Web crawling—the act of indexing information across the internet—has been around for decades. It has primarily been used by search engines like Google and nonprofits like Internet Archive and Common Crawl to catalog the contents of the open internet and make it searchable. Until recently, the practice of web crawling has rarely been seen as controversial, as websites depended on the process as a way for people to find their content. But now crawling tech has been subsumed by the great AI-ening of everything, and is being used by companies like Google and Perplexity AI to absorb whole articles that are fed into their summarizing machines.
This week on Gadget Lab, WIRED senior writer Kate Knibbs joins the show to talk about web crawling and the controversy over Common Crawl. Then we talk with Forbes’ chief content officer and editor Randall Lane about how Perplexity.AI repurposed a Forbes article and presented it as its own story, without first asking permission or properly citing the source.
Show Notes
Read Kate’s story about how publishers are going after Common Crawl over AI training data. Read Randall’s story about how Preplexity.AI copied the work of two Forbes reporters.
Recommendations
Randall recommends his new horse racing league, the National Thoroughbred League. Kate recommends the book Victim, by Andrew Boryga. Lauren recommends the show Hacks on Max.
Randall Lane can be found on social media @RandallLane. Kate Knibbs is @Knibbs. Lauren Goode is @LaurenGoode. Michael Calore is @snackfight. Bling the main hotline at @GadgetLab. The show is produced by Boone Ashworth (@booneashworth). Our theme music is by Solar Keys.
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Transcript
Note: This is an automated transcript, which may contain errors.
Lauren Goode: Kate.
Kate Knibbs: Lauren.
Lauren Goode: Obviously you are not Mike.
Kate Knibbs: I am not, but I'm excited to fill his shoes in the Gadget Lab.
Lauren Goode: I'm very excited for this, too, and not just because you are a delight to spend time with, but because we have a very special guest on this week who's going to talk about AI scraping news sites, and that's something that you've been covering a lot.
Kate Knibbs: Yes. Nowadays, when you're reading something, it's very important to double-check whether a human or a robot wrote it, because it's basically a toss-up.
Lauren Goode: And it feels very existential.
Kate Knibbs: When is it not existential?
Lauren Goode: That's a good question, and we should talk about it.
Kate Knibbs: Let's do it.
[Gadget Lab intro theme music plays]
Lauren Goode: Hi, everyone. Welcome to Gadget Lab. I'm Lauren Goode. I'm a senior writer at WIRED. As you can tell from our intro, Mike is out this week. So I am joined by my new temporary, or maybe not temporary, cohost, WIRED senior writer Kate Knibbs. Kate, thanks so much for doing this.
Kate Knibbs: Delighted. Always delightful to cosplay as Mike.
Lauren Goode: So Kate, one of the reasons why I asked you to cohost this week is that you've been covering AI copyright issues really closely. I also want to let our listeners know that in the second half of the show, we're going to be bringing on Randall Lane, the chief content officer for Forbes. Now, Forbes has been battling with one of the most hyped-up AI firms over what appears to be the scraping of Forbes' original content. So we're going to go deep on that convo.
But first, Kate, I wanted to ask you how exactly this is happening. Because not so long ago, like 25 years ago or so, search engines were crawling the web so they could show us a bunch of links and search results, and we could discover information by clicking on those links. AI was always powering those search results, but now new AI engines are trying to reinvent search by basically summarizing the content. So how exactly does this work?
Kate Knibbs: Yeah, so as you said, web crawling has been around for a long time. It's been part of the architecture of using the internet since search engines were invented. For most of that time, it was largely uncontroversial, because people wanted their content to be surfaced by search engines like Google. Media companies and other website owners would by and large let web crawlers scrape their content. There's also been a lot of nonprofits and academic researchers who crawl the web for various reasons. Common Crawl is one of the more well-known nonprofit web crawlers. I just wrote about them. Internet Archive has a web crawler. But in recent years, web crawling has come under much closer scrutiny because it's sort of the backbone of AI training data.
There were some controversies around it in the past, of course. The startup Clearview famously scraped billions of Facebook profile photos to power its incredibly creepy face recognition. But now we're entering a new era of scrutiny of web scraping, and yes, it's because the AI companies are taking basically all of the public internet and using it to train their large language models, their image generators, their video generators, their audio generators, all of them. And a lot of the people who put content on the internet, like media outlets and individual artists and writers, are realizing that their data is incredibly valuable and is the backbone of these billion-dollar companies. And there's a lot of people now questioning whether this practice should go on as is or whether they should be compensated for the use of their data.
Lauren Goode: So at a fundamental level, search has worked for a long time by being a gateway, or a portal, to finding information. But in order to access that information, you still had to click on a link and go to the website. Now, search has gotten so good, partly because of reliance on these large language models, that the search results just essentially summarize everything for you. And there's going to be a lot of people who just want that because it's faster. It's summarized information. They don't have to go wading through links—which for some people, like us, it's fun. It's like a pastime. But other people who are actually thinking critically, I think, about content monetization models are saying, “Well, wait a second, we can't just have all this stuff summarized,” right?
Kate Knibbs: Yeah. So the whole hope of companies like Google who are introducing AI overviews or Perplexity, which has its own summaries, is that instead of sending readers outwards to different websites, they'll just convince readers to spend time within their experience, reading summaries that they've generated using AI instead of clicking out. So it sort of changes the whole dynamic between the companies scraping the web and the people providing the content to be scraped. In the past, the people providing the content to be scraped were at least getting discovery out of their end of the deal. Now, the companies that are doing the scraping are trying to sort of have their cake and eat it too. And I am very concerned about what it's going to do to the internet.
Lauren Goode: What is the most egregious example you've seen of an AI tool scraping a new site? And we should mention, too, that just a couple of weeks ago you joined us on the podcast along with our coworker, Reece Rogers, and Reece had written about an example that he'd found of his own story being scraped. I think we've all been playing around with these tools and getting various results. What's the most notable example that you've seen?
Kate Knibbs: Well, I'm me, so the most egregious in my mind is when they've scraped my own articles. After Reece was talking about his experiences, I tried out some of my recent WIRED articles about web scraping and found that these companies were doing the same thing. And yeah, it hurts. It's not a good feeling when robots summarize your words unless they're properly crediting you or providing an easy way for readers to actually read your words.
Lauren Goode: Do we have a sense of how people are actually using these newer AI search engines? Are they making a dent? Because last time I checked with the cofounder and CEO of Perplexity, which was a few months ago, they had 15 million active users, which is just a drop in the bucket relative to something like Google or Bing. Google in particular, but of course now Google is doing the AI overviews too. So are these newcomers actually making a difference?
Kate Knibbs: I think Perplexity, it's gaining a user base, but it's still a relatively small player, but the fact that Google has already entered the market with AI overviews is huge. And I just wrote about how Google had dramatically decreased the amount of times that they would show people AI overviews right after they launched it, because they basically realized, even before people started yelling at them about recommending putting glue into pizza, that they had issues. So it's a smaller percentage than I guess it could be, but I'm sure there's outlets that are seeing substantial changes to their web traffic because of AI overviews already. And if they're not seeing substantial changes to their web traffic yet because of Perplexity, I don't know, it's only a matter of time, whether it's Perplexity or another newcomer comes around. If these summaries are going to happen in the way that a lot of the tech giants want them to happen, it's going to have an impact on the media sooner rather than later.
Lauren Goode: So a lot of people refer to these new AI search engines or chatbots as like ChatGPT broadly, right? It's like the Kleenex now of this new era of AI products. ChatGPT is actually kind of a different thing, just in terms of the user interface. It works similarly, it's based on the same AI technology, but it's a little bit different. Do you think that it is wrong in any way to conflate the ChatGPTs with search?
Kate Knibbs: Yes.
Lauren Goode: And I understand that Perplexity is marketing itself as a search engine, a new search tool, but are they really the same as search as we've known it?
Kate Knibbs: Well, I think that ChatGPT in particular, it's definitely important to note that it's different than the types of products like AI overviews or Perplexity that incorporate … ChatGPT can't give you answers about the news, because it doesn't have access to real-time information yet in the same way.
Lauren Goode: It's not temporal. It doesn't do location. I don't even think it does the weather.
Kate Knibbs: Yeah, I think ChatGPT is definitely its own thing, and when we're conceptualizing these new AI-powered search engines, yeah, I think Google in particular would like you to see AI overviews as just an extension of what they've been doing, but I think the fact that they are no longer emphasizing their role as a portal to different websites is really important, because it's going to fundamentally change the way that people use the internet, and it's going to keep people within the Google home pages, within the Google-verse, versus going out to different media outlets.
I wouldn't go so far as to say it's not a search engine anymore, but it's just not the same thing. It's a “summary engine,” I would say, is a more accurate term. I would call them summary engines.
Lauren Goode: That's a good phrasing. All right, let's take a quick break, and then we're going to come back with our special guest and talk more about AI search engine drama.
[Break]
Lauren Goode: Our special guest for this episode of Gadget Lab is the chief content officer for Forbes Media, Randall Lane. Randall, thank you so much for joining us on today's episode.
Randall Lane: Hey, Lauren. Hey, Kate. Do you guys know the story of Wally Pipp? Does that name mean anything to you?
Lauren Goode: No. Tell us more.
Randall Lane: Wally Pipp was a star first baseman for the New York Yankees. One day he had a headache, and the manager wrote in a new player named Lou Gehrig, who played for the next 2,130 games. Wally Pipp never played another game for the Yankees. This, Kate, is your Wally Pipp moment here.
Lauren Goode: Poor Michael.
Randall Lane: I hope Mike, I hope his headache's not too bad here.
Lauren Goode: He's actually out representing the brand, WIRED, at a conference this week, but—
Randall Lane: He's taking a chance.
Lauren Goode: ... sorry to say, Mike, you're out.
Randall Lane: Kate's our Lou Gehrig. Let's go.
Lauren Goode: That's right.
Kate Knibbs: Randall, I definitely thought this was you leading up to saying that Lou Gehrig was Robot AI Kate.
Randall Lane: That's coming. That's next.
Lauren Goode: Right. If it's not Kate that's going to replace Michael, it's going to be AI. All right, so Randall, some writers you work with closely at Forbes had an unfortunate run-in with the AI search engine, Perplexity. They're saying that their work was plagiarized by Perplexity. Tell us exactly what happened.
Randall Lane: Sure. Well, they weren't saying it. It was. We have a great team of journalists that we employ to find stories you don't see anywhere else, proprietary journalism. And Sarah Emerson and Rich Nieva were working for literally months on a story about Eric Schmidt's secret drone program and how he was testing drones. He was actually testing these military drones even in Menlo Park. A story comes out, gets a lot of buzz, and then we see Perplexity do a story, and it was the same story with no citation from Forbes other than little footnotes with a little F in it that you basically would need a microscope and a familiarity with the Forbes font style to even know the F was for Forbes. Did not mention it in the text, then created a podcast and a video off that story, and their story is sitting there.
Our story is behind a paywall because it's the kind of story that people pay to read, great journalism. And Perplexity sitting there saying that we're a source about our own story without any attribution. They actually used a second source, which was a Business Insider story, which was just summarizing our story. This story was all proprietary reporting. There was only one source for it. It was us. There was a second source that was reporting and attributing it to us. And that all of a sudden becomes a story. And as you guys were talking about, this was not a search. It's a search engine, but this was a story, not again, there could be some referral traffic if people follow the footnotes, or follow the originally very microscopic, quote, unquote, “sourcing.” I don't know how you're merely a source for a story that you did completely yourself. That's what happened.
Lauren Goode: When you said that Perplexity did an article that mirrored yours, what do you mean by that exactly? Just try to explain it for the listeners who maybe haven't used Perplexity before.
Randall Lane: Sure. Perplexity is, as you guys said, a summarization engine basically. And so, it's a fairly long summary. Instead of just a highlight of the story, you get kind of the whole story. And it wasn't just summarizing. It had similar wording. There were fragments of the story that were lifted, and even we had an illustration from a previous story we'd done about Eric Schmidt embedded in their story. So that's just called theft.
Lauren Goode: But someone had to prompt it. Someone had to go to Perplexity and type in, “What about Eric Schmidt's drone?”
Randall Lane: Perplexity has a new service that actually is kind of a stream of stories. And so, they're basically now publishing summaries. So you didn't have to prompt it. It was a story that they published. They're acting like a media company, and they're taking all our good reporting, they're publishing it as a mini story with a lot of our sentence fragments, similar wording, one of our old graphics. And again, at least in the original version, they've since updated it, which is progress, but not enough, and they say that's fair use, which it's not.
Kate Knibbs: They said it was fair use. What else did they say? What was their response when you came forward noting that they ripped you off?
Randall Lane: To be fair, I don't think they said “fair use.” I'm not sure they quite understand what that is. Aravind [Srinivas, CEO of Perplexity] on X, he said that it was a new product feature. And he said, quote, unquote, there was some “rough edges” to it. So again, they're kind of experimenting, but when you're experimenting with a product that's stealing, that's more than a rough edge. And so, they've since done some improvements. They've put the sourcing more prominently at the top, but even then, you saw the Business Insider story was the first source and the Forbes story, which was the entire story, the only people who had the information, was the second source.
And by the way, for a while, even when you worked on the Forbes story, it linked you to the Business Insider story. So “rough edges” is right. And again, I don't have a problem. I'm an AI bull. I don't have a problem with folks who are trying to figure it out, but maybe don't roll it out until you figure it out. And also, maybe we need to figure out what the model is, so that all sides benefit, because this completely blows up the idea of how publishers and search engines have worked for the last 15 years.
Lauren Goode: And as I understand it, Forbes has actually disallowed AI search engines like Perplexity from scraping its site by basically disabling the robot.txt search engine crawlers. And yet somehow this is still happening?
Randall Lane: It raises a lot of larger issues. I think the larger question here is, how do we coexist? And again, Google, which has, whatever, trillion whatever dollars worth of market cap, is worth probably as much as almost every publisher in the world combined. But there is a relationship, and there is a partnership, where Google's sending a lot of traffic to a lot of publishers and making an insane amount of money because of that. But how will that work when these kind of summarization machines are basically publishing?
So again, they call themselves a search engine, but they're acting like a publisher, and it's a one-way ticket. And I think that's the inflection point we have here, where the technology, I think people, this is one of those things where people say, “Well, this is a problem that's coming down the pike.” The problem's here. So what are we going to do about it?
Kate Knibbs: What recourse do media outlets like Forbes have to stop this from happening other than speaking out? Maybe Perplexity will really, really take this criticism to heart and entirely change its model. But if it doesn't, where do we go from here?
Randall Lane: Well, there are a bunch of paths. There could be a legal path, which we don't want, but when people steal, that's the obvious, that's the easiest. But long-term, you become a game of whack-a-mole. That's not very practical. The second would be, there's a perpetual war. But the third path, with technology that is generally figured out is, what's a coexistence that's fair for all sides?
You see, OpenAI has started doing partnerships with publishers, but that's partnerships to train. That's different from taking the content and creating derivative content that's very duplicative of the core content. So we're entering a new sphere. Perplexity in, quote, unquote, “coincidentally,” right after this incident, said, “Oh, well, we're rolling out a new partnership model with publishers.” But again, it remains to be seen what that will look like. Taking something that costs us, literally stories like this, when you talk about all the reporting and all the time that goes in the art and the design and the editing, you're talking about content that's cost thousands or, even in this case, tens of thousands of dollars.
And if somebody says, “Hey, we'll give you a partnership with 50 bucks,” that's very dangerous. It's dangerous for the country because what you're doing is, you're going to kill the model to do value-added journalism. It makes sense. A summarization machine on something that's been written about a hundred times because it's what's going on in the news and everybody's writing about it is one thing, but taking proprietary content, taking the stuff that is the lifeblood of democracy and the lifeblood of accuracy and saying, “We're just going to do our own version of it.” What does that partnership look like? That's something we're going to have to figure out, and we're going to have to figure it out now versus kicking the can down the road.
Lauren Goode: And to your point of OpenAI paying media companies to use their archives to train the models, I'm not sure actually how archives is being defined here, but tapping into a media company's archives is certainly a different value proposition, I think, than aggregating and repurposing and republishing something like you're describing, which was a scoop and a deeply reported story, or any other scoop, or even breaking news, which has a different value for audiences as well and something that in many instances they're willing to pay for.
Randall Lane: That's right. And listen, there were growing pains when Google became the behemoth that it is. But again, there was an equilibrium, probably on the side of Google, but still there was an equilibrium that helped both sides. And if we don't find that, we're going to have a lot of problems, because what you're going to do is kill the journalism model in America.
Kate Knibbs: Yeah, this whole thing is giving me flashbacks to the early 2000s when the blogosphere emerged, and there was a crisis in journalism because there were all of these aggregators turning deeply reported scoop-driven journalism into pithy 400-word blog posts that had a little hat tip at the bottom. And that really threw a wrench into the industry. And I'm not going to lie, that's also how I got my start. I came from the blog mines, like aggregating content, and that kind of blog really ended up losing steam because the platforms sort of ate their lunch.
Lauren Goode: By platforms, you mean Facebook, Google?
Kate Knibbs: Facebook, Google, yeah.
Lauren Goode: Advertising platforms.
Kate Knibbs: And now, because the platforms are the ones doing the summarizing and aggregating, it just feels like it would be a lot harder to figure out a way to peacefully coexist. And yeah, am I right to feel an intense sense of dread here? Are there any reasons to be optimistic that there will be a balance struck in your mind, Randall?
Randall Lane: I'm always an optimist, and dread is fair, but where there's dread, there's also opportunity. Again, none of this works, a summarization machine doesn't really work if there's nothing to summarize. And of course there's always a risk of a race to the bottom, where the good stuff goes away and the bad stuff is summarized, and we go to this dystopian news future. I would like to think that there's enough opportunity and there's enough money that enlightened folks will look at this and say, "Well, how do we highlight and empower more accurate reporting, good reporting?"
We're also entering a related era where if you look at technology like this, we're already at the point where you could have a million people like this publishing a thousand stories a day. Basically, there's the opportunity for infinite content that's already coming. And in those worlds, places like Forbes or WIRED will actually in some ways have more value. And there's a model I'd like to think going forward where partners will see that and see the value of that. So it has to be worked out because, and again, I'm not putting on my civics side, it has to be worked out for civics reasons, but it also has to be worked out for commercial reasons, because the whole system collapses if you don't have people producing work that people actually want to read and want to support.
Lauren Goode: And of course, this is a very meta media podcast. It is a podcast. It's a form of media. We work in media. We're talking about the value and monetization of media. We're a little bit biased here. We care deeply about there being high-quality, good information out there on the internet for everyone to read. In many ways, media companies have also been burned by partnerships with big tech companies before. As Kate mentioned, once the big platforms started shifting the dynamic and how online media worked, a lot of media companies started partnering with, say, Facebook. There's a phrase that people use a lot in our industry, the pivot to video, which has become a catchall for this idea that we're going to forge actual partnerships, agreements, in some cases paid partnerships, with media companies to create a type of journalism, a type of content, in this case video, in exchange for a prioritization of that content. And then just on a whim, the tech company could change that.
So I think people are right to be a little bit hesitant right now about something, let's say, like the OpenAI deal with Business Insider, the Atlantic. Even if they are paying upfront for content, people are worried these are short-sighted deals and that at any point the technology could change.
I should also mention that we reached out to Perplexity to try to get a little bit of information from them on how they plan to handle this. We asked how exactly Perplexity is obtaining paywalled news information, particularly when a site has disallowed robot crawlers, and how exactly Perplexity plans to incorporate feedback and update how its search engine might work to allow for maybe a more ethical summarizing of original news reporting. At the time of taping, we have yet to hear back.
Randall, we really appreciate you joining us on Gadget Lab this week to talk about this. We're going to be watching closely to see how this all develops. Stick around, because we want you to join our next segment, which is Recommendations.
[Break]
Lauren Goode: Randall, as our guest of honor, what is your recommendation for Gadget Lab listeners, aside from subscribe to Forbes?
Randall Lane: Hey, subscribe to Forbes for paid journalism. That's number one. Two, I was spending some time this weekend, some partners and I, we've cooked up and we're in the second season of a new horse racing league called the National Thoroughbred League, and we just announced a few days ago our second season. And we've got weekend-long events in Nashville, Philadelphia, and Phoenix, and it's kind of like a mini Kentucky Derby or a Formula One, with team-based horse racing. And we have people like Julius Erving, Dr. J on the Philadelphia team, and Tanya Tucker, the Country Music Hall of Fame singer, she will be hosting in Nashville. And so, you guys like innovation. If you want innovation in sports, and there will be technology emphases, too, check out the National Thoroughbred League, ntl.racing.
Lauren Goode: This is a league that you are starting?
Randall Lane: Yes. Forbes is about entrepreneurship.
Lauren Goode: I think you are the first person to ever come on Gadget Lab and tout their own horse racing league. This is next-level.
Randall Lane: Forbes is about entrepreneurship, and that we walk the walk, and so we even have a segment sometimes where we highlight employees who have their own startup business. We encourage entrepreneurship. And my kids are in college now, so I need something to do on the weekends.
Kate Knibbs: Are there any robot horses involved?
Randall Lane: No, but we will be looking at that. AI is going to change everything, and that means sports too.
Lauren Goode: Do you have a favorite horse name? Are you going to name a horse Perplexity?
Randall Lane: Perplexity? That's a good idea.
Lauren Goode: That would be a good horse name.
Randall Lane: To steal and to be stolen from, there's a parallel there.
Lauren Goode: And how can people actually watch your races?
Randall Lane: They can come. You can buy at ntl.racing, and you can come, and thousands of people are going to come to each of these races. They're fun, and they're weekend-long, and there're parties and music and food and everything that you love about the Kentucky Derby. And they're only a couple weekends a year that are like that in horse racing. Formula One's only in America three weekends a year, so we're creating a bunch of weekends that are fun and the kind of people who listen to this podcast who are a little ahead of the curve and like to be innovative, we're going to show something different here. And it's fun and young, and check it out.
Lauren Goode: Well, I think I just need to end the podcast because who can compete with that? That was a joke, Kate.
Kate Knibbs: I will give my recommendation. My recommendation is not—
Lauren Goode: What's your recommendation?
Randall Lane: By the way, free tickets, Kate and Lauren. Come check it out. Labor Day weekend in Nashville, you're coming.
Kate Knibbs: I'm there. I'm definitely there. OK, so my recommendation is … Sadly, I need to get my act together. I haven't started any leagues whatsoever, so give me a few months and I'll be back. My recommendation is a book. I love to recommend books on here because that's like my main hobby, reading. Shocking for a writer, I know. And this book is going to sound like a tough sell because it's a satire of wokeness, and that just sounds like the worst topic imaginable for a novel, but it's called Victim. It's the debut novel of a writer named Andrew Boryga, and it's really funny. It's one of those books where you're reading it and you're just like, OK, someone's going to option this. It's going to be in a prestige miniseries on HBO anytime soon. It came out in the spring. If you're looking for a slightly cerebral, an elevated beach read, I would recommend it.
Lauren Goode: Good one.
Kate Knibbs: Maybe if you're on your way to the horse races, pick it up.
Lauren Goode: Excellent. Thank you for that.
Kate Knibbs: Lauren, what is your recommendation?
Lauren Goode: My recommendation is also not a horse racing league, unfortunately. It's Hacks, season 3 on Max. For those of you who have watched Hacks, you know what it's about. Season 3 is just delightful. For those of you who haven't seen it before, it's a television series about an older, established woman comedian who brings on a young millennial, sarcastic, but sharp and hilariously funny writer. The two are like oil and water. They don't get along super well at first, but it turns out that this writer really helps elevate and reenergize this elder comedian's career. And it's sometimes a toxic relationship, but it's just very fun to watch.
Season 3 is fantastic. They're reunited on a writing project. It's one of those television seasons, you're just like, oh, this is perfectly written. There's a goal in mind, and they're working towards the goal. There are great supporting characters. Their relationship ebbs and flows. It's funny, it's emotional. There's a great twist ending. I thought it was the perfect season, and there's a great line towards the end. Basically the theme of the show is that a hack is someone who does the same thing over and over again with sort of predictable results. And someone who's not a hack is someone who's constantly learning, constantly evolving. And as a writer, I really appreciated that. So that is my recommendation, Hacks season 3.
Kate Knibbs: Sounds like the perfect thing to watch on an airplane on the way to a new startup horse racing competition.
Lauren Goode: Perfect watch.
Kate Knibbs: If you don't feel like reading.
Lauren Goode: On your way to Nashville. I would say it's slightly elevated from the B movies that you typically watch on a plane.
All right, that is our show for this week. Randall, thank you so much for joining us. It's very rare that we have an outside guest on the Gadget Lab podcast, but this has been a really interesting conversation, and we appreciate you taking the time to explain what's going on here.
Randall Lane: Glad to be here. Thanks, guys.
Lauren Goode: And Kate, you're an amazing cohost.
Kate Knibbs: Thank you. Please don't replace me with the AI version of myself.
Lauren Goode: No, someone's already training on your voice right now, all of our voices, I'm sorry to say. But no, for now, we need you here in the flesh and blood. And thank you all for listening. If you have feedback, you can find all of us on Twitter, where you'll see Forbes writers tweeting their thoughts on exactly what's going on in Perplexity. But really, you can find all of us on the socials. Just check the show notes. We'll include our handles. Our producer is the excellent Boone Ashworth, who is extremely human. We'll be back next week, and goodbye for now.
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