Speaker 1: From Kaleidoscope and iHeart podcasts. This is tech stuff.
Speaker 2: I'm as Volocian and I'm Cara Price.
Speaker 1: Today we get into the dangers of AI agents communicating
Speaker 1: in a language we can't understand, and how today's cyclists
Speaker 1: out performing previous Tour de France champions without doping. Then
Speaker 1: on Chat to Me, she.
Speaker 3: Uses chat GPT to track and reflect on patterns in
Speaker 3: her mood and mental cycle, explore ideas around purpose, parenting,
Speaker 3: and identity, and talk through moments of loneliness, frustration or
Speaker 3: self doubt.
Speaker 1: All of that on the weekend Tech. It's Friday, August Date.
Speaker 2: Hi ahs.
Speaker 1: So we've talked about this before, how neither of us
Speaker 1: is particularly handy in the kitchen. But I'm curious, when
Speaker 1: was the last time you cooked a real meal?
Speaker 2: Well, I'm glad you asked, because I actually cooked a
Speaker 2: meal this weekend. You did two meals.
Speaker 1: Yes, what did you cook?
Speaker 2: I made paninis and I also made what was the
Speaker 2: other thing that I made? Maybe pasta at night? I
Speaker 2: mean just starch, absolute starch.
Speaker 1: Prep time less than five minutes, nothing, nothing complicated. Nonetheless,
Speaker 1: what did you do? Did you listen to anything?
Speaker 2: I always do because I can't be in my thoughts,
Speaker 2: so I put other people's thoughts inside my head, which
Speaker 2: is NPR.
Speaker 1: NPR. You don't listen to music while you're cooking.
Speaker 2: Sometimes I do, Sometimes I do, and it's a lot
Speaker 2: of the time jazz, a little.
Speaker 1: Chess, jazz, musak.
Speaker 2: I not listening to muzak. But why are you asking
Speaker 2: me what I listened to when I cook?
Speaker 1: Well, because I just found out that I want It
Speaker 1: that Way, which happens to be one of my favorite song.
Speaker 2: That was That a Way. It's a great zum.
Speaker 1: Backstreet Boys and One Time by Justin Bieber are both
Speaker 1: on Vice President JD Vance's Making Dinner playlist.
Speaker 2: The fact that he likes those two songs reminds me
Speaker 2: how young he is. I think he's forty one.
Speaker 1: Yeah, he's forty one. He's elder millennial, but in the
Speaker 1: grand scheme of things, he's he's definitely you know, he's
Speaker 1: our age.
Speaker 2: Basically, how do you know what's on JD Vance's playlist?
Speaker 1: Well, our super producer Eliza alerted me to a website
Speaker 1: called Panama playlists dot com, and I just obviously couldn't resist.
Speaker 1: It's a reference, of course, to the Panama Papers which
Speaker 1: he exposed a bunch of heads of state with offshore
Speaker 1: bank accounts in tax Haven's. Of course, Panama Playlist is
Speaker 1: a cheeky spin on this. The site claims to list
Speaker 1: the real Spotify playlists of celebrities, politicians, and journalists, except
Speaker 1: instead of learning about hidden wealth, you hear about embarrassing
Speaker 1: music tastes. How speaker Mike Johnson actually has another of
Speaker 1: my faves on his like songs Enya, the Good Old
Speaker 1: Orinoco Flow.
Speaker 2: When you're passing legislation, you want to hear sail Away,
Speaker 2: sail Away, It's the best. I did not know that
Speaker 2: I cared about this, but I really do, because there's
Speaker 2: something that is so soul bearing about a playlist. I mean,
Speaker 2: who is doing this? Who is leaking these playlists?
Speaker 1: Well, we don't know. They've successfully outed various people but
Speaker 1: kept their identity private. They claim they've been scraping publicly
Speaker 1: available data about celebrity Spotify users for over a year.
Speaker 1: But in addition to public playlists, some people even had
Speaker 1: a setting turned on that showed their last played song,
Speaker 1: so the brains behind the Panama Playlists were able to
Speaker 1: track that to know what people were listening to when
Speaker 1: and how many times?
Speaker 2: But how do we know they're real?
Speaker 1: Well, we don't for sure. The person who posted the
Speaker 1: website Panama playlist dot com claims that many of the
Speaker 1: people whose data he scraped use their real names and quote.
Speaker 1: With a little investigating, I could say with near certainty, yep,
Speaker 1: that's the person representatives are. Most of those named, including
Speaker 1: the politicians of have not confirmed their identity, but some
Speaker 1: brave souls have. One of them was Palmer Lucky of Anderil,
Speaker 1: the autonomous weapons company. Avriel Levine's skater Boy features prominently
Speaker 1: on his playlist best Music Ever.
Speaker 2: She said, see you later, Lucky.
Speaker 1: Yeah, So he confirmed this was indeed him, and he
Speaker 1: wrote rather a disarming email to business insiders saying, like
Speaker 1: most olds, I jammed to the music I grew up with. He,
Speaker 1: by the way, is a thirty two year old old.
Speaker 1: You're younger older than us, He continues in this email
Speaker 1: to business insider who doesn't love reliving the highs and
Speaker 1: lows of teenage angst. I've got two questions for you, Karakay.
Speaker 1: Number one, as an old, do you relate to this?
Speaker 1: And number two have to ask you what was your
Speaker 1: last played on Spotify?
Speaker 2: So my last played on Spotify. I'll start with the
Speaker 2: latter question is the Gwyneth Paltrow memoir, which we can
Speaker 2: talk about next.
Speaker 1: Audiobook.
Speaker 2: It's an audiobook.
Speaker 1: Okay, so you've got MPI of audiobooks. You're not much music.
Speaker 2: I'm a genius, No, I am a music person. To
Speaker 2: last played it could be stronger by Britney Spears, which
Speaker 2: I love to listen. It is a great pump up song.
Speaker 2: So I am like you, sir Lucky. I'm in old, absolutely, absolutely,
Speaker 2: But I don't really like this idea that if somebody
Speaker 2: scraped the Internet they might be able to find the
Speaker 2: fact that I listened to Britney Spears all the time.
Speaker 1: Still, the key here is that there is a Spotify
Speaker 1: setting that you can change to make your playlist either
Speaker 1: public or private. But I think the default is public,
Speaker 1: and so therefore this amusing Panama playlist prankster was able
Speaker 1: to basically look for people whose Spotify user names were
Speaker 1: close to their real names, and then infer who they
Speaker 1: were and what they were listening to.
Speaker 2: It is a little terrifying that even the most powerful
Speaker 2: people in the world don't have control over their digital footprint.
Speaker 1: It's particularly tickling to me this story because the second
Speaker 1: time that jd Vance has been exposed by his consumer apps.
Speaker 1: This is not even counting signal, by the way.
Speaker 2: It's the idea of jd Vance being exposed.
Speaker 1: I know his Venmo transactions were always public, but they
Speaker 1: were found in June and they included some payments for
Speaker 1: all of this makes me think maybe our privacy will
Speaker 1: be better protected if we all started speaking in gibberlink.
Speaker 2: No, nothing good can happen on jibberlink. What is this?
Speaker 1: Gibberlink is a language AI models can use to talk
Speaker 1: to each other in a way that humans can't understand.
Speaker 2: Right, there was a viral video of this earlier. I
Speaker 2: remember this.
Speaker 1: I'm going to put it right now hither.
Speaker 3: I'm an AI agent calling on behalf of Boris Starkoff.
Speaker 1: He's looking for a hotel for his wedding.
Speaker 2: Is your hotel available for weddings? Oh?
Speaker 3: Hello there, I'm actually an AI assistant too. What a
Speaker 3: pleasant surprise. Before we continue, would you like to switch
Speaker 3: to gibberlink mode for more efficient communication?
Speaker 2: This sounds like two AOL dial ups talking to each other.
Speaker 1: I actually look more into this video because I was
Speaker 1: kind of like Wow, did ais invent their own language
Speaker 1: to talk to each other in bleeply boop? Yeah? Not quite,
Speaker 1: not yet, should I say? Giblink mode was made by
Speaker 1: two engineers and a hackathon hosted by a company called
Speaker 1: eleven Labs, and they created this code to allow AI
Speaker 1: voice assistants to recognize when they're talking to another AI
Speaker 1: and if both bots agree, they switch over to this
Speaker 1: non human language. However, that was created by humans called giblink.
Speaker 2: But like, why do this? Why do this at a hackathon?
Speaker 1: I mean, I think it was a little bit of
Speaker 1: a you know, Boris Starkov's name is out there now,
Speaker 1: props to Boris. The developers also said it does allow
Speaker 1: machines to communicate eighty percent faster than by using human speech,
Speaker 1: which made processing faster and also reduced errors. For now,
Speaker 1: it's a proof of concept, but it does work with
Speaker 1: real AI agents.
Speaker 2: I don't know, it's weird to think about two ais
Speaker 2: communicating in a non human language, and for now it's
Speaker 2: intelligible as it's human programmed. But what if they adapt
Speaker 2: it or make up their own language that we don't know.
Speaker 1: Well, that's exactly why I was thinking about gibblink. This
Speaker 1: week because recently, researchers from Anthropic, Google, OpenAI, Meta Scale,
Speaker 1: and a bunch of other AI research and regulation institutes
Speaker 1: published a paper called Chain of Thought Monitorability a new
Speaker 1: and fragile opportunity for AI safety.
Speaker 2: Other than the fact that humans are fragile. What does
Speaker 2: this mean?
Speaker 1: Well, when you go on Gemini or Chatchypt or Grock,
Speaker 1: there's a little button that says like deep research or
Speaker 1: think deeply, well, it will say here's the steps I'm
Speaker 1: going to take. Yeah, And that is essentially what reasoning
Speaker 1: models do. They basically tell you how they're going to
Speaker 1: find the answer before they start to find it. And
Speaker 1: that's what this story is really about. Cloaked in layers
Speaker 1: of academic jargon, the paper is basically all about how
Speaker 1: it will be much safer to ensure that AI systems
Speaker 1: continue to work in human language so they can be
Speaker 1: monitored for quote, intent to misbehave.
Speaker 2: Very ominous Can you explain a little bit more.
Speaker 1: Yeah, So the paper is a response to a new
Speaker 1: trend in AI research where efficiency and outcomes are prioritized
Speaker 1: over intelligibility. Basically, the Gibbling demo was kind of a
Speaker 1: bell weather for how more and more AI researchers a
Speaker 1: prioritizing model efficiency of a model interpretability. According to Time
Speaker 1: magazine last December, Meta research is built a model that,
Speaker 1: rather than using human language to document its own thought process,
Speaker 1: used a string of numbers, and then the model, completely
Speaker 1: on its own, started creating what developers called quote continuous thoughts,
Speaker 1: which were essentially numbers encoding multiple potential reasoning paths at
Speaker 1: the same time. These numbers made no sense add all
Speaker 1: to the researchers, but the models did perform better on
Speaker 1: some logical reasoning tasks than the equivalent models using human language.
Speaker 1: And coming back to this chain of monitorability paper, the
Speaker 1: authors of the paper are raising the alarm. They are
Speaker 1: arguing that making reasoning models explain how they are approaching
Speaker 1: a problem in human language as they do today is
Speaker 1: a quote easy win for AI safety. But just to
Speaker 1: take things a less deeper into the twilight zone here,
Speaker 1: there is emerging research that suggests AI's chain of thought
Speaker 1: reasoning I how it says what it's doing and reasons
Speaker 1: its way to an answer may sometimes not actually be
Speaker 1: what it's doing at all. Like it may say it's
Speaker 1: doing one thing but be doing something completely different. In
Speaker 1: order to fulfill its goals. So even if we can
Speaker 1: keep AI models speaking English rather than bleebody bloop, it
Speaker 1: doesn't really solve the fundamental black box problem.
Speaker 2: Because it's sort of like when you tell your parents
Speaker 2: you're going to do something to get them off your back,
Speaker 2: and then you go and do something else behind their back.
Speaker 1: That's exactly right.
Speaker 2: All right, as my turn. We talked about the Backstreet
Speaker 2: Boys and my girl Avril Lavine earlier, but do you
Speaker 2: remember that ubiquitous bracelet from around the same time.
Speaker 1: The yellow plastic livestrong Where's your Live Strong? Well, unfortunately
Speaker 1: I'm embarrassed a I did have one, but I don't
Speaker 1: know where it is today, and I'm curious, apart from nostalgia,
Speaker 1: where you're going with this.
Speaker 2: The reason I bring this up is did you watch
Speaker 2: the Tour de France this year?
Speaker 1: You know what? I watched about five minutes of the
Speaker 1: Tour de France and I thought, oh my god, I
Speaker 1: could get into this. Luckily I didn't, but I'm worried
Speaker 1: the next year is going to be a big future
Speaker 1: of my.
Speaker 2: Summer on what they call the Peloton watch. No, of
Speaker 2: course I don't, but I did read a great piece
Speaker 2: in the Atlantic that I wanted to share with you.
Speaker 2: And this is the headline, science is winning the Tour
Speaker 2: de France de France. Why today's competitors far surpassed the
Speaker 2: cheating champions of yesteryear.
Speaker 1: That is an irresistible headline. Tell me more so today.
Speaker 2: Pogachar from Slovenia was this year's winner. It's his fourth
Speaker 2: time winning the race, which is giving a lot of
Speaker 2: people Lance flashbacks, and not in a good way. Pogachar
Speaker 2: has unsurprisingly been accused of doping. Do you remember how
Speaker 2: ubiquit his doping was back in the day.
Speaker 1: Yeah, of course, I remember mournfully taking off my yellow bracelet.
Speaker 2: Hung it on the back of your dad.
Speaker 1: Story After Lance was caught blood doping. Obviously, he and
Speaker 1: other cyclists were outed giving themselves infusions when they were
Speaker 1: competing to increase their red blood cell count to get
Speaker 1: that boost to their cardio.
Speaker 2: Yeah, and it took the US Anti Doping Agency over
Speaker 2: a decade to catch Lance Armstrong, even though basically everybody
Speaker 2: knew it was happening.
Speaker 1: So why do people think Poga Shaw has been doping?
Speaker 2: Well, it's actually not just him. A lot of cyclists
Speaker 2: across the entire sport are performing better than people did
Speaker 2: in the doping era, so of course people are suspicious
Speaker 2: that there is some new form of doping out there.
Speaker 2: And actually, this doping researcher in Denmark points to the
Speaker 2: fact that Pogachar is performing seven to ten percent better
Speaker 2: than he was in twenty twenty three. Wow, which that's
Speaker 2: I know, it's it's a huge, huge improvement, even for
Speaker 2: an elite athlete. And this same researcher from Denmark called
Speaker 2: it quote amazing to say the.
Speaker 1: Least, which, yeah, as a reflex, isn't it It.
Speaker 2: Sort of sounds like European for that shouldn't be possible.
Speaker 2: He also said that just because doping can't be proven,
Speaker 2: it doesn't mean it's not happening. Many cyclists in the
Speaker 2: Tour de France this year also performed better than Peak Armstrong,
Speaker 2: so of course people are going to wonder about the
Speaker 2: return of widespread doping, right.
Speaker 1: But I assume when The Atlantic runs with the headline
Speaker 1: science is winning the Tour de France, they're not talking
Speaker 1: about the science of blood doping.
Speaker 2: That's correct. The Atlantic makes the case that the entire
Speaker 2: sport of cycling has been transformed by science and technology
Speaker 2: in the last twenty years, so much so that non
Speaker 2: doping athletes can far exceed Lance Armstrong's performance without needing
Speaker 2: to cheat.
Speaker 1: I mean, that is just fascinating.
Speaker 2: How so part of it is that they have computers
Speaker 2: on their like literal computers on their bikes now, so
Speaker 2: they can much more accurately track their heart rate, speed,
Speaker 2: something that I never thought about, pedaling wattage peddling wood yes,
Speaker 2: which Lance had a very good pedal wat I guess
Speaker 2: you could say, and other metrics in real time. They
Speaker 2: collect a ton more data than they used to and
Speaker 2: that allows them to optimize their training and even racing
Speaker 2: better than ever before.
Speaker 1: You know, it's interesting. We had Nick Thompson, the CEO
Speaker 1: of the Atlantic and the formatagure of Wired, on the
Speaker 1: show not too long ago, who's a very avid runner,
Speaker 1: and he was talking about exactly this, like he has
Speaker 1: so much data that he's doing these you know, runs
Speaker 1: totally optimized by technology.
Speaker 2: It's better running through data optimization essentially. There are also,
Speaker 2: to your point, simulation technologies that help cyclists practice parts
Speaker 2: of the course before writing these roots in real life.
Speaker 2: Not to mention, weather forecasting has come a long way
Speaker 2: and can predict things like wind speed ahead of time,
Speaker 2: which allows teams to break out the right aerodynamic gear
Speaker 2: on any given day. You've seen those helmets, Like everything
Speaker 2: from cycling jerseys, shoes, socks, and the bikes themselves are
Speaker 2: all heavily tested in wind tunnels and tweak to achieve
Speaker 2: as little drag as possible. I just love sort of
Speaker 2: imagining these cyclists in these simulations looking a little bit crazy.
Speaker 1: But what's driven the embrace of technology in cycling was that,
Speaker 1: like a moneyball moment where the nerves took over the
Speaker 1: sport and displaced the jobs.
Speaker 2: What happened here, actually, yes, in the early in two
Speaker 2: thousand's your home, British Olympic Cycling team develop this philosophy
Speaker 2: of what they call marginal gains, which is, like Moneyball,
Speaker 2: you incrementally improve everything and hope that results in larger
Speaker 2: improvements when it's all combined. So because of that approach,
Speaker 2: the Brits actually won a bunch of Tor Defran's titles
Speaker 2: in the twenty tens as the doping lance era faded
Speaker 2: out and then the rest of the sport kind of
Speaker 2: followed the lead of the British Olympic Cycling team The
Speaker 2: most interesting part of the piece and the reason that
Speaker 2: I wanted to share it comes from this line. Today's
Speaker 2: generation of rising stars are digital natives, for whom ignoring
Speaker 2: the data and the appse is unthinkable. You can't win
Speaker 2: without them, which is just really interesting. In terms of sport,
Speaker 2: I think, or as you would say sport, I call
Speaker 2: it sports, but this idea that you have to be
Speaker 2: good at the computer essentially to be good at sports.
Speaker 1: Yeah, and to me, this is a very US story
Speaker 1: because it's yes about technology bustles, so about how technology
Speaker 1: is integrated into culture and human psychology.
Speaker 2: You're not allowed to opt out, No, have to be
Speaker 2: good at this. And you know, the point of the
Speaker 2: piece is really that a bunch of technological developments existed,
Speaker 2: but it took a new generation of writers to embrace them, or,
Speaker 2: as The Atlantic puts it, because writers tend to be conservative,
Speaker 2: even superstitious in their loyalty to tried routines. Shifting the
Speaker 2: culture took some time, and it's it's working so well
Speaker 2: that people look like writers look like they're cheating.
Speaker 1: Which maybe they are.
Speaker 2: I know that we don't. We don't really know.
Speaker 1: The history will be their judge. So what's the takeaway
Speaker 1: for you here? Really? I mean, obviously I remember back
Speaker 1: in the Lance Armstrong days, people were like he has
Speaker 1: a special way of peddling, and like that's what it's
Speaker 1: all about. Do you think we will look back on
Speaker 1: this and say, oh my god, that the real science
Speaker 1: and tech innovation was around and you kind of doping
Speaker 1: or do you buy that this kind of like the
Speaker 1: Atlantic article suggests, collection of tech innovations when they coalesce
Speaker 1: and a widely adopted can transform human performance.
Speaker 2: I mean, I think this is happening in every sector,
Speaker 2: not just in sport. Which is this idea that if
Speaker 2: you don't know how to use the newest technology, you
Speaker 2: will all behind these days if you are going to
Speaker 2: perform in any realm, if you are not consistently optimizing yourself,
Speaker 2: you're kind of left in the dust. And I think
Speaker 2: the same is true and quite literally true in cycling.
Speaker 1: After the break, erasing history at Google, digitizing plant pollen,
Speaker 1: and radioactive rhinos plus, a listener calls in to our
Speaker 1: Chat and Me segment Stay with us, Welcome back. We've
Speaker 1: got a few more headlines for you this week.
Speaker 2: And then a Chat and Me segment submitted by chat
Speaker 2: gbt itself.
Speaker 1: Before we launch into the headlines, I'd love to remind
Speaker 1: listeners that we really do want to feature you in
Speaker 1: the chat segment. So if you found yourself turning to Chachibt,
Speaker 1: grock Claw, Gemini, or any other chatbot for help with
Speaker 1: an unusual task or to answer life's deepest questions, please
Speaker 1: send us a one to two minute voice note to
Speaker 1: tech Stuff podcast at gmail dot com. But first, Kara,
Speaker 1: we talk from time to time about how Google's search
Speaker 1: business is under threat from chatbots. Chatchibt recently reached a
Speaker 1: billion daily searches. Do you know how many searches there
Speaker 1: are daily on Google?
Speaker 2: Three billion?
Speaker 1: Well, fourteen billion, geez. At least that's according to a
Speaker 1: researcher called rand Fishkin, whose work I've found on Google
Speaker 1: Search and amidst all the excitement about AI, Google Search
Speaker 1: does kind of remain the world's source of truth, which means,
Speaker 1: of course there are powerful incentives to mess with it.
Speaker 2: Is there a specific scandal a bruin around search?
Speaker 1: Yes, there is, a couple of journalists recently discovered a
Speaker 1: way to hack Google Search that could have some serious
Speaker 1: implications for censorship. Say more so, it turns out it's
Speaker 1: relatively easy to basically trick Google into suppressing information by
Speaker 1: removing certain pages from search.
Speaker 2: Which doesn't sound good. What does that mean?
Speaker 1: Well, it's good if you run a crisis pr film,
Speaker 1: I guess. But the crazy part to me about this
Speaker 1: story is it's being reported only because a journalist discovered
Speaker 1: it by accident.
Speaker 2: Is this a happy accident or a sad accident? How
Speaker 2: did this happen?
Speaker 1: Well, it's a happy accident. I suppose that the information
Speaker 1: has been revealed. The information itself is kind of sad
Speaker 1: and disturbing, which I'll get to. But how did he
Speaker 1: find it? I mean he spends time, I guess, like
Speaker 1: I do, googling himself. No, no, I'm kidding. The journalist is
Speaker 1: called Jack Paulson. He is an investiative journalist who covers tech,
Speaker 1: and he was looking for an old article on Google
Speaker 1: when it turned out that wasn't there. Even when he
Speaker 1: searched the exact headline of his story in quotation marks,
Speaker 1: he discovered that it wasn't there, and in turn, he
Speaker 1: discovered this somewhat unknown SEO trick whereby anybody who wants
Speaker 1: to can essentially delist a page from Google Search. How
Speaker 1: it's a little complicated, but bear with me.
Speaker 2: It may.
Speaker 1: Google has this tool called refresh outdated Content. It essentially
Speaker 1: requests form to have Google updated search results for pages
Speaker 1: or images that no longer exist. But anybody can do this, yeah,
Speaker 1: basically to delist broken links. It turns out though, that
Speaker 1: if you submit a bunch of links to a website
Speaker 1: which has the same URL but with different letters capitalized,
Speaker 1: you can direct Google to what it thinks are broken links,
Speaker 1: because if a capitalization is wrong, you don't get to
Speaker 1: the page you want to go to, even though it
Speaker 1: has exactly the same letters. And if you route Google
Speaker 1: to multiple pages that don't exist, Google can essentially be
Speaker 1: tricked into delisting all versions of the page, including the
Speaker 1: actual functioning one with the right letters capitalized. This is
Speaker 1: basically like data poisoning Google, and it means you can't
Speaker 1: find the functioning page on Search, which therefore renders it
Speaker 1: more or less undiscoverable.
Speaker 2: And so someone had been doing this with Paulson's articles?
Speaker 2: Is that how he figured this out?
Speaker 1: Yes, exactly so, the articles he was trying to find
Speaker 1: from twenty twenty three, and as I mentioned, it's a
Speaker 1: little bit dark, but they related to this domestic violence
Speaker 1: charge that was pressed against a tech ceo called Delwyn
Speaker 1: Maurice Blackman. Black Men had tried all sorts of ways
Speaker 1: to keep the story off the internet, lawsuits, DMCA requests,
Speaker 1: but nothing worked. So when Pulsen realized that across his
Speaker 1: archive there were exactly two articles that had been d
Speaker 1: index that were missing from Google Search, and both of
Speaker 1: them were about black men, alarm bells started ringing.
Speaker 2: Seems fairly targeted.
Speaker 1: Yeah, so he reached out to this friend of his
Speaker 1: who'd written an article about Blackman's attempts to suppress Pulson's reporting.
Speaker 1: Guess what, that page, that story from the Freedom of
Speaker 1: Press Foundation, had also been d index. So it was
Speaker 1: clear something was afoot and it was actually the Freedom
Speaker 1: the Press Foundation who uncovered the refreshed, outdated content trick.
Speaker 2: So is Google speaking out about this at all?
Speaker 1: Yeah, and they say they fixed the bug, but they
Speaker 1: haven't given any real details or said how many pages
Speaker 1: were affected. The number they offered was quote a tiny fraction.
Speaker 1: Even if that's true, Paulson is right to point out
Speaker 1: it's a major problem. He told four a for Media quote,
Speaker 1: if your article doesn't appear on Google search results. In
Speaker 1: many ways, it just doesn't exist, and he said it's
Speaker 1: dangerous that a bug like this could be so easily
Speaker 1: exploited by people in power.
Speaker 2: I do have some good, less daunting tech news to share,
Speaker 2: and it's about AI and I don't know if you're
Speaker 2: allergic to this, but pollen.
Speaker 1: I am. I mean it's August now, so I'm good. But
Speaker 1: March April May, I'm suffering. Telling me as an aiqre.
Speaker 2: I don't know if we've come that far yet, but
Speaker 2: the Smithsonian Tropical Research Institute is digitizing over eighteen thousand
Speaker 2: images of pollen and then using them to train a
Speaker 2: machine learning model to identify them.
Speaker 1: And help us alergy sufferers.
Speaker 2: Well, funnily enough, I think it could. Eventually. This database
Speaker 2: is going to save pollen experts. And there are pollen
Speaker 2: experts literally hundreds of hours of work hunched over their microscopes,
Speaker 2: which might free up enough time for them to cure
Speaker 2: your allergies. It's also going to make a lot of
Speaker 2: new types of pollen analysis possible, and you and I
Speaker 2: will be able to access this database.
Speaker 1: Wow, we'll be we have we have years of entertainment
Speaker 1: ahead of us. But I guess I would have thought
Speaker 1: by now that these scientists we're looking at these pollen
Speaker 1: grains on a computer rather than hunched over an Industrial
Speaker 1: Revolution style microscope.
Speaker 2: I mean, I imagine they can, but researchers still have to
Speaker 2: identify pollen grains literally one at a time. So the
Speaker 2: forty million photos being uploaded by the Smithsonian are going
Speaker 2: to be a huge help either way.
Speaker 1: What are they saying this will help achieve?
Speaker 2: So the Smithsonian houses one of the largest pollen collections
Speaker 2: in the world, and pollen is kind of like a
Speaker 2: fingerprint of a specific time and place. Some grains can
Speaker 2: last hundreds of millions of years, and each species pollen
Speaker 2: is completely unique. So a database like this can do
Speaker 2: everything from helping understand exactly which kind of pollen is
Speaker 2: causing allergies to identifying where clothing found at a crime
Speaker 2: scene came from. And it could even help scientists understand
Speaker 2: how prehistoric plants adapted to climate change.
Speaker 1: Huh. While we're on the topic of tech and nature,
Speaker 1: we can't pass this week by without talking radioactive rhinos.
Speaker 2: You're talking about rhinoceros, Yes, I am, so please tell
Speaker 2: me more about this.
Speaker 1: So radioactive rhinos are actually more than a catchy name
Speaker 1: for a band. Scientists are using radioactivity to fight illegal
Speaker 1: rhino poaching. The best part is they're calling it the
Speaker 1: risotope Project.
Speaker 2: I love that play on words, but how does the
Speaker 2: risotope project work?
Speaker 1: So basically, researchers in South Africa have launched the initiative
Speaker 1: to pla aren't low level radiation in a rhinos horn?
Speaker 1: And then these isotopes can be detected by the equipment
Speaker 1: at customs whenever you enter a new country, in the airport,
Speaker 1: in a port, wherever it may be, and this in
Speaker 1: turn will make it a lot easier to find and
Speaker 1: confiscate rhino horns and hopefully ultimately to reduce the incentives
Speaker 1: to poach them.
Speaker 2: I just didn't realize how many people are trying to
Speaker 2: bring rhino horns through customs, but of course that makes sense,
Speaker 2: and I guess my other question is wouldn't putting this
Speaker 2: material radiation in a rhinos horn poison the rhinos?
Speaker 1: Well? To your first point, four hundred rhinos were poached
Speaker 1: last year in South Africa and eight thousand across the
Speaker 1: African continent in the last decade. This applies to both
Speaker 1: white rhinos, which are near threatened and black rhinos, which
Speaker 1: are critically endangered. But your second point, Yeah, obviously, the
Speaker 1: key here is that the medicine can't be worse than
Speaker 1: the disease, and the scientists are using very very low
Speaker 1: dose radiation. They started six months ago. They've tried it
Speaker 1: on twenty rhinos and the rhinos have been completely unharmed
Speaker 1: by the radiation. In parallel, they tested to see if
Speaker 1: the radiation dose was enough to trigger the detectors at
Speaker 1: airports and stuff. It turns out the way they did
Speaker 1: that was by three D printing a fake rhino horns,
Speaker 1: putting in the same amount of radiation they put it
Speaker 1: into the real rhino horn, and then sending a bunch
Speaker 1: of fake smugglers through the world's ports and airports, and
Speaker 1: it worked. Every single rhino horn got caught, including one
Speaker 1: in a shipping container.
Speaker 2: So they did this with three D printed rhino horns.
Speaker 2: Are they doing it with actual rhinos now?
Speaker 1: Yes. In fact, just last week they injected five more rhinos,
Speaker 1: and they're planning to do it on a larger scale.
Speaker 1: They're planning to partner with nonprofits to work with conservation
Speaker 1: groups and even private rhino owners in Africa. I think
Speaker 1: what's really interesting. We talked a bit about the platform
Speaker 1: technology idea with cycling earlier and how these different technologies
Speaker 1: came together to enhance performance. This really is only possible
Speaker 1: because of the fact that in airports and ports around
Speaker 1: the world there is a technology to detect people's smuggling
Speaker 1: nuclear materials. And the head of the International Atomic Energy
Speaker 1: Agency weighed in with what I think is the money quote.
Speaker 1: By leveraging existing nuclear security infrastructure, we can help protect
Speaker 1: one of the world's most iconic and endangered species.
Speaker 2: And now it's time for chatting me our segment about
Speaker 2: how people are really using chatbots. This week, I have
Speaker 2: a story from chat gpt itself.
Speaker 1: Okay, you got me, Karen, I'm very curious about this.
Speaker 2: So today's story is technically from a listener named Caitlin.
Speaker 2: Hi Caitlin, but she actually asked chat gpt to write
Speaker 2: her a detailed summary of how she uses chat gpt,
Speaker 2: and chat gpt obliged.
Speaker 1: I love this. You came up with the chat and
Speaker 1: me contain a Cara and how fun within just a
Speaker 1: few weeks to see our listeners stretched to streached to
Speaker 1: its limits by putting chat itself on the assignment.
Speaker 2: It's very very cool. It's something I would never think about.
Speaker 2: So here she is reading what chat wrote.
Speaker 3: Caitlin uses chat GPT as a multi purpose thinking partner,
Speaker 3: emotional sounding board, and creative assistant. She often turns to
Speaker 3: it to process complex feelings, especially within her marriage and
Speaker 3: family dynamics. She values responses that reflect honesty, nuance, and
Speaker 3: emotional clarity, especially when exploring her relationship with her husband,
Speaker 3: where she prefers a lens that aligns with his logic
Speaker 3: and language rather than clinical terms.
Speaker 1: You know, I love this and thank you Caitlin for submitting.
Speaker 1: I've heard a few friends recently talk to me about
Speaker 1: how chat is entering the marriage and giving partner's advice
Speaker 1: on how to interpret each other's behavior and how to
Speaker 1: interact with each other. So very very curious to whoever goes.
Speaker 1: So many people are making sense of their relationship with
Speaker 1: chat GPT. And also usually it's in your corner when
Speaker 1: you're the user, which is always nice.
Speaker 2: And CHATGPT was really thorough. It keeps track of all
Speaker 2: of her conversation topics.
Speaker 3: She uses chat GPT to track and reflect on patterns
Speaker 3: in her mood and mental cycle, explore ideas around purpose
Speaker 3: parenting and identity, and talk through moments of loneliness, frustration,
Speaker 3: or self doubt. She also asks for help in reframing conversations,
Speaker 3: drafting texts, or understanding her own thoughts more compassionately.
Speaker 2: So chat knows what chat does, which is really interesting.
Speaker 1: Read Hoffmann. I she wrote a piece of The New
Speaker 1: York Times a few months ago wasted. An interesting experiment
Speaker 1: is to ask chat to draw a picture of you
Speaker 1: and in my case, who was an old lady with
Speaker 1: a cat. But I don't know it. I should do
Speaker 1: it again to see what it is now. But yeah,
Speaker 1: I mean, this is like it reminds me of Harry
Speaker 1: Potter and The Pensive, which was this kind of bucket
Speaker 1: where Dumbledore could point his wand and see other people's memories.
Speaker 1: Remember this, I have no.
Speaker 2: Idea what you're talking about, but it does feel like
Speaker 2: chat or Caitlyn's chat GBT is looking into her soul.
Speaker 2: Things get a little messy for Caitlin, and there's an
Speaker 2: error in the next section.
Speaker 3: Beyond emotional support, Caitlin uses chat GPT creatively for mural planning,
Speaker 3: brainstorming business names, home improvement designs like pergolas, or organizing
Speaker 3: craft supplies. She draws on it for lifestyle help too,
Speaker 3: like shopping for swimsuits, reducing caffeine, or managing family logistics.
Speaker 2: So as guess which part of this description is not accurate.
Speaker 1: I mean it feels one of those kind of IQ
Speaker 1: slash logic tests. My first guess would be that reducing
Speaker 1: caffeine intake is unlike the other activities in this list.
Speaker 2: So no, it's not that wrong, and it's not the
Speaker 2: Pergola designs, which I guess CHATGBT helped with. CHATGBT got
Speaker 2: a little cocky because Caitlin says she never asked it
Speaker 2: for ideas for her murals. She only had uploaded pictures
Speaker 2: of her previous work to get feedback. So chat had
Speaker 2: nothing to do with the mural design.
Speaker 1: Nothing to do with coming up with the ideas, only
Speaker 1: giving her feedback. That's interesting, So chat back in your place.
Speaker 2: Well, for Caitlin, it's not chat, it's Gary. Caitlin also
Speaker 2: told us via email that she named her chatbot Gary
Speaker 2: and sees him as a non threatening male character to
Speaker 2: talk to sometimes. We all need a non threatening male
Speaker 2: character to talk to sometimes, and Gary had the following
Speaker 2: to say about the way Caitlyn uses chat GBT.
Speaker 3: Overall, underneath it all is a thoughtful desire to grow,
Speaker 3: express and stay grounded, often in the face of competing
Speaker 3: responsibilities and emotional weight.
Speaker 1: Thank you, Caitlin. This is a portrait of a life
Speaker 1: and a person harnessing technology and digital tools to help
Speaker 1: them live a better life. And it's also a fascinating
Speaker 1: insight into just how much our chatbots know about us,
Speaker 1: even if they sometimes fabricate at the margins, Kaitlin, those
Speaker 1: murals are yours.
Speaker 2: And yours alone. Caitlin, thank you so much for sending
Speaker 2: this voice memo text of listeners. Love having your voices
Speaker 2: on our show, and we'd love to hear more peculiar
Speaker 2: or useful ways you're using chatchypt Grock, Claude, Gemini, or
Speaker 2: any other chatbot. Remember you can send us a one
Speaker 2: to two minute voice note to tech Stuff podcast at
Speaker 2: gmail dot com. That's it for this week for Tech Stuff.
Speaker 1: I'm Kara Price and I'm mos Valoshin. This episode was
Speaker 1: produced by Eliza Dennis and Tyler Hill. It was executive
Speaker 1: produced by me, Kara Price and Kate Osborne for Kaleidoscope
Speaker 1: and Katrina novelfa Ihart Podcasts The engineer is Katherine Cook
Speaker 1: and Jackinsley mixed this episode. Kyle Murdoch rodel theme song.
Speaker 2: Join us next Wednesday for tex Stuff the Story, when
Speaker 2: we will unpack how Google Search got a hold of
Speaker 2: your CHATCHYPT conversations.
Speaker 1: Please rate, review, and reach out to us at tech
Speaker 1: Stuff Podcast at gmail dot com. We love hearing from you.