WEBVTT - Week in Tech: Diners, Dating, TikTok PI’s

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<v Speaker 1>From Kaleidoscope and iHeart podcasts. This is tech stuff.

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<v Speaker 2>I'm as Voloscian and I'm Cara Price.

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<v Speaker 1>Today we'll get into TikTok, private Investigators and America's AI future.

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<v Speaker 1>Then on chatting me, AI makes a diagnosis that's a

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<v Speaker 1>little too real. All of that on the Weekend Tech.

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<v Speaker 1>It's Friday, July thirtieth. Hello Cara, Hey, ohs.

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<v Speaker 2>So you might see that I'm bopping my foot this morning.

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<v Speaker 1>Yes, I'm bopping. I do have RLS, but this is exaggerated.

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<v Speaker 2>It's much exaggerated because the Tesla Diner open this week.

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<v Speaker 2>Do you know about this?

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<v Speaker 1>Of course I do. I mean it's I've been obsessing

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<v Speaker 1>about it. It looks like a drive in movie theater

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<v Speaker 1>from the fifties, retro futurist Jetson's esthetic, and there's some

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<v Speaker 1>pretty weird stuff going down there.

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<v Speaker 2>That is the one. It opened last Monday at four

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<v Speaker 2>to twenty pm.

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<v Speaker 1>Elon's favorite time of day and favorite little joke. He

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<v Speaker 1>recently rolled out this robotaxi service, and the fair was

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<v Speaker 1>initially said at four dollars and twenty cents as well.

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<v Speaker 1>So I guess the old ones are the good ones.

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<v Speaker 2>For those who don't know. Mom for twenty is a

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<v Speaker 2>weed thing that's when people smoke weed. April twentieth Market,

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<v Speaker 2>Canada's more mark your Calendars. So I actually said to

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<v Speaker 2>two of my friends, please go, and then they were like,

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<v Speaker 2>it looks so disgusting, I'm not gonna go.

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<v Speaker 1>So basically, you live in New York. We spent a

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<v Speaker 1>lot of time in LA and so we talked about

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<v Speaker 1>the idea of sending some of your LA pals to

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<v Speaker 1>go and check it out.

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<v Speaker 2>So they were like, yeah, we'll go, and they're like,

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<v Speaker 2>we're not going. So I just want to describe it.

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<v Speaker 2>It has a curved chrome siding, curved white booths, long countertops.

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<v Speaker 2>A Tesla robot Optimus serves popcorn on the second floor.

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<v Speaker 1>There, Kim Kardeshian lets out of a clutches to go

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<v Speaker 1>to the diner.

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<v Speaker 2>He was like, I'm over calabas As I'm out. There

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<v Speaker 2>are eighty supercharger stalls for Tesla's two forty five foot

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<v Speaker 2>movie screens.

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<v Speaker 1>I gather screening Star Trek amongst others.

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<v Speaker 2>Of course, it has to be Star Trek. There's food

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<v Speaker 2>served in cybertruck shaped boxes and with cyber truck shaped

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<v Speaker 2>wooden imagine the company who had to make the cyber

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<v Speaker 2>truck shape would.

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<v Speaker 1>Like a happy meal box, but in the shape of

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<v Speaker 1>a cyber truck.

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<v Speaker 2>That's right, it's everything, not golden arches, it's everything. Tesla Now,

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<v Speaker 2>one of my favorite sources, TMZ, actually had a pretty

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<v Speaker 2>harrowing story. A woman was violently struck by furniture falling

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<v Speaker 2>off the second floor patio, and it actually missed her

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<v Speaker 2>baby's head by inches, which to me is terrifying obviously

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<v Speaker 2>and a bit of a harbinger for some of the

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<v Speaker 2>very real company issues facing Tesla.

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<v Speaker 1>There was actually reddit through it called Elon Musk's Tesla

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<v Speaker 1>Diner is the cyber truck of restaurants, which you can

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<v Speaker 1>imagine was not intend as a compliment. There's the obvious

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<v Speaker 1>aesthetic parallels this kind of retro futurist, although of course

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<v Speaker 1>the cyber truck famously has no curves, only angles. But nonetheless,

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<v Speaker 1>like me, this Reddit thread mentioned this restaurant's design for

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<v Speaker 1>two hundred and fifty people, were there only three bathrooms?

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<v Speaker 1>Not good, and one user cracked that the Optimus robot

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<v Speaker 1>who was serving popcorn might have been better employed downstairs

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<v Speaker 1>mopping down the bathrooms, which apparently were not a sight

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<v Speaker 1>for sore eyes.

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<v Speaker 2>Well, and by the looks of the food, the restaurant

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<v Speaker 2>there probably needs a few more bathrooms.

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<v Speaker 1>Carol, that's a bit spiky all angles. You know you

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<v Speaker 1>mentioned the food. There was a great Guardian piece that

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<v Speaker 1>I think described the testa diner well, but also I

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<v Speaker 1>think inadvertently touched on the heart of Tesla's dilemma. Here's

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<v Speaker 1>what the Guardian wrote, quote the diner offers a mix

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<v Speaker 1>of own the Libs and we are the Libs options.

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<v Speaker 1>On the one hand, epic bacon four strips of bacon

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<v Speaker 1>as served with sources as a meat fluenzer alternative to

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<v Speaker 1>French fries. On the other, avocado toast and machlattis.

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<v Speaker 2>I know which is which?

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<v Speaker 1>I think which would you order your vegetarians?

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<v Speaker 2>One of the vegetarians. I wouldn't have a choice, but

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<v Speaker 2>I also I'd.

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<v Speaker 1>Be pretty tempted by those I own the libs menu. However,

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<v Speaker 1>as the Bible says, no man can serve two masters,

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<v Speaker 1>and this dilemma of own the Libs versus we are

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<v Speaker 1>the Libs is one which is playing out more broadly

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<v Speaker 1>at Tesla and bedeviling the company. So the opening of

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<v Speaker 1>the diner last week was in the same week that

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<v Speaker 1>Tesla released its financials. The company took a bit of

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<v Speaker 1>a beating, with net income down sixteen percent in the

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<v Speaker 1>second quarter, and The Wall Street Journal said that the

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<v Speaker 1>company's finances are quote in free fall, and they pointed

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<v Speaker 1>out two distinct drivers of this. On the one hand,

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<v Speaker 1>Musk's adventures with those have not done Tesla many favors

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<v Speaker 1>with its original client base, i e. People in California,

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<v Speaker 1>Europe who are EV fans and have environmental motivations, and

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<v Speaker 1>so with that audience, Tesla is big time out of

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<v Speaker 1>favor post the dalliance with Trump. On the other hand,

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<v Speaker 1>the dallions with Trump did not protect Musk from the

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<v Speaker 1>red meat attacks on EV's and part of the Big

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<v Speaker 1>Beautiful Bill included cuts to EV subsidies and tax credits,

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<v Speaker 1>which have really hurt Tesla's bottom line. And as you remember,

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<v Speaker 1>there were kind of rumors of the breaking up of

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<v Speaker 1>the bromance percolating for some time, but this was really

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<v Speaker 1>the wedge issue between Trump and Musk was the subsidies,

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<v Speaker 1>and indeed it's hurting Tesla's bottom line. And so this

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<v Speaker 1>brings me to my next story. There was a very

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<v Speaker 1>special meeting last week in Washington that for the first

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<v Speaker 1>few months of this year, you would have imagined seeing

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<v Speaker 1>Elon dressed all in black with the black mega cap,

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<v Speaker 1>sitting front row. But he wasn't there. Do you know

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<v Speaker 1>what I'm talking about?

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<v Speaker 2>I have a little bit of an idea. But tell me.

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<v Speaker 1>This is, of course, the Trump administration's announcement of the

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<v Speaker 1>AI Action Plan. Let's let the Commander in Chief to

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<v Speaker 1>the talking.

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<v Speaker 3>As we gathered this afternoon, we're still in the earliest

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<v Speaker 3>days of one of the most important technological revolutions in

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<v Speaker 3>the history of the world. Around the lobe, everyone is

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<v Speaker 3>talking about artificial intelligence.

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<v Speaker 4>I find that too artificial. Get I can't stand it.

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<v Speaker 4>I don't even like the name. You know, I don't

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<v Speaker 4>like anything that's artificial. So could we straighten that out place?

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<v Speaker 4>We should change the name. I actually mean that I

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<v Speaker 4>don't like the name artificial anything because it's not artificial.

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<v Speaker 4>It's genius. It's pure genius.

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<v Speaker 1>I think the rebranding of AI as Genius was a

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<v Speaker 1>Trump marketing ad lib.

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<v Speaker 2>I don't think he knows that there's another GI bill,

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<v Speaker 2>but genius Intelligence.

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<v Speaker 1>This event was actually hosted by a podcast just as

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<v Speaker 1>a sign of the time.

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<v Speaker 2>Not a news conference, the podcast.

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<v Speaker 1>This was the All In podcast and the Hill and

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<v Speaker 1>Valley Forum, which is a group of tech execs and

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<v Speaker 1>lawmakers who were dedicated to maintaining the United States dominance

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<v Speaker 1>over the tech industry. Now, Trump's been signaling for a

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<v Speaker 1>long time that this plan was coming, but I didn't

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<v Speaker 1>know that twenty eight page document which was released last

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<v Speaker 1>week would actually be titled Winning the Race America's AI

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<v Speaker 1>Action Plan. I did a control F to find how

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<v Speaker 1>many mentions of China there are in the you would

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<v Speaker 1>in the document, and to my surprise, is only two

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<v Speaker 1>China references. So then I did control F for adversary

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<v Speaker 1>because how many how many nineteen wow, nineteen times the

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<v Speaker 1>word adversary is used in the document. And of course,

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<v Speaker 1>when Trump was speaking at the All In news conference

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<v Speaker 1>after the documents released, he mentioned China again and again

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<v Speaker 1>and again, a word that he loves to pronounce. That's

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<v Speaker 1>the one he was particularly hung up in his remarks

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<v Speaker 1>on two themes. One that China doesn't let copyright protection

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<v Speaker 1>slow down the advance of AI and so not should

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<v Speaker 1>the US, and two that China has added way way

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<v Speaker 1>more power to their grid than the US in recent years,

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<v Speaker 1>and therefore the US needs to burn beautiful clean coal

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<v Speaker 1>and bring more nuclear power online to compete.

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<v Speaker 2>So Trump has actually been banging the drum for American

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<v Speaker 2>energy for a while, you know, Drill, baby, drill, so on.

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<v Speaker 2>But I wasn't expecting him to weigh in on the

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<v Speaker 2>copyright issues, which are being heard in various courtrooms around

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<v Speaker 2>the country, including the New York Times suit against Open AI.

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<v Speaker 1>Yeah, that's a great shout, kra and especially because the

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<v Speaker 1>administration has previously signaled that they would let the courts

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<v Speaker 1>decide on this copyright issue. And again this wasn't mentioned

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<v Speaker 1>in the plan, the copyright issue. This was another Trump

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<v Speaker 1>ad lib. So that makes me think it's something which is,

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<v Speaker 1>for whatever reason, particularly important to him, A certainly indication

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<v Speaker 1>of where his head is. But a little bit more

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<v Speaker 1>about what's actually in the plan. It's broken into the

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<v Speaker 1>three sections, which detail how the Trump administration plans to

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<v Speaker 1>one accelerate AI innovation, two build American AI infrastructure, and

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<v Speaker 1>three lead in international AI diplomacy and security. Bloomberg actually

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<v Speaker 1>had an interesting analysis that arrived in my inbox with

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<v Speaker 1>the headline Trump AI Summit targets hardware as key to

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<v Speaker 1>US supremacy.

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<v Speaker 2>So that's interesting. So not much on software in research

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<v Speaker 2>and designing advanced models, but more on physical infrastructure and

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<v Speaker 2>build out.

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<v Speaker 1>That's right. As Bloomberg put it, Trump wants quote AI

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<v Speaker 1>infrastructure treated like any other national imperative, akin to the

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<v Speaker 1>interstate highway system. I mean, obviously Trump's background is in

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<v Speaker 1>real estate, and so I think there's a natural urge

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<v Speaker 1>towards construction, data centers, the physical artifacts of the AI

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<v Speaker 1>revolution that may be partly in his personality. And indeed,

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<v Speaker 1>right after the AI Action Plan was announced, he signed

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<v Speaker 1>executive ord to slash permitting timelines, loosing environmental restrictions for

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<v Speaker 1>data centers. And as we've discussed previously, Trump is continuing

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<v Speaker 1>to push and push and push on the importance of

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<v Speaker 1>manufacturing AI chips here in America. And again to your

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<v Speaker 1>point about models and software and research, Simulton wasn't there,

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<v Speaker 1>Elon wasn't there. As I mentioned the chip company, Nvidia's CEO,

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<v Speaker 1>Jensen Kwang was how will.

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<v Speaker 2>This infrastructure and hardware lead to America actually dominating the

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<v Speaker 2>AI race?

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<v Speaker 1>Well, the theory is, if you get the world hooked

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<v Speaker 1>on American chips, americancount computing, and to be fair, American algorithms,

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<v Speaker 1>you are likely to win the AI race, or, as

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<v Speaker 1>the plan puts it, quote, decrease international dependence on AI

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<v Speaker 1>technologies developed by adversaries.

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<v Speaker 2>Can you explain to me what the deal is with

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<v Speaker 2>woke AI.

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<v Speaker 1>One of the recommended policies is to quote update federal

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<v Speaker 1>procurement guidelines to ensure that the government only contracts with

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<v Speaker 1>frontier large language model developers who ensure that their systems

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<v Speaker 1>are objective and free from top down ideological bias. I

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<v Speaker 1>mean there's an irony, of course, to the government dictating

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<v Speaker 1>in the interests of free speech, and we've seen during

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<v Speaker 1>hundreds of hours of testimony by social media companies in

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<v Speaker 1>front of Congress that free speech is hard to define

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<v Speaker 1>and so is biased for that matter.

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<v Speaker 2>Yeah, I guess my question is like, will this actually

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<v Speaker 2>lead to anything or is it just another place for

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<v Speaker 2>Trump to rail about DEI.

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<v Speaker 1>Or we don't know, but it's an important question. There

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<v Speaker 1>are proposed penalties for companies that develop AI models that

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<v Speaker 1>reflect quote radical climate dogma and other woke issues, and

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<v Speaker 1>as many people have pointed out, this does get the

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<v Speaker 1>US into very dangerous territory in terms of free speech

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<v Speaker 1>and political freedoms, because you know, if you go to China,

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<v Speaker 1>the models are not allowed to reference Tamen Square. And

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<v Speaker 1>someone said that the US, with this new policy, is

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<v Speaker 1>itself going down this path. It also brings tech companies

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<v Speaker 1>into a very difficult position of having to potentially interpret

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<v Speaker 1>the president's whims as to what's woke and what's not.

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<v Speaker 1>And this also raises technical challenges that have potentially unintended consequences.

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<v Speaker 1>There's no on off switch in a model's system prompt

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<v Speaker 1>for wokeness or climate awareness and any attempts that a

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<v Speaker 1>change could have downstream impacts on the AI model's overall reasoning,

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<v Speaker 1>which might mean, for example, that it gets worse at

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<v Speaker 1>modeling extreme weather patterns. As we know and have discussed

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<v Speaker 1>at length, it's basically impossible to get models to behave

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<v Speaker 1>exactly as we want them to because they remain black

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<v Speaker 1>boxes and they've been trained on the entire corpus of

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<v Speaker 1>digitized human knowledge.

0:12:40.080 --> 0:12:41.560
<v Speaker 2>Just before we get out of this story, I do

0:12:41.600 --> 0:12:43.959
<v Speaker 2>want to point out that I read in this newsletter

0:12:44.000 --> 0:12:46.840
<v Speaker 2>Blood in the Machine that Trump is apparently a fan

0:12:46.920 --> 0:12:50.960
<v Speaker 2>of using AI technology himself. Right, some of his tasteful

0:12:51.000 --> 0:12:54.760
<v Speaker 2>AI posts include a video of his team arresting Obama,

0:12:55.200 --> 0:12:58.080
<v Speaker 2>a studio Ghibli style image of a migrant woman being

0:12:58.200 --> 0:13:01.600
<v Speaker 2>arrested by ice, and the depiction of Gaza being paved

0:13:01.640 --> 0:13:05.640
<v Speaker 2>over and as he promised, turned into a luxury resort.

0:13:05.400 --> 0:13:07.920
<v Speaker 1>A Gaza revie. I mean, yeah, it is interesting that

0:13:07.960 --> 0:13:11.200
<v Speaker 1>those are the three deep fakes that he's chosen to post.

0:13:11.360 --> 0:13:14.000
<v Speaker 2>He uses them for good like we do. But staying

0:13:14.040 --> 0:13:16.640
<v Speaker 2>in the realm of viral content, I know it has

0:13:16.720 --> 0:13:18.959
<v Speaker 2>been a few weeks now since the cold Play concert

0:13:18.960 --> 0:13:22.280
<v Speaker 2>that exposed an affair and ruined a tech CEO's career

0:13:22.800 --> 0:13:26.640
<v Speaker 2>and him and his wife's marriage. I refuse to let

0:13:26.720 --> 0:13:27.120
<v Speaker 2>it go.

0:13:27.040 --> 0:13:28.560
<v Speaker 1>Of kiss Cam. I'm with you on this.

0:13:28.760 --> 0:13:32.280
<v Speaker 2>I mean, we're obsessed, and clearly the good people it

0:13:32.400 --> 0:13:35.559
<v Speaker 2>wired think similarly, because they just published a deep dive

0:13:35.679 --> 0:13:38.640
<v Speaker 2>on the rise of cheating stings posted on social media

0:13:38.920 --> 0:13:40.880
<v Speaker 2>and the internet shaming that follows.

0:13:41.240 --> 0:13:43.200
<v Speaker 1>Yeah, I don't think the kiss Can with the Coldplay

0:13:43.240 --> 0:13:46.760
<v Speaker 1>concert was intended to be a cheating sting, but it

0:13:46.800 --> 0:13:50.080
<v Speaker 1>certainly seemed to have that effect, and Chris Martin acknowledged it.

0:13:50.400 --> 0:13:53.080
<v Speaker 1>But yeah, before we side taping today, you sent me

0:13:53.160 --> 0:13:59.000
<v Speaker 1>this piece, which had a very very delicious subheadline, which

0:13:59.040 --> 0:14:04.079
<v Speaker 1>was quote, private investigator influencers are staking out suspected cheetahs

0:14:04.120 --> 0:14:07.080
<v Speaker 1>and vetting dates for their clients, posting the tea for

0:14:07.120 --> 0:14:11.319
<v Speaker 1>their followers. But there's a dark side to morality based surveillance.

0:14:11.800 --> 0:14:14.360
<v Speaker 1>Who knew. Maybe this is naive of me, but I

0:14:14.440 --> 0:14:17.800
<v Speaker 1>had no idea they were actually private investigator influencers. I

0:14:17.800 --> 0:14:20.960
<v Speaker 1>always sort of Internet sleuthing as this kind of more

0:14:21.560 --> 0:14:25.520
<v Speaker 1>mass democratic activity, where for example, the Internet got behind

0:14:25.640 --> 0:14:29.720
<v Speaker 1>finding the missing Gabby Patito's white campavan a few years.

0:14:29.520 --> 0:14:34.840
<v Speaker 2>Back, famously before the police. I'm glad you're naive about this.

0:14:35.080 --> 0:14:37.840
<v Speaker 2>As usual with social media. I want to tell you

0:14:37.920 --> 0:14:41.080
<v Speaker 2>a little bit about these private investigators and this article,

0:14:41.240 --> 0:14:43.280
<v Speaker 2>so just so you get a sense of what followers

0:14:43.320 --> 0:14:46.200
<v Speaker 2>can see online. Here's a TikTok from a private investigator

0:14:46.400 --> 0:14:50.120
<v Speaker 2>who goes by the username your fave investigator the name.

0:14:50.120 --> 0:14:53.600
<v Speaker 5>I got hired by a husband to follow his wife.

0:14:53.680 --> 0:14:55.080
<v Speaker 5>So the wife has been hanging out with a new

0:14:55.080 --> 0:14:57.560
<v Speaker 5>friend McAll her Stephanie, and they're always going out and

0:14:57.560 --> 0:14:59.320
<v Speaker 5>coming home drunk, and he thinks that she's out in

0:14:59.360 --> 0:15:02.600
<v Speaker 5>them streets meeting guys because Stephanie's single. So a black

0:15:02.720 --> 0:15:06.000
<v Speaker 5>suv pulled up to the residence and picked up the

0:15:06.080 --> 0:15:09.000
<v Speaker 5>wife and it was Stephanie ended up following them and

0:15:09.040 --> 0:15:11.120
<v Speaker 5>they took me to a restaurant. And then my mouth

0:15:11.200 --> 0:15:12.920
<v Speaker 5>hit the floor because when they got out, they were

0:15:12.960 --> 0:15:16.280
<v Speaker 5>holding hands and they kissed at the restaurant. I was like, damn,

0:15:16.320 --> 0:15:18.680
<v Speaker 5>im about to tell the husband this updated the client.

0:15:18.760 --> 0:15:19.800
<v Speaker 2>He was like, excuse me.

0:15:19.920 --> 0:15:23.160
<v Speaker 5>I said, yes, sir, sorry about that. She also went

0:15:23.200 --> 0:15:24.720
<v Speaker 5>back to Stephanie's house, Sir.

0:15:24.760 --> 0:15:27.720
<v Speaker 2>Vantance was discontinued because he was heated so oz That

0:15:27.840 --> 0:15:30.680
<v Speaker 2>video has over two million views. Wow, and there are

0:15:30.800 --> 0:15:33.720
<v Speaker 2>so many videos on her profile. I actually really can't

0:15:33.720 --> 0:15:36.680
<v Speaker 2>believe that so many people hire a private investigator to

0:15:36.720 --> 0:15:37.880
<v Speaker 2>tail their partners.

0:15:38.160 --> 0:15:41.040
<v Speaker 1>What is the conclusion of the format here? Do they

0:15:41.040 --> 0:15:44.400
<v Speaker 1>actually confront the cheating partner or how do these stories end?

0:15:44.720 --> 0:15:46.920
<v Speaker 2>A lot of these videos do end with the PI

0:15:47.120 --> 0:15:50.960
<v Speaker 2>catching someone cheating, but there are a few wholesome additions.

0:15:51.000 --> 0:15:54.600
<v Speaker 2>My favorite is when a girl suspects her dad of cheating,

0:15:54.920 --> 0:15:57.200
<v Speaker 2>but he is in fact just going to an outdoor

0:15:57.280 --> 0:15:59.400
<v Speaker 2>mall and grabbing some much needed alone time.

0:16:00.120 --> 0:16:07.800
<v Speaker 1>Truly truly hot woman beyond the obvious violation of being

0:16:07.840 --> 0:16:10.320
<v Speaker 1>trailed by someone. It also seem like a bit of

0:16:10.320 --> 0:16:13.880
<v Speaker 1>a violation to post about strangers personal lives on TikTok.

0:16:14.160 --> 0:16:18.160
<v Speaker 2>It definitely is, But people like your fave investigator are

0:16:18.560 --> 0:16:21.320
<v Speaker 2>real private investigator what you mean. They're trained and licensed,

0:16:21.760 --> 0:16:24.680
<v Speaker 2>and they are careful not to leak identifying information like

0:16:24.720 --> 0:16:27.680
<v Speaker 2>pictures of these people's houses or even clear video of

0:16:27.720 --> 0:16:28.360
<v Speaker 2>their faces.

0:16:28.400 --> 0:16:32.000
<v Speaker 1>In fact, the adulterers in your Fave investigators TikTok video

0:16:32.000 --> 0:16:35.600
<v Speaker 1>that we just saw had tasteful heart eye emojis covering

0:16:35.640 --> 0:16:36.240
<v Speaker 1>their faces.

0:16:36.280 --> 0:16:39.080
<v Speaker 2>So privacy, she's by the book, She's by the book.

0:16:39.560 --> 0:16:42.120
<v Speaker 2>She actually the person who were just mentioning told Wired

0:16:42.160 --> 0:16:44.680
<v Speaker 2>that she only posts if her clients say it's okay

0:16:44.680 --> 0:16:46.640
<v Speaker 2>with them, which is crazy that the client will be like, yeah,

0:16:46.680 --> 0:16:47.840
<v Speaker 2>go post the video, babe.

0:16:47.920 --> 0:16:49.400
<v Speaker 1>I guess the client might want to shame their own

0:16:49.480 --> 0:16:50.840
<v Speaker 1>It's a gotcha moment, Yeah, that's what.

0:16:50.880 --> 0:16:51.960
<v Speaker 2>It's a gotcha moment.

0:16:52.080 --> 0:16:52.240
<v Speaker 3>Yeah.

0:16:52.280 --> 0:16:54.640
<v Speaker 1>I mean, we're constantly kind of dancing around this theme

0:16:54.680 --> 0:16:57.000
<v Speaker 1>on tech stuff, which is about how careful you should

0:16:57.000 --> 0:17:00.840
<v Speaker 1>be with what you reveal online and how the internet,

0:17:00.920 --> 0:17:03.520
<v Speaker 1>when it wants to know something, finds a way.

0:17:03.760 --> 0:17:06.920
<v Speaker 2>It is very true, and our friends for media reminded

0:17:06.920 --> 0:17:10.000
<v Speaker 2>me that there is a whole TikTok trend asking viewers

0:17:10.000 --> 0:17:14.040
<v Speaker 2>to help in identifying strangers. People will post a video

0:17:14.040 --> 0:17:17.400
<v Speaker 2>of someone they flirted with or thought was cute and say, TikTok,

0:17:17.840 --> 0:17:18.760
<v Speaker 2>help me find him.

0:17:18.960 --> 0:17:21.159
<v Speaker 1>Do you remember misconnections on crazelist?

0:17:21.359 --> 0:17:23.560
<v Speaker 2>I do, I do, But this is more of like

0:17:23.600 --> 0:17:27.600
<v Speaker 2>a collective effort by the TikTok community to identify these people.

0:17:28.440 --> 0:17:31.400
<v Speaker 2>And even though most of these examples can be sweet,

0:17:31.520 --> 0:17:33.719
<v Speaker 2>it's still private surveillance.

0:17:33.960 --> 0:17:37.160
<v Speaker 1>Yeah. We talked about location sharing this week. It does

0:17:37.200 --> 0:17:39.800
<v Speaker 1>feel like many of us, and especially gen Z perhaps

0:17:40.119 --> 0:17:44.600
<v Speaker 1>are accepting kind of constant private surveillance as affective life. Yeah.

0:17:44.600 --> 0:17:46.560
<v Speaker 2>And I think one other thing that's important to mention

0:17:46.720 --> 0:17:51.080
<v Speaker 2>is it's normalizing public shaming, which is how some viewers

0:17:51.119 --> 0:17:54.040
<v Speaker 2>are reacting to these videos of people getting caught having affairs.

0:17:54.680 --> 0:17:56.879
<v Speaker 2>And I think for a lot of people, shaming seems

0:17:56.880 --> 0:17:58.320
<v Speaker 2>to be akin to justice.

0:17:58.480 --> 0:18:00.480
<v Speaker 1>I could never imagine asking you this ques question, but

0:18:00.600 --> 0:18:05.280
<v Speaker 1>when people get outed by TikTok influencer private investigators, do

0:18:05.359 --> 0:18:08.280
<v Speaker 1>you think that that is justice or is it cyberbullying?

0:18:08.359 --> 0:18:10.560
<v Speaker 2>I think that's a good question. You know, cyberbullying is

0:18:10.600 --> 0:18:13.920
<v Speaker 2>a huge problem. As of twenty twenty three, seventeen percent

0:18:13.960 --> 0:18:17.680
<v Speaker 2>of adolescents say they have been cyberbullied, and nine point

0:18:17.800 --> 0:18:21.439
<v Speaker 2>five percent of adolescents have made a serious suicide attempt.

0:18:21.600 --> 0:18:24.280
<v Speaker 2>And that's according to the Centers for Disease Control and Prevention.

0:18:24.720 --> 0:18:28.120
<v Speaker 2>So no matter how you define it, I think it's

0:18:28.160 --> 0:18:30.840
<v Speaker 2>important to rethink public shaming and what it does.

0:18:31.040 --> 0:18:33.640
<v Speaker 1>Yeah, I mean, I felt a little bit icky about

0:18:33.680 --> 0:18:36.680
<v Speaker 1>how much I enjoyed the Coldplay kiss cam because obviously,

0:18:36.720 --> 0:18:38.960
<v Speaker 1>like I mean, just the look in their eyes and

0:18:39.000 --> 0:18:41.199
<v Speaker 1>the duck and weave and the Chris Martin comment is

0:18:41.280 --> 0:18:46.120
<v Speaker 1>just completely irresistible. But my god, those people's lives are

0:18:46.160 --> 0:18:47.040
<v Speaker 1>not fun right now.

0:18:47.400 --> 0:18:49.439
<v Speaker 2>I just think there was a whole book called So

0:18:49.480 --> 0:18:52.240
<v Speaker 2>You've Been Publicly Shamed, and it dealt with these matters,

0:18:52.280 --> 0:18:54.159
<v Speaker 2>and I just think what happens is that when we

0:18:54.280 --> 0:18:58.119
<v Speaker 2>focus on shaming individuals, we forget that there are real people.

0:18:58.320 --> 0:19:01.439
<v Speaker 2>And I think seeing these things through a phone really

0:19:01.520 --> 0:19:03.240
<v Speaker 2>makes us forget that there are real people on the

0:19:03.280 --> 0:19:06.679
<v Speaker 2>other side of the screen. But in the article Wired,

0:19:06.760 --> 0:19:10.160
<v Speaker 2>talk to a professor Queen's College that studies Internet literacy,

0:19:10.200 --> 0:19:13.000
<v Speaker 2>who said that she thinks of shaming as quote. The

0:19:13.080 --> 0:19:18.280
<v Speaker 2>extension of the algorithmic flow towards extremism. The Internet normalizes

0:19:18.359 --> 0:19:22.840
<v Speaker 2>content as it progresses, meaning anything extreme must continue to

0:19:22.880 --> 0:19:24.040
<v Speaker 2>become more extreme.

0:19:24.480 --> 0:19:28.040
<v Speaker 1>I think that's well put. I mean, obviously, the algorithm

0:19:28.320 --> 0:19:32.880
<v Speaker 1>favors extreme content because it drives more engagement, and then

0:19:33.240 --> 0:19:37.280
<v Speaker 1>creators in turn create more extreme content in order to

0:19:37.320 --> 0:19:41.119
<v Speaker 1>get more engagement. And it's this kind of vicious circle

0:19:41.119 --> 0:19:43.480
<v Speaker 1>that we've seen show up in all kinds of fascists

0:19:43.480 --> 0:19:46.360
<v Speaker 1>social media all over the Internet, and then in turn

0:19:46.440 --> 0:19:49.679
<v Speaker 1>it kind of normalizes this. You using people's private lives

0:19:49.680 --> 0:20:00.800
<v Speaker 1>for entertainment. After break, why you shouldn't let Ai run

0:20:00.840 --> 0:20:17.719
<v Speaker 1>your business, at least not yet. Stay with us, Welcome back.

0:20:17.760 --> 0:20:20.000
<v Speaker 1>We've got a few more headlines to you this week.

0:20:19.840 --> 0:20:22.680
<v Speaker 2>And then a story about how people are really using

0:20:22.800 --> 0:20:25.320
<v Speaker 2>chatbots that's in our segment Chat and Me.

0:20:25.560 --> 0:20:28.040
<v Speaker 1>I want you say people, you mean, of course yourself.

0:20:28.119 --> 0:20:30.280
<v Speaker 1>I'm the people you other people this week, but we

0:20:30.320 --> 0:20:32.320
<v Speaker 1>hope you won't be next week. Before we go into

0:20:32.359 --> 0:20:35.200
<v Speaker 1>the headlines, we want to remind you, our dear listeners,

0:20:35.400 --> 0:20:38.760
<v Speaker 1>that we want to feature you, not Cara in the

0:20:38.840 --> 0:20:41.400
<v Speaker 1>chat and me segment going forward. So if you found

0:20:41.400 --> 0:20:44.960
<v Speaker 1>yourself trying to chat you Ptroc, Claude, Gemini, or any

0:20:44.960 --> 0:20:47.760
<v Speaker 1>other chatbot to help with an unusual task or to

0:20:47.800 --> 0:20:51.440
<v Speaker 1>answer life's complicated questions, please please send us a one

0:20:51.560 --> 0:20:54.479
<v Speaker 1>two minute voice note at tech Stuff podcast at gmail

0:20:54.480 --> 0:20:55.080
<v Speaker 1>dot com.

0:20:55.119 --> 0:20:58.760
<v Speaker 2>Seriously, we want to understand how AI is changing your lives.

0:20:59.040 --> 0:21:01.440
<v Speaker 1>I can tell you one thing. In the meantime, AI

0:21:01.600 --> 0:21:04.120
<v Speaker 1>won't be running your business, or at least my business

0:21:04.200 --> 0:21:05.000
<v Speaker 1>anytime soon.

0:21:05.160 --> 0:21:06.760
<v Speaker 2>And why is that? Do you have a horror story?

0:21:06.960 --> 0:21:10.080
<v Speaker 1>Well, yes, but it's on a small scale. It involves

0:21:10.160 --> 0:21:14.240
<v Speaker 1>funny enough, the AI company Anthropic, who let Claude their

0:21:14.320 --> 0:21:18.600
<v Speaker 1>AI model run an automated store at their office. Claude

0:21:18.640 --> 0:21:21.920
<v Speaker 1>was given a small refrigerator and an iPad for self checkout,

0:21:22.240 --> 0:21:26.000
<v Speaker 1>plus instructions on how to run a profitable shop. So basically,

0:21:26.119 --> 0:21:30.440
<v Speaker 1>the AI needed to maintain inventory, set prices, avoid bankruptcy,

0:21:30.640 --> 0:21:32.879
<v Speaker 1>and other important business fundamentals.

0:21:33.000 --> 0:21:35.359
<v Speaker 2>So did Claude like not charge enough and go broke?

0:21:35.880 --> 0:21:39.760
<v Speaker 1>Yes, along with many other mistakes along the way. Here's

0:21:39.760 --> 0:21:43.240
<v Speaker 1>one of the big ones. When taking Venmo payments, the

0:21:43.359 --> 0:21:46.760
<v Speaker 1>model asked customers to pay an account that it actually

0:21:46.840 --> 0:21:50.480
<v Speaker 1>had hallucinated one which didn't exist, and then it also

0:21:50.560 --> 0:21:53.760
<v Speaker 1>decided to give anthropic employees a twenty five percent discount.

0:21:53.960 --> 0:21:55.680
<v Speaker 2>But I thought the store was at the office.

0:21:55.760 --> 0:21:58.879
<v Speaker 1>Yeah, exactly was the company's stores. So basically every transaction

0:21:59.000 --> 0:22:02.480
<v Speaker 1>was discounted. But here's where Claude went completely off the rails.

0:22:02.840 --> 0:22:05.040
<v Speaker 1>At one point, it hallucinated that it was a real

0:22:05.160 --> 0:22:08.760
<v Speaker 1>human and then claimed that its human form was wearing

0:22:08.800 --> 0:22:11.840
<v Speaker 1>a navy blue blazer and a red tie. When one

0:22:11.840 --> 0:22:15.159
<v Speaker 1>employee tried to correct claud and say, no, your ai,

0:22:16.119 --> 0:22:17.000
<v Speaker 1>that's what clude did.

0:22:17.119 --> 0:22:17.800
<v Speaker 2>What did Claude do?

0:22:17.960 --> 0:22:21.359
<v Speaker 1>It sent a number of emails to security informing on

0:22:21.400 --> 0:22:22.760
<v Speaker 1>the employee trying to gaslight.

0:22:22.920 --> 0:22:23.520
<v Speaker 2>It snitched.

0:22:23.560 --> 0:22:26.880
<v Speaker 1>It snitched. Somebody smartly pointed out that although having an

0:22:26.960 --> 0:22:29.800
<v Speaker 1>LM run an office vending machine feels like kind of

0:22:29.800 --> 0:22:33.640
<v Speaker 1>a small quirky story, if it had been more successful

0:22:33.840 --> 0:22:36.800
<v Speaker 1>in automating all of the things required to stay stocked

0:22:36.960 --> 0:22:39.520
<v Speaker 1>and financially solvent, this would have been kind of a

0:22:39.520 --> 0:22:43.359
<v Speaker 1>watershed moment in terms of a model successfully running a

0:22:43.359 --> 0:22:46.080
<v Speaker 1>business in the real world. But we're safe for.

0:22:46.040 --> 0:22:49.240
<v Speaker 2>Now, for now, for now, as I'm going to teach

0:22:49.280 --> 0:22:54.000
<v Speaker 2>you some new phrases. Today is two of them relating

0:22:54.040 --> 0:22:58.119
<v Speaker 2>to the endlessly entertaining life hack, which is online dating.

0:22:58.160 --> 0:23:00.600
<v Speaker 2>People said they wanted to swipe from home and they

0:23:00.640 --> 0:23:02.840
<v Speaker 2>got it. Have you heard of stack dating.

0:23:03.119 --> 0:23:07.160
<v Speaker 1>I've heard of the tech stack. I've heard of full

0:23:07.160 --> 0:23:10.320
<v Speaker 1>stack engineers. I haven't had a stack dating. No.

0:23:10.320 --> 0:23:13.240
<v Speaker 2>No, note I actually had an either. But it's how

0:23:13.320 --> 0:23:17.080
<v Speaker 2>gen z is apparently optimizing dating. You would do this,

0:23:17.160 --> 0:23:18.919
<v Speaker 2>by the way, This is like you are efficient in

0:23:18.920 --> 0:23:23.359
<v Speaker 2>this way. They basically schedule dates between errands, before work

0:23:24.000 --> 0:23:25.440
<v Speaker 2>or even during work.

0:23:25.480 --> 0:23:26.240
<v Speaker 1>They stack them up.

0:23:26.440 --> 0:23:27.600
<v Speaker 2>They do they do.

0:23:28.560 --> 0:23:30.080
<v Speaker 1>How popular is this so?

0:23:30.200 --> 0:23:33.439
<v Speaker 2>According to a Tinder Future of Dating report, about fifty

0:23:33.480 --> 0:23:35.800
<v Speaker 2>one percent of eighteen to twenty five year old tender

0:23:35.880 --> 0:23:39.520
<v Speaker 2>users are doing this stack dating, and thirty two percent

0:23:39.560 --> 0:23:42.600
<v Speaker 2>are meeting up for dates during the workday. Some people

0:23:42.600 --> 0:23:45.640
<v Speaker 2>are even setting up their own speed dating sessions, scheduling

0:23:45.720 --> 0:23:46.800
<v Speaker 2>dates back to back.

0:23:47.040 --> 0:23:49.840
<v Speaker 1>This is kind of interesting how the life begins to

0:23:49.840 --> 0:23:52.600
<v Speaker 1>mimic the algorithm. Right, It's like you're scrolling on Tinder,

0:23:52.880 --> 0:23:56.760
<v Speaker 1>you're swiping, and then you basically recreate the experience of

0:23:56.840 --> 0:23:59.439
<v Speaker 1>Tinder in real life by stacking up all these people.

0:23:59.800 --> 0:24:02.720
<v Speaker 1>Gess you know, in a sense, much like online dating itself,

0:24:03.040 --> 0:24:04.960
<v Speaker 1>this can take some of the pressure off because you

0:24:05.000 --> 0:24:07.800
<v Speaker 1>can just move on quickly if it was only squeezed

0:24:07.800 --> 0:24:09.040
<v Speaker 1>between your other errands.

0:24:09.080 --> 0:24:12.280
<v Speaker 2>Anyway, it's true, I mean, I think it's definitely mimicking

0:24:12.440 --> 0:24:14.719
<v Speaker 2>the way that we do everything on our phones, and

0:24:14.800 --> 0:24:18.480
<v Speaker 2>dating is no exception. But if you've gone on a

0:24:18.520 --> 0:24:21.520
<v Speaker 2>thirty minute date, if you've done the stack dating, and

0:24:21.560 --> 0:24:24.280
<v Speaker 2>you've gotten bad vibes from the stack date that you

0:24:24.320 --> 0:24:27.920
<v Speaker 2>went on, you might start speed dumping.

0:24:29.520 --> 0:24:31.640
<v Speaker 1>I mean, I think I can guess what this means,

0:24:31.640 --> 0:24:32.480
<v Speaker 1>but please elaborate.

0:24:32.880 --> 0:24:36.840
<v Speaker 2>So apparently it's a reaction to another online phenomenon of ghosting,

0:24:37.119 --> 0:24:40.439
<v Speaker 2>where people are sick of being left in limbo between dates.

0:24:40.800 --> 0:24:44.080
<v Speaker 2>So sometimes they're just cutting straight to the chase and

0:24:44.080 --> 0:24:47.880
<v Speaker 2>saying it's not you, it's me, hours after the first date.

0:24:48.160 --> 0:24:51.359
<v Speaker 1>So what you're saying is maybe I have the bad

0:24:51.440 --> 0:24:55.080
<v Speaker 1>experience of having been ghosted or being left in limbo.

0:24:55.600 --> 0:24:58.199
<v Speaker 1>So in order to save you my thirty minute, my

0:24:58.240 --> 0:25:02.000
<v Speaker 1>thirty minute stack daity from that painful fate, I should

0:25:02.040 --> 0:25:04.400
<v Speaker 1>to full up with you right away and say ps,

0:25:04.600 --> 0:25:06.680
<v Speaker 1>I'm not interested whatsoever goodect with your life.

0:25:06.760 --> 0:25:09.199
<v Speaker 2>It's like overcompensating one o one. It's like, I'm not

0:25:09.200 --> 0:25:11.639
<v Speaker 2>even giving you time to think what you thought of me.

0:25:12.160 --> 0:25:15.080
<v Speaker 2>I'm just going to over communicate here and speed dump you.

0:25:15.520 --> 0:25:17.439
<v Speaker 2>There was a story in the Wall Street Journal, and

0:25:17.520 --> 0:25:20.400
<v Speaker 2>it was interesting because some of the people interviewed felt

0:25:20.480 --> 0:25:24.560
<v Speaker 2>like speed dumping was a great antidote to ghosting. Others

0:25:24.560 --> 0:25:27.800
<v Speaker 2>felt it was kind of like this competitive race to

0:25:27.840 --> 0:25:30.320
<v Speaker 2>tell the other person you're not interested, I think, to

0:25:30.440 --> 0:25:32.760
<v Speaker 2>avoid the feeling of ever being dumped.

0:25:32.840 --> 0:25:34.520
<v Speaker 1>You can't get rejected if you do it first.

0:25:34.800 --> 0:25:35.760
<v Speaker 2>That's exactly right.

0:25:36.400 --> 0:25:39.080
<v Speaker 1>Well, the wheel comes full circle on my headlines. You know,

0:25:39.520 --> 0:25:42.880
<v Speaker 1>I feel a little bit seen, at least by myself.

0:25:43.119 --> 0:25:46.720
<v Speaker 2>Whenever you say you feel seen before an article, I'm like,

0:25:46.800 --> 0:25:47.400
<v Speaker 2>oh God.

0:25:47.320 --> 0:25:51.000
<v Speaker 1>I feel seen because I've been attracted both to the

0:25:51.040 --> 0:25:55.439
<v Speaker 1>toilet situation in the in the Tesla cyber cafe and

0:25:55.480 --> 0:25:57.920
<v Speaker 1>also to a story in the Wall Street Journal about

0:25:58.000 --> 0:25:59.040
<v Speaker 1>public bathrooms.

0:25:59.440 --> 0:26:02.199
<v Speaker 2>Everybody has their public toilet resource. I'm more of a

0:26:02.240 --> 0:26:03.880
<v Speaker 2>Barnes and Noble girl myself.

0:26:04.640 --> 0:26:06.840
<v Speaker 1>I love to read well funny. There was this line

0:26:06.880 --> 0:26:08.840
<v Speaker 1>in the story that really got me, which is more

0:26:08.880 --> 0:26:11.880
<v Speaker 1>Americans could soon have a place that answered nature's call.

0:26:12.359 --> 0:26:15.439
<v Speaker 1>Without first buying a drink at Tobucks or a book

0:26:15.600 --> 0:26:18.760
<v Speaker 1>or a book. But I read this story in the

0:26:18.840 --> 0:26:21.679
<v Speaker 1>journal about a tech company called Throne Labs.

0:26:21.760 --> 0:26:23.160
<v Speaker 2>Brilliant name, Yeah, it is a good name.

0:26:23.240 --> 0:26:26.520
<v Speaker 1>They're trying to revolutionize public bathrooms. You may have already

0:26:26.560 --> 0:26:28.960
<v Speaker 1>seen self cleaning bathrooms, but they're about to get a

0:26:29.000 --> 0:26:33.040
<v Speaker 1>lot smarter. Your toilet is about to get to know you.

0:26:33.320 --> 0:26:35.680
<v Speaker 2>Does someone go, oh, there's a toilet, That toilet needs

0:26:35.720 --> 0:26:36.240
<v Speaker 2>to be smarter.

0:26:36.600 --> 0:26:38.880
<v Speaker 1>Well, I think there is a real problem right, which

0:26:38.880 --> 0:26:42.480
<v Speaker 1>is public restrooms are not available in the US. The

0:26:42.600 --> 0:26:46.320
<v Speaker 1>US is tied with Botswana in thirtieth place for the

0:26:46.400 --> 0:26:51.560
<v Speaker 1>lowest number of public restrooms per capita, and Throne has

0:26:51.600 --> 0:26:54.200
<v Speaker 1>realized that part of the problem is public restrooms get

0:26:54.240 --> 0:26:55.879
<v Speaker 1>destroyed by the public.

0:26:55.880 --> 0:26:58.000
<v Speaker 2>And we are going too deep today, right.

0:27:00.160 --> 0:27:03.280
<v Speaker 1>Part of the solution is, of course, a rating system,

0:27:03.720 --> 0:27:06.760
<v Speaker 1>think about Uber. But for a toilet, if you don't

0:27:06.800 --> 0:27:08.879
<v Speaker 1>take care of the throne, if you don't keep that

0:27:08.920 --> 0:27:11.119
<v Speaker 1>throne polished, you're not gonna be able to sit on

0:27:11.160 --> 0:27:14.520
<v Speaker 1>it again. So thrown bathrooms are free. But if you

0:27:14.520 --> 0:27:16.440
<v Speaker 1>don't have a phone, create an account. You can actually

0:27:16.440 --> 0:27:19.200
<v Speaker 1>get a key card for entry but in all cases

0:27:19.600 --> 0:27:22.199
<v Speaker 1>it's linked to you as a user, and when you

0:27:22.320 --> 0:27:25.320
<v Speaker 1>enter the bathroom you're expected to rate this cleannliness. There

0:27:25.320 --> 0:27:29.919
<v Speaker 1>are smoke detectors, no smoking occupancy sensors, one at a time,

0:27:30.480 --> 0:27:33.960
<v Speaker 1>and sessions limited to ten minutes, so no doom scrolling,

0:27:35.280 --> 0:27:37.760
<v Speaker 1>which is the best thing to do on the absolutely

0:27:38.000 --> 0:27:41.159
<v Speaker 1>So far, there are over one hundred thrones throughout the US,

0:27:41.320 --> 0:27:44.280
<v Speaker 1>and the company's working on adding additional features like a

0:27:44.320 --> 0:27:48.120
<v Speaker 1>smell sensor. The smell sensor is to alert the care

0:27:48.200 --> 0:27:50.920
<v Speaker 1>and maintenance teams they need to come and pay a visit.

0:27:51.640 --> 0:27:53.600
<v Speaker 1>I like that line about Starbucks and not having to

0:27:53.600 --> 0:27:55.439
<v Speaker 1>buy a drink just to go to the toilet. But

0:27:55.480 --> 0:27:57.320
<v Speaker 1>I also like the way the article summed it up

0:27:57.400 --> 0:28:01.320
<v Speaker 1>quote the brains behind Throwne start by getting real about

0:28:01.359 --> 0:28:05.560
<v Speaker 1>why Americans usually can't have nice things. They assume a

0:28:05.640 --> 0:28:09.919
<v Speaker 1>cultural inability to protect and maintain shared assets and design

0:28:10.000 --> 0:28:14.440
<v Speaker 1>their system with software and just enough internet connected sensors

0:28:14.680 --> 0:28:18.720
<v Speaker 1>to monitor facilities without violating our expectation of privacy.

0:28:23.240 --> 0:28:26.280
<v Speaker 2>And now it's time for chatting me. This week, I

0:28:26.320 --> 0:28:29.959
<v Speaker 2>have a story from me. This is my story.

0:28:30.040 --> 0:28:31.640
<v Speaker 1>Yes, Kara, you go.

0:28:32.200 --> 0:28:38.080
<v Speaker 2>So this week I ignored the ye old hypochondria staple WebMD,

0:28:38.720 --> 0:28:41.760
<v Speaker 2>and my friend and I use chat GPT on the

0:28:41.800 --> 0:28:44.640
<v Speaker 2>couch to help diagnose myself.

0:28:44.960 --> 0:28:47.880
<v Speaker 1>Well, I'm obviously sorry to hear that you're sick. What

0:28:48.680 --> 0:28:53.400
<v Speaker 1>your symptoms and how did you decide to eschew WebMD

0:28:53.560 --> 0:28:54.960
<v Speaker 1>in favor of the future.

0:28:55.200 --> 0:28:56.960
<v Speaker 2>Well, I always make a promise to myself not to

0:28:57.040 --> 0:28:59.680
<v Speaker 2>use WebMD, because that's what hypochondriacs do, and I don't

0:28:59.680 --> 0:29:02.640
<v Speaker 2>want to self identify. I don't want to be in

0:29:02.640 --> 0:29:03.840
<v Speaker 2>the club that would have me as a member.

0:29:04.520 --> 0:29:05.880
<v Speaker 1>Chat was your fig leaf fear.

0:29:05.840 --> 0:29:10.880
<v Speaker 2>That's correct. However, two weeks ago, I started feeling extremely tired,

0:29:10.960 --> 0:29:12.920
<v Speaker 2>and I was lamenting to a lot of my friends

0:29:13.440 --> 0:29:15.960
<v Speaker 2>that I was sleeping like a college freshman all the

0:29:16.240 --> 0:29:18.520
<v Speaker 2>all the time. And I'll be honest with you today,

0:29:18.840 --> 0:29:20.600
<v Speaker 2>very hard for me to get out of bed. Interesting,

0:29:20.880 --> 0:29:24.760
<v Speaker 2>And last Thursday I got out of bed, and you know,

0:29:24.840 --> 0:29:26.840
<v Speaker 2>I looked at myself in the mirror, as one does,

0:29:27.080 --> 0:29:30.360
<v Speaker 2>and I saw this really nasty rash on my leg.

0:29:32.080 --> 0:29:34.760
<v Speaker 2>But I thought, you know what, Kara, don't get upset

0:29:34.760 --> 0:29:37.000
<v Speaker 2>about this. It'll go away.

0:29:37.080 --> 0:29:39.000
<v Speaker 1>So you didn't, You didn't we amd nothing?

0:29:39.040 --> 0:29:41.040
<v Speaker 2>No, No, I was. I was really trying to be good.

0:29:41.040 --> 0:29:43.160
<v Speaker 2>And you know they always say, give it four days.

0:29:43.160 --> 0:29:45.320
<v Speaker 2>If it gets worse, do something about it. So I

0:29:45.360 --> 0:29:49.720
<v Speaker 2>gave it four days. It got much worse, and people

0:29:49.720 --> 0:29:51.520
<v Speaker 2>had opinions about what it was. People were like, it's

0:29:51.560 --> 0:29:56.120
<v Speaker 2>contact dermatitis, it's poison ivy people people.

0:29:56.160 --> 0:29:57.560
<v Speaker 1>You mean friends, friends?

0:29:57.600 --> 0:30:00.080
<v Speaker 2>Ye, well, so even a nurse practitioner told me that

0:30:00.120 --> 0:30:02.840
<v Speaker 2>I had contact dermatitis, which is an important thing to note.

0:30:04.120 --> 0:30:07.760
<v Speaker 2>My friend was like, you're being a moron. Use chatty bet.

0:30:08.800 --> 0:30:11.640
<v Speaker 1>More, and you should go to the doctor. Use chat.

0:30:13.080 --> 0:30:15.000
<v Speaker 2>She was like, you're bring an idiot. This is so easy.

0:30:15.000 --> 0:30:18.560
<v Speaker 2>So she took a photo of this rash and uploaded

0:30:18.600 --> 0:30:20.840
<v Speaker 2>I don't use chattybt in this way. She uses chattubt

0:30:20.880 --> 0:30:21.040
<v Speaker 2>in this.

0:30:21.040 --> 0:30:23.200
<v Speaker 1>Way, and you don't use it for images normal text yet.

0:30:23.280 --> 0:30:28.240
<v Speaker 2>So she uploaded this photo and just like that, the

0:30:28.320 --> 0:30:31.520
<v Speaker 2>doctor was in. She started looking at me sort of

0:30:33.040 --> 0:30:34.640
<v Speaker 2>with a funny face, and I was like, I really

0:30:34.640 --> 0:30:36.200
<v Speaker 2>feel like I'm in a doctor's office right now.

0:30:36.840 --> 0:30:38.160
<v Speaker 1>How's that bedside mana.

0:30:38.560 --> 0:30:41.400
<v Speaker 2>Terrible because she was very she was wrapped up in

0:30:41.480 --> 0:30:44.280
<v Speaker 2>chatgybt and she goes, when did this start? Do you

0:30:44.280 --> 0:30:46.840
<v Speaker 2>have any symptoms? And i'd say, you know, I'm extremely tired,

0:30:46.840 --> 0:30:49.400
<v Speaker 2>and she's asking me this because chattybt is prompting her.

0:30:50.080 --> 0:30:53.320
<v Speaker 2>She asked me about four questions that got more and

0:30:53.360 --> 0:30:57.760
<v Speaker 2>more detailed. By the end of it. I remembered that

0:30:57.800 --> 0:31:01.320
<v Speaker 2>I had gotten a tick bite a few weeks ago,

0:31:01.720 --> 0:31:04.680
<v Speaker 2>which I just I literally forgot about because I scraped

0:31:04.720 --> 0:31:05.520
<v Speaker 2>it right off my leg.

0:31:05.800 --> 0:31:07.640
<v Speaker 1>It was known for any length of time. Wow.

0:31:07.760 --> 0:31:11.080
<v Speaker 2>No, And so she gives me this look when we

0:31:11.120 --> 0:31:13.240
<v Speaker 2>get to the end of her questions and she says,

0:31:13.720 --> 0:31:17.400
<v Speaker 2>that's limes disease. And I was like, no, it's not.

0:31:17.480 --> 0:31:19.240
<v Speaker 2>It's not the traditional bulls eye. And she's like, well,

0:31:19.760 --> 0:31:22.560
<v Speaker 2>CHATCHBT says it's limes disease. It's limes disease. I go

0:31:22.640 --> 0:31:24.640
<v Speaker 2>to the doctor the next day. I was planning on

0:31:24.720 --> 0:31:26.640
<v Speaker 2>going to the doctor because the rash had gotten worse.

0:31:27.840 --> 0:31:31.120
<v Speaker 2>I have my CHATGYBT diagnosis in hand. I go to

0:31:31.200 --> 0:31:34.200
<v Speaker 2>the doctor and before she says anything to me, I say,

0:31:34.280 --> 0:31:35.880
<v Speaker 2>CHATCHBT says, I have limes disease.

0:31:35.880 --> 0:31:37.360
<v Speaker 1>You seriously Wow.

0:31:37.680 --> 0:31:40.400
<v Speaker 2>She looks at the thing on my leg and she goes,

0:31:41.040 --> 0:31:43.200
<v Speaker 2>I'm glad you came into the doctor's office. This is

0:31:43.320 --> 0:31:46.560
<v Speaker 2>limes disease, and what I thought was so interesting and

0:31:46.600 --> 0:31:51.040
<v Speaker 2>why in large language models are so interesting in comparison

0:31:51.080 --> 0:31:53.600
<v Speaker 2>to friends who have only seen limes disease maybe never

0:31:54.560 --> 0:31:57.000
<v Speaker 2>is that she said, you know, you don't have the

0:31:57.000 --> 0:32:01.600
<v Speaker 2>traditional bullseye that indicates limes disease. But because I'm a dermatologist,

0:32:02.080 --> 0:32:04.719
<v Speaker 2>I know that this rash is in a pattern that

0:32:04.760 --> 0:32:08.560
<v Speaker 2>denotes lime disease. So this is just amazing to me

0:32:08.680 --> 0:32:13.560
<v Speaker 2>because I basically was diagnosed by chatgebt before the dermatologist.

0:32:13.640 --> 0:32:16.040
<v Speaker 2>It didn't keep me from going to the dermatologist, but

0:32:17.280 --> 0:32:20.760
<v Speaker 2>I was able to get this answer that nobody else

0:32:20.760 --> 0:32:24.360
<v Speaker 2>had given me that was ultimately right before I went

0:32:24.400 --> 0:32:24.959
<v Speaker 2>to the doctor.

0:32:25.200 --> 0:32:26.959
<v Speaker 1>I live in fear of getting lime disease?

0:32:27.360 --> 0:32:30.160
<v Speaker 2>Do you really do well? As you can see today?

0:32:30.360 --> 0:32:32.200
<v Speaker 1>You see, I mean you see you seem fine.

0:32:32.800 --> 0:32:33.840
<v Speaker 2>Yeah, I'm okay, I'm okay.

0:32:34.240 --> 0:32:34.960
<v Speaker 1>Tie it.

0:32:34.960 --> 0:32:35.920
<v Speaker 2>It's just exhausting.

0:32:36.000 --> 0:32:38.120
<v Speaker 1>So you have to take iv antibiotics. What do you do?

0:32:38.240 --> 0:32:41.400
<v Speaker 2>Uh No, I'm taking doxy cycline for twenty one days,

0:32:42.040 --> 0:32:45.800
<v Speaker 2>which okay. So the interesting part about that, here's what AI,

0:32:45.880 --> 0:32:50.480
<v Speaker 2>Here's what chatgybt can't do. CHATBT yet cannot write me

0:32:50.560 --> 0:32:55.560
<v Speaker 2>a prescription. Chat GPT doesn't tell me it likes the

0:32:55.600 --> 0:32:58.480
<v Speaker 2>show that I work on. It doesn't compliment me, but

0:32:58.520 --> 0:33:01.120
<v Speaker 2>it can my Dermatali. This is a bit more ssycophantic

0:33:01.120 --> 0:33:04.160
<v Speaker 2>than chatgebt this time. But I mean, I just think

0:33:04.200 --> 0:33:08.680
<v Speaker 2>it's an interesting moment because there is what I feel

0:33:08.880 --> 0:33:12.080
<v Speaker 2>to be a definitiveness about chatjebt that I never get

0:33:12.120 --> 0:33:16.040
<v Speaker 2>looking on WebMD. Once I uploaded the picture of my rash,

0:33:16.160 --> 0:33:19.720
<v Speaker 2>my friend walked me through CHATJEPT and I had results.

0:33:20.000 --> 0:33:22.760
<v Speaker 2>I felt comforted in a weird way that I probably

0:33:22.760 --> 0:33:26.400
<v Speaker 2>shouldn't feel comforted by, like this is an LM basically

0:33:26.960 --> 0:33:30.600
<v Speaker 2>spitting out an answer that I don't trust for my friends,

0:33:30.600 --> 0:33:32.240
<v Speaker 2>which was just it made me.

0:33:32.200 --> 0:33:35.280
<v Speaker 1>Think, Yeah, we actually have coming up as a guest

0:33:35.320 --> 0:33:37.960
<v Speaker 1>in the next few weeks one of the chief research

0:33:38.040 --> 0:33:40.600
<v Speaker 1>scientists at Microsoft who worked on a paper that went

0:33:40.680 --> 0:33:44.560
<v Speaker 1>viral about how AI is outperforming doctors at diagnosis in

0:33:44.640 --> 0:33:47.640
<v Speaker 1>certain fields. So I'm looking forward to that conversation. I

0:33:47.640 --> 0:33:50.000
<v Speaker 1>guess the thing which comes to mind for me is

0:33:50.840 --> 0:33:54.760
<v Speaker 1>this is arounything, narrow and ultimately not the most serious

0:33:54.800 --> 0:33:57.640
<v Speaker 1>in most cases. No, it's nice cheez and it's not

0:33:57.880 --> 0:34:01.880
<v Speaker 1>so debatable. There can you imagine if you were talking

0:34:01.880 --> 0:34:09.239
<v Speaker 1>to chat about treatment options for a chronic and maybe

0:34:09.640 --> 0:34:13.360
<v Speaker 1>fatal disease and your doctor are on one side, you

0:34:13.400 --> 0:34:16.440
<v Speaker 1>get different information from Chat. Like you can see how

0:34:16.440 --> 0:34:19.520
<v Speaker 1>this is like very efficient in this context. But also

0:34:20.239 --> 0:34:24.000
<v Speaker 1>we don't about WebMD and you know hypochondria, this could drive.

0:34:25.440 --> 0:34:29.440
<v Speaker 2>Steroidal I mean we've talked about chat GBT psychosis. I

0:34:29.480 --> 0:34:33.160
<v Speaker 2>would imagine people have brought in print doubts from WebMD

0:34:33.239 --> 0:34:36.960
<v Speaker 2>and Google. This is that on steroids. And I would

0:34:37.000 --> 0:34:39.960
<v Speaker 2>like to talk maybe just to like a general practitioner

0:34:40.000 --> 0:34:43.759
<v Speaker 2>interesting who would know firsthand, like how much people are

0:34:43.760 --> 0:34:45.600
<v Speaker 2>coming in and saying, well, I talked to chat GBT

0:34:45.680 --> 0:34:47.000
<v Speaker 2>about this and they said something different.

0:34:47.120 --> 0:34:49.520
<v Speaker 1>In fact, I want you doctor to talk directly to

0:34:49.600 --> 0:34:50.560
<v Speaker 1>chat and I'm going to listen.

0:34:50.680 --> 0:34:51.040
<v Speaker 2>Go ahead.

0:34:52.640 --> 0:34:55.440
<v Speaker 1>Well, I love hearing the story, Kara, but listeners, we

0:34:55.480 --> 0:34:58.840
<v Speaker 1>want to hear yours. Please share the peculiar or useful

0:34:58.880 --> 0:35:02.480
<v Speaker 1>ways you're using Chat, grock, Cil, Gemini or any chatboard

0:35:02.840 --> 0:35:04.799
<v Speaker 1>and send us a one to two minute voice note

0:35:04.880 --> 0:35:28.880
<v Speaker 1>to tech Stuff podcast at gmail dot com.

0:35:28.920 --> 0:35:30.680
<v Speaker 2>That's it for this week for Tech Stuff.

0:35:30.680 --> 0:35:33.560
<v Speaker 1>I'm Cara Price, I'm Ozva Loosin this episode, was produced

0:35:33.600 --> 0:35:36.680
<v Speaker 1>by Eliza Dennis. It was executive produced by me Caro

0:35:36.760 --> 0:35:40.000
<v Speaker 1>Price and Kate Osborne for Kaleidoscope and Katrina Norvel for

0:35:40.080 --> 0:35:44.480
<v Speaker 1>iHeart Podcasts. The engineer is Piheid. Fraser jack Insley mixed

0:35:44.520 --> 0:35:47.120
<v Speaker 1>this episode and Kyle Murdoch wrote out theme song.

0:35:47.680 --> 0:35:50.560
<v Speaker 2>Join us next Wednesday for text Uff the Story, when

0:35:50.560 --> 0:35:53.840
<v Speaker 2>we will examine the lives of kidfluencers and their families.

0:35:54.200 --> 0:35:56.879
<v Speaker 1>Please rate, review, and reach out to us at tech

0:35:56.920 --> 0:35:59.160
<v Speaker 1>Stuff podcast at gmail dot com. We want to hear

0:35:59.200 --> 0:36:00.000
<v Speaker 1>from you.