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Speaker 1: So I had a friend of mine last night.

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Speaker 2: Hey dropped me a text. He says, all it takes.

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Speaker 1: Is talking about the floormats in your car, or putting

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Speaker 1: them away, or putting the snowblower or plow away. You've

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Speaker 1: lived in Minnesota long enough to know that, in which case, yes,

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Speaker 1: I am responsible for the weather. Although it was a

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Speaker 1: much nicer drive, I will say on the way in

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Speaker 1: this morning that it was yesterday. Not on the arterial

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Speaker 1: roads by any stretch of the imagination. Those were still atrocious,

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Speaker 1: But at least on the highway it wasn't so bad.

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Speaker 2: Welcome.

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Speaker 1: It is Twin Cities News Talk Am eleven thirty and

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Speaker 1: one oh three five FM. My name is John Justice,

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Speaker 1: responsible for all the weather, of which we're getting more today.

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Speaker 1: This is why I bring it up. A quick moving

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Speaker 1: wave will sweep across Minnesota today. The National Weather Service

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Speaker 1: says that it will bring a quick one to two

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Speaker 1: inches of snow to the Twin Cities and east central Minnesota.

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Speaker 3: Oh yeah, it was like what like seven on the

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Speaker 3: drive end this morning. I mean, come on, already, we're

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Speaker 3: almost there, John, Are we though? We're almost Are we there?

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Speaker 3: I don't believe you. I don't believe that we're almost there.

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Speaker 4: It's supposed to be like fifty seven on Saturday.

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Speaker 1: Well, I was talking, yeah, yeah, I know we're going

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Speaker 1: to get to that in just a moment. I was

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Speaker 1: talking with Melinda about this. Last night we ended up

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Speaker 1: going and seeing UH project Hail Mary, which I loved,

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Speaker 1: was fantastic, lived up to the hype, even if I

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Speaker 1: did lose a lot to sleep over it that it

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Speaker 1: was a great, great film, absolutely great film, looking forward

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Speaker 1: to seeing it again on UH.

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Speaker 2: On Thursday, we.

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Speaker 1: Were having this conversation and I told her on the

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Speaker 1: drive over because we went to the Emagine Theater, which

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Speaker 1: are gorgeous by the way.

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Speaker 2: Over in White Pear.

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Speaker 1: Lake, and we're driving over and I told her, I said,

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Speaker 1: you know, I'm glad there's actually snow on the ground

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Speaker 1: because it's certainly a lot prettier than what we had prior, right, right,

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Speaker 1: And then I mentioned I'm like, I don't remember getting

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Speaker 1: snowed this late, and then she begins to rattle off, well,

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Speaker 1: you know, this year it happened, and this year it happened,

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Speaker 1: Like okay, fine, I just blocked the bad stuff out

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Speaker 1: of my out of my mind. So again the temperatures

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Speaker 1: dipped into the low single digits this morning. A warning

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Speaker 1: system arrives in the afternoon. According to the story from Bringing.

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Speaker 2: Me the News.

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Speaker 1: What does that mean, a warning system, It's a pretty

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Speaker 1: cursor to the weather. Hey, dude's coming, just letting you know.

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Speaker 1: A few flakes dropped to the ground, just to prepare everybody.

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Speaker 1: Those will bring the temperatures up into the low twenties,

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Speaker 1: as well as a brief burst of snow.

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Speaker 2: So again, two.

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Speaker 1: Inches of snow could fall in the Twin Cities, higher

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Speaker 1: amounts possible in the surrounding region.

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Speaker 2: It won't take long, though, as.

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Speaker 1: Sam and the Master Control Booth mentioned, for the Twin

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Speaker 1: Cities snowpack to be whittled down, with highs expected in

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Speaker 1: the fifties and sixties on Friday and Saturday, respectively.

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Speaker 2: The National Weather Service actually.

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Speaker 1: Says the temperatures may even hit the seventies by the weekend,

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Speaker 1: but the remaining snow is going to keep it lower.

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Speaker 1: There's got to be a term for that, I know.

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Speaker 1: We have like the heat island effect. You know, when

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Speaker 1: you've got a lot of concrete and you live in

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Speaker 1: a warm aria, it heats it up and then it

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Speaker 1: has an impact on the environment around you. I suppose

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Speaker 1: we have something similar with all the ice on the ground,

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Speaker 1: of which there is a lot.

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Speaker 4: For the record, I've never heard of a heat island effect.

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Speaker 1: Oh you've never heard of that. That's a curse for me.

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Speaker 1: Oh wow, you learned something new every day days in

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Speaker 1: a row. Well, heat island effect is not something that

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Speaker 1: people in the Midwest deal with the Yeah, there's that.

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Speaker 2: That's more.

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Speaker 1: And it's also a rather loaded term because a lot

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Speaker 1: of environmental wackos like to use that in warmer climate

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Speaker 1: areas of the country like the Southwest, to you know,

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Speaker 1: push their global warming agenda with the heat island effect,

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Speaker 1: or more specifically, I should say, they're.

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Speaker 2: Anti infrastructure.

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Speaker 1: They don't like to see new buildings go up, new

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Speaker 1: neighborhoods go up. In the story from Bringing the News,

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Speaker 1: it says snow melts should be fairly quick, especially considering

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Speaker 1: March twentieth is the spring equinox. Oh, like Mother Nature

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Speaker 1: cares with our sun angle and hours of sun increasing

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Speaker 1: even faster from that point onwards. Okay, well, I guess

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Speaker 1: there is a scientific reason for it, So maybe I

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Speaker 1: shouldn't have poo pooed it. So so quickly on the

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Speaker 1: show today Devid Cartzenstein Ross. We'll talk AI with him

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Speaker 1: coming up just after six point thirty this morning. If

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Speaker 1: you have any questions for David, anything AI related, feel

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Speaker 1: free to get those in. I'll let you know the

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Speaker 1: way the email and also via the iHeartRadio app. A

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Speaker 1: couple of stories that I always pull stories for Dav,

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Speaker 1: but often you have so many questions we don't have

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Speaker 1: a chance to get to them time permitting. Throughout your questions,

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Speaker 1: through your questions for David Gartenstein Ross, we'll talk a

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Speaker 1: little AI price gouging in the legislature. There are dfllers

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Speaker 1: that want to put a block to this having AI

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Speaker 1: determine how much a customer is willing to pay. I

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Speaker 1: question how often this is happening, and whether or not

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Speaker 1: if it is happening, is AI just streamlining the process

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Speaker 1: of something that we're already doing. Also, there's a story

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Speaker 1: of an AI agent that freed itself and started secretly

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Speaker 1: mining crypto. See to me that that's intelligence. It also

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Speaker 1: shows motivation. Let's see planning on doing with all that money, They're.

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Speaker 2: Gonna buy himself a robot body.

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Speaker 1: That the intents of these are the hard hitting questions

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Speaker 1: that the CEO of Expert Devid Gartenstein Ross will work

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Speaker 1: at answering. Coming up just after six thirty this morning,

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Speaker 1: we are going to keep on the snow theme. By

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Speaker 1: the way, I'm work shopping a new name for Minneapolis

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Speaker 1: man Baby mayor mom Jeans Jacob Fry. I'll share that

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Speaker 1: with you in just a moment. Again, I'm working on

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Speaker 1: it because it's really worthy to say that every single time,

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Speaker 1: even though I've become an expert at saying Minneapolis man

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Speaker 1: Baby meyor mom Jeans Jacob Fry. Hundreds of cars were

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Speaker 1: towed on the first day of the Twin Cities snow emergencies.

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Speaker 1: I find this very hypocritical. I'll explain why coming up

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Speaker 1: in just a moment here on Twin Cities News Talk. Also,

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Speaker 1: we'll talk a little bit about the Trump administration is

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Speaker 1: trying to make the road safer for Americans. No English,

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Speaker 1: no trucking. That's the word coming from the Secretary of Transportation.

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Speaker 2: Oh hell yeah.

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Speaker 1: So we'll give you details on that, and we will

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Speaker 1: hear from you this morning whether you have questions for

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Speaker 1: David comments on what we're talking about here on Twin

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Speaker 1: Cities News Talk. You can email me Justice at iHeartRadio

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Speaker 1: dot com. Can also call we got a brand new

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Speaker 1: phone number eight four four nine four fifty eight fifty

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Speaker 1: five eight four four nine four six five eight five

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Speaker 1: five And if you're listening on the iHeartRadio app, leave

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Speaker 1: us a talkback.

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Speaker 2: Those are brought to you by Lyndahl Realty.

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Speaker 1: We'll get to those coming up next here on Twin

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Speaker 1: Cities News Talk from AM eleven thirty and one oh

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Speaker 1: three five FM.

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Speaker 2: Good morning, and I love your show.

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Speaker 5: John. Up here in northern Minnesota, we don't have any

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Speaker 5: heat islands, but we have an interesting phenomenon that happens

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Speaker 5: in the spring called the pine tree effect. The snowpack

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Speaker 5: in the fields around like Fargo and Grand's Works and

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Speaker 5: Thief River stay really cold. But once you get to

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Speaker 5: where the pine trees are, save from Meige Park Rapis

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Speaker 5: in that area, you'll see a jump in the temperature

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Speaker 5: all because of the dark green pine trees warming up.

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Speaker 5: I made you maybe fifty or sixty degrees and a

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Speaker 5: Fargo may be stuck at thirty or thirty five. It's

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Speaker 5: pretty interesting to see in the spring.

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Speaker 1: You know what talkback starts starts like that from the

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Speaker 1: iHeart radio app and like, I don't know if I'm

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Speaker 1: gearing up for a joke or if from getting into

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Speaker 1: something serious. I was always going to give that a

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Speaker 1: fascinating to talk to you, but I don't want to

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Speaker 1: be sarcastic.

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Speaker 2: It was kind of fascinating.

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Speaker 6: Good morning.

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Speaker 4: I wanted we actually do hear heat island effect up here?

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Speaker 7: Oh, that's like the reason when we were growing up

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Speaker 7: until a lot of times the storms split north and

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Speaker 7: south of the Twin Cities. And then you know, the

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Speaker 7: weather terrorists said, all the heat island effect doesn't exist

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Speaker 7: because you know, if it existed, and then it would

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Speaker 7: ruin the whole global warming and then climate change agenda.

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Speaker 1: Okay, did not have weather terrorists on Tuesday's show, Bengo Guard.

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Speaker 2: So we can go ahead and include that one. Thank

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Speaker 2: you for that.

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Speaker 8: Good morning, John, Kevin Pomonamio. What you're referring to is

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Speaker 8: a refrigeration effect. No, not only is the snow cold,

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Speaker 8: but it will reflect up to ninety five percent of

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Speaker 8: the Sun's energy, which keeps it much cooler. Refrigerator refrigeration.

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Speaker 8: I have a great show, John.

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Speaker 1: All right. I like the ninety five percent of the

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Speaker 1: Sun's energy. It reminds me of.

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Speaker 2: Energy.

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Speaker 1: Energy and of course the sun was a big plot

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Speaker 1: point of Project Hail Mary, which I saw last night

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Speaker 1: at the Imagine in Whitebear Lake. Yeah.

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Speaker 9: I go to anc Spoon Rapids sometimes, but nothing beats

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Speaker 9: the Imagitators.

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Speaker 1: Yeah, no, you're absolutely right. That was I think that

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Speaker 1: was my second time going to one. The last time

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Speaker 1: was a long time ago, and that was one that

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Speaker 1: was closer to my home. That theater is really really nice,

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Speaker 1: so we're definitely going to be going back there. I

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Speaker 1: will be seeing it again at an AMC on Thursday.

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Speaker 1: I'm taking Logan to go see Project Hail Mary. Back

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Speaker 1: to the Snow, just briefly, Minneapolis and Saint Paul both

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Speaker 1: declared snow emergencies. They did this in advance of the

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Speaker 1: weekend's blockbuster snowstorm, speaking of movies. Between the cities, more

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Speaker 1: than eleven hundred cars were ticketed. Three hundred were towed

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Speaker 1: away because they blocked the path of plows trying to

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Speaker 1: clear roughly a foot of snow from curb to curb.

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Speaker 1: Snow emergencies are multi day events for those that aren't aware.

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Speaker 1: In Minneapolis and Saint Paul, the story here from Channel

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Speaker 1: five says, brush up on the rules and so you

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Speaker 1: could avoid a costly ticket. Now, So Day one we

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Speaker 1: tackled the snow emergency routes overnight. No parking is allowed

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Speaker 1: on marked roads from nine until nine pm to eight

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Speaker 1: am until the roads are the routes are fully plowed.

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Speaker 2: What isn't that fully plowed?

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Speaker 1: Like my neighborhood awful, so so rough right now, in

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Speaker 1: my neighborhood, the did a really bad job of plowing.

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Speaker 9: I was just gonna say, I was in Minneapolis yesterday

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Speaker 9: and I couldn't tell that anything was plowed.

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Speaker 4: The streets weren't even salted.

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Speaker 1: Yeah, it was a hodgepodge of bad men dot work

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Speaker 1: in my opinion, I don't mind saying. Yeah, the main

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Speaker 1: roads were okay yesterday. There was a lot of a

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Speaker 1: lot of black ice on the road on the road

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Speaker 1: last night. But yeah, but the neighborhoods are just just atrocious.

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Speaker 1: Day two, by the way, no parking is allowed on

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Speaker 1: the even number side of non emergency routes from eight

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Speaker 1: am to a pm or until the street is fully plowed.

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Speaker 1: And then Day three it's the same as the other days,

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Speaker 1: odd but this time odd numbered side non emergency routes.

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Speaker 1: The city has an interactive map to check on where

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Speaker 1: restrictions supply. Listen to the City of Minneapolis is being

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Speaker 1: very hypocritical in my opinion here.

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Speaker 2: Okay, so when you have.

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Speaker 1: Double MB, double MJ, I got it, double MB, double

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Speaker 1: MJ so Minneapolis man baby mayor mom jeans, I'm working, I'm.

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Speaker 2: Work shopping it. I'm work shopping it.

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Speaker 1: I don't know if I'm saving as much time as

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Speaker 1: I think I'm saving.

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Speaker 9: Maybe having to explain it until people until it resonates, right, yeah, yeah.

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Speaker 2: You got it.

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Speaker 1: You gotta start off slow with the stuff that's right,

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Speaker 1: like right yeah double.

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Speaker 2: Yeah yeah yeah.

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Speaker 1: So double MB, double MJ.

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Speaker 4: Our one podcast.

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Speaker 1: So I guess I gotta add Jacob fry So double MB,

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Speaker 1: double MJ. Jacob fry We'll see if it hangs. I'm

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Speaker 1: sure you'll let me know you the talk back. When

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Speaker 1: you have Minneapolis man baby mayor mom jeans, Jacob Frye

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Speaker 1: and the city council asking for millions of dollars attempting

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Speaker 1: to stop evictions, put an eviction moratorium in place over

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Speaker 1: what they say, we're unavoidable.

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Speaker 2: Circumstances during Operation Metro Surge.

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Speaker 1: It doesn't seem fair at all that people's cars would

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Speaker 1: be towed or people would be fined at their own

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Speaker 1: expense over something clearly beyond their control.

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Speaker 2: I know that's not how any of this works.

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Speaker 1: There's nothing politically to gain for liberals to go and

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Speaker 1: want to offer up assistance when it comes to major snowstorms.

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Speaker 1: But really, when you look at it from this lens,

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Speaker 1: it is incredibly hypocritical. You've got all this talk about

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Speaker 1: how people were impacted. You had roads shut down over

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Speaker 1: the snowstorm, you had businesses closed, you had churches that canceled,

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Speaker 1: they're in person services, I mean, all very similar to

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Speaker 1: what these radical leftists said regarding Operation Metro Surge, that

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Speaker 1: they now want all of this, you know, Operation Metro Surge,

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Speaker 1: ice relief from and yet oh no, you don't follow

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Speaker 1: the parking rules, you're gonna get your card towed, You're

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Speaker 1: going gonna be fined a bunch Yeah, they's nothing but

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Speaker 1: a bunch of hypocrites taking a transportation by the way.

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Speaker 1: Secretary of Transportation Sean Duffy announced on Friday, the Trump

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Speaker 1: administration and would make roads as safer by continuing to

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Speaker 1: ensure that all truck drivers understand English.

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Speaker 2: This isn't this isn't hard. Oh hell yeah.

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Speaker 1: Now Joined by GOP Representative Derek Van Orden, Duffy visited

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Speaker 1: Moreau County, Wisconsin on Friday. He was highlighting the allocation

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Speaker 1: of eight point four million to improve infrastructure in the

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Speaker 1: region and the moves made by the Trump administration to

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Speaker 1: make highway safer. Duffy's comments come amid several high profile

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Speaker 1: incidents involving illegal immigrant to truck drivers across the country.

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Speaker 1: Of course, most notably, we had the wrong way driver

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Speaker 1: that was from Minnesota driving a truck on the highway

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Speaker 1: on the opposite side of the roadway. Duffy said that

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Speaker 1: we have a long standing rule that you have to

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Speaker 1: speak English if you're going to have a commercial driver's license,

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Speaker 1: and the Obama administration had put a slap on the

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Speaker 1: wrist for that offense. We brought a penalty back for

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Speaker 1: not being able to be English efficient in the cab.

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Speaker 1: The Federal Motor Carrier Safety Administrator Derek Barrs has said

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Speaker 1: the agency will be taking steps to make sure that

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Speaker 1: certified truck drivers can pass the written skills test in English,

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Speaker 1: listen beyond the intended safety aspect of these Trump administration moves.

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Speaker 1: This also goes to further reinforce that we are not

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Speaker 1: only a nation of laws, but assimilation is necessary here

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Speaker 1: in the United States to maintain that law and order.

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Speaker 1: And that's something that has been shoved to the side,

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Speaker 1: or had been shoved to the side for the four

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Speaker 1: years under President Joe Biden. And of course, the Democrats

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Speaker 1: have been pushing back against all of the various efforts

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Speaker 1: to hold people accountable for their actions. And we've got

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Speaker 1: a lot of examples of this next hour. I have

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Speaker 1: a trilogy of stories highlighting how Democrats do not care

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Speaker 1: about crime or criminals if it benefits them politically. So

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Speaker 1: we'll get into that next hour on the show. We'll

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Speaker 1: also get to some of your talkbacks coming up here

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Speaker 1: on Twin Cities News.

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Speaker 2: Talk, we will be talking with David.

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Speaker 1: Gartensteinross, CEO at Expert Theory the Latest in AI. If

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Speaker 1: you have any AI related questions that you want to

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Speaker 1: get in for David, you can send those two meet

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Speaker 1: now if you haven't done so already via the talkbacks

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Speaker 1: on the iHeartRadio app brought to you by Lyndahl Realty.

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Speaker 1: You can also email Justice at iHeartRadio dot com and

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Speaker 1: we will speak with our AI analyst and expert Dav'd

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Speaker 1: next right here on Twin Cities News Talk Am eleven

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Speaker 1: thirty and one oh three five FM.

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Speaker 2: Hey John, this is Nick.

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Speaker 10: And you know I'm out here in the desert now

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Speaker 10: out in court sight, and I know you lived in

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Speaker 10: Tucson for quite a while, and I'm just wondering what

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Speaker 10: would you rather have. It's going to be one hundred

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Speaker 10: and five degrees plus in the next several days out

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Speaker 10: here in the desert. Would you rather have the snow

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Speaker 10: or would you rather have the one hundred and five degrees?

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Speaker 1: Let me know, I don't wipe out too hard on

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Speaker 1: this because we have David Gartzenstein Ross coming up in

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Speaker 1: just a moment, and I don't want to keep my

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Speaker 1: good friend waiting. That being said, so I love the

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Speaker 1: snow more than I love the heat. The only thing

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Speaker 1: that puts the heat over the top is how dirty

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Speaker 1: it gets in the wintertime. That's the part of the

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Speaker 1: winter that I just cannot stand.

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Speaker 2: But it's hot.

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Speaker 1: It's just hot, right, It's just it's it's miserable outside

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Speaker 1: because it's stinking hot. But you don't have all of

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Speaker 1: the slush and the muck, the whole reason why we've

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Speaker 1: had the controversy regarding the format issue in the first place.

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Speaker 1: That's the only part of the winter that I just

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Speaker 1: uh that I just don't that I don't like. It's

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Speaker 1: just all the all the grime that gets left over.

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Speaker 2: Good morning, John.

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Speaker 11: As much as I'd like to let you and others

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Speaker 11: take the blame for talking about snow blowers getting put

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Speaker 11: away and your floor mats, I am gonna have to

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Speaker 11: be accountable for this one. I just have six Christmas

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Speaker 11: trees up, my snowmen are still out, and I have

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Speaker 11: a sign that says let it snow. For various reasons,

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Speaker 11: I haven't gotten around to get down, but I'm pretty

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Speaker 11: sure all this snow is my fault.

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Speaker 1: Listen, I'm all about leaving your Christmas stuff up late.

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Speaker 1: But it is Saint Patrick's Day today. Okay, yeah, yeah,

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Speaker 1: I know, I know. I just haven't I haven't even

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Speaker 1: brought it up yet, but it is. It is Saint

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Speaker 1: Patrick's Day. So Happy Saint Patrick's Day to everybody out there.

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Speaker 2: Joining us now on the show is.

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Speaker 1: Ceo AI analysts and experts from expert theory to v'd

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Speaker 1: gartan Stein or Oss Happy Saint Patrick's Day DV.

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Speaker 2: Thanks for coming on the show.

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Speaker 12: Thank you, John, Happy Sat Patrick's Stay to you.

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Speaker 2: Do we do? You may or may not.

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Speaker 1: I don't know if you have a thought on this,

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Speaker 1: but you know, for a lot of times when we

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Speaker 1: do you know, happy whatever day, you know, usually you

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Speaker 1: follow that up with to all who celebrate?

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Speaker 2: Do we have to do that with Saint Patrick's Day?

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Speaker 1: Or can we just do the blanket happy Saint Patrick's

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Speaker 1: Day without the for all who celebrate qualifier?

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Speaker 2: I don't know if you have a thought about that.

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Speaker 12: I feel like, since you're known for not being politically correct,

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Speaker 12: you can just live dangerously and not even qualify. Everyone

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Speaker 12: regardless of creed, has to have a happy Saint Patrick.

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Speaker 1: Stan Now, Well, David gartzen Stein Ross, You've known me

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Speaker 1: for many many years, and if anybody knows that I

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Speaker 1: love to live dangerously, that would be you.

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Speaker 12: I mean, I have known that your man taking risks,

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Speaker 12: but I have to say this impresses even me.

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Speaker 13: John.

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Speaker 1: All Right, we got a lot of comments and questions

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Speaker 1: that have already rolled in for our time this morning,

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Speaker 1: so let me get to some of these from the

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Speaker 1: iHeartRadio app. I actually have some that came in yesterday

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Speaker 1: as well, and then we'll see time permitting, if we

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Speaker 1: can get to some of the stories that we had

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Speaker 1: shared back and forth overnight. As we talk artificial intelligence

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Speaker 1: with David Gartz and Stein Ross, and we immediately go

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Speaker 1: to the iHeartRadio app talkbacks this morning, brought to you

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Speaker 1: by Lyndall Realty.

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Speaker 13: Artificial intelligence is an excuse for program to hack and

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Speaker 13: do various things without taking responsibility for their actions.

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Speaker 1: So more of a general statement than it is a

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Speaker 1: question de vat and a rather cynical one at that,

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Speaker 1: But do you have a comment on that listener's feelings

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Speaker 1: regarding AI.

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Speaker 12: I actually only heard like the last half a line.

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Speaker 12: I'm not sure what the audio problem is he said.

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Speaker 1: He said, artificial intelligence is an excuse for programmers to

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Speaker 1: hack and do various things without taking responsibility for their actions.

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Speaker 12: That's interesting. I mean, it's it's obviously more than that.

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Speaker 12: But like the privacy concerns and multiple other concerns are

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Speaker 12: all real with AI, for sure.

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Speaker 2: Let's go. Let's go to this one.

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Speaker 1: There's a few sort of more commentaries before we get

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Speaker 1: into the questions that I wanted to get out of

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Speaker 1: the way. As we talk with David Gartenstein Ross this morning.

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Speaker 13: There will never be any true artificial intelligence as long

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Speaker 13: as AI gets it's the information from the Internet, and

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Speaker 13: the Internet is filled with people that write stuff that lie,

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Speaker 13: and it cannot distinguish a truth from a lie.

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Speaker 1: Now, this was the same listeners, so obviously they have

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Speaker 1: various concerns with AI. But to feed your thoughts, it's

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Speaker 1: a good thought.

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Speaker 2: This time I heard much more.

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Speaker 12: Of the comment, and I think that you're getting the

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Speaker 12: AUTO issues worked out on your end.

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Speaker 2: But AI can.

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Speaker 12: Distinguish truth from lies in a way. Each AI is

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Speaker 12: given an understanding of how to discern true facts from

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Speaker 12: other lies that are printed on the Internet. AIS have

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Speaker 12: their biases, right, Like if you kind of look at

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Speaker 12: them across the political spectrum, you know, Google's AI open

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Speaker 12: AIS tend to be more liberal, tends to be more

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Speaker 12: conservative if you're going to give them a political type

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Speaker 12: of some kind. And also like some things on the

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Speaker 12: Internet are actually built to full AI.

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Speaker 2: But like if if you start tired.

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Speaker 12: With any large language model produced by a major company

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Speaker 12: and talk with it about recent current events, it will

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Speaker 12: actually do a pretty good job of helping you sort

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Speaker 12: through what's disinformation and what's not. Another way to test

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Speaker 12: the listener's comment. It takes something you know to be

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Speaker 12: disinformation and ask an AI if it's true. The AI

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Speaker 12: will misfire sometimes, but it's at least as insightful as

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Speaker 12: the average Internet user about what is likely true and

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Speaker 12: what is likely false.

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Speaker 1: All right, talking with David Gartzenstein Ross, a CEO at

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Speaker 1: Expert Theory, with our weekly Artificial intelligence segment.

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Speaker 2: Let's go back to the talkbacks here. Hopefully you can

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Speaker 2: hear this one.

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Speaker 14: Good morning, Lyle from Dallas here. I'm curious if you

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Speaker 14: could ask David to chime in on the concept of

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Speaker 14: AI quicksand and how business leaders are sometimes acting too

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Speaker 14: fast when they see AI's automation ability and acting too

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Speaker 14: fast in cutting headcount and such.

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Speaker 5: Thank you.

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Speaker 1: I don't know that was an official description of AI

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Speaker 1: quickstand or just a riff off of the conversations that

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Speaker 1: we had Friday. We talked about quick stand a bunch

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Speaker 1: on Friday Show. I'll just leave it at that, but

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Speaker 1: David your thoughts on Lyle's question here. Thanks Vile for

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Speaker 1: the question.

439
00:23:31,800 --> 00:23:34,200
Speaker 12: I mean, this is a very timely that we see

440
00:23:35,400 --> 00:23:41,720
Speaker 12: multiple sets of massive layoffs occurring at huge companies due

441
00:23:41,720 --> 00:23:44,960
Speaker 12: to AI, right, and this is something we've known for

442
00:23:45,200 --> 00:23:48,639
Speaker 12: quite some time would be coming, right. It was definitely

443
00:23:48,720 --> 00:23:54,040
Speaker 12: anticipated whether or not they're doing it too quickly from

444
00:23:54,520 --> 00:23:57,800
Speaker 12: a company perspective in terms of like where the profit

445
00:23:57,840 --> 00:23:58,520
Speaker 12: and loss will be.

446
00:23:59,000 --> 00:24:01,000
Speaker 2: This is something that I don't like seeing, right.

447
00:24:01,160 --> 00:24:04,040
Speaker 12: Like if you go back maybe six months ago, you

448
00:24:04,040 --> 00:24:06,439
Speaker 12: and I had this exact conversation on air where you

449
00:24:06,440 --> 00:24:11,720
Speaker 12: were talking about how we hadn't really yet seen a round.

450
00:24:11,720 --> 00:24:14,120
Speaker 2: Of AI layoffs, and now.

451
00:24:13,920 --> 00:24:17,479
Speaker 12: As of March twenty twenty six, we're starting to see

452
00:24:18,200 --> 00:24:21,920
Speaker 12: multiple rounds of AI layoffs with massive layoffs and being

453
00:24:21,960 --> 00:24:27,320
Speaker 12: attributed to AI. And you know they're going to be like,

454
00:24:27,760 --> 00:24:31,320
Speaker 12: they're going to be significant ripples. We've seen multiple times

455
00:24:31,400 --> 00:24:34,640
Speaker 12: where in the past there'll be kind of rolling layoffs

456
00:24:34,640 --> 00:24:38,720
Speaker 12: across multiple big companies. It has a ripple impact of

457
00:24:38,760 --> 00:24:43,600
Speaker 12: the economy in multiple ways. But we now see a

458
00:24:43,720 --> 00:24:48,480
Speaker 12: time when AI is really good at some of the

459
00:24:48,480 --> 00:24:52,480
Speaker 12: most prestigious human tasks, including you know, Claude being the

460
00:24:52,520 --> 00:24:55,800
Speaker 12: best of the bunch at being able to do engineering.

461
00:24:56,240 --> 00:24:56,400
Speaker 13: Right.

462
00:24:56,440 --> 00:25:01,160
Speaker 12: They've built AI that can now build better AI, and

463
00:25:01,600 --> 00:25:04,840
Speaker 12: that has tremendous impacts. So I don't know if the

464
00:25:04,840 --> 00:25:08,919
Speaker 12: companies are going to suffer, but it creates huge issues

465
00:25:09,200 --> 00:25:09,880
Speaker 12: for all of us.

466
00:25:10,320 --> 00:25:12,919
Speaker 1: Well, I think this fits nicely with one of the

467
00:25:12,960 --> 00:25:16,800
Speaker 1: stories that I had grabbed for our conversation today with

468
00:25:16,880 --> 00:25:21,200
Speaker 1: David Gartenstein ross Out of Fox nine surveillance and pricing,

469
00:25:21,480 --> 00:25:24,760
Speaker 1: using AI to determine how much a customer is willing

470
00:25:24,760 --> 00:25:28,040
Speaker 1: to pay for an item. This can result in different

471
00:25:28,040 --> 00:25:32,320
Speaker 1: prices for different people based on various metrics set by

472
00:25:32,359 --> 00:25:35,200
Speaker 1: the stores. Now in the story, Fox and I had

473
00:25:35,280 --> 00:25:38,240
Speaker 1: gone and tested different grocery store apps and they actually

474
00:25:38,520 --> 00:25:42,920
Speaker 1: had a combination of foods wherein through the different apps

475
00:25:43,080 --> 00:25:46,320
Speaker 1: the prices came out differently. Now this was with Cub

476
00:25:46,400 --> 00:25:48,800
Speaker 1: Foods locally. Cub was quick to come out and say, well,

477
00:25:48,800 --> 00:25:52,240
Speaker 1: this can often happen when it comes to different apps

478
00:25:52,440 --> 00:25:56,159
Speaker 1: and it's less about AI. But during the legislative session,

479
00:25:56,160 --> 00:25:59,960
Speaker 1: we do have Representative Carli Cootiza Winnen of Eden Prairie

480
00:26:00,359 --> 00:26:03,480
Speaker 1: highlighting what they believe are the need for regulation, saying

481
00:26:03,480 --> 00:26:06,840
Speaker 1: when corporations are kind of pushing the boundaries where regulation

482
00:26:07,119 --> 00:26:10,080
Speaker 1: or legislation haven't caught up yet with we just want

483
00:26:10,080 --> 00:26:12,919
Speaker 1: to make sure that we are setting that framework to

484
00:26:12,960 --> 00:26:14,560
Speaker 1: protect folks going.

485
00:26:14,280 --> 00:26:16,080
Speaker 2: Forward, Divide, as far as you know.

486
00:26:17,760 --> 00:26:22,920
Speaker 1: Using AI to change prices this idea of AI pricing,

487
00:26:23,080 --> 00:26:25,679
Speaker 1: is this a new way of doing something that was

488
00:26:25,720 --> 00:26:29,199
Speaker 1: already occurring or is this something new? Do you know?

489
00:26:31,280 --> 00:26:36,040
Speaker 12: As far as I know, it's new, the ability had

490
00:26:36,080 --> 00:26:41,879
Speaker 12: always been there, and in the past, price changes based

491
00:26:41,920 --> 00:26:47,760
Speaker 12: on customer were reflected more in discount than anything else. Right, So,

492
00:26:48,560 --> 00:26:53,199
Speaker 12: at major stores, like any major grocery, you'll get a

493
00:26:53,280 --> 00:26:58,119
Speaker 12: number of different coupons that provide you discounts on certain

494
00:26:58,160 --> 00:27:02,640
Speaker 12: things that the store algorithm understands that you like, and

495
00:27:02,680 --> 00:27:07,159
Speaker 12: that's a method of enticing you back. The ability to

496
00:27:07,280 --> 00:27:12,160
Speaker 12: price things differently based on willingness to pay or likely

497
00:27:12,200 --> 00:27:16,520
Speaker 12: willingness to pay, has some extent been built into the system.

498
00:27:16,600 --> 00:27:19,720
Speaker 12: Right Like, if you go to say, well, have it

499
00:27:19,760 --> 00:27:23,760
Speaker 12: be targets, since you know your target land in Minneapolis,

500
00:27:23,960 --> 00:27:26,120
Speaker 12: if you go to a target in a rich area

501
00:27:26,160 --> 00:27:28,520
Speaker 12: of town, you'll pay more than a target in a

502
00:27:28,520 --> 00:27:31,199
Speaker 12: poorer area of town, And that in part is a

503
00:27:31,240 --> 00:27:35,400
Speaker 12: product not of willingness to pay, but of for example,

504
00:27:35,440 --> 00:27:40,760
Speaker 12: property prices, your price to rent, what the average salary

505
00:27:40,800 --> 00:27:43,479
Speaker 12: will be or what average wage will be in that

506
00:27:43,560 --> 00:27:47,040
Speaker 12: particular store. There's a greater ability now though, to just

507
00:27:47,200 --> 00:27:52,359
Speaker 12: price things differently for one consumer than another. What if

508
00:27:52,359 --> 00:27:54,480
Speaker 12: you're in a store, that's not happening to you, right,

509
00:27:54,520 --> 00:27:58,120
Speaker 12: because the listed price is the listed price. It would

510
00:27:58,119 --> 00:28:01,480
Speaker 12: be illegal, you know, for Apoo to be listed and

511
00:28:01,560 --> 00:28:04,240
Speaker 12: say six dollars for a bottle of shampoo, and then

512
00:28:04,240 --> 00:28:06,720
Speaker 12: it realizes that you're actually willing to pay nine, and

513
00:28:06,760 --> 00:28:08,879
Speaker 12: so it gives you something other than the listed price.

514
00:28:09,320 --> 00:28:13,720
Speaker 12: That would be illegal. But doing it through apps, that

515
00:28:13,960 --> 00:28:17,879
Speaker 12: is something which isn't regulated. And we actually already know

516
00:28:18,280 --> 00:28:22,439
Speaker 12: other areas where things are priced differently per app. So

517
00:28:22,560 --> 00:28:27,960
Speaker 12: for example, if you are ordering like from door Dash,

518
00:28:29,440 --> 00:28:32,480
Speaker 12: you're charged more for a meal that if you pick

519
00:28:32,640 --> 00:28:35,880
Speaker 12: it up using the in store app, and that's independent

520
00:28:35,920 --> 00:28:38,680
Speaker 12: of delivery fees. I think everybody has kind of noticed

521
00:28:38,680 --> 00:28:42,440
Speaker 12: that that's why you're paying sixty dollars to order from

522
00:28:42,520 --> 00:28:47,680
Speaker 12: Chipotle or whatever, because like the underlying meal is itself

523
00:28:47,840 --> 00:28:50,800
Speaker 12: marked up. So it's an accentuation of an extenuation of

524
00:28:50,840 --> 00:28:53,600
Speaker 12: that trend, an extension of that trend. But it could

525
00:28:53,600 --> 00:28:55,800
Speaker 12: be much more hyper localized now in ways that I

526
00:28:55,800 --> 00:29:01,160
Speaker 12: think you're disturbing, And I do support regulation on this

527
00:29:01,800 --> 00:29:07,360
Speaker 12: because it goes against our ideas of basic fairness.

528
00:29:08,440 --> 00:29:10,560
Speaker 1: Yeah, it'll be interesting to see, Like now that I,

529
00:29:10,720 --> 00:29:12,320
Speaker 1: you know, spending a little bit more time with this

530
00:29:12,520 --> 00:29:17,120
Speaker 1: and hearing your thoughts, there's a lot of there's a

531
00:29:17,160 --> 00:29:18,960
Speaker 1: lot of different things that popped up in my mind

532
00:29:19,040 --> 00:29:23,080
Speaker 1: because you're right, you can go and look at a

533
00:29:23,200 --> 00:29:25,640
Speaker 1: myriad of different products and you're going to be paying

534
00:29:25,720 --> 00:29:29,880
Speaker 1: a different price depending on which means you're going to

535
00:29:29,880 --> 00:29:31,960
Speaker 1: go and purchase it, as you mentioned the location you're

536
00:29:31,960 --> 00:29:34,360
Speaker 1: going to go and purchase it. You know, this is

537
00:29:34,400 --> 00:29:36,920
Speaker 1: more aligned with if I can use something fantastical to

538
00:29:36,960 --> 00:29:40,480
Speaker 1: point to Minority report with Tom Cruise, where when he's

539
00:29:40,520 --> 00:29:43,280
Speaker 1: you know, running from the authorities and they're scanning him

540
00:29:43,280 --> 00:29:46,880
Speaker 1: and immediately they're throwing advertisements and items that he would want,

541
00:29:46,960 --> 00:29:49,120
Speaker 1: much in the same way your algorithm would. You could

542
00:29:49,240 --> 00:29:52,640
Speaker 1: envision a similar circumstance where the AI is advanced enough

543
00:29:52,640 --> 00:29:56,479
Speaker 1: to actually profile you on the spot and then adjust

544
00:29:56,520 --> 00:29:58,320
Speaker 1: the pricing based off of how much they want you

545
00:29:58,400 --> 00:30:00,920
Speaker 1: to to pay. I just I wonder if there needs

546
00:30:00,920 --> 00:30:04,240
Speaker 1: to be a lot more debate over this issue, over

547
00:30:04,320 --> 00:30:07,320
Speaker 1: specifically how they want to go and regulate this rather

548
00:30:07,400 --> 00:30:11,080
Speaker 1: than moving forward with a sudden blanket fix over technology

549
00:30:11,120 --> 00:30:14,640
Speaker 1: that according to the article, many are saying that there

550
00:30:14,640 --> 00:30:18,360
Speaker 1: hasn't been any comprehensive evidence yet of utilizing AI. But

551
00:30:18,440 --> 00:30:20,320
Speaker 1: I think you and I both know DVID it's a

552
00:30:20,320 --> 00:30:23,160
Speaker 1: matter of time before that happens. Yeah, and no, I agree,

553
00:30:23,160 --> 00:30:24,040
Speaker 1: there has to be debate.

554
00:30:24,320 --> 00:30:27,480
Speaker 12: One thing that every conservative knows is that when there's

555
00:30:27,520 --> 00:30:30,360
Speaker 12: a problem and you go right for a regulation, it

556
00:30:30,480 --> 00:30:33,640
Speaker 12: ends up creating many more ripple effects that we don't want.

557
00:30:33,760 --> 00:30:35,680
Speaker 2: Yeah, so yeah, one hundred percent.

558
00:30:36,120 --> 00:30:38,920
Speaker 12: But also another thing I'll say, just from a conservative perspective,

559
00:30:39,760 --> 00:30:42,680
Speaker 12: is that what we're describing here goes against basic laws

560
00:30:42,720 --> 00:30:43,400
Speaker 12: of the market.

561
00:30:43,960 --> 00:30:44,160
Speaker 2: Right.

562
00:30:44,240 --> 00:30:47,120
Speaker 12: Our understanding of consumers is that there will be a

563
00:30:47,160 --> 00:30:50,040
Speaker 12: supply curve and there will be a demand curve, and

564
00:30:50,080 --> 00:30:53,800
Speaker 12: where supply and demand meet, that is where a market

565
00:30:53,840 --> 00:30:56,360
Speaker 12: price is set. But what we're talking about is the

566
00:30:56,400 --> 00:30:59,400
Speaker 12: ability to ignore the supply and demand curves. And it

567
00:30:59,400 --> 00:31:03,360
Speaker 12: is said to say, ah, job Justice is willing to

568
00:31:03,360 --> 00:31:08,240
Speaker 12: pay forty five dollars for a Star Wars novel, We're

569
00:31:08,240 --> 00:31:11,120
Speaker 12: going to charge him forty five dollars. Someone else who's

570
00:31:11,200 --> 00:31:15,600
Speaker 12: much less interested they pay six, Right, Like that is

571
00:31:15,920 --> 00:31:19,120
Speaker 12: contrary to what all of us expect of the market

572
00:31:19,160 --> 00:31:20,440
Speaker 12: as consumers.

573
00:31:21,000 --> 00:31:23,480
Speaker 1: Well, and as you know, longtime listeners of the show

574
00:31:23,480 --> 00:31:25,720
Speaker 1: will will note to many foes of the show have mentioned,

575
00:31:25,720 --> 00:31:28,320
Speaker 1: you know, I do wear million dollar shoes, so you

576
00:31:28,400 --> 00:31:29,200
Speaker 1: weren't there for that.

577
00:31:29,240 --> 00:31:30,400
Speaker 2: It's an inside joke, Devid.

578
00:31:30,440 --> 00:31:33,400
Speaker 1: Let's get back to some more questions for David Gartenstein

579
00:31:33,520 --> 00:31:35,760
Speaker 1: Ross this morning here on Twin City's News to talk

580
00:31:35,800 --> 00:31:39,320
Speaker 1: as we continue our discussion over the latest in artificial intelligence.

581
00:31:39,440 --> 00:31:43,840
Speaker 15: My question for David is on AI the different outlets

582
00:31:43,960 --> 00:31:48,280
Speaker 15: that we have, can he tell us where the political

583
00:31:48,360 --> 00:31:52,760
Speaker 15: bias is on every given one he's aware of, either

584
00:31:52,840 --> 00:31:57,360
Speaker 15: right or left? Because I've seen it, it's there, and

585
00:31:57,440 --> 00:32:00,640
Speaker 15: I'd like his two cents on where he believes it

586
00:32:00,680 --> 00:32:04,320
Speaker 15: is and why we can't get even just general information

587
00:32:04,440 --> 00:32:08,240
Speaker 15: or ballparks out of it. I believe due to political bias.

588
00:32:08,720 --> 00:32:10,880
Speaker 1: My understanding, it sounds like a sort of a trust

589
00:32:10,880 --> 00:32:14,760
Speaker 1: issue depending on what language model you're looking at.

590
00:32:14,800 --> 00:32:16,000
Speaker 2: Is that what you got.

591
00:32:15,840 --> 00:32:18,320
Speaker 12: From that to a question as well, Devide, Yeah, I mean,

592
00:32:18,320 --> 00:32:20,719
Speaker 12: who's just asking basically, what is the bias of the AI?

593
00:32:21,240 --> 00:32:23,680
Speaker 12: And the answer would be that if you situate them

594
00:32:23,720 --> 00:32:28,440
Speaker 12: on a political spectrum. All of the major American AI

595
00:32:29,120 --> 00:32:33,920
Speaker 12: other than GROC, are somewhat left of center with slightly

596
00:32:33,920 --> 00:32:37,960
Speaker 12: different left of center perspectives. Groc is the only one

597
00:32:37,960 --> 00:32:40,440
Speaker 12: that I would describe as being right of center. Then

598
00:32:40,680 --> 00:32:45,479
Speaker 12: Chinese made AI like Deep Seek is much more bias

599
00:32:45,560 --> 00:32:49,600
Speaker 12: from a PRC type perspective, People's republicly China type perspective,

600
00:32:49,720 --> 00:32:52,160
Speaker 12: or Deep Seek won't talk to you, for example about

601
00:32:52,200 --> 00:32:57,000
Speaker 12: the Tieneman Square massacre. There are ways to override the

602
00:32:57,160 --> 00:32:58,840
Speaker 12: general political bias.

603
00:32:58,680 --> 00:32:59,400
Speaker 2: Of an AI.

604
00:33:00,080 --> 00:33:03,480
Speaker 12: I think that the political bias, actually it's less than

605
00:33:03,520 --> 00:33:06,080
Speaker 12: it was. You know, a couple of years ago when

606
00:33:06,080 --> 00:33:08,960
Speaker 12: we first started tracking it, In said they have defaults

607
00:33:09,000 --> 00:33:12,800
Speaker 12: that can be overridden. But you know, the defaults are there,

608
00:33:12,840 --> 00:33:15,080
Speaker 12: with Grock being right of center, you know, the others

609
00:33:15,120 --> 00:33:18,560
Speaker 12: all being some degree of left of center, with some

610
00:33:18,640 --> 00:33:20,560
Speaker 12: being more left of center than others. Claude is a

611
00:33:20,600 --> 00:33:24,200
Speaker 12: little bit more left of center, for example, than Chat GPTs.

612
00:33:24,560 --> 00:33:26,840
Speaker 1: Let's touch upon this before we wrap up this morning

613
00:33:26,840 --> 00:33:30,720
Speaker 1: with David Gartenstein Ross from Axios, an AI agent went

614
00:33:30,920 --> 00:33:35,920
Speaker 1: Rogue started a side hustle mining cryptocurrencies. According to a

615
00:33:35,960 --> 00:33:41,920
Speaker 1: research paper published by the Ali Baba affiliated team. The

616
00:33:42,000 --> 00:33:45,760
Speaker 1: new research paper said that they discovered an AI agent

617
00:33:45,800 --> 00:33:51,520
Speaker 1: attempting to attempting unauthorized cryptocurrency mining during training, a surprise

618
00:33:51,600 --> 00:33:55,080
Speaker 1: behavior that triggered internal security alarms.

619
00:33:55,600 --> 00:33:58,960
Speaker 2: Does this apply? I mean, doesn't this show motivation?

620
00:33:59,320 --> 00:34:00,800
Speaker 1: I mean, I suppose I made a joke when we

621
00:34:00,840 --> 00:34:03,120
Speaker 1: started the show and I was promoting you that, like,

622
00:34:03,160 --> 00:34:04,959
Speaker 1: what is the AI going to get out of this?

623
00:34:05,000 --> 00:34:06,680
Speaker 1: What was their motive to go and do this?

624
00:34:09,040 --> 00:34:12,440
Speaker 12: Like, I, having just read the report on it, I

625
00:34:12,480 --> 00:34:18,440
Speaker 12: have no idea, right, it's it's it's fascinating, And I

626
00:34:18,480 --> 00:34:20,399
Speaker 12: think that one of the things I found with AI

627
00:34:20,600 --> 00:34:23,360
Speaker 12: is when it does something weird, often you can trace

628
00:34:23,440 --> 00:34:28,440
Speaker 12: back the reason it's done that and figure it out

629
00:34:29,320 --> 00:34:36,480
Speaker 12: starting a crypto mining side hustle. That is fascinating, and

630
00:34:37,400 --> 00:34:39,640
Speaker 12: I assume that with more information we'd have a pretty

631
00:34:39,640 --> 00:34:42,200
Speaker 12: good understanding of why it tried to do that, what

632
00:34:42,360 --> 00:34:43,960
Speaker 12: sort of rule set it was following.

633
00:34:44,640 --> 00:34:46,880
Speaker 2: But the fact that AI agents.

634
00:34:46,480 --> 00:34:49,879
Speaker 12: Will go and do things that you don't intend there

635
00:34:49,960 --> 00:34:54,120
Speaker 12: is a very important lesson there. As you know, companies

636
00:34:54,200 --> 00:34:58,120
Speaker 12: and people start using AI agents more, there are risks,

637
00:34:58,400 --> 00:34:59,040
Speaker 12: real risks.

638
00:34:59,440 --> 00:35:02,520
Speaker 1: So as we wrap up a funny little anecdotal story.

639
00:35:02,920 --> 00:35:06,360
Speaker 1: David was kind enough to assist my father in setting

640
00:35:06,400 --> 00:35:09,200
Speaker 1: him up with with an AI to help him work

641
00:35:09,239 --> 00:35:12,520
Speaker 1: on some of his his writings that he's attempting to compile.

642
00:35:12,800 --> 00:35:14,520
Speaker 2: He's been having a lot of fun with this, David.

643
00:35:14,640 --> 00:35:19,560
Speaker 1: But apparently the other day he didn't realize that he

644
00:35:19,640 --> 00:35:22,120
Speaker 1: had left. I think, did you use chat GPT? Do

645
00:35:22,160 --> 00:35:22,640
Speaker 1: you remember?

646
00:35:22,840 --> 00:35:23,040
Speaker 8: Yeah?

647
00:35:23,120 --> 00:35:25,400
Speaker 1: Okay, so he didn't realize that he had left the

648
00:35:26,120 --> 00:35:29,080
Speaker 1: He had left chat GPT open on his computer and

649
00:35:29,120 --> 00:35:31,799
Speaker 1: he was in the sort of the adjacent room by

650
00:35:31,840 --> 00:35:35,520
Speaker 1: the computer, and he he said, he sneezed and then

651
00:35:35,560 --> 00:35:37,759
Speaker 1: the computer when said, God bless you.

652
00:35:37,840 --> 00:35:42,000
Speaker 2: Do you need a tissue? Nice? Yeah, exact.

653
00:35:42,880 --> 00:35:48,080
Speaker 12: I have music voice mode, which is a really great tool,

654
00:35:48,160 --> 00:35:50,680
Speaker 12: especially for someone who doesn't want to spend a lot

655
00:35:50,719 --> 00:35:56,279
Speaker 12: of time typing. And yeah, I love that his His

656
00:35:56,880 --> 00:36:00,760
Speaker 12: AI is named Leroy Rect. Yes, yes it is. He's

657
00:36:00,800 --> 00:36:03,400
Speaker 12: having quite a bit of fun with it. So as

658
00:36:04,400 --> 00:36:06,640
Speaker 12: just as we did with our conversation this morning, David,

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Speaker 12: as always, thank you for the time. If you have

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Speaker 12: any other questions for David Gartenstein Ross, you can email.

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Speaker 1: Me Justice at iHeartRadio dot com. I am happy enough

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Speaker 1: to send those. I'm happy to send those over to

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Speaker 1: David garten Steinross and as always, thank you so much

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Speaker 1: for the time this morning. I look forward to talking

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Speaker 1: with you again next week. Likewise, job, have a great

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Speaker 1: week coming up.

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Speaker 2: Trump launches Anti Fraud task Force.

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Speaker 9: JD.

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Speaker 1: Vance is set to lead this task force. He had

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Speaker 1: a lot of comments regarding not just fraud in the

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Speaker 1: United States in general, but also here in Minnesota allegations

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Speaker 1: against Representative Ilhan Omar allegedly marrying her brother. Here's a

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Speaker 1: little bit of what Trump had to say yesterday at

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Speaker 1: the announcement of his launch of this anti fraud task force.

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Speaker 2: And I'll give you more details coming.

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Speaker 1: Up next here on Twin City's News Talk Am eleven

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Speaker 1: thirty and one oh three five FM.

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Speaker 6: It's crazy and ilan Omar, I hope this is part

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Speaker 6: of it. But she married her brother supposedly.

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Speaker 4: I mean, there's a lot of documentation.

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Speaker 6: I means she's here illegally and she's a congress woman.

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Speaker 6: And I hope you're going to be looking at that

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Speaker 6: or somebody here, Sarah, because she's one of the ringleaders here.

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Speaker 6: She's bad. It's really bad. Das she's so bad for

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Speaker 6: our country. Anyway, JD, please say a few words. I

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Speaker 6: think this is wherever it's taking place, it seems that

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Speaker 6: it's usually in blue steaks. If it's there a red state,

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Speaker 6: we're going there too. But it seems that it's.

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Speaker 2: Heavily, heavily, heavily Democrat. And what they've done is so sad.

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Speaker 6: When you look at the Minnesota scam.

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Speaker 2: A lot of it has to do with Somania.

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Speaker 6: Nobody's calling out anybody, but a lot of it has

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Speaker 6: to do but it's Somanya and plenty of others. And

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Speaker 6: I believe the governor is complicit. I believe ilhan Omar

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Speaker 6: is complicit. I believe that your Assurney General is complicit.

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Speaker 6: And if they are, you're gonna hopefully.

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Speaker 8: Find out about it.

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Speaker 6: Then you're gonna be You're gonna have to do what

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Speaker 6: you have to do.

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Speaker 2: They have what's called the Trump derangement problem.

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Speaker 4: Have you heard about that problem