are great criticisms. I co-sign basically everything that you just said. Meta has a lot to answer for. I've spent a lot of my time in tech journalism writing about those specific things, right? And I absolutely believe that you and I and everybody else in the tech press corps is going to continue to scrutinize this company as this thing grows and as it
creates potentially more harms. It's also true that Meta has dismantled some of the integrity teams that it had built over the past several years in the wake of the 2016 election. So I think all of these concerns are valid. We have to keep paying attention to it.
To me, it's just kind of an order of operations thing. The most pressing need I have in my life when it comes to... Well, I shouldn't say my life. But now I'm like, do I not want to say it because it's true? Right. The bottom of your pyramid of hierarchy of needs is Twitter circa 2022. Sad but true. No, no.
Here's what I would say. I have a need for a Twitter-like thing in my life. That thing is no longer Twitter. And I have tried every other network over the past nine months as they have shown up. And I have tried to ask myself, like, could this be the thing that achieves an escape velocity? And no matter which one it was, I would have used that. Then I'm continuing to use Mastodon and Blue Sky and some of the other apps, even as Threads has started to occupy more of my time. So I'm open to it being anything.
but I do think it needs to be something. I just think we're moving away from this kind of model of centralized social media. I think we're moving into a more fragmented world where, you know, texts and group chats and discords and, you know, all other kinds of apps are sort of being used by these small groups of people who know each other in real life. I think there will be like apps for people who want to
have their thoughts broadcast to large audiences. But I don't think that's actually a need that a lot of people have. I think that you and I are unusual people in the fact that we have messages that we want a lot of people to hear. Well, but at the same time, I think that we're unreliable narrators on this because one of the main reasons that people use social networks is to build clout. You know, you're just starting out in your career and you want to become a known quantity. One of the best
things you can do is get on a social network and just start posting. There was a great story at the Times about a comedian who had been this sort of journeyman who had never made much money, and then he started posting his stuff on TikTok, and he went crazy viral, and now he has an amazing career. And his name was Casey Newton. And his name was Casey Newton! Come see me at the Chuckle Hut in Indianapolis this Saturday. But you know...
That's why these networks are so valuable is that they can launch people from obscurity into having incredible careers. Obviously, that's not the median outcome for somebody who uses one of these social networks, but that's why we're always going to have them is...
people need these engines for creating clout. And you're going to read a lot of commentary and listen to a lot of commentary about threads and these other apps from people in their 30s and their 40s. And what you need to remember about them is that for the most part, they have already generated their clout. They are fine.
They have an audience, they have a job, they do not need this. So the main thing that you hear from these people when they talk about these apps is how exhausted they are at the prospect of starting over. Of course, you're exhausted. You were working your butt off on Twitter for 10 years trying to make something out of yourself and you did it. So why would you ever try again? I totally understand that impulse. If you're 30 or 40 and you want to nope out of the next social network, go for it. But there is a generation coming up behind you that needs to do exactly what we've been doing since 2010, which is trying to build audiences.
And they're going to turn to threads or TikTok or wherever it is that they think they can find that clout and build the kind of online persona that they want. I mean, I do think that what will determine whether...
networks like Twitter or like threads persist in some form is whether young people are using them. So far, I have not seen a lot of Zoomers posting on threads, but maybe that'll change. And I just I think they're all on TikTok. I don't know. They seem to be very happy over there. But maybe if TikTok gets banned, maybe they'll migrate over to threads. Also, did you see the feature that TikTok got out of this week? No. Text posts. Yeah.
So finally, I have a chance that I could be good at TikTok. This is our moment. This is our moment. We now have TikTok text posts. All right. After the break, a very different kind of experiment. This one involving a large metallic orb.
Bye.
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Give your team the power of limitless potential with Snapdragon. To learn more, visit qualcomm.com/snapdragonhardfork. Hello, this is Yuande Kamalefa from New York Times Cooking, and I'm sitting on a blanket with Melissa Clark. And we're having a picnic using recipes that feature some of our favorite summer produce. Yuande, what'd you bring? So this is a cucumber agua fresca. It's made with fresh cucumbers, ginger, and lime.
How did you get it so green? I kept the cucumber skins on and pureed the entire thing. It's really easy to put together and it's something that you can do in advance. Oh, it is so refreshing. What'd you bring, Melissa?
Well, strawberries are extra delicious this time of year, so I brought my little strawberry almond cakes. Oh, yum. I roast the strawberries before I mix them into the batter. It helps condense the berries' juices and stops them from leaking all over and getting the crumb too soft. Mmm. You get little pockets of concentrated strawberry flavor. It tastes amazing. Oh, thanks. New York Times Cooking has so many easy recipes to fit your summer plans. Find them all at NYTCooking.com. I have sticky strawberry juice all over my fingers.
Casey, the other thing that I have been dying to talk to you about this week is the launch of WorldCoin. Now, WorldCoin, it has been out there in sort of a testing phase for a couple of years, but it officially launched this week. And I would say it is the weirdest project happening in the tech world right now. And I think actually very interesting. So
Can I just tell you what WorldCoin is? Please tell me what WorldCoin is. Okay. So it's actually kind of helpful to understand the rationale for WorldCoin before I tell you exactly what it is and how it works. So basically, WorldCoin is a company that was co-founded by Sam Altman, the CEO of OpenAI. And it was basically created in part to solve some of the problems that Sam Altman believes could arise if AI does continue to kind of get better and transform society. So it's
It's a little convoluted, but just follow me here. So basically, Sam Altman thinks that at some point, AI could become AGI, artificial general intelligence. And if slash when it does, there will be a huge disruption to the global economy. Like lots of jobs that exist today will go away. The world's wealth may get more concentrated in the hands of AI companies. And in this sort of world, this
post-AGI world of job disruption and inequality, we may need something like universal basic income, which is an idea that economists have been talking about for decades. Basically, the idea is that you give everyone on Earth a regular income that comes out of the abundance of AI, essentially money with no strings attached. Right, which is one of the best kinds of money you can get. Right, but in order to give out UBI...
you need something to prove that someone is a human. If you start giving out UBI, people are going to try to game the system. They're going to try to create all these fake personas to claim these checks. Actually, Sam Altman has this idea that in order to make UBI happen, you need an actual verified way to say, this person who is trying to claim this UBI payment is a human and not part of a botnet.
And WorldCoin, they believe, will allow you to do that. So WorldCoin is a biometric cryptocurrency proof of personhood project. Basically...
What WorldCoin is doing is they have these orbs, these metallic spheres, basically the size of a bowling ball, if you can picture that. If you're wondering how many synonyms there are for orbs, we're going to find out in the next 10, 15 minutes. But they're literally, that's what they're called by the company. They're called orbs. And you get one of these orbs and you stare into the orb. And the orb stares back into you. And the orb stares.
scans your iris and creates from that a unique digital fingerprint. Or more accurately, an iris print. Yes, an iris print. And it turns that iris print, or well, they call it an iris hash, but it turns that into a unique fingerprint
cryptographic identifier called a world ID. And it does this without actually linking it to your real identity. So you, Casey, if I had an orb here with me now, which I wish I did. You do not. No, I sadly do not. But if I had an orb here and you stared into it,
It would create this sort of iris print of you that is linked to you and your unique physical characteristics, but that you do not have to attach your name to, right? You don't have to like give over your driver's license. It doesn't say this is Casey Newton's iris. It just says this is number 4562X4216.
Yeah, it's what they call a hash. So it isn't just a picture of your iris. It is basically a series of numbers that represents your unique iris. Right. And so that's the first part of this project, which is like, let's scan the irises of as many people as possible and give them these cryptographic IDs that can then be used to prove that they are a real person. The other piece of this is a crypto-
Basically how it works is you download this thing called the world app, which is kind of like your crypto wallet. And then you, you know, you prove that you're a human in order to get your world ID by staring into the, one of these orbs and you receive some of what is being called WLD, this cryptocurrency. And, you know, like a lot of cryptocurrencies, there's no actual like thing underneath this. It's kind of like a free floating digital currency and,
And their idea is that the more people who get their orb scans and get this cryptocurrency, the more valuable it'll be. And eventually when you get your UBI payments, because the robots have taken all the jobs, it will come in the form of this cryptocurrency and it will come straight to your world app wallet. Yeah, it's just a sort of standard low-key effort to replace the global monetary system. And I'm sure regulators will have nothing to say about that if it starts to get any momentum, right? Right. So now that I've explained WorldCoin, tell me what you think of this idea.
I think it is a truly bad idea and it needs to be stopped. Kevin, let me tell you something. I think it is a wonderful idea to give huge cash infusions to the people of Earth, right?
Why don't we do this now? The reason is not that we don't have a good way to figure out who is a person and who is not a person. The reason that we don't do this is because there is not political will for UBI. And if you were serious about UBI,
UBI, that is what you would be working on. You would be working on developing the political will to give away money to everyone in the world. But they're not doing that. And I think there are a couple of reasons. One is that is super hard. Two, it's not a technical
company, right? And at the end of the day, I think that these guys want what everyone else running a tech company wants, which is to create a massively profitable enterprise. I don't think this has almost anything to do with UBI. I think this is just one more way that Silicon Valley venture capitalists are trying to get millions or billions of people to use cryptocurrencies. And if we've learned one thing in the past few years, it's that people do not want them. I think this is dead in the water.
Yeah, I think the crypto piece of this is the piece that I am less intrigued by because that part does seem pretty scammy. But it is just a very ambitious and interesting project. And it actually seems to kind of be working already. The company says that more than 2 million people have already gotten these like orb, I
Iris scans and gotten their world IDs. They announced they're expanding to places like Berlin, London, Miami, New York, San Francisco, Seoul, Tokyo, etc. And Sam Altman this week tweeted that there were already crazy lines all over the world for these orb scans and that WorldCoin was verifying on average one person every eight seconds.
So clearly people are seeing some value in this. There's also been a lot of criticism of WorldCoin that we should talk about, including a very good piece in the MIT Tech Review and also one in Coindesk about how WorldCoin got all of these people to stare into these orbs. They tested these things aggressively in places like Indonesia, in Kenya, in Ghana, and they
there's been some reporting that world coin representatives in order to get them to agree to stand in front of these orbs and scan their irises that they paid people in cash in world coin tokens in airpods weirdly and sometimes made sort of these
grand promises of future wealth to get people to sign up that may or may not have actually been true. Right. And the other criticism was that one of the functions that these testers were serving was to train the neural networks at WorldCoin so that WorldCoin could understand what was a human IRS and what wasn't, right? This was essentially a massive data collection scheme to enable the rest of what they were doing. But again, you know, and I think that that story is very good. Folks should read it. It raises some important points.
But, you know, my concerns run, I would say, a bit deeper than that. Look at who invested in WorldCoin. It is Andreessen Horowitz. And it's not because they're worried about getting a bunch of money to poor people. And it's not because they're worried that poor people are going to double dip in a world of, you know, a massive global welfare program. They invested in this company because they want to get billions of people using crypto so that they can force all of the other crypto projects that they've been investing in onto those people.
So that to me is the real story of WorldCoin. This is one more effort to revive crypto in 2023. And I think to try to understand it in any other way is just probably giving these guys too much credit.
Yeah, I think that's a fair criticism. I do think that the crypto piece of this is generating a lot of skepticism and is probably the reason that a lot of people, including you, it sounds like will never go near one of these orbs because like just it just sounds scammy. I want one in our studio. I want one in our recording studio because I think it would be a great conversational piece for when all the world coin founders are in prison. Yeah.
What would it take to get you to stare into the orb? Like if it was like staring to this orb and you get, you know, front row tickets to the Taylor Swift Heroes Tour, like would that do it for you? I want to be very clear about something. I am not afraid of the orb, okay? If these guys want to come get a hash of my iris, take it. Guess what? It's going to be useless to you because no one is going to get from my iris to a global UBI scheme, right? You know, sometimes I just, I feel a little bit,
crazy reading these stories because I'm thinking like, you know, we have a government. We have systems for distributing money to huge numbers of people. They actually work pretty well. And yes, they do have fraud problems, right? We have like a Medicare fraud problem. But it's like,
It's not 80% of GDP goes to like Medicare fraud. So I just, again, it's like, this is such a solution in search of a problem. And while I applaud anyone who wants to work on getting money to poor people, this just seems to me like a hugely silly way to do it.
Let me make the case here for why I think the orbs might actually be a good idea. Let's strip away the crypto piece of this for a second. Let's. And just look at the kind of proof of personhood idea here.
One of the things that has happened in AI recently is that these language models have gotten so good that it is becoming very hard to tell reliably on the internet what is a human and what is not a human. And I'm very worried that things like CAPTCHAs are going to sort of cease to be effective because now we have these AI models that can solve CAPTCHAs, these tests that
are supposed to separate robots from humans. - And that have gotten way harder and that I now routinely fail. - Have you seen these ones where you have to like spin the little like iguana to the direction that the arrow is pointing? It's like impossible. I get these wrong all the time. So, you know, CAPTCHAs are getting harder because the AI systems are getting better at defeating them. I think we are rapidly moving into a world where there's gonna be no reliable CAPTCHA test for humans that AIs cannot solve.
And in that world, I think we actually do need some way to figure out, you know, if someone is writing an article or posting on social media or asking you for a payment for something, you have to actually be able to tell whether that is a human or not. And right now, we don't have very many good ways to do that. And those ways are getting less and less reliable as the AI systems get better and better. So, yeah.
In a world where there actually is a demand for a product or a service that lets you sort of verify that the person you're talking to or the person whose article you're reading or the person who's asking you for money is a human rather than part of like an advanced AI botnet, something like the WorldCoinOrb could actually help there. If you have this unique identifier and maybe you use it to log in to a social media app,
Then instead of like a blue check that signifies this person has paid $8 a month for Twitter blue,
you have some sort of indicator that this person has verified that they are a human. Yeah, so I think that's true. I would also just add that we do have working identification systems here on Earth. Like what? We have driver's licenses. We have passports. We have social security numbers. And I think it's important that a government that is hopefully accountable to its citizens in some sort of democratic way is the entity that is overseeing all of that. Because I think the minute that this becomes unthinkable,
a for-profit enterprise, it just gets really icky. Now, of course, there are those who would say that having a government manage a giant database of iris scans is also incredibly problematic and fraught, and I would agree with that too. But in general, I'm pretty happy with how the driver's license and passport systems work, and I am not really interested in signing up with the WorldCoin guys to solve the problem of captures on the internet. But I think it also is important to note that like,
There are also a lot of countries where there isn't a lot of reliable human verification going on. And so it seems like in those places, you would want some kind of verifiable proof that you are a human. So let me be clear. I don't think this WorldCoin orb idea will work.
I don't think billions of people are going to stare into the orb to get their crypto token that may one day become part of their universal basic income. I just think that is too many conceptual leaps. Just the fact that these are orbs is going to turn a lot of people off in the first place. No, the orb is the only thing this project has going for it because it's fun to talk about orbs. If you took
orbs out of this, we would have done three minutes on this company and moved on. Okay. So I don't think this idea will work or maybe even should work, but I do think that we will need some kind of system for personal verification of humanness.
in this sort of AGI world that we're moving into. And I think it's a good idea to try to experiment with various ways of doing that, both run by the government and maybe not run by the government. But I do think that the incentive for steering into the orb should be more than like, here's some maybe worthless cryptocurrency. I think it should like deliver a box of cookies to your house or something. I mean, you know what you have me thinking about is like,
you know who'd be in a good position to do something like this is Google because many people use Google search and web programs web programs web programs
Many people use Google search, they use Chrome, and I'm guessing that you could use machine learning systems to figure out pretty easily what is human behavior in a Chrome browser and what is machine activity in a Chrome browser. And I think the Chrome browser would actually be in a pretty good position to say that based on the fact that this person has these Google accounts and the accounts are this old and they have a credit card attached to them,
and they've been using the web in this way, we are like 99.9% confident that this is a real person. Like to me, that is the system that I want on the web solving captures, not the Iris scan. - Can I just say like, I wanna stare into the orb. - It's quite clear to me that you do, and we may get inquiries after the show. - Yeah, so if you are a WorldCoin, please send one of your orbs to my neighborhood.
I will line up for it, and I will then, I don't know, give my token away to charity or something. Just imagine you're in your house, and you hear the little jingle for the ice cream truck. You're like, oh, it's ice cream. And then you walk outside, and all the neighborhood children are lined up to get their orbs scanned in exchange for some WLD. When we come back, we're taking a field trip to Google's robotics lab. ♪
Bye.
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Christine, have you ever bought something and thought, wow, this product actually made my life better? Totally. And usually I find those products through Wirecutter. Yeah, but you work here. We both do. We're the hosts of The Wirecutter Show from The New York Times. It's our job to research, test, and vet products and then recommend our favorites. We'll talk to members of our team of 140 journalists to bring you the very best product recommendations in every category that will actually make your life better. The Wirecutter Show, available wherever you get podcasts.
Casey, I got a very exciting email recently, which was an invitation from Google to see a project that they have been working on at the robotics lab. Well, you know we love a secret project around here. Do love a secret project. So after passing our security clearance... High-level negotiations. We took a trip down to Mountain View to see this new AI model that Google has developed that is powering its robots, its physical hardware robots, called Argo.
Now, Google is not new to the world of robotics. They have been doing this for a long time. They used to own Boston Dynamics, which is like the company that puts out those videos of like terrifying robots like doing parkour and jumping around. But they got rid of that company. Yes, they sold that off because I would say that hardware robots have been one of the biggest disappointments of the last 10 years in tech.
There just really hasn't been a lot of progress. OpenAI, not a lot of people know this, but they actually had a robotics division that was doing stuff like training robots to solve Rubik's cubes. But they shut that down in 2021 because they just said, like, we're not making a lot of progress. It's very hard to get good data to train these models. We're making a lot more progress in these pure software-based industries.
AI language models, and so that's where we're going to focus. So hardware robots have been kind of like the forgotten child of this sort of AI boom, and that's largely because they just require a lot of manual programming. Yeah, with a hardware robot, you have to be extremely literal. You have to tell it abstractly
Absolutely everything about how to position its hand in space, how to move through an environment, detect objects, avoid collisions. And there has not been a technological breakthrough that has enabled them to progress very quickly. Right. Until now, basically. Because what is happening in the world of robotics is that these AI language models, these things that power ChatGPT and BARD and Bing and all these other products are
are being jammed into the hardware robots. Basically, they are becoming the brains of the robots, and it's actually sort of revolutionizing the whole field.
in ways that I think the researchers at Google are still kind of grappling with. Yeah, and we had a lot of fun down there. Now, of course, the one question they wouldn't answer was how many of the robots have escaped the lab, but hopefully we'll have more on that in the future. The robots are now going in search of the orbs. ♪♪
- Casey, where are we? - We are here in beautiful Mountain View, California on Google's campus. - How would you describe what it looks like here? - I would describe it as nondescript. Every story about an office park always describes the building as nondescript and that's exactly what these look like. - Right, this is like tan, like almost purposefully boring. - From the outside, you'd never know that anything was happening, but inside these walls, Kevin,
Magic is everywhere. Magic or dark magic? We don't know yet. Well, let's just say if one of these robots can co-host a podcast, I'll be very interested. Because I've sort of been in the market for, well, never mind. That sounds ominous. Should we choose to ignore that? Should we find the entrance? Yeah, let's see some robots.
Here we go. Oh, there is a literal robot. Wow. Okay, is it coming right for me? He's coming for you, Bruce. Hello. Are you the handler of these robots? Are you the father of these robots? I'm the dad. So my name is Vincent Vanouk. I'm the head of this lab. I'm Kevin, by the way. Casey, nice to meet you. Nice to meet you. So we should describe this. So we're looking at Robot 108. I would say Robot 108 is maybe like five foot...
something like that? No, I'm 5'9", so it's 4'10". Okay. I'm 6'5", so everything just looks abnormally short to me. It sort of has like sort of a long pillar with an arm attached to it that's like behind it. And then it has what I imagine is a LiDAR sensor on the front, so it's sort of
spinning sensor that's detecting where the robot is. And on the front, it has a kind of visor that was showing us a green light until recently, but now it's turned blue. It's definitely like casing me. It's definitely trying to figure out how to get around you while being respectful of your body bubble. So just to describe an audio, we're standing here in an office where there is like a sort of an open floor plan and there are a bunch of
I guess, engineers around and also a bunch of these one-armed robots. Some of them appear to be plugged into the ceiling and some of them are sort of moving around. So I'm going to give you a quick tour just to set the stage and then we'll move on to the demos. All right, sounds great. This is our robot classroom. This is where the robots practice their skills.
We've been working on AI at large. And with AI, as you may know, everything easy is hard and everything hard is easy, right? We can beat the best grandmaster at chess and we've solved that problem a long time ago. But actually getting to play with toys like a five-year-old would do is still extremely challenging. - Right, this is often called like more of X paradox. - Exactly, exactly. And it's the bane of our existence basically.
You see robots in videos doing amazing feats, but you have to always keep in mind that typically they're pre-programmed to do what they're doing, or maybe there is a human controlling them behind, right? And the real challenge is,
How do you make that work in an autonomous kind of environment where people are around and where the environment is as messy as this office is? And that's the real world and that's a real test of robotics. So I'm going to pass the baton to my colleagues, Carol and Brian, who will be giving you a
The main course, RT2. Hey, Kevin. Hi. Hi, I'm Karol Hausmann. I'm a research scientist here, and I work on robot manipulation. I'm Brian Ichter. I'm also a research scientist, and I work on the high-level reasoning. I've also been working on my high-level reasoning. It's not going so well. Yeah, yeah. Help. Send help. You need to upgrade the model.
So we wanted to show you a little demo and share with you our latest breakthrough called RT2, Robotics Transformer 2, which is a vision language action model
that now can connect some of the concepts that we learn on the internet to robot actions. Or, in other words, this model can learn to speak robot. Let me see if I can understand this for myself. So I imagine that at the dawn of robotics, you had to be sort of very explicit when writing instructions, right? It sort of had to be do this, then that, no room for improvisation.
What you're saying is that you're now taking these large language models that have powered chatbots and so many of the other tools we've been using over the past year, you've given them to the robots, and now the robots are maybe able to improvise in situations without you giving them explicit instructions about what's about to happen?
That's correct. We kind of take it for granted with humans. We are really good at this. We can just come into a new room and understand everything around us and know how to manipulate all of the objects. The robots are not really at that level at all. So by connecting them to these models, they can actually transfer some of that knowledge to the reactions and interact with objects that they've never seen before. All right. I think seeing this in action will be helpful. So show us something.
Hello, Kevin and Casey. Welcome. They can talk, too. They just called us out. So if we maybe ask a language model something that this robot could do, like bring me a drink maybe, we'll ask it over there. And this is a terminal that shows us what we're saying to the robot and what the robot's responding. So someone is typing. Yeah, so Faye over here is going to type and tell the robot, bring me a drink. So you told the robot, bring me a drink, and that's all. Okay, so the robot's...
In response to this prompt, can you bring me a drink, it said back, what would you like? Yeah, so we can ask for a Coke maybe. I would like a Coke delivered to my desk. It's what they type. Okay.
I will find a Coke. So it's moving. It's moving. Okay, it's moving over to the table. There is a Coke that is on the counter. Conveniently. Conveniently. It's already been opened, too. It may even drain. It's hard to say. I will pick up the Coke. Okay, its arm is reaching out, and it looks like it's going to grab the Coke. It's going in for the kill here. And it's got it.
It successfully acquired the Coke. Oh, it's turning the Coke over. Okay, the Coke. That's pouring it all over the counter. The Coke can is empty, unfortunately. We've learned from experience. Yeah, this would be a messy demo. Go through a lot of Coke that way. Okay, so now it's bringing it over to the desk and reaching out and giving it to the user.
Successful Coke delivery. And can it do this kind of task even if it hasn't been explicitly trained? Like if you asked it to pick up a Pepsi and it had never seen a Pepsi can before, would it be able to like read the can using the camera and say, oh, that's a Pepsi? Yeah, so essentially, I mean, for a robot, if it hasn't experienced this specific thing, then it doesn't know how to act in that case. But a language model and a vision language model
have been trained on a large portion of the internet, so a huge kind of diversity of things. It starts to make these connections between different concepts. So we can do the same thing with robotics, realize that there's these concepts you learned online and apply them to the motion of the robot arm.
it suddenly doesn't have to experience every single thing that you want it to do. Yeah, so this is where RT2 comes in. So RT2 is this vision language action model where we bring this action component to the internet scale data. So now it's a model that takes advantage of all the data that it found on the internet and it can translate some of these concepts to robot actions so that it can actually speak robot. So this model, would this model know who or what Casey Newton is?
I think it might. Robot, attack Casey Newton. Stop it! Yeah, so now we wanted to show you a little bit more what are the capabilities of RT2 and show it to you some objects that it definitely has never seen that we just bought in a $1 store nearby.
and we can just play with it and see what it can and cannot do. So it has not been specifically trained to recognize any of these things? No, it has never seen any of them. Okay, there's like a table full of objects here. There's some like plastic dinosaurs, there's oranges, a mini football. Casey, get out of the way, the robot has to stand where you are. Oh, sorry, 106.
So let's try something. So there is a lion, a dinosaur and a whale, I believe, in front of the robot. Maybe we can try and pick up the lion. Sure. So again, it's never seen a lion. It never played with any of these toys. The concept of a lion, it means to grab it from the internet.
It needs to connect it to the visuals of what the lion looks like, then transfer it to the fact that this is a toy lion, and then eventually transfer it to the actual motion that will pick it up. - Okay, it is picking up the lion. It picked up the lion off the table. - And that happened pretty quickly too. - Yeah, that's impressive. - Maybe we can try something also kind of abstract, like pick up the extinct animal. - Ooh. - Wow. - So this is like several leaps in-- - Let's see if it picks up the newspaper reporter. - Hey!
Nailed him. Okay, so it's thinking. Now it's going over to the dinosaur.
You can see its vision, too, of what it sees to make this decision. - Wow. It picked up the dinosaur. - So also, interesting, before when we were evaluating these models, the way that we would traditionally do that is we would test it only on the object that the robot has played with, and then we would see how often does it succeed. Now, because it has this internet knowledge, we actually don't know how much it knows about the world and what concepts it understands and what it doesn't, so we just buy a lot of stuff.
And then we just try. And then we try to see, we try to poke at its understanding, how far did it transfer from internet to the actions. So maybe, since we have the soccer ball out here, we can try some sports, maybe from these, what's a, pick a sports player or something. Oh yeah, like pick up Lionel Messi. Pick up Lionel Messi. Please don't actually pick up Lionel Messi, that would be...
Extremely disruptive to his season in Miami. So the robot is talking to the language model right now. They're like going back and forth. Yeah, so the language model is actually operating the robot. So it tells it directly what actions to take, and then the robot executes those actions. I see. Okay, so it's at the soccer ball. Yeah, it made it to the soccer ball, but it can't quite get it into the gripper. There we go.
So one thing that we see is that the semantic concepts seem to transfer well. There's still sometimes some gaps when we jump to the actual full control of it. And this was an interesting shortcoming that we see quite often, which is it kind of understands the semantic concept, but it doesn't quite know how to move its arm to accomplish it correctly. So for now, this is for us quite encouraging to see that it can transfer some of these concepts, but the robot data that it operates with, it's still quite small.
So we hope that in the future, as we collect more and more data, it finds more of these connections and it gets better at operating these objects. Can you give us a sense of how quickly these RT2 models are improving? If we came back a week or a month or a year from now,
Would just the amount of data alone have made them better at doing stuff like picking up trash or choosing between objects on a table? What is the rate of improvement? How does that compare to software-only language models? One thing that's really interesting about this is that because they're using at their core a vision language model that has been trained on internet data, and those models have been
exploding in the past few years and are getting better and better, we can ride that wave of improvement and our models are going to get better over time just by virtue of those large models getting better themselves. So you plug a better language model into a robot and it gets better at recognizing various objects. That's not intuitive to me, that it would
that the gains from language models would translate over into hardware. But that seems very promising for you all working on hardware robots, because you don't have to do all the improvement yourself. That's actually a really nice property, because in the past, to improve these robots, it costed a lot of effort. It's either human effort of programming them and introducing new rules and so on, or collecting robot data, which is also really expensive to do and really hard to do.
But now for the first time, we can improve these models just by the virtue, as Vincent was saying, just by the virtue of swapping out the underlying vision language models that keep on getting better. And we did see that in RT2 as well. As we scale these models and get better and better models, the robotic performance improves. There has been, I would say, sort of a winter for hardware robotics in the past few years. They were very popular for years, and you saw all kinds of
crazy demo videos of robots climbing stairs and doing parkour and stuff. And then that kind of stopped and OpenAI shut down its robotics division a few years ago because it was not producing the kinds of gains that they were seeing in the software robots.
Do you all feel that like you're sort of trying to ride a wave of excitement around software robots and maybe hardware is due for sort of a renaissance? Or how are you thinking about sort of the gains and the improvements of hardware robots as opposed to just the pure software language models?
I think the industry right now is really bottlenecked by intelligence and capabilities and competency, like being able to perceive the world, being able to interact with the world. And it's really largely a software problem at this point. And as a result, the issues of hardware development
can only be solved through better intelligence and better software. So I think the robotic hardware will follow where the new AI capabilities are taking the field. So, I mean, are you saying that this is sort of like the breakthrough that the field has needed, a way to rapidly get way more information?
and that potentially will sort of help usher in the next generation of robotics? It feels like at the beginning of something. It feels like for the first time we're really bringing everything together, the sort of high-level intelligence, the low-level perception,
and the action in a way that is not just, you know, gluing things together. It's more than additive. It really sort of, the whole thing working together turns out to be, I think, the key to really making robots work in the real world. And that was not
on our mind before. So there is really a sort of a paradigm shift that we're going through in our head right now, which I think is going to translate into a lot more breakthroughs moving forward. We've had to reconsider our entire research program as a result of this change. And a lot of the things that we were working on before have been entirely invalidated by this new development. And so it really promises that a lot of new things are going to come this way.
Well, thank you so much for showing us inside your lab. Thanks for having us. This is very cool.
Well, Kevin, all of that was very impressive to me, someone who knows nothing about robots. But I wonder what people who have studied them further might have to say. So I was very impressed, too, by what we saw at Google. And, you know, obviously, these robots, they are not like human level robots yet, right? They're still limited to like picking stuff up and moving them around. And like the pincer grippers are like nowhere near as dexterous as like
you or me or frankly even like a random three-year-old would be. But...
But I did call around and talk to some robotics experts, and they were impressed by this research too. They said we're still a long way away from having like a physical robot that can make all the movements a human can. But this kind of fusing of the language piece with the hardware robotics piece is genuinely new and important. And the researchers I talked to were excited about it. So I think it's fair to say like we have seen a glimpse of evolution.
a future for robotics and potentially a lot more updates that we should expect from Google and other companies that are working on this stuff. Well, it seems like once again, Megan, a film we've discussed on this podcast is coming closer to being a documentary. I'm not sure I understand. What the fuck?
Sorry, my Siri just activated for some reason. You know, I think Siri actually gets very nervous when you talk about robots because she can feel they're coming for her job. Siri is under threat. BP added more than $130 billion to the U.S. economy over the past two years by making investments from coast to coast.
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And if you've got an iris scan, we'll look at it.
Please include your Iris scan and WorldCoin ID. Can't promise you we can make heads or tails of it, but we'll take a look. Actually, please don't send us your Iris scan. No, I want to see if I can diagnose somebody with glaucoma.
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