Speaker 1: From Kaleidoscope and iHeart podcasts. This is tech stuff. I'm
Speaker 1: os Volocian and.
Speaker 2: I'm Cara Price.
Speaker 1: Today we'll get into why websites claiming to catch cheetahs
Speaker 1: using facial recognition should frighten us all and Trump's crypto empire.
Speaker 2: Then unchat me.
Speaker 3: Every story has two sides, even chat. This time she
Speaker 3: has shown her green.
Speaker 2: Side all of that on the Weekend Tech. It's Friday,
Speaker 2: October twenty fourth.
Speaker 1: So, Kara, often you come in wearing a baseball cap,
Speaker 1: that's right. Not today today, I come in wearing a
Speaker 1: black windbreaker. Yes, I don't normally wear. What does it
Speaker 1: say on it?
Speaker 2: It says the science of genetics, the business of discovery.
Speaker 2: Colossal Labs.
Speaker 1: Colossal Labs. So, a few weeks ago you sent me
Speaker 1: an article about the company trying to revive the DODO.
Speaker 1: I did, What did you say?
Speaker 2: I said, we should have this guy on.
Speaker 1: I'm so glad your session avid listener when you're not
Speaker 1: on the show, Cara, I interviewed him a few weeks ago.
Speaker 2: Yes, I was like, well, that's great, I'm glad you
Speaker 2: did that.
Speaker 1: This is Ben Lamb, the CEO and founder of Colossal Biosciences.
Speaker 1: Just for some background, this is the company whose mission
Speaker 1: is to revive the wooly mammoth.
Speaker 2: Have they been successful?
Speaker 1: They're getting there. So one of their big milestones along
Speaker 1: the way was to gene edit mice to have wooly
Speaker 1: mammoth fur. These were the so called they broke the
Speaker 1: Internet around March April. And then of course you're with
Speaker 1: the die wolves. Yes, majestic white wolves, beautiful wolves staring
Speaker 1: out from the cover of Time magazine. Yes, was that
Speaker 1: colossal Colossal as well?
Speaker 2: That was colossal as well.
Speaker 1: And now the Dodos is on the agenda, so incredible.
Speaker 1: Gives something to believe in about just how powerful the
Speaker 1: new science and tech revolution really is. I got the
Speaker 1: reason I'm wearing Colossal Bioscience is swag is not because
Speaker 1: I've become an employee of Colossal Biosciences.
Speaker 2: Or a hYP Well, you're a kind of a hype man.
Speaker 1: I got to go to the lab yesterday in Dallas.
Speaker 2: Cool.
Speaker 1: It was really really cool.
Speaker 2: Can you describe some of the environs.
Speaker 1: Yeah, I think it's a little on the top secret side,
Speaker 1: but you basically go, you put on a lab code
Speaker 1: and then you walk past all these different labs. Whether
Speaker 1: each there's a team of scientists working on all different problems.
Speaker 1: One is extracting DNA from ancient bones, another is implanting
Speaker 1: DNA into eggs. Another is working on an artificial womb,
Speaker 1: essentially growing animals without needing a parent animal. They're trying
Speaker 1: to grow, growing uff from embryo to maturity. I mean,
Speaker 1: it really is totally mind bobbling. There are two big
Speaker 1: questions I think about this story. One is is it real?
Speaker 1: And some people, when the die Walls came out, said, well,
Speaker 1: you know you've basically gene edited normal wolves to give
Speaker 1: them white fur and make them a little bit bigger, right,
Speaker 1: And Ben Lamb, the CEO of Colossal Biosciences, pushes back,
Speaker 1: including by saying, well have you done that exactly? The
Speaker 1: other thing people say is what is the business case here?
Speaker 1: And when Ban Lamb came on the show, I asked
Speaker 1: him about exactly this is this really in your heart
Speaker 1: of hearts? More about the de extinction project? Or is
Speaker 1: the the extinction project the best meme in the world
Speaker 1: to allow you to advance the cause of synthetic biology.
Speaker 2: So so it depends on who you ask, right, have.
Speaker 4: Yeah, you know, because because I'm very passionate about, you know, conservation,
Speaker 4: which I hope we get into, but you know, for me,
Speaker 4: it is about the de extinction, right. I think that
Speaker 4: that we are at this like truly at the the
Speaker 4: doorway of what we can do with synthetic biology. And
Speaker 4: I think that if Colossal word is your every major
Speaker 4: disease and help conservation and build technologies that could radically
Speaker 4: transform di directed evolution and genetic engineering in all species,
Speaker 4: including humans, and make every single species that we wanted
Speaker 4: except the mammoth, I would consider us a failure.
Speaker 1: So it's a little bit of both.
Speaker 4: But my heart is still kind of pretty much in
Speaker 4: love with the pursuit of some of the really large
Speaker 4: de extinction projects.
Speaker 1: And just for the sake of clarity, the term de
Speaker 1: extinction is defined by Colossal as quote, the process of
Speaker 1: generating an organism that both resembles and is genetically similar
Speaker 1: to an extinct species.
Speaker 2: All right, as I want to move on to the
Speaker 2: big headlines of the week. As you know, my beat
Speaker 2: on this show is dating in the age of tech,
Speaker 2: and so of course I have to bring you a
Speaker 2: video that's been replicated many times over. So I'm going
Speaker 2: to show you a video of a girl who's been
Speaker 2: interviewed on the street.
Speaker 5: You've been engaged for six months?
Speaker 1: Yeah, you're out here?
Speaker 5: Where's he?
Speaker 2: He's in?
Speaker 5: That never caused conflict. I know a lot of times
Speaker 5: military men are like a red flag.
Speaker 1: I mean I always have those thous in my mind.
Speaker 5: Well, yeah, you're a woman, of course.
Speaker 1: Of course.
Speaker 5: I have an AI software called Cheeterbuster, and we can
Speaker 5: find out using spacial recognition if anyone's on a dating app.
Speaker 2: What's his name, Cameron?
Speaker 1: How old is he? City? He said, Jacksonville, North Carolina.
Speaker 5: Can you have a picture of him on your phone
Speaker 5: right now? Cheetabuster eye is gonna do its thing. And
Speaker 5: remember it uses a marified photo recognition.
Speaker 2: So that selled me. That's on his ID.
Speaker 5: It uses that it's real. He's gonna find him. If
Speaker 5: he's on here, we're gonna find him. Okay, I did
Speaker 5: find an account.
Speaker 1: Is this him?
Speaker 2: Yeah?
Speaker 1: That's it searching for men? Is this real?
Speaker 2: Well, the app is real. I can't promise that the
Speaker 2: girl in it isn't a plant.
Speaker 1: I have to say I definitely avoid the situation. This
Speaker 1: woman found herself in of a man in the street.
Speaker 1: Interview being taped to social media. Do it?
Speaker 2: Let's see what Cameron's.
Speaker 1: This is insane?
Speaker 2: Yes, So I just want to start by saying, this
Speaker 2: is a real app called Cheaterbuster AI. So Joseph Cox,
Speaker 2: who's a reporter for four or four, noticed that videos
Speaker 2: like the one I just showed you were like flooding
Speaker 2: feeds of Instagram and TikTok, and of course was like,
Speaker 2: what the hell is this?
Speaker 1: This is well, this is Jerry's spring of the for
Speaker 1: the age of Jerry. Jerry exactly, Everyone's Jerry now.
Speaker 2: Well, no Jerry is using AI now, which is crazy.
Speaker 2: So let me just break down how cheater Bus the
Speaker 2: site asks I would say, OZ thirty six New York,
Speaker 2: I would upload a photo of you, not all of
Speaker 2: it has to be precise, by the way, which is
Speaker 2: really interesting.
Speaker 1: You mean you could say, I don't know.
Speaker 2: Whatever, it doesn't have to be super precise. Then there's
Speaker 2: an option called face matches different names to see results
Speaker 2: of anyone who looks like the photo uploaded.
Speaker 1: So, in other words, the name and the age and
Speaker 1: the location are essentially narrowing criteria that's right to allow
Speaker 1: the facial recognition matching software to do about a.
Speaker 2: Job yes, Okay, then you get a list of Tinder
Speaker 2: profiles and you can look to see if your person
Speaker 2: is cheating. All of this twenty dollars a month, wow
Speaker 2: to use.
Speaker 1: Wow. What about really good looking people who other people
Speaker 1: are using to catfish on Tinder? Their lives could be
Speaker 1: ruined by this.
Speaker 2: That's absolutely that's a very good point. I didn't think
Speaker 2: of that. So facial reognition, to me is the scariest
Speaker 2: part of all of this. I mean, we obviously know
Speaker 2: what facial recognition is. It's the biometric technology that identifies
Speaker 2: a person by analyzing their features, like the distance between
Speaker 2: their eyes or the shape of their nose and so.
Speaker 2: Cheeterbusters is a consumer app and is one of many
Speaker 2: apps out there that use facial recognition to expose a cheater.
Speaker 2: But this is also a technology that's used by the
Speaker 2: Department of Defense. It just trips me out.
Speaker 1: And the police and the police. It's funny appropos the police.
Speaker 1: I was told to somebody who had attended the No
Speaker 1: King's protests yeah this weekend, and she said to me,
Speaker 1: oh my goodness, I realized I probably should have worn
Speaker 1: a mask, right, No, no, because I don't want to
Speaker 1: be in a database if people matched to my identity
Speaker 1: who attended to just totally can you imagine. I mean,
Speaker 1: like five ten years ago, people said, you know, this
Speaker 1: is the nightmare of living in a techno authoritarian state.
Speaker 1: Now it's our life, yes, but it's not just being
Speaker 1: used by the authorities. It's being used into into wider
Speaker 1: culture for cheat busting and of course great social videos exactly.
Speaker 1: And the thing is, I mean, obviously cheetahbusting is one
Speaker 1: use case, but by far and away not the only one.
Speaker 1: I mean, I could theoretically take a picture of someone
Speaker 1: I saw on the subway and then trace it to
Speaker 1: their Tinder profile, figure out geolocation where they're based, and
Speaker 1: like hunt them down.
Speaker 2: Eva Galprin, who was actually the director of cybersecurity at
Speaker 2: the Electronic Frontier Foundation, said quote, I think that an
Speaker 2: app that allows you to find the dating app profile
Speaker 2: and general location of a person based on just one
Speaker 2: photo is an excellent tool for stalkers. And I'm like,
Speaker 2: you think, well, because you make a great point, which
Speaker 2: is that, like I could come into an office any
Speaker 2: day catt someone into giving me a photo of them,
Speaker 2: or just take one, or take one of.
Speaker 1: You put on your meta ray bands or your o.
Speaker 2: The meta ray bands, that's right, opens us up to
Speaker 2: something new.
Speaker 1: I'm glad you brought this story because I think it's
Speaker 1: it's a bigger story. Obviously, facial recognition technology in the
Speaker 1: hands of authorities to do authoritarianism is really bad and
Speaker 1: something we've been talking about for a while and something
Speaker 1: we should all be scared of and is basically you're
Speaker 1: already here. Yeah.
Speaker 2: Joseph Cox from four from Media has actually done multiple
Speaker 2: stories on how ice in law enforcement is currently using
Speaker 2: this exact kind of technology to track people.
Speaker 1: But when any normal person walking around the street can
Speaker 1: be identified and geolocated by anybody with camera, man.
Speaker 2: I mean it makes you feel not like a member
Speaker 2: of the human race, but a member of the database
Speaker 2: in a strange way.
Speaker 1: What do you use cheap busters? Yeah?
Speaker 2: Probably it's I mean that's the thing. It's like, it's
Speaker 2: the lure of this technology is like too strong. It's
Speaker 2: the same thing as giving it. Would I give away
Speaker 2: my data? Yeah, in exchange for something else? Sure? Why not?
Speaker 2: So caro.
Speaker 1: We haven't done too many stories on tech stuff about crypto.
Speaker 2: Crypto is something that I should be interested in, but
Speaker 2: I'm just not.
Speaker 1: It's not, honestly, where my curiosity naturally leads me. I
Speaker 1: prefer wooly mammoths and cheat Cheetahbuster. But it's obviously it's
Speaker 1: it's impossible to an Yeah, yeah, and I saw a
Speaker 1: store in the Financial Times that will be a perfect
Speaker 1: way for us to have a little bit of it.
Speaker 2: And if it's in your heart's.
Speaker 1: In my heart exactly. The headline is how the Trump
Speaker 1: companies made a billion dollars from crypto and billion dollars.
Speaker 1: By the way, there's a billion dollars of pre tax
Speaker 1: profits last year. The FT asked Eric Trump for some
Speaker 1: comment on the story. He said, quote, it's probably more's
Speaker 1: did you have any idea about this?
Speaker 2: I did not realize they made this much money?
Speaker 1: But he knew that.
Speaker 2: I knew that they were involved in crypto. Yeah, but
Speaker 2: I did not know it was a billion.
Speaker 1: And that's a lot. That's a lot of money.
Speaker 2: That's a ton of money.
Speaker 1: So before we kind of get into the whole story,
Speaker 1: I want to give you a little bit of background
Speaker 1: on Trump's own relationship with crypto. As recently as twenty
Speaker 1: twenty four, he was actually in our camp. He labeled
Speaker 1: crypto as a quote based on thin air and called
Speaker 1: bitcoin a scam. But Trump, obviously he has a better
Speaker 1: risk appetite than I do, and so he's all in
Speaker 1: on crypto at the moment. The way it started, though,
Speaker 1: was in twenty twenty four, Trump was in all kinds
Speaker 1: of legal trouble, and this translated to financial trouble because
Speaker 1: of huge civil penalties, and he actually claimed at a
Speaker 1: certain moment that he would have to start selling his
Speaker 1: real estate assets to meet this five hundred million dollar
Speaker 1: civil penalty, so he needed money. And then separately, he
Speaker 1: was also claiming that he was being debanked, in other words,
Speaker 1: that big major financial institutions refuse to carry his accounts,
Speaker 1: which is something that normally happens to people who are
Speaker 1: criminals or have very bad credit, or people who the
Speaker 1: banking system essentially doesn't want to integrate.
Speaker 2: Didn't he have a coin? Wasn't there some sort of
Speaker 2: coin related to him?
Speaker 1: You're exactly right. So there's actually a Millennia coin, right,
Speaker 1: That's what I thought, and a Trump coin. Before we
Speaker 1: get to those, there are two quick sort of definitional things.
Speaker 1: We're going to talk about meme coins, which are like
Speaker 1: the Trump coin and the millennial.
Speaker 2: Trend coin like trend coin.
Speaker 1: Yeah, yeah, and their cryptocurrency, but anyone can issue them
Speaker 1: and they're very much based on like internet hype. And
Speaker 1: then you have stable coins, do you not? Stable coins
Speaker 1: are but I don't know.
Speaker 2: I've heard of it, but I don't know.
Speaker 1: So a stable coin is a coin that's tied to
Speaker 1: a real asset that the stable coin issuer has to
Speaker 1: all so own. So, in other words, a stable coin
Speaker 1: is backed by gold or by US dollars. And if
Speaker 1: I own a stable coin, I can redeem it at
Speaker 1: any point for the real asset. Oh interesting, so much,
Speaker 1: that's White's stable. Let's start with those mean coins, dollar
Speaker 1: Trump and Dollar Millennia. So these coins were both issued
Speaker 1: right before the inauguration and have since lost over ninety
Speaker 1: percent of their evaluation. Really but two important points here,
Speaker 1: really important points. The Trump and Millennia coins, whenever they're
Speaker 1: bought or sold, generate fees to the mean coin issuer.
Speaker 1: So the trading volume, regardless of the price, enriches the
Speaker 1: mean coin issuer. Guess how much the ft estimates that
Speaker 1: the Trumps have made from the buying and selling of
Speaker 1: these mean coins much? Four hundred million.
Speaker 2: Dollars just on fees fees.
Speaker 1: Bear in mind these Trump and Millennia coins made all
Speaker 1: the headlines, but they aren't actually the real play. The
Speaker 1: ft reports on World Liberty Financial. The company is set
Speaker 1: up by Trump's sons and Steve Wickcoff sons. Wickcoff is
Speaker 1: the Special Envoy the Middle East as well as kind
Speaker 1: of an ambassador at large. Four for Trump the Suns,
Speaker 1: it's the neo the Nebow crypto. This company, World Liberty Financial,
Speaker 1: has released two major tokens. WLFI, which gives you governance
Speaker 1: rights in World Liberty Financial if you're a holder. This
Speaker 1: has owned five hundred and fifty million dollars so far,
Speaker 1: and then USD one, which is a stable coin whose
Speaker 1: price is paged to the US dollar, which has sold
Speaker 1: two point seventy one billion dollars of this USD one
Speaker 1: stable coin. Bear in mind, twenty twenty five is the
Speaker 1: real boom kickoff of this stuff. In twenty twenty four,
Speaker 1: Trump declared a personal income of fifty seven point three
Speaker 1: million dollars just from World Liberty Financial.
Speaker 2: Is it legal what he's doing?
Speaker 1: I mean, I couldn't appine on that. I'm sure that
Speaker 1: there will be legal plenty of legal challenges to this,
Speaker 1: but he's also in a position of changing the laws.
Speaker 1: Drawing that famous line from Frost Nixon, if the president
Speaker 1: does it, it is the.
Speaker 2: Law that was a good Franklin, thank you.
Speaker 1: So we're in that era, I think again. To say
Speaker 1: the least, this crypto thing has two levers in terms
Speaker 1: of exerting influence potentially on the president. On the domestic side,
Speaker 1: American crypto companies donate heavily to the Trump campaign and
Speaker 1: the World Liberty, Digital Financial Freedom Pack and Go Figure. Basically,
Speaker 1: there's been post Trump presidents did a lot of inflow
Speaker 1: of like institutional capital into crypto, which is bolstering the
Speaker 1: whole industry internationally. An Abu Dhabi based investment firm bought
Speaker 1: two billion dollars of a Trump backstable coin. A Chinese
Speaker 1: company called gd Culture Group announced it had raised three
Speaker 1: hundred million dollars to spend on bitcoin and the Trump
Speaker 1: meme coin, and Trump's sec stopped a fraud investigation into
Speaker 1: the Chinese born crypto billionaire just in so after he
Speaker 1: put seventy five million dollars into World Devity Financial.
Speaker 2: Again, it just feels us.
Speaker 1: I mean, it's as little as to say the least,
Speaker 1: But I've got some really good reassuring news. Actually, please,
Speaker 1: The president's crypto adventures are actually in a trust really
Speaker 1: managed by Donald Trump Junior. Now, this is a quote
Speaker 1: in the Financial Time from Richard Painter, who was the
Speaker 1: former chief White House ethics lawyer to President George W. Bush. Quote.
Speaker 1: Every other president since the Civil War has avoided any
Speaker 1: significant financial conflict of interest with their official duties. You know,
Speaker 1: going back to the original Trump administration in twenty sixteen
Speaker 1: to twenty twenty, people have fixated, Oh my god, he's
Speaker 1: getting people spend money in the hotel right right, right,
Speaker 1: right now. It's you know, the Trump family are going
Speaker 1: to be billionaires for generations just from this.
Speaker 2: From this, Yeah, that's incredible. After the break, satellites reveal
Speaker 2: private phone calls. Uber has drivers training, AI and a
Speaker 2: new health tracker guaranteed to make a splash. Then on
Speaker 2: chatting me, a listener's life gets a little greener.
Speaker 1: Stay with us, Welcome back, Hello again, Kara. Do you
Speaker 1: remember this sort of phrase the gig economy, Yeah, of course,
Speaker 1: I mean this idea that you could like also be
Speaker 1: a number driver for like two hours, or deliver a
Speaker 1: package or whatever. It may be. So we're now in
Speaker 1: the meta gig economy, the giga economy. I saw a
Speaker 1: headline in Axios. Uber wants drivers to train AI in
Speaker 1: their free time. No, yeah, So basically the idea is
Speaker 1: you're driving for Uber and you might have some time
Speaker 1: between picking up passengers. That's what do you do?
Speaker 2: You train AI?
Speaker 1: Basically you can do like a one to three minute
Speaker 1: task in the Uber app and get paid, like, you know,
Speaker 1: a dollar. So average time per task is one to
Speaker 1: three minutes. Pay is between fifty cents and a dollar
Speaker 1: per task. So let's see you pull over time for
Speaker 1: your break, you're having your lunch. You basically you get
Speaker 1: a notification saying would you like to do some work
Speaker 1: to get additional income?
Speaker 2: And what are they training?
Speaker 1: Like?
Speaker 2: What are what is the data for?
Speaker 1: So there's a separate AI company which is part of
Speaker 1: Uber called Uber Ai Solutions. It's really to do with
Speaker 1: the kind of human labeling aspect of data that is
Speaker 1: required to train.
Speaker 2: That a computer can't do exactly.
Speaker 1: And then Uber sells their human driven AI data labeling
Speaker 1: and data to other AI companies. The other thing is
Speaker 1: some of this data is being sold onto self driving
Speaker 1: tech companies like Aurora and Tier four. So essentially, the
Speaker 1: uber drivers in their free time, are training AI companies
Speaker 1: to replace human drivers.
Speaker 2: So they're basically training themselves out of a job.
Speaker 1: Do you remember Wiley Coyote.
Speaker 2: Who's a coyote? What is that? That's like payota?
Speaker 1: What do you say?
Speaker 2: Coyote?
Speaker 1: Coyote, coyote.
Speaker 2: It's like a coy little coyote.
Speaker 1: Well, I feel I feel suitably embarrassed now, but you
Speaker 1: know that the image of the yeah, of course, running
Speaker 1: coyote cliff, running off the cliff and he's pedaling his
Speaker 1: feet like crazy. Underneath him, it's nothing but in there,
Speaker 1: and then he realizes and all of a sudden he's
Speaker 1: on the floor. Yes, that's us.
Speaker 2: That's a very good image.
Speaker 1: I saw this week as well as a story in
Speaker 1: Bloomberg about how Open a Eye has hired one hundred bankers.
Speaker 1: Do you see this, No, they're paying them one hundred
Speaker 1: fifty dollars an hour bankers former investment banker to train
Speaker 1: open Aiy's new product to do financial modeling tool financial modeling.
Speaker 1: So so bankers are now being paid one hundred fiey
Speaker 1: dollars an hour to train an open air product to
Speaker 1: do this instead of them.
Speaker 2: So I mean that's putting themselves out of I.
Speaker 1: Mean, one hundred few dollars an hour is nice. Yeah,
Speaker 1: it's better than fifty cents a task. Yeah, But it's
Speaker 1: the same thing where it's like when an't we going
Speaker 1: to wake up and realize that this intermediate opportunity of
Speaker 1: getting some extra cash to train AI is potentially at
Speaker 1: the expense of putting the entire human workforce out of
Speaker 1: business as a business.
Speaker 2: It's really interesting. I I mean, I guess it's a
Speaker 2: short term gain for a long term problem for these drivers.
Speaker 1: I mean, I think that's exactly right. If you have
Speaker 1: an opportunity to make some make sure money out of
Speaker 1: your time while you're in your car, more power to
Speaker 1: you as an individual. As a society, is it the
Speaker 1: right thing to be doing?
Speaker 2: Well? As you know, I like stories about things that
Speaker 2: should not be happening that are happening that make me go,
Speaker 2: wait a minute, that doesn't feel right. And so the
Speaker 2: story that I want to bring you today is the
Speaker 2: following quote. Satellites beam data down to Earth all around
Speaker 2: us all the time, so you might expect that those
Speaker 2: space based radio communications would be encrypted to prevent any
Speaker 2: snoop with a satellite dish from accessing the torrent of
Speaker 2: secret information constantly raining from the sky, you would, to
Speaker 2: a surprising and troubling degree, be wrong. What there are
Speaker 2: sky snoops? So researchers that you see San Diego and
Speaker 2: the University of Maryland just found that roughly half of
Speaker 2: geostationary satellite signals are entirely vulnerable to eavesdropping.
Speaker 1: Huff half. Wow.
Speaker 2: For three years, researchers have developed and used an off
Speaker 2: the shelf, meaning we could buy it, eight hundred dollars
Speaker 2: satellite receiver system. They put it on the roof of
Speaker 2: a university building in San Diego, pointed the dish at
Speaker 2: different satellites and interpreted the obscure but unprotected signals. And
Speaker 2: this team accessed all kinds of unencrypted consumer, corporate, and
Speaker 2: government communications from these satellites. Wow, it's a ton.
Speaker 1: What kind of communications of these? I mean, it's like
Speaker 1: phone calls, texts or the above.
Speaker 2: It's all of the above, calls and texts from t mobiles,
Speaker 2: cell network data from airline passengers, from in flight Wi
Speaker 2: Fi browsing. And this is the one that I mean,
Speaker 2: it's all scary, but us and Mexican military and law
Speaker 2: enforcement communications, which revealed the locations of personnel, equipment and facilities.
Speaker 1: This is really remarkable.
Speaker 2: But wait, there's more. I should say that some companies
Speaker 2: in the study, like T Mobile and AT and T
Speaker 2: Mexico have actually already addressed the issue, but there is
Speaker 2: like a lot of data still out there. Researchers estimated
Speaker 2: that what they were able to pick up was actually
Speaker 2: only fifteen percent of global satellite transponder communications.
Speaker 1: Wow.
Speaker 2: To me, the craziest part of this story is that
Speaker 2: anyone can access this data and that's because of two things.
Speaker 2: The tech the actual satellite receiver system is eight hundred
Speaker 2: dollars and this is the craziest part. The researchers are
Speaker 2: releasing their software tool for interpreting satellite data on githubs.
Speaker 2: So even though this data from satellites comes in obscured,
Speaker 2: now anyone with access to GitHub, meaning everyone can interpret
Speaker 2: the data.
Speaker 1: Why why would they release it?
Speaker 2: So researchers actually argue that this could push companies to
Speaker 2: secure their data, so they're sort of doing it to
Speaker 2: force the hand of companies to be like, guys, this
Speaker 2: is something that's possible. Get your act together. Well, they're
Speaker 2: kind of like white hats.
Speaker 1: Actually that's a good framing, and white hat hackers are
Speaker 1: people who basically find the vulnerabilities in systems in order
Speaker 1: that those systems can be repaired and made less vulnerable,
Speaker 1: rather than to blackmail the people or steal their data
Speaker 1: and for nefarious purposes exactly. In other words, if these
Speaker 1: researchers hadn't released the open source tool to interpret the data,
Speaker 1: maybe Wide magazine wouldn't to cover the story. Karen, what
Speaker 1: if I told you you could turn your bathroom into
Speaker 1: a connected, data informed health and wellness hub.
Speaker 2: I'd say absolutely no, thank you, Let's stay out of
Speaker 2: my bathroom.
Speaker 1: And this is quite a fascinating story for me. It's
Speaker 1: about Cola and a new health tracker they've announced called
Speaker 1: the decoder that lives in your toilet bowl.
Speaker 2: I get it as in decoder exactly.
Speaker 1: This is a very interesting story to me because it
Speaker 1: actually harkens back to my childhood watching daytime television in Britain.
Speaker 1: There was a TV doctor called Gillian McKeith whose concept
Speaker 1: was to go into people's houses and examine their bathroom
Speaker 1: to tell them about what they could do to improve
Speaker 1: their health. Julie McKay's actually had a second life. I
Speaker 1: recently saw a story about my favorite showbiz publication, Bang Showbiz,
Speaker 1: with the headline my Pooh tiktoks have saved lives.
Speaker 3: Someone just told me their pooh bobs around in the
Speaker 3: bottom of the toilet bowl.
Speaker 1: It does not flash. Your toilet's not broken.
Speaker 3: No, no, no, but your digestion is waving a big
Speaker 3: brown flag and begging for attention.
Speaker 1: But now everyone can have a Chillian McKee in their toilet,
Speaker 1: up their toilet. So the decoder tracks a few things
Speaker 1: the frequency, consistency, and shape of your waist, which in
Speaker 1: turn can give you recommendations like are you probably hydrated,
Speaker 1: are you absorbing nutrients? And of course, to Jillian's point,
Speaker 1: you know, are you actually sick? Do you have some
Speaker 1: kind of bowel issue that could be anything up to deadly?
Speaker 2: What's effective? In that way it.
Speaker 1: Can be effective. The product comes in three parts. There
Speaker 1: is a sensor that clamps to most toilet bowls don't
Speaker 1: have to have a color, a wall mount that communicates
Speaker 1: between the bowl sensors, and has a fingerprint sensor to
Speaker 1: track different users. So one oh, so.
Speaker 2: It's not just it's anyone can lock into the ball.
Speaker 2: That's just not stuff I want to get stolen data
Speaker 2: that I don't want.
Speaker 1: There's also a health app for phones and per the
Speaker 1: Verge advanced sensors that use spectroscopy to observe how light
Speaker 1: interacts with your waist. The sensors are angled down so
Speaker 1: they can only see the inside of the bowl. They're
Speaker 1: not looking up to speak. And this is seven dollars
Speaker 1: a month, or sixty ninety nine per month for single users,
Speaker 1: or twelve ninety nine per month for family plants chebusters.
Speaker 1: It's cheaper than cheap bust.
Speaker 2: It's just crazy, especially for the whole family.
Speaker 1: And your point about privacy, and I'm not surprised you're
Speaker 1: on the privacy track after our satellite story. The data
Speaker 1: is end to end ENCRYPTID.
Speaker 2: It's as hard as the stool that's in it. I'm
Speaker 2: sorry I had.
Speaker 1: To so, I mean, look, this is this is funny.
Speaker 1: Health tracking is obviously a huge trend. I mean, I
Speaker 1: wonder how many how many different do you get? The
Speaker 1: or ring, the whip band, the decoder, the mattress insert You're.
Speaker 2: Just a moving biometric yeah at that point, which I mean,
Speaker 2: I don't know if I'm that interested in that like
Speaker 2: do every day. I want to know that something is
Speaker 2: inspecting my excrement, which it feels like inspector gadget.
Speaker 1: And now it's time for Chat and me.
Speaker 2: This week we've got a listener's submission. All the way
Speaker 2: from the Netherlands, Nina sent a recording called the green
Speaker 2: Side of Chat.
Speaker 3: It is often said that the enormous rise of AI
Speaker 3: poses a threat to the environment due to its high
Speaker 3: consumption of energy and water, but perhaps you'd like to
Speaker 3: hear that AI can sometimes also contribute to improving our
Speaker 3: living environment.
Speaker 2: So lovely again. Nina said that the Netherlands is very
Speaker 2: densely populated, which has caused a lack of green space.
Speaker 2: So the government has actually been encouraging people for a
Speaker 2: few years to start replacing the pavement in their yards
Speaker 2: with more greenery.
Speaker 3: This summer, to tackle my garden and replace quite a
Speaker 3: few square meters of stones with beautiful shrubs, plants and flowers.
Speaker 3: But I didn't want to just plant any greenery. I thought,
Speaker 3: why not kill two birds with one stone and choose
Speaker 3: native plants that also attract bees, butterflies and birds. I
Speaker 3: just didn't know where to start, because I also wanted
Speaker 3: it all to look nice, of course.
Speaker 1: Well, Anina, thank you for sending this in. I just
Speaker 1: want to say to you directly, if you're not narrating
Speaker 1: books already, you should be. You've got to be great.
Speaker 1: You've got a great voice and a great delivery. And
Speaker 1: this really hits home to me, Cara, because I had
Speaker 1: just moved into a house with a yard, with a yard,
Speaker 1: and it's a landlord owned property, and the landlord has
Speaker 1: moved to another country, and part of the deal was
Speaker 1: that I would take care of the yard. And David,
Speaker 1: if you're listening, I promise I'm gonna do my best,
Speaker 1: but I am pretty overwhelmed.
Speaker 2: Do you have a green thumbers?
Speaker 1: Well, my grandmother, my grandmother and my farm they were
Speaker 1: both big gardeners, so I kind of grown up with
Speaker 1: care for gardens in mind. But like, oh my goodness,
Speaker 1: I went to mow of the grass, went to prune
Speaker 1: the roses, like I don't. The last thing I want
Speaker 1: is for this beautiful garden to turn into a healthscape.
Speaker 1: And this for David, So Anina, I'm going to take
Speaker 1: a leave out of your book haha, so to speak,
Speaker 1: and follow your lead here. I assume what we're going
Speaker 1: to hear about is how Nina is used Chat to
Speaker 1: develop a green thumb.
Speaker 2: Indeed, look what she says.
Speaker 3: I gave chat Jipt a description of the layout of
Speaker 3: the garden, how much some the different parts get each day,
Speaker 3: and my wishes regarding the types of plants I wanted.
Speaker 3: To my surprise, I not only received a list of
Speaker 3: plants that would fit well in my new ecologically responsible garden,
Speaker 3: but Chap also offered to make a planting plant for me,
Speaker 3: taking to account the height, color, and structure of the
Speaker 3: various species.
Speaker 1: I'm very curious if this was a Chat hallucination or
Speaker 1: if the garden was transformed into a paradise.
Speaker 2: Well, I will let Anina tell you, because I just
Speaker 2: never want to stop listening to her voice.
Speaker 3: Well, I have now created my AI based garden, and
Speaker 3: it looks completely wonderful. It meets my expectations in every way.
Speaker 3: It has become a beautiful green garden where butterflies and
Speaker 3: bees come and go, and all kinds of birds forage
Speaker 3: for food. So you see, every story has two sides,
Speaker 3: even Chat. This time she has shown her green side.
Speaker 3: Thank you Chat, I.
Speaker 2: Like the Chat genders.
Speaker 1: Chat. She takes a leaf out of your book. That's
Speaker 1: true and thank you. That was one of my favorite
Speaker 1: ever chat That is incredible. It'll be good and personally
Speaker 1: useful as well, which was part of the idea for
Speaker 1: doing a segment. So thank you. Just to close, we
Speaker 1: really want to hear from you, our listeners. Please send
Speaker 1: us all of your chat stories, the good, the bad,
Speaker 1: and the ugly, Tech Green and the Green, the good,
Speaker 1: the bear, the green and the ugly. Tech Stuff podcast
Speaker 1: at gmail dot com.
Speaker 2: That's it for this week for tech Stuff.
Speaker 1: I'm Cara Price and I'm as Voloshin. This episode was
Speaker 1: produced by Eliza Dennis, Tyler Hill and Melissa Slaughter. It
Speaker 1: was executive produced by me Kara Price, Julian Nutter, and
Speaker 1: Kate Osborne for Kaleidoscope and Katrian Norvell for iHeart Podcasts.
Speaker 1: The engineer is Bihid Fraser and Jack Insley mix this episode.
Speaker 1: Kyle Murdoch wrotear theme song.
Speaker 2: Join us next Wednesday for a conversation all about tech
Speaker 2: induced paranoia.
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.