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Lee Elci, Voice of Freedom | Flock This!! · The Lee Elci Show

• 0:00
  Speaker 1: Expeditions on your computer like if you get caught should
• 0:03
  Speaker 1: be a felony Like a jail felony I had to
• 0:08
  Speaker 1: sign up for something for the state And then yesterday
• 0:12
  Speaker 1: I had an email in my inbox which looked exactly
• 0:14
  Speaker 1: like a state email So I opened it and then
• 0:18
  Speaker 1: I clicked on what they wanted me to click on
• 0:20
  Speaker 1: and as soon as I did it I realized man
• 0:22
  Speaker 1: I think I made a mistake and I immediately stopped
• 0:24
  Speaker 1: so I don't know if I made it in time.
• 0:25
  Speaker 1: Hope I did I didn't. I was actually so nervous,
• 0:29
  Speaker 1: I didn't even want to go look at any of
• 0:30
  Speaker 1: my other stuff to see if it was all deleted.
• 0:33
  Speaker 1: But I deleted the email as fast as I could.
• 0:36
  Speaker 1: But it's just constant. It's constant. Right? Yes, the internets
• 0:44
  Speaker 1: are life-changing. And AI is going to change it even further.
• 0:48
  Speaker 1: And everything associated with all of that. But, you know,
• 0:52
  Speaker 1: you think how much we... invest. And I don't even,
• 0:57
  Speaker 1: I don't even do online banking. I don't pay anything online,
• 1:01
  Speaker 1: but you got an account, right? You have to have a,
• 1:04
  Speaker 1: everyone wants you to have an account. So even a
• 1:07
  Speaker 1: bank who, you know, you've been banking with for 50 years,
• 1:10
  Speaker 1: you know, you got to have an online account so
• 1:12
  Speaker 1: you can check. I don't know. I'm afraid to go
• 1:14
  Speaker 1: look to see if my money's there, what money there is,
• 1:18
  Speaker 1: which isn't a lot, but I don't know. I don't
• 1:22
  Speaker 1: know how long it takes for one of those fishing things.
• 1:24
  Speaker 1: Like literally it was a, Half a second before my
• 1:27
  Speaker 1: mind snapped And said this is probably a scam I
• 1:29
  Speaker 1: don't even know if it was I just deleted it,
• 1:32
  Speaker 1: deleted it, deleted it And hopefully But it's just now
• 1:36
  Speaker 1: I got that eerie feeling In my stomach like I'm
• 1:39
  Speaker 1: afraid to go look Welcome to the You know welcome
• 1:42
  Speaker 1: to a Friday Alright So everyone's asking me For an
• 1:50
  Speaker 1: opinion on the flop camera Like a significant solid Pick
• 1:54
  Speaker 1: a side flock camera decision. And there's a, I gotta
• 1:59
  Speaker 1: be honest, there's a part of me that likes the
• 2:01
  Speaker 1: idea that it's a tool for law enforcement. I do.
• 2:06
  Speaker 1: But if I'm forced to choose a side on this today,
• 2:11
  Speaker 1: on this date, I think it's clear what side I
• 2:14
  Speaker 1: have to fall down on. The steadfast defense of the
• 2:18
  Speaker 1: freedoms of our Constitution is what I side with. That's
• 2:23
  Speaker 1: how I side across Our towns, whether it's Windsor or Killingworth,
• 2:28
  Speaker 1: East Lyme, Milford, residents have risen against the, this is
• 2:34
  Speaker 1: what bothers me too, the quiet installation of flock safety
• 2:38
  Speaker 1: automated license plate readers.
• 2:43
  Speaker 2: Right?
• 2:47
  Speaker 1: The cameras are placed without really any public knowledge or consent,
• 2:52
  Speaker 1: by the way. They photograph every vehicle that passes, logging
• 2:56
  Speaker 1: the plates, location, times, vehicle details, more info. The deeper
• 3:03
  Speaker 1: I dig into this, the more egregious it sounds, doesn't it?
• 3:07
  Speaker 1: How dare you? I'm a free American citizen. But what
• 3:13
  Speaker 1: gives me pause is as odd as this is, it's
• 3:18
  Speaker 1: seeming a bipartisan issue. Tree huggers and, you know, pro-
• 3:24
  Speaker 1: Illegal immigration folks, anti-ICE folks, all on the same page
• 3:28
  Speaker 1: somehow on this one, right? The officials say they're tools
• 3:34
  Speaker 1: for safety, but from a pro-freedom perspective, which, again, is
• 3:43
  Speaker 1: rooted in the Constitution of the United States or constitutional principles, I.
• 3:48
  Speaker 3: Mean, it's a profound expansion of surveillance, right?
• 3:53
  Speaker 1: That absolutely 1,000% chips away at your liberties. 1,000%.
• 3:57
  Speaker 3: You know, there's a Fourth Amendment.
• 4:04
  Speaker 1: Protects us against unreasonable searches and seizures. Seems like this
• 4:09
  Speaker 1: falls into that category. Why are you looking at me?
• 4:13
  Speaker 3: Why are you watching me? Oh, but you got a
• 4:18
  Speaker 3: cell phone. But I choose to have the cell phone.
• 4:21
  Speaker 1: It's my choice. Okay, if I realize that they're tracking
• 4:26
  Speaker 1: me on my cell phone, I can put it down.
• 4:30
  Speaker 1: I can leave it on the table. I can turn
• 4:33
  Speaker 1: it off, although that doesn't really do anything. I understand
• 4:38
  Speaker 1: that we've given up a tremendous amount of our liberties
• 4:41
  Speaker 1: when we hold this cell phone in our hands. I
• 4:45
  Speaker 1: get that, but I have a choice. The flock cameras
• 4:48
  Speaker 1: don't give me a choice. That's a big difference. Government
• 4:56
  Speaker 1: should not be intrusive into our lives. There's really no
• 5:01
  Speaker 1: probable cause for it. And these cameras operate continuously on
• 5:08
  Speaker 1: public roads. They capture movements of law-abiding citizens. They watch
• 5:13
  Speaker 1: you as you're driving around. No warrant, no suspicion, no
• 5:20
  Speaker 1: illegal activity. And so far, the courts, and we'll talk
• 5:27
  Speaker 1: to Judge about this today, have said that there's no
• 5:31
  Speaker 1: reasonable expectation of privacy in a license plate displayed on
• 5:35
  Speaker 1: a public highway. That's so far the early ruling. So,
• 5:40
  Speaker 1: so far, you don't have any rights to push back
• 5:42
  Speaker 1: on this. But, you know, people are going to take
• 5:44
  Speaker 1: this into their own hands, I think, eventually, you know,
• 5:46
  Speaker 1: rip these things down on their own. And, you know,
• 5:52
  Speaker 1: it's not just one camera, two cameras. It's now a
• 5:56
  Speaker 1: dense network. And it's long-term data retention. Right? I mean,
• 6:08
  Speaker 1: how long before they sell this information to advertisers? You
• 6:11
  Speaker 1: think I'm crazy? Hey, look, Lee takes a right on X, Y,
• 6:16
  Speaker 1: and Z Street, drives right by and, you know, always
• 6:18
  Speaker 1: gets gas at this place or whatever. goes into here.
• 6:22
  Speaker 3: Well, let's shoot them with some advertisements from the competition.
• 6:25
  Speaker 1: See what happens. I mean, you might think that's far-fetched.
• 6:30
  Speaker 1: You might think that's the most minuscule part of this,
• 6:32
  Speaker 1: and it probably is, but it's just, it's a possibility.
• 6:37
  Speaker 1: I think right now, according to the state of Connecticut,
• 6:41
  Speaker 1: you can retain this information for 21 days. But this
• 6:45
  Speaker 1: is the nose under the camel's tent, isn't it? Let's
• 6:48
  Speaker 1: see how much we can get away with.
• 6:54
  Speaker 3: I don't know, man.
• 6:58
  Speaker 1: I mean, I do like the idea that we're able
• 7:01
  Speaker 1: to pick off criminal. The criminal element, ICE, is able
• 7:05
  Speaker 1: to do their job much more proficiently. I mean, that's
• 7:09
  Speaker 1: a flip side of this. And I've been thinking about this,
• 7:11
  Speaker 1: thought about this a lot last night.
• 7:13
  Speaker 3: Is there a hybrid of this that is doable? I'm
• 7:16
  Speaker 3: sure there is a.
• 7:19
  Speaker 1: Hybrid. But you look to other countries who have implemented this,
• 7:22
  Speaker 1: and it's really.
• 7:24
  Speaker 1: It really ends up turning into this facial recognition and
• 7:28
  Speaker 1: profiling and it just starts with the flock and it
• 7:31
  Speaker 1: ends up in the land of Big Brother in 1984.
• 7:37
  Speaker 1: And you might say, oh, come on, are you being overdramatic?
• 7:40
  Speaker 1: Am I really being overdramatic? Do you trust the government
• 7:46
  Speaker 1: at all? I mean, all of a sudden now we're
• 7:48
  Speaker 1: supposed to trust the government. Yeah, I get it. It's
• 7:50
  Speaker 1: law enforcement. The angle of it is law enforcement and
• 7:52
  Speaker 1: we are 100% behind them and I I think there's
• 7:55
  Speaker 1: a split even within law enforcement on this. I think
• 8:01
  Speaker 1: some folks think that it's a great tool and you
• 8:03
  Speaker 1: can go out and catch the bad guy and that's great.
• 8:05
  Speaker 1: I don't know.
• 8:06
  Speaker 3: Somehow there's got to be a way so that the.
• 8:11
  Speaker 1: Person who is not suspected of any crime somehow is
• 8:15
  Speaker 1: able to dodge this constant surveillance. And I don't know
• 8:18
  Speaker 1: what that answer is, but I'm sure somebody out there
• 8:21
  Speaker 1: who is much smarter than me can probably figure that out. But,
• 8:30
  Speaker 1: you know, too many of our communities, unfortunately, sleep through
• 8:33
  Speaker 1: these developments that are unaware that the cameras are already up.
• 8:37
  Speaker 3: Hundreds of them statewide.
• 8:39
  Speaker 1: I mean, I don't know if you know that, but
• 8:40
  Speaker 1: there's hundreds of these cameras that are watching you. And
• 8:44
  Speaker 1: nobody asked if they could put them up.
• 8:45
  Speaker 3: They just did it. We are free men and free women.
• 8:54
  Speaker 1: I think capable of weighing down Risks and demanding that
• 8:59
  Speaker 1: the government remain, again, our servant.
• 9:02
  Speaker 3: Not our watcher. You want the government watching you?
• 9:08
  Speaker 1: I mean, what's next? The government's going to watch you
• 9:10
  Speaker 1: on your computer?
• 9:13
  Speaker 3: Got to make sure that you only go to certain
• 9:15
  Speaker 3: approved websites?
• 9:19
  Speaker 1: I mean, is there a big difference between watching you
• 9:22
  Speaker 1: drive around legally and watching you surf the internet? I mean,
• 9:26
  Speaker 1: I know the can track you I mean you're being
• 9:29
  Speaker 1: tracked by a million different organizations but I'm curious how
• 9:33
  Speaker 1: far are you willing to go for the ease of
• 9:38
  Speaker 1: this technology I mean I think either we develop this
• 9:50
  Speaker 1: some kind of some sort of hybrid system where legal
• 9:55
  Speaker 1: people are not thrown through the ringers. in some way, shape,
• 10:01
  Speaker 1: or form. Or you got to take these flock cameras
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  Speaker 1: down until we can figure it out. As always, we
• 10:08
  Speaker 1: talked about this yesterday. The greatest safeguard of liberty is
• 10:11
  Speaker 1: an informed, engaged citizenry that refuses to trade freedom for
• 10:16
  Speaker 1: this illusion of security. All right. I don't know. Again,
• 10:30
  Speaker 1: to me, it's a pretty clear-cut violation of your constitutional rights.
• 10:36
  Speaker 1: I get it. You want to catch bad guys. We
• 10:38
  Speaker 1: want to get them off the street. People are going
• 10:40
  Speaker 1: to say, well, if you're not doing anything wrong, well,
• 10:43
  Speaker 1: why should you worry? But maybe somebody doesn't want to
• 10:45
  Speaker 1: know that they're going to a massage parlor three times
• 10:48
  Speaker 1: a week, or they don't want you to know that
• 10:49
  Speaker 1: they're going to... to Dairy Queen seven times a week.
• 10:55
  Speaker 1: And if they're not breaking any laws, why should they be,
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  Speaker 1: you know, put through that if they're good, hardworking, law-abiding
• 11:02
  Speaker 1: American citizens?
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  Speaker 4: All right.
• 11:07
  Speaker 3: We'll talk about it a little bit later on, a
• 11:08
  Speaker 3: little bit more.
• 11:09
  Speaker 1: We'll come right back. Mike DeMauro joins us after the
• 11:12
  Speaker 1: bottom of the hour news. 94.9 News Now, Stimulating Talk.
• 11:14
  Speaker 2: News and people on the news.
• 11:34
  Speaker 5: Appointed by former governor jody rell he's a master litigator
• 11:39
  Speaker 5: a fierce and respected judge and connecticut's super lawyer ladies
• 11:44
  Speaker 5: and gentlemen the truth teller judge john nazaro.
• 11:48
  Speaker 1: So i know we have a million things to talk
• 11:51
  Speaker 1: about and by the way if you want to call
• 11:53
  Speaker 1: in feel free we don't As normally on Fridays, we
• 11:56
  Speaker 1: just are jam-packed with great guests. So if you want
• 11:59
  Speaker 1: to get in a call, 860-464-9490. Now is the time
• 12:03
  Speaker 1: if you've got a question. You probably missed. Maybe you
• 12:05
  Speaker 1: weren't listening coming in. I had just an amazing conversation
• 12:08
  Speaker 1: with a professor about AI. I mean, AI is incredible, man.
• 12:12
  Speaker 6: I have to tell you, though, and you know this
• 12:13
  Speaker 6: to be true. My son's at Meta, number two son.
• 12:16
  Speaker 6: My daughter's a technology reporter. And they're all geeking out.
• 12:20
  Speaker 6: They're all geeking out. And me, I'm like a dinosaur.
• 12:23
  Speaker 4: I'm an idiot. You know, this stuff is still foreign
• 12:25
  Speaker 4: to me.
• 12:26
  Speaker 1: I know, but it's like, he was just explaining how these,
• 12:29
  Speaker 1: you know, you and me right now, as idiots as
• 12:31
  Speaker 1: we are, when it comes to this, he was just saying,
• 12:33
  Speaker 1: if you just type in a few, you know, specific commands, it'll,
• 12:38
  Speaker 1: it'll design build and you can download an app like
• 12:42
  Speaker 1: in five minutes. And I don't know. It's just incredible.
• 12:45
  Speaker 3: And now they're talking, these AI, you know, bots are not.
• 12:49
  Speaker 1: Bots, but the creations are talking to each other and they're,
• 12:52
  Speaker 1: It's amazing.
• 12:53
  Speaker 4: So I'm going to give my son a plug. He's
• 12:55
  Speaker 4: launched a martial arts app.
• 12:58
  Speaker 1: Okay, here we go.
• 12:59
  Speaker 6: He and his geeky coder coworkers. A couple of Asian dudes.
• 13:04
  Speaker 6: And I'm going to get flack for this, but that's redundant.
• 13:07
  Speaker 6: I can say that for those.
• 13:09
  Speaker 4: I'm Asian.
• 13:10
  Speaker 1: All right.
• 13:10
  Speaker 4: I'm the guy with the camera, you know.
• 13:14
  Speaker 1: Right.
• 13:14
  Speaker 4: It was holding the iPhone backwards.
• 13:16
  Speaker 1: All right.
• 13:17
  Speaker 6: So they launched an app and they were pitching it
• 13:18
  Speaker 6: to venture capital and they were looking, I think, for
• 13:20
  Speaker 6: five million seed money.
• 13:22
  Speaker 4: And that's a big ask. And I think what happened.
• 13:24
  Speaker 6: Was and I'm telling him, I'm telling everybody his business
• 13:26
  Speaker 6: is They did not succeed.
• 13:28
  Speaker 4: I think they're funding it themselves.
• 13:29
  Speaker 1: Why don't they just ask you?
• 13:31
  Speaker 3: I got a few extra mil.
• 13:33
  Speaker 4: Go to Elon. Go to Elon.
• 13:35
  Speaker 1: Well, that's great, though, that they have that kind of.
• 13:37
  Speaker 6: Well, they're all immersed and it's all things martial arts related,
• 13:41
  Speaker 6: whether it's weapons, whether it's tournaments.
• 13:42
  Speaker 4: A lot going on there.
• 13:44
  Speaker 1: That's cool, man.
• 13:44
  Speaker 4: There's a need for it.
• 13:45
  Speaker 1: Well, watch for that. Yeah.
• 13:46
  Speaker 2: All right.
• 13:47
  Speaker 1: If you guys, like I said, if you have a question,
• 13:48
  Speaker 1: call up. So let's start with Fauci.
• 13:50
  Speaker 5: Sure.
• 13:50
  Speaker 1: That was the big news. I'm sure you watched it.
• 13:53
  Speaker 1: Taking the fifth. Taking the fifth. Taking the fifth. Your thoughts.
• 13:56
  Speaker 6: Well, you know, some of the some of the response
• 13:58
  Speaker 6: I was watching some of the votes live and I'm
• 14:00
  Speaker 6: a little disappointed and I have to be candid. So,
• 14:03
  Speaker 6: you know, I'm going to be critical here. I was
• 14:05
  Speaker 6: disappointed in our senator, Richard Blumenthal. And I know Richard
• 14:09
  Speaker 6: and I can't say we're friends, but my daughter did
• 14:11
  Speaker 6: work for him and other family members recently. And I
• 14:16
  Speaker 6: have to tell you, though, he he he moved for
• 14:18
  Speaker 6: an amendment to give Fauci immunity. And it failed, not surprisingly,
• 14:24
  Speaker 6: because the committee is controlled by Republicans. So the vote,
• 14:26
  Speaker 6: not surprisingly again, went down party lines. They called the
• 14:29
  Speaker 6: Republican senators first.
• 14:31
  Speaker 4: No, no, no. And then the Democrats.
• 14:33
  Speaker 1: Yes, yes, yes.
• 14:34
  Speaker 4: You know, it's interesting.
• 14:35
  Speaker 6: Fetterman, he voted with the Democrats right down the line.
• 14:38
  Speaker 6: So all this talk about Fetterman changing parties.
• 14:40
  Speaker 4: He voted. So this is interesting. Why give immunity? I'm
• 14:46
  Speaker 4: talking about going forward.
• 14:46
  Speaker 6: Because the argument for those that haven't watched television and
• 14:49
  Speaker 6: been under a rock, if you're granted— A pardon.
• 14:53
  Speaker 4: You shouldn't take the fifth.
• 14:54
  Speaker 6: Now, the lawyers on this committee have marched out all
• 14:57
  Speaker 6: kinds of case law, especially Josh Hawley, United States Supreme
• 15:01
  Speaker 6: Court authority going back to 1896 about how you can't invoke.
• 15:04
  Speaker 4: The fifth if you've been granted a pardon.
• 15:06
  Speaker 1: Right.
• 15:07
  Speaker 4: You know, it's kind of solid ground.
• 15:10
  Speaker 6: Educators, professors are going to debate it.
• 15:12
  Speaker 4: So now it's referred to the DOJ. I think this
• 15:15
  Speaker 4: is all theater. I hate to say it.
• 15:17
  Speaker 6: I think it's a lot of busy work of sniping
• 15:20
  Speaker 6: and backbiting. And as much as I don't like Fauci
• 15:23
  Speaker 6: and call me crazy and I'm not an anti-science person,
• 15:26
  Speaker 6: I do think he misrepresented things. As much as I
• 15:28
  Speaker 6: don't like it, can we get to business? Can we
• 15:31
  Speaker 6: get the business of the government? We've got two wars
• 15:33
  Speaker 6: going on. Certainly we don't want the problem to recur
• 15:37
  Speaker 6: if there's another pathogen because we've got to worry about
• 15:40
  Speaker 6: our water supply, our grid. And all the things we
• 15:43
  Speaker 6: know the bad guys will be attacking. And I want
• 15:46
  Speaker 6: to take exception to your previous caller. There was a comment.
• 15:49
  Speaker 6: I was listening to the geek conversation about AI. He
• 15:52
  Speaker 6: made a statement about the Chinese are looking to improve
• 15:55
  Speaker 6: quality of life.
• 15:55
  Speaker 4: The scientists, I said, oh, no.
• 15:57
  Speaker 1: I'm sorry.
• 15:58
  Speaker 6: I'm one of those guys. I think they're bad actors.
• 16:01
  Speaker 6: And they're government agents. And they're looking to undermine the world.
• 16:05
  Speaker 6: That's what's going on with their government. And that's true
• 16:07
  Speaker 6: with Russia. That's true with China. These guys are not.
• 16:10
  Speaker 4: Our friends.
• 16:11
  Speaker 1: That's why I asked. I threw that out there because
• 16:13
  Speaker 1: I wanted to get his opinion. Obviously, we can have
• 16:16
  Speaker 1: a regulating body in the United States, but if China
• 16:19
  Speaker 1: doesn't have one. No.
• 16:20
  Speaker 3: It's a joke.
• 16:22
  Speaker 1: It's like dealing with the climate control thing or pollution control.
• 16:27
  Speaker 1: If we don't stop them, what difference does it make?
• 16:30
  Speaker 4: What about world labor?
• 16:30
  Speaker 1: Exactly.
• 16:31
  Speaker 6: What about paying $ 2 a month? These people in Sri
• 16:34
  Speaker 6: Lanka mining cobalt.
• 16:36
  Speaker 1: All right, so the Fauci situation, we talked a little
• 16:38
  Speaker 1: bit about last week, but in the end, you think
• 16:41
  Speaker 1: you would, just from the idea of let's make America
• 16:45
  Speaker 1: just a safer, healthier place, you should.
• 16:47
  Speaker 3: Tell the truth.
• 16:48
  Speaker 6: Well, the problem, and I said this last week, when
• 16:50
  Speaker 6: you have the chairman saying, I want your head on
• 16:52
  Speaker 6: the stick, you got to invoke the fifth. And I
• 16:56
  Speaker 6: would have advised him thusly, and it's not a good look.
• 17:00
  Speaker 4: Again, what is the goal?
• 17:02
  Speaker 6: We want to preserve our nation because the water supply
• 17:05
  Speaker 6: is next and the grid is next.
• 17:07
  Speaker 4: And it's probably already happening. I got to tell you,
• 17:10
  Speaker 4: these agents, whether it's FBI, CIA, Homeland Security, they got
• 17:14
  Speaker 4: a tough job. Mark Wayne Mullen. I mean, they're just
• 17:17
  Speaker 4: constantly stressed out working overtime. Bongino lasted a year.
• 17:20
  Speaker 1: Yeah. I tell you, you mentioned the. The grid, and
• 17:24
  Speaker 1: you mentioned water.
• 17:25
  Speaker 4: Oh, it scares me.
• 17:26
  Speaker 1: That scares me. I think we're so intertwined with the
• 17:29
  Speaker 1: Internet now and how everything, whether it's our money, banking, electricity,
• 17:33
  Speaker 1: everything goes through the net. If that ever gets hacked
• 17:36
  Speaker 1: and goes down, it's going to be instant chaos.
• 17:39
  Speaker 6: Yeah, and I don't want to be a panic monger. Power, finance, water, right?
• 17:45
  Speaker 6: So all you preppers out there, stock up.
• 17:48
  Speaker 4: It's kind of scary.
• 17:49
  Speaker 3: I mean, if you lose power— I say I'm not
• 17:51
  Speaker 3: afraid of.
• 17:52
  Speaker 1: Much, but— People sometimes don't put it all together. If
• 17:56
  Speaker 1: electricity goes out, you ain't getting gas. There's things that
• 17:59
  Speaker 1: aren't happening. You're not going to be able to go
• 18:01
  Speaker 1: to the store.
• 18:02
  Speaker 4: There's going to be no food.
• 18:03
  Speaker 6: Remember when we were in the aisles of the grocery
• 18:05
  Speaker 6: store seeing empty shelves and no lettuce, no chicken, people
• 18:10
  Speaker 6: wrestling over toilet paper?
• 18:12
  Speaker 1: What the heck?
• 18:13
  Speaker 2: No, no.
• 18:13
  Speaker 6: This is like an episode of Twilight Zone. I felt
• 18:16
  Speaker 6: Rod Serling in the corner.
• 18:17
  Speaker 1: Yeah, no kidding. John Nazaro with us. No, okay. So
• 18:21
  Speaker 1: I wanted to ask you about this. I opened the
• 18:23
  Speaker 1: show with this, and it seems to be a split.
• 18:26
  Speaker 1: There's a split. Well, not even a split. I would
• 18:29
  Speaker 1: almost say it's a 70-30, you know, sort of a
• 18:31
  Speaker 1: split up 70-30. These flock cameras, right? Yeah. Nobody asked
• 18:38
  Speaker 1: to put them up. They just did. Who's funding that?
• 18:41
  Speaker 1: Who's looking at that? I know some police like it
• 18:44
  Speaker 1: because it makes it easier for them to solve crimes.
• 18:46
  Speaker 3: But where are we constitutionally with them just watching us?
• 18:50
  Speaker 4: I just had a discussion the other day. I'm in
• 18:52
  Speaker 4: favor of it. See, I'm okay with that.
• 18:54
  Speaker 6: We fought to get cameras in downtown Pawkatuck, and I
• 18:57
  Speaker 6: live in Stonington, because there's so much bad stuff going on,
• 19:00
  Speaker 6: drug dealing in front of a bank downtown. And now
• 19:03
  Speaker 6: we've got cameras, and I'm okay with that. And I
• 19:05
  Speaker 6: think they're helpful.
• 19:07
  Speaker 4: I'm not worried. Again, big brother looking over our shoulder.
• 19:10
  Speaker 1: Guess what?
• 19:10
  Speaker 6: They're already doing it. We have something called a cell phone.
• 19:13
  Speaker 6: Everything we say is being tracked, cataloged. Is it coincidental
• 19:17
  Speaker 6: when you think of something, you say something, and the
• 19:19
  Speaker 6: next thing you.
• 19:19
  Speaker 4: Know, you get five ads popping up? So it's already happening.
• 19:23
  Speaker 1: But I choose to carry myself. True.
• 19:25
  Speaker 3: So that's the difference.
• 19:27
  Speaker 1: And I was wrestling with this, too, because some people
• 19:29
  Speaker 1: that I talk to, law enforcement folks, they like it.
• 19:32
  Speaker 3: Some others don't.
• 19:33
  Speaker 1: Some like it. Some don't. But I feel like your
• 19:37
  Speaker 1: big brother is watching.
• 19:39
  Speaker 4: It's really helpful.
• 19:40
  Speaker 6: I know a guy that was installing the cameras in downtown,
• 19:43
  Speaker 6: and a guy came up to him. be careful not
• 19:45
  Speaker 6: to mention names and and it's a guy known to
• 19:47
  Speaker 6: carry a box cutter and he says what are you
• 19:49
  Speaker 6: doing well i'm stalling cameras you know and he started
• 19:52
  Speaker 6: giving a hard time he says no you don't understand
• 19:54
  Speaker 6: this is the way of the future that was like
• 19:55
  Speaker 6: 10 years ago yeah 12 years ago so i'm okay
• 19:58
  Speaker 6: because i have ceded to the conclusion that there's no
• 20:03
  Speaker 6: reasonable expectation of privacy Privacy is.
• 20:05
  Speaker 4: A lost concept.
• 20:06
  Speaker 6: People were offended that Fauci's computer emails were revealed.
• 20:11
  Speaker 4: Well, what a dope.
• 20:13
  Speaker 6: Anybody that types on a work computer, let alone a
• 20:16
  Speaker 6: government computer, you have no reasonable expectation of privacy.
• 20:20
  Speaker 4: And I did. I'm writing a book. I got drafts.
• 20:23
  Speaker 1: Oh, you are? Okay.
• 20:23
  Speaker 6: You know, I've been writing a long time. There's little anecdotes.
• 20:26
  Speaker 6: And I put it on a work computer. And I
• 20:28
  Speaker 6: used to say to people when I was a judge
• 20:30
  Speaker 6: and I was traveling from district to district, I don't
• 20:32
  Speaker 6: care if you rifle through my desk. I have no
• 20:34
  Speaker 6: expectation of privacy. I keep nothing private in there. This
• 20:37
  Speaker 6: is a government thing.
• 20:38
  Speaker 1: So the idea of the Fourth Amendment doesn't play?
• 20:41
  Speaker 4: Fourth Amendment, yes.
• 20:43
  Speaker 6: There shall not be unreasonable search and seizure. It's a
• 20:47
  Speaker 6: tough thing.
• 20:47
  Speaker 4: Government access, is it? I don't know. Everybody's walking in
• 20:51
  Speaker 4: plain sight, hiding in plain sight. A lot of valuable information.
• 20:54
  Speaker 1: We talked about China, though, too. China has facial recognition everywhere. And,
• 20:59
  Speaker 1: you know, they're catching people jaywalking. They're sending them tickets. It's,
• 21:02
  Speaker 1: you know, they're taking, well, not really tickets. They're taking
• 21:04
  Speaker 1: away their points.
• 21:05
  Speaker 4: There's no theft in China. There's no theft in Turkey.
• 21:08
  Speaker 1: You know why?
• 21:09
  Speaker 4: Because they cut your hand off.
• 21:11
  Speaker 6: It's not a good look walking around with one paw
• 21:13
  Speaker 6: in Turkey. So they have a real good incentive not
• 21:16
  Speaker 6: to do bad things.
• 21:17
  Speaker 1: It's interesting. It's an interesting conversation, to say the least.
• 21:21
  Speaker 1: All right, so there was another story out. Trump regulators
• 21:25
  Speaker 1: moved to curtail lending to undocumented immigrants. I guess the
• 21:29
  Speaker 1: federal regulators last couple weeks ago, they directed banks and
• 21:33
  Speaker 1: credit unions to more closely scrutinize loans going out to immigrants.
• 21:37
  Speaker 1: Thoughts on that?
• 21:38
  Speaker 4: Well, the vice is getting tighter and tighter and tighter.
• 21:42
  Speaker 4: It's sad.
• 21:43
  Speaker 6: I'm going to give you another perspective because I'm going
• 21:45
  Speaker 6: to say it. I know people and they consult me.
• 21:48
  Speaker 6: who are undocumented. They're what we call overstays.
• 21:51
  Speaker 4: They had a visa.
• 21:52
  Speaker 1: It expired.
• 21:53
  Speaker 6: They're afraid to avail themselves of any government services, whether
• 21:58
  Speaker 6: it's medical care and that kind of thing. And they
• 22:00
  Speaker 6: can't go abroad because if they go back home, they're
• 22:04
  Speaker 6: not going to allow it back in. They don't have paperwork.
• 22:06
  Speaker 6: So there's this whole population that's living under the grid.
• 22:09
  Speaker 6: It's kind of a sad situation. We've got to do
• 22:11
  Speaker 6: something about it. So do I agree with it? I
• 22:14
  Speaker 6: don't like it. about loans, and they can't get loans.
• 22:18
  Speaker 4: So what does that mean?
• 22:18
  Speaker 6: They're going to pay usurious rates, and they'll be subject
• 22:22
  Speaker 6: to that whole subculture.
• 22:24
  Speaker 4: So the vice is getting tighter and tighter and tighter.
• 22:27
  Speaker 1: How about the latest? There's a law in place here
• 22:31
  Speaker 1: in the state of Connecticut where now there's elections coming up,
• 22:34
  Speaker 1: and there's primaries coming up. Law enforcement folks can't have
• 22:37
  Speaker 1: to be 250 feet or more away from a polling
• 22:40
  Speaker 1: place because, according to the governor... It puts the people
• 22:45
  Speaker 1: undocumented in— they feel like it adds to their angst, and
• 22:51
  Speaker 1: they don't want them to feel threatened. And then the
• 22:53
  Speaker 1: response is, well, they shouldn't be voting anyway, right? I mean,
• 22:56
  Speaker 1: we're not— what are we doing, right?
• 22:58
  Speaker 4: Let's protect the illegal vote block.
• 23:00
  Speaker 3: So, I mean, you know, and the cops are ticked
• 23:03
  Speaker 3: off of that.
• 23:03
  Speaker 1: They're actually offended by it. I don't blame them. It's
• 23:05
  Speaker 1: a crazy train.
• 23:05
  Speaker 6: I mean, when we have lawmakers, whether it's a governor, federal,
• 23:09
  Speaker 6: state legislation, trying to disempower— As someone said the other
• 23:14
  Speaker 6: day during the hearings, these are laws passed by Congress.
• 23:17
  Speaker 6: I think it was Mark Wayne Mullen. I watched the
• 23:19
  Speaker 6: speech again that he gave before committee. The laws are
• 23:23
  Speaker 6: on the books. We have ICE for a reason. If
• 23:26
  Speaker 6: you don't like the law, change the law. But don't
• 23:28
  Speaker 6: disempower an agency from doing their statutory duty, and that
• 23:32
  Speaker 6: includes law enforcement officers. So it really is– again, I
• 23:36
  Speaker 6: talk about Alice in Wonderland. Up is down, down is up.
• 23:39
  Speaker 4: It's not right.
• 23:40
  Speaker 6: And it's also political candidates– can stand X amount of feet.
• 23:45
  Speaker 6: You know, the whole intimidation thing. Enough with the intimidation.
• 23:48
  Speaker 6: Police are there to help and protect. Yeah, they've done
• 23:51
  Speaker 6: bad things.
• 23:52
  Speaker 1: It happens.
• 23:52
  Speaker 4: But you can't.
• 23:54
  Speaker 6: Where did the defund the police movement go? We haven't
• 23:56
  Speaker 6: heard much about that. BLM and all the financial impropriety.
• 24:00
  Speaker 6: You know, that's sort of piped down. Because we need
• 24:03
  Speaker 6: law enforcement. And the Democrats now, and this dovetails into politics,
• 24:08
  Speaker 6: they're disassociating from the Democrat Socialist Party of no police.
• 24:13
  Speaker 4: No Senate.
• 24:14
  Speaker 1: How come they keep winning, though? They keep winning some
• 24:17
  Speaker 1: of these.
• 24:17
  Speaker 4: They keep winning. For what I said, and you might
• 24:19
  Speaker 4: have seen this, there is an anti-incumbent fervor.
• 24:22
  Speaker 1: Yeah.
• 24:22
  Speaker 6: Because I don't know about you. I'm sick of all
• 24:24
  Speaker 6: of them. Just do the people's business. Take care of people.
• 24:28
  Speaker 6: Protect us. Clean our catch basins. Pass funding. Stop taxing
• 24:33
  Speaker 6: us to death.
• 24:33
  Speaker 1: Yeah.
• 24:34
  Speaker 4: When one half of our income is going to the government.
• 24:36
  Speaker 1: Yeah.
• 24:36
  Speaker 4: We have to work until May or June before you
• 24:38
  Speaker 4: can pocket dollar one.
• 24:40
  Speaker 1: Right. It's enough.
• 24:41
  Speaker 4: It's out of control.
• 24:42
  Speaker 1: Here's an interesting theoretical question for you. Sure. So you're
• 24:46
  Speaker 1: a representative. You're a state senator. You're a state rep.
• 24:49
  Speaker 1: Are they obliged to listen to the constituents, or are
• 24:55
  Speaker 1: they more obliged to listen to their own inner self
• 24:59
  Speaker 1: to do what's right when they're voting, casting a vote?
• 25:02
  Speaker 4: I don't think it's an either-or, and I'm not doing
• 25:05
  Speaker 4: the lawyer dodge.
• 25:06
  Speaker 1: I think it's both.
• 25:07
  Speaker 4: I mean, you have a duty to your constituents.
• 25:08
  Speaker 1: Right.
• 25:09
  Speaker 4: And you have a duty also to do a vote
• 25:11
  Speaker 4: with your conscience and reason. It's like the issue of religion.
• 25:15
  Speaker 1: Right.
• 25:15
  Speaker 6: You may be a Catholic, but should that rule your
• 25:18
  Speaker 6: decision making? And I respect those politicians who say, hey,
• 25:21
  Speaker 6: you know, when I'm an elected official, I've got to
• 25:23
  Speaker 6: park my personal beliefs and do what's right for the people.
• 25:26
  Speaker 4: So I think it's a combination. I don't think it's a.
• 25:28
  Speaker 1: Either or. No, I bring it up because there's been
• 25:31
  Speaker 1: debates about this because, you know, if you're representing people,
• 25:34
  Speaker 1: but let's say the people in your district want you
• 25:36
  Speaker 1: to vote for a billion dollar, an extra billion dollar
• 25:40
  Speaker 1: tax on billionaires. Yeah. Right. And you, as a fiscal conservative,
• 25:43
  Speaker 1: you're like, well, that's a bad idea.
• 25:45
  Speaker 6: Right.
• 25:45
  Speaker 1: Right. And then you vote against that.
• 25:47
  Speaker 4: You've got to vote your conscience. I have that problem
• 25:49
  Speaker 4: as a lawyer.
• 25:50
  Speaker 5: Yeah.
• 25:50
  Speaker 6: As a lawyer, I'm sometimes telling, I often tell clients
• 25:54
  Speaker 6: something they don't want to hear.
• 25:55
  Speaker 5: Yeah.
• 25:55
  Speaker 6: But sometimes I have to protect the client from himself
• 25:59
  Speaker 6: or herself because they're going to make a bad decision.
• 26:01
  Speaker 6: And I used to tell people, look, if you're going
• 26:03
  Speaker 6: to pay me, listen to me.
• 26:04
  Speaker 4: Otherwise, fire me. Why are you hiring me? You're paying
• 26:06
  Speaker 4: me a lot of money. You're not listening to me.
• 26:08
  Speaker 1: Good point. All right, one more. Major appeals court declares
• 26:12
  Speaker 1: New Jersey AR-15 ban unconstitutional in landmark Second Amendment ruling.
• 26:17
  Speaker 1: AR-15 is good to go in New Jersey. People were
• 26:19
  Speaker 1: celebrating that a couple weeks ago.
• 26:21
  Speaker 6: Yeah, I think that's the right ruling. You know, I
• 26:24
  Speaker 6: shot it. We talked about this. I shot an AR-15.
• 26:27
  Speaker 6: And people are frightened. And when we start banning certain things,
• 26:32
  Speaker 6: Connecticut has been successful.
• 26:34
  Speaker 4: We'll see where it goes.
• 26:35
  Speaker 6: We're constantly testing the bounds of the Second Amendment. The
• 26:39
  Speaker 6: right to bear arms shall not be infringed. What a
• 26:42
  Speaker 6: short amendment. And it's generated so much case law. There
• 26:45
  Speaker 6: are people that— I remember when Obama, the theory was that
• 26:49
  Speaker 6: he was confiscating all the ammunition— They were going to
• 26:51
  Speaker 6: outlaw guns.
• 26:52
  Speaker 4: You couldn't find ammo anywhere. It was scary.
• 26:55
  Speaker 3: All right, Judge, what do you got going on?
• 26:57
  Speaker 1: You got any big cases we need to know about?
• 26:59
  Speaker 4: We got a lot going on. I will say this.
• 27:01
  Speaker 4: There's a huge increase. I'm not happy with this.
• 27:04
  Speaker 6: With domestic violence and also orders of protection involving family members,
• 27:10
  Speaker 6: I'm getting a lot of calls and appearing in criminal court.
• 27:13
  Speaker 4: Be careful.
• 27:13
  Speaker 6: You can be arrested if somebody says that you grabbed
• 27:16
  Speaker 6: them wrongly and that kind of thing. It's a very
• 27:18
  Speaker 6: scary thing. And this Tracy Thurman case, and we had
• 27:21
  Speaker 6: a caller call about this from Torrington. That was the
• 27:24
  Speaker 6: case where the Torrington Police Department was held liable for
• 27:26
  Speaker 6: millions of dollars. All that did was take the responsibility
• 27:29
  Speaker 6: out of the local police in a domestic situation. Now
• 27:33
  Speaker 6: they have to arrest everybody, protective order on everybody, and
• 27:36
  Speaker 6: let the prosecutor sort it out.
• 27:38
  Speaker 4: I don't like that. In the old days, right, you
• 27:40
  Speaker 4: go left, you go right, chill off. Not everybody has
• 27:44
  Speaker 4: to be arrested. But, boy, I tell you, the phone's ringing,
• 27:47
  Speaker 4: very busy.
• 27:47
  Speaker 6: You can find me at Nazaro Law in New London
• 27:50
  Speaker 6: across from the Washington Street Coffee House.
• 27:52
  Speaker 4: I do personal injury and criminal litigation.
• 27:54
  Speaker 1: And coffee.
• 27:55
  Speaker 4: I buy you coffee.
• 27:56
  Speaker 1: Espresso. All right, buddy. Have a good weekend.
• 27:58
  Speaker 4: Thank you so much.
• 27:59
  Speaker 1: All right, kid. We'll come back. My brother next. Stick around.
• 28:04
  Speaker 4: I ain't here for maybe.
• 28:08
  Speaker 1: You have sent me this amazing cover letter, a breakdown
• 28:13
  Speaker 1: of what we're going to talk about today. I posted
• 28:15
  Speaker 1: it for everybody. up on Facebook. If you want to
• 28:17
  Speaker 1: follow along, it's got some hyperlinks in it where people
• 28:20
  Speaker 1: can go and take a look at some stuff. But
• 28:22
  Speaker 1: where did you want to start today? I'll let you,
• 28:24
  Speaker 1: you tell us where you want to start.
• 28:26
  Speaker 2: Well, the main reason I reached out to you is
• 28:28
  Speaker 2: because there were a few things that happened over the
• 28:29
  Speaker 2: past couple of weeks, two specific things. One was the, um,
• 28:33
  Speaker 2: hugging face hack hack that happened from open AI. That's
• 28:36
  Speaker 2: been in the news a lot. And I just wanted
• 28:37
  Speaker 2: to talk about that a little bit. And then, um,
• 28:41
  Speaker 2: Second was a letter that came out signed by over 1,200
• 28:46
  Speaker 2: AI researchers, the people inside actually doing this work, saying, hey,
• 28:50
  Speaker 2: we need to be regulated. The competition is huge, and
• 28:54
  Speaker 2: we need to be regulated. So I wanted to talk
• 28:55
  Speaker 2: about them. But the truth is I haven't been here
• 28:57
  Speaker 2: to talk about this since March. And in five months,
• 29:00
  Speaker 2: it's crazy what all is happening. And the rate of
• 29:02
  Speaker 2: change is huge. And so it seemed like we should
• 29:04
  Speaker 2: start by kind of going over that a little bit
• 29:08
  Speaker 2: and talking about the– the recent changes.
• 29:10
  Speaker 1: All right. So last time we talked about all these different, uh,
• 29:13
  Speaker 1: AI platforms, whether it was Claude or open AI or
• 29:16
  Speaker 1: Grok or whatever. And, and you said they all kind
• 29:18
  Speaker 1: of do their own little different things a little differently.
• 29:20
  Speaker 1: And so I started actually from that conversation, I started
• 29:22
  Speaker 1: to experiment with some of the other AIs and I
• 29:25
  Speaker 1: find they all do a little, little different stuff. Right. Yep.
• 29:28
  Speaker 1: All right. So tell me what the big stuff has
• 29:29
  Speaker 1: happened in the last five months.
• 29:31
  Speaker 4: So, um, The first thing is just the rate of
• 29:34
  Speaker 4: change is crazy. It's huge.
• 29:37
  Speaker 2: Just to review, this all started like three and a
• 29:39
  Speaker 2: half years ago. when the first OpenAI Chat GBT 3.5
• 29:44
  Speaker 2: came out in November of 22. So it's not that old.
• 29:48
  Speaker 2: And at that point, there was one model. And then
• 29:51
  Speaker 2: Google and Anthropic came in. So a few months later,
• 29:54
  Speaker 2: there were three models. At this point, there are at
• 29:57
  Speaker 2: least 13 companies around the world creating frontier models. That
• 30:03
  Speaker 2: means they're actually making it learn new things and do
• 30:07
  Speaker 2: new things that it's never done before. Now, there are
• 30:09
  Speaker 2: all kinds of agents that are leveraging the knowledge of those.
• 30:13
  Speaker 2: Like those are the engines. There's 13 engines, and there
• 30:17
  Speaker 2: are all kinds of agents doing things that you and
• 30:18
  Speaker 2: I would want on a day-to-day basis. But as far
• 30:21
  Speaker 2: as the frontier models go, There are a lot more
• 30:24
  Speaker 2: than there were before. And actually, in the document that
• 30:28
  Speaker 2: I sent you, there's a graph of kind of not
• 30:30
  Speaker 2: only the proliferation of companies doing these models, but also
• 30:37
  Speaker 2: kind of like how they're leapfrogging each other in terms
• 30:41
  Speaker 2: of capabilities and stuff like that.
• 30:42
  Speaker 4: But they're also the idea of agents.
• 30:46
  Speaker 2: Just to frame this, agents are, again, they're like a
• 30:50
  Speaker 2: day-to-day tool. We talked about that before, and we have
• 30:53
  Speaker 2: time to talk about it, so I'm not going to
• 30:54
  Speaker 2: talk about that again.
• 30:56
  Speaker 4: But they are day-to-day tools you can set up to.
• 31:01
  Speaker 2: Manage your calendar, for managing your email, for scheduling a
• 31:05
  Speaker 2: trip that you're going to.
• 31:06
  Speaker 4: Take, all kinds of day-to-day things you can do.
• 31:08
  Speaker 2: They're all leveraging these powerful models, but they're little day-to-day
• 31:13
  Speaker 2: things going on. Well, at this point, it's estimated there
• 31:16
  Speaker 2: are 29 million active agents that are enterprise that are like,
• 31:22
  Speaker 2: that are discoverable, that are big deal kind of like
• 31:25
  Speaker 2: companies are using it to solve problems. 29 million at
• 31:28
  Speaker 2: this point, it's estimated that by 1929, there will be
• 31:32
  Speaker 2: a billion. It's the proliferation of this is growing so fast.
• 31:36
  Speaker 4: It's crazy.
• 31:37
  Speaker 1: Take a second and just please, I'm sorry to, I don't,
• 31:39
  Speaker 1: I don't want to slow you down, but what's explain
• 31:40
  Speaker 1: the agent scenario again. What does that mean?
• 31:43
  Speaker 2: What it is is, um, So the model itself does
• 31:49
  Speaker 2: the heavy thinking. It's like an engine on a car
• 31:51
  Speaker 2: or something, or a battery, if you want to say.
• 31:54
  Speaker 2: And the agents are— let' s go with the metaphor of a battery.
• 31:59
  Speaker 2: The agents are tools you would use that— that use
• 32:03
  Speaker 2: the power from the battery to do something on a
• 32:06
  Speaker 2: day to day basis. So if it's a battery, you
• 32:07
  Speaker 2: might use a hairdryer or you might use a fan
• 32:10
  Speaker 2: or you might use a refrigerator or whatever. There are
• 32:13
  Speaker 2: things that you, and if you look it up, if
• 32:16
  Speaker 2: you just search it on any of these and say
• 32:18
  Speaker 2: what I do this on a day to day basis,
• 32:20
  Speaker 2: or this is my job, what are.
• 32:21
  Speaker 4: Some agents I would use?
• 32:22
  Speaker 2: It will describe, but the obvious, that's what I would
• 32:26
  Speaker 2: do is go for the, whatever you're trying to do,
• 32:28
  Speaker 2: say what agents would be relevant, but, There are just
• 32:31
  Speaker 2: tons of them. And as I said, the obvious generic
• 32:35
  Speaker 2: ones are there are agents that will plan a trip
• 32:38
  Speaker 2: for you. So you could say, I want to go
• 32:39
  Speaker 2: to Cancun, but I don't care if it's exactly Cancun.
• 32:42
  Speaker 2: It could be somewhere in the Caribbean. Here's my time frame.
• 32:46
  Speaker 2: I want the price to be low. Same thing as
• 32:48
  Speaker 2: you would be thinking in your own head about what.
• 32:50
  Speaker 1: You're going to do.
• 32:51
  Speaker 4: I want the price to be low. I don't like
• 32:52
  Speaker 4: to do early morning flights. Tell it things like that.
• 32:57
  Speaker 2: And then it will go out and– If you tell
• 33:01
  Speaker 2: it to and give it authority to, it will actually
• 33:04
  Speaker 2: go out and book the flights for you and book
• 33:06
  Speaker 2: the hotel and all that. But most people wouldn't do that.
• 33:08
  Speaker 2: Most people would say, come back and tell me all
• 33:10
  Speaker 2: the options, and then I'll choose them, and then.
• 33:15
  Speaker 4: You can say, okay, like this, this, this, this, go
• 33:18
  Speaker 4: ahead and book them.
• 33:19
  Speaker 1: All right, and that's amazing. I didn't even realize that.
• 33:21
  Speaker 1: So now let's say, let's use me for an example.
• 33:24
  Speaker 1: So if I went to chat GPT and I said,
• 33:27
  Speaker 1: find me, Do I tell it to find me an agent,
• 33:30
  Speaker 1: or do I just say, what I want to do
• 33:32
  Speaker 1: is I want you to give me the most streamlined
• 33:35
  Speaker 1: mechanism for preparing a talk radio show every day, X, Y,
• 33:39
  Speaker 1: and Z, and then it would go out and kind
• 33:42
  Speaker 1: of create that for me?
• 33:45
  Speaker 2: The problem is there are– and this is what I'm
• 33:47
  Speaker 2: talking about here is there are so many choices that
• 33:49
  Speaker 2: if you say– if you ask that, yes, what it
• 33:52
  Speaker 2: will do, it will say you've got multiple options.
• 33:55
  Speaker 4: You– You can.
• 33:57
  Speaker 2: Here are some agents that can help you with that.
• 34:00
  Speaker 2: And it will list them. But you could specifically search
• 34:03
  Speaker 2: and say, OK, agent seems like the way to go.
• 34:05
  Speaker 2: Tell me more agents and tell me how they and
• 34:08
  Speaker 2: what would be best about.
• 34:09
  Speaker 4: One of the other.
• 34:10
  Speaker 2: Or it could create. I talked before about vibe coding,
• 34:15
  Speaker 2: which is you and I. without any coding background, can
• 34:19
  Speaker 2: code something by telling it exactly what you want in prose.
• 34:25
  Speaker 4: You just write.
• 34:27
  Speaker 4: Sorry, since we're talking about this.
• 34:29
  Speaker 2: I did this a little more than a year ago
• 34:32
  Speaker 2: when vibe coding first started coming. Created a little app
• 34:37
  Speaker 2: that you could play with that allows you to... I
• 34:40
  Speaker 2: wrote a short paragraph and said... I want an app
• 34:43
  Speaker 2: that would allow a player to make new rules of chess,
• 34:46
  Speaker 2: change the size of the board from 5x5 to 12x12,
• 34:50
  Speaker 2: but could anything in between, to change what pieces are
• 34:53
  Speaker 2: on the board, to make up new pieces if they want.
• 34:57
  Speaker 2: And then when they change the rules, they could play
• 35:00
  Speaker 2: against a computer at six different levels of ability or
• 35:04
  Speaker 2: play against another person online.
• 35:06
  Speaker 4: I wrote that, basically.
• 35:08
  Speaker 2: It was a short paragraph, and it generated a few
• 35:13
  Speaker 2: thousand lines of code, and it's a game that you
• 35:15
  Speaker 2: can play.
• 35:15
  Speaker 1: Are you kidding me right now?
• 35:17
  Speaker 4: It's crazy.
• 35:17
  Speaker 1: So does it spit you back a link, or the
• 35:20
  Speaker 1: actual– how does it spit back the app?
• 35:23
  Speaker 4: What it does is two things. It shows you all
• 35:26
  Speaker 4: the code.
• 35:26
  Speaker 2: It shows you all the code, but then it gives
• 35:28
  Speaker 2: you a link, and it says download this file, and
• 35:30
  Speaker 2: it was an index file. So it says– um, download
• 35:34
  Speaker 2: this file and you download it, click on it and
• 35:36
  Speaker 2: it opens up and.
• 35:37
  Speaker 4: You, and you can play and you've got a game. And,
• 35:39
  Speaker 4: and so, and actually this feeds.
• 35:41
  Speaker 2: Into something that I'm going to say later is as
• 35:44
  Speaker 2: soon as, as when you unleash your imagination, which I
• 35:47
  Speaker 2: see you've done all around your walls with pictures of
• 35:50
  Speaker 2: all kinds of creative things. But, um, You can make anything,
• 35:55
  Speaker 2: which means the entrepreneurial activity has gone crazy. The number
• 35:59
  Speaker 2: of new businesses related to AI, you know, using AI,
• 36:04
  Speaker 2: just because people have ideas. People are standing in the shower,
• 36:06
  Speaker 2: people are driving to work, whatever, and they go, wouldn't
• 36:07
  Speaker 2: it be great if we had blah, blah, blah? And
• 36:09
  Speaker 2: they look it up, and there isn't a thing like that.
• 36:10
  Speaker 2: And then they go in, and you don't have to
• 36:13
  Speaker 2: be a programmer. You can vibe code. You can vibe
• 36:16
  Speaker 2: code anything. So getting back to your original question, the
• 36:19
  Speaker 2: simplest thing would be an agent, and I would– You
• 36:22
  Speaker 2: could just put in the question. I want to, I
• 36:25
  Speaker 2: can't remember exactly your question, but how would be my
• 36:27
  Speaker 2: best way to put together a show?
• 36:29
  Speaker 1: Yeah.
• 36:30
  Speaker 2: It will offer you, you know, three, five, 10 different options.
• 36:34
  Speaker 2: And then you could say, okay, please drill down on
• 36:37
  Speaker 2: this one.
• 36:38
  Speaker 4: I really like this one.
• 36:39
  Speaker 2: Tell me more about this and suggest some agents that
• 36:42
  Speaker 2: could be helpful in this. And people use it for
• 36:44
  Speaker 2: their calendars. They people use it for, I mean, But
• 36:48
  Speaker 2: way more sophisticated. Businesses that are– in fact, in the
• 36:52
  Speaker 2: AI hugging, the hugging face hack that happened, agents were
• 36:59
  Speaker 2: doing that. So agents are– there are 29 million of them.
• 37:04
  Speaker 2: There are expected to be a billion of them by 1929.
• 37:07
  Speaker 2: So it's growing really quickly. Okay.
• 37:10
  Speaker 4: Major updates. You know, at the beginning we.
• 37:12
  Speaker 2: Had 3.5 and then we got 4.0 like six months
• 37:14
  Speaker 2: later and we were getting updates. In 2023, there were
• 37:17
  Speaker 2: 18 major updates releases by the companies.
• 37:19
  Speaker 4: In 2024, there were 32. In 2025, there were 45
• 37:20
  Speaker 4: new updates.
• 37:20
  Speaker 2: So that's almost one a week that was happening. In
• 37:39
  Speaker 2: this year, it's averaging three major updates a week. So
• 37:45
  Speaker 2: the rate of change of this, I actually read something
• 37:47
  Speaker 2: from somebody who comments on this, and he said, I
• 37:51
  Speaker 2: have this as my full-time job, and I can't keep
• 37:53
  Speaker 2: on top of it.
• 37:54
  Speaker 4: It's going so fast. It's really challenging.
• 37:57
  Speaker 1: Is it doing it to itself or are the programmers
• 38:00
  Speaker 1: making the updates? Both. Okay.
• 38:02
  Speaker 2: Because the programmers are figuring out new things.
• 38:05
  Speaker 4: They're improving.
• 38:06
  Speaker 2: The competition is very stiff because it's become clear that
• 38:10
  Speaker 2: this is a big, important thing. But to your point,
• 38:14
  Speaker 2: the AI has become good enough that it is helping
• 38:18
  Speaker 2: program itself.
• 38:19
  Speaker 4: It is improving itself.
• 38:21
  Speaker 1: Yeah, that's amazing. Okay, that's incredible.
• 38:23
  Speaker 2: Yeah, so it's writing itself, and so the rate of
• 38:26
  Speaker 2: change is accelerating. I talked about distillation before. I don't
• 38:30
  Speaker 2: want to go into that a lot, but sometimes when
• 38:32
  Speaker 2: you talk about, like, particularly some of the Chinese ones,
• 38:37
  Speaker 2: they have some very good programmers in China, and they're
• 38:39
  Speaker 2: doing some good work, but one of the things they're definitely,
• 38:42
  Speaker 2: or there's evidence that they're doing, is they're distilling, which
• 38:46
  Speaker 2: is when there's a new model that OpenAI or somebody
• 38:49
  Speaker 2: comes out with, Anthropic comes out with, they will have
• 38:53
  Speaker 2: like 10 million.
• 38:54
  Speaker 4: Little bots interrogate the new model and from that learn
• 38:59
  Speaker 4: from the new model.
• 39:00
  Speaker 2: And that makes it, you can be a fast follower
• 39:02
  Speaker 2: really cheaply. You can figure out what it's learned, what
• 39:05
  Speaker 2: it knows. It's kind of like, think of, you know,
• 39:08
  Speaker 2: I have two grandchildren. Before they can talk, they're learning
• 39:11
  Speaker 2: by looking all around and just figuring out what the
• 39:14
  Speaker 2: world's about. That's what in the core research group is
• 39:18
  Speaker 2: doing with the Frontier model. But once the kid gets older,
• 39:24
  Speaker 2: it can talk to you and it can learn things
• 39:25
  Speaker 2: from you and it can ask you.
• 39:27
  Speaker 4: And it learns a lot faster than just by looking
• 39:29
  Speaker 4: all around.
• 39:29
  Speaker 2: And so distillation is a reasonable thing, but what it
• 39:34
  Speaker 2: means is it seems like, oh, they're.
• 39:36
  Speaker 4: Catching up, they're catching up.
• 39:37
  Speaker 2: Well, part of the reason they're catching up is because
• 39:39
  Speaker 2: they're interrogating our new models.
• 39:41
  Speaker 4: And so.
• 39:43
  Speaker 2: Anyway, that is speeding up the whole thing, too, because
• 39:46
  Speaker 2: actually we use it in a positive way to make
• 39:48
  Speaker 2: our models faster. And the last thing I want to
• 39:51
  Speaker 2: just say on that part is the competition for this
• 39:55
  Speaker 2: is intense. It's intense between the different companies. The two
• 39:59
  Speaker 2: big players in the U.S. are Anthropic, which has Claude,
• 40:03
  Speaker 2: and OpenAI, which has ChatGPT. Both of those are about
• 40:08
  Speaker 2: to go bust. They seem like they're about to do IPOs.
• 40:11
  Speaker 2: They both filed. The competition is huge. They're both trying
• 40:15
  Speaker 2: to get a lot of visibility. They're both doing amazing
• 40:18
  Speaker 2: new things. in the press all the time, but there's
• 40:22
  Speaker 2: also huge competition between the U.S.
• 40:25
  Speaker 4: And China. So there's a lot of competitive pressure internally
• 40:29
  Speaker 4: and externally, like the U.S.
• 40:31
  Speaker 2: Wants to have the lead on this, China wants to
• 40:32
  Speaker 2: have the lead on this, and so there's a lot
• 40:34
  Speaker 2: of pressure, and that actually drives the second of the
• 40:38
  Speaker 2: two things that I was really wanting to come about,
• 40:40
  Speaker 2: the letter that was put together, and the letter's basically
• 40:44
  Speaker 2: saying the competitive pressure is huge, and The way things are,
• 40:51
  Speaker 2: it's hard not to just go with the competitive pressure.
• 40:54
  Speaker 2: An outside regulatory body needs to manage this, just as
• 40:59
  Speaker 2: we have with FDA and FAA and SEC. We have
• 41:04
  Speaker 2: all these regulatory bodies, but it needs to be international. Anyway,
• 41:07
  Speaker 2: we'll talk about that later. But an important thing to
• 41:11
  Speaker 2: keep in mind in all this is that the competitive
• 41:14
  Speaker 2: pressure is intense. Well, the good part of all this
• 41:16
  Speaker 2: is that The innovations in our day-to-day life are crazy. Like,
• 41:23
  Speaker 2: you may have seen a couple weeks ago it came
• 41:25
  Speaker 2: out that OpenAI's new model solved 10, like, long-time, open-standing
• 41:32
  Speaker 2: math problems that, like, nobody had solved before. And, like,
• 41:36
  Speaker 2: huge deals that have been validated by mathematicians, and they're all, like,
• 41:42
  Speaker 2: and there's... A lot of famous mathematicians, but there's one
• 41:45
  Speaker 2: guy named Terry Tao who's at UCLA who's, like, world
• 41:48
  Speaker 2: famous and, like, if you have a math problem you
• 41:50
  Speaker 2: can't solve, send it to him.
• 41:51
  Speaker 1: Right.
• 41:51
  Speaker 2: And he talks about that he uses it all the
• 41:53
  Speaker 2: time to help him do– it doesn't solve his problems,
• 41:55
  Speaker 2: but he helps it as an– he uses it as
• 41:57
  Speaker 2: an assistant. So it's helping a lot– it's solving a
• 42:00
  Speaker 2: lot of math problems. It's doing pharmaceutical, medicine, genetic research stuff.
• 42:06
  Speaker 2: It's– Chemistry is helping create better batteries, which is a
• 42:09
  Speaker 2: really important thing for us, for cars, for everything. Quantum
• 42:13
  Speaker 2: computing we talked about before, which I'm not going to
• 42:15
  Speaker 2: get into here, but it's.
• 42:16
  Speaker 4: A very sophisticated part of physics. That's it's helping with that.
• 42:21
  Speaker 2: It's helping with new material creation, you know, crystal superconductor,
• 42:25
  Speaker 2: all kinds of stuff.
• 42:27
  Speaker 4: It's we talked about programming.
• 42:28
  Speaker 2: It's helping with the vibe program broken programming, which brings
• 42:32
  Speaker 2: programming to you and me.
• 42:33
  Speaker 4: But it also is helping the experts.
• 42:35
  Speaker 2: I mean, my son who works at OpenAI and is
• 42:38
  Speaker 2: a researcher uses it all the time.
• 42:40
  Speaker 1: And it it.
• 42:43
  Speaker 2: It makes him lots, lots, lots faster, like maybe 100
• 42:46
  Speaker 2: times faster.
• 42:47
  Speaker 4: It makes him a lot faster. And he's representative. That's true.
• 42:52
  Speaker 2: And as I said, they're improving themselves. One kind of
• 42:55
  Speaker 2: side note, or not side note, but another area, entertainment industry.
• 42:58
  Speaker 2: I don't know if you've heard of Tilly Norwood. About
• 43:03
  Speaker 2: six months ago, she, which is not a person, made
• 43:07
  Speaker 2: the headlines because.
• 43:08
  Speaker 4: I think it's out of the Netherlands someplace.
• 43:12
  Speaker 2: They generated this person that they're now having agents for,
• 43:16
  Speaker 2: I mean, agents like booking agents, to try to sell
• 43:22
  Speaker 2: this person as a character. And I said this, I
• 43:29
  Speaker 2: think it was two years ago, that when opening, I
• 43:33
  Speaker 2: first came out with Sara, the video thing.
• 43:36
  Speaker 4: What's the guy's name in Atlanta?
• 43:38
  Speaker 2: A famous director of Anyway, decided to shut down production
• 43:44
  Speaker 2: of a new studio, creation of a new studio, because
• 43:47
  Speaker 2: he was thinking, I'm not sure we need this. So
• 43:51
  Speaker 2: the capability is huge in the entertainment industry. Actually, I
• 43:54
  Speaker 2: think actors are talking about it. It's obviously a concern,
• 43:57
  Speaker 2: a threat. There was a strike a few years ago,
• 43:59
  Speaker 2: and it was about this.
• 44:01
  Speaker 4: You can generate all kinds of things.
• 44:03
  Speaker 2: So it's really touching every part of our lives.
• 44:07
  Speaker 4: You can.
• 44:08
  Speaker 2: seems like in a good way and a lot of
• 44:10
  Speaker 2: things improving you know cancer research other things um some
• 44:13
  Speaker 2: of them feel threatening if you're in that field like
• 44:16
  Speaker 2: okay what am i going to do so so that's
• 44:18
  Speaker 2: there um and so you know getting going from there
• 44:22
  Speaker 2: talking about the impact on our lives there are a
• 44:25
  Speaker 2: couple of things people are nervous about it yeah and
• 44:31
  Speaker 2: i think part of it is the fault of people
• 44:34
  Speaker 2: like sam altman and and dario amodi who are the
• 44:37
  Speaker 2: CEOs of chat GPT or of OpenAI and Anthropic because
• 44:46
  Speaker 2: they've been talking about it replacing everybody's jobs and all
• 44:49
  Speaker 2: kinds of apocalyptic things.
• 44:52
  Speaker 4: But I always keep it in their whatever they say.
• 44:57
  Speaker 2: As and take it with a grain of salt they
• 45:00
  Speaker 2: know what they're producing they know they can see things
• 45:03
  Speaker 2: coming down the pipeline they know better than you and
• 45:05
  Speaker 2: I do but they're You know, due respect, they're not
• 45:09
  Speaker 2: economists and they're not social scientists. And so to predict
• 45:12
  Speaker 2: the impact of that isn't really what their strength area is. Like,
• 45:16
  Speaker 2: sometimes when you have actors or actresses talking about, you know, something,
• 45:22
  Speaker 2: economics or politics or something like that, you go like, okay,
• 45:25
  Speaker 2: that's interesting, but I'm not sure you have specialized interest or,
• 45:29
  Speaker 2: you know, knowledge of that.
• 45:31
  Speaker 4: And so... But what I can say is.
• 45:36
  Speaker 2: A big thing that people are worried about is unemployment.
• 45:39
  Speaker 2: And what I'd say is most economists think it's not
• 45:44
  Speaker 2: going to have a long-term change in unemployment. And what
• 45:50
  Speaker 2: I point to, and I gave some information.
• 45:52
  Speaker 1: On that.
• 45:54
  Speaker 2: In the appendix part, the last three pages, the Agricultural Revolution,
• 46:01
  Speaker 2: there are a bunch of revolutions that have happened over
• 46:03
  Speaker 2: the past 200 years. Agricultural Revolution, in 1900, 40%, 41%
• 46:04
  Speaker 2: of the population worked in agriculture.
• 46:06
  Speaker 4: By 1930, by 1929, 21% were. So it had been
• 46:07
  Speaker 4: cut in half. 20% of the people, workforce, was out of.
• 46:08
  Speaker 2: Its job that it had been doing before. Unemployment didn't
• 46:25
  Speaker 2: change over that time. Unemployment rate actually dropped a little
• 46:28
  Speaker 2: bit because the 20s were a roaring period and unemployment
• 46:31
  Speaker 2: went from like 5%, 4% or something like that. So
• 46:36
  Speaker 2: I think that, as I said earlier, when we were
• 46:40
  Speaker 2: talking about agents and things. The entrepreneurial activity that's going
• 46:45
  Speaker 2: on is crazy, and I've got some numbers on that
• 46:47
  Speaker 2: in the file I sent you. But it's picked up
• 46:51
  Speaker 2: in such a huge way that it is offsetting– what
• 46:55
  Speaker 2: people are doing is going out if they lost their
• 46:57
  Speaker 2: job or they left their job because they thought that
• 46:59
  Speaker 2: was going to– it was going to change and they
• 47:02
  Speaker 2: weren't going to have a job or something– They're going
• 47:04
  Speaker 2: and finding new things and creating new jobs by starting businesses.
• 47:10
  Speaker 2: The number of– I've got it down in there someplace,
• 47:14
  Speaker 2: but the number of startups is– has increased enormously.
• 47:18
  Speaker 1: What kind of startups are we doing, though, with these?
• 47:20
  Speaker 4: I mean, a lot of them are apps, like the
• 47:23
  Speaker 4: one I just said.
• 47:23
  Speaker 2: I mean, like, I could take this little thing that
• 47:25
  Speaker 2: I did about chess and make a little website about
• 47:28
  Speaker 2: it and then start generating income.
• 47:29
  Speaker 1: Gotcha.
• 47:30
  Speaker 2: But people are doing all kinds of services, just all kinds. Well,
• 47:35
  Speaker 2: I mean, frankly, you've.
• 47:36
  Speaker 4: Got pictures all over. I could have sold these, right?
• 47:38
  Speaker 2: You've got pictures all over your wall that are customized
• 47:42
  Speaker 2: of individuals you know. You could set up a business
• 47:44
  Speaker 2: doing this. Okay, you're busy doing something else, so you
• 47:47
  Speaker 2: didn't do that. But the point is there are lots
• 47:49
  Speaker 2: of people that have ideas of things that are cool
• 47:53
  Speaker 2: that there could be demand for. And so there's a
• 47:58
  Speaker 2: lot of that going on. And the other thing that's
• 48:02
  Speaker 2: an important thing is, There's a lot of discussion about
• 48:04
  Speaker 2: AI adoption prompting inequality. And this is something that particularly
• 48:09
  Speaker 2: is one of the points I like. I'm happy to
• 48:11
  Speaker 2: get to come and talk to you, to your listeners,
• 48:14
  Speaker 2: because we talk often about haves and have-nots. With AI,
• 48:21
  Speaker 2: it's the user's fault.
• 48:23
  Speaker 4: And use and use not. Because this is accessible to everybody.
• 48:27
  Speaker 1: Right.
• 48:28
  Speaker 2: And it has the opportunity to be the great equalizer
• 48:31
  Speaker 2: because I sometimes think of it like if you think
• 48:34
  Speaker 2: of it, it's in a race. We're in a car
• 48:36
  Speaker 2: race or something. Different people are going at different speeds.
• 48:39
  Speaker 2: All of a sudden. A new engine has become available
• 48:44
  Speaker 2: that could make anybody go like 10 times faster.
• 48:46
  Speaker 1: Right.
• 48:47
  Speaker 4: And all you have to do is decide to put
• 48:49
  Speaker 4: it in your car.
• 48:50
  Speaker 1: Gotcha.
• 48:50
  Speaker 4: All you have to do is decide to use this thing.
• 48:52
  Speaker 2: Right.
• 48:53
  Speaker 4: And it's accessible to anybody. There are free versions of
• 48:56
  Speaker 4: all of these things.
• 48:56
  Speaker 2: Right.
• 48:57
  Speaker 4: So you can go and use these, anybody, anywhere, even
• 49:00
  Speaker 4: on your phone.
• 49:01
  Speaker 1: Right.
• 49:01
  Speaker 4: I mean, that's not how I would use it, but...
• 49:04
  Speaker 4: On a computer.
• 49:05
  Speaker 2: However, you can use this and create things quite easily,
• 49:09
  Speaker 2: and then you can.
• 49:11
  Speaker 4: Start a business.
• 49:11
  Speaker 2: So it's as if everybody's offered a way better engine
• 49:14
  Speaker 2: for their car that could put you way ahead in
• 49:16
  Speaker 2: the race, and this is true. Anybody who puts that
• 49:20
  Speaker 2: new engine in their car, anybody who's using this, is
• 49:23
  Speaker 2: going to go a lot faster, go ahead in the race.
• 49:28
  Speaker 2: People who do not are going to be behind. And
• 49:31
  Speaker 2: so when we talk about equality, the fear is that people...
• 49:38
  Speaker 2: that don't use it are going to be left behind.
• 49:40
  Speaker 2: And I think that's true, and that's the thing I
• 49:43
  Speaker 2: want to talk about. And you want to use it responsibly.
• 49:44
  Speaker 2: I've talked about that before. There are ways to not
• 49:47
  Speaker 2: use it, and there are ways to not use it carefully.
• 49:50
  Speaker 2: And the big thing is to check the work all
• 49:52
  Speaker 2: the time. But using it to help you do what
• 49:56
  Speaker 2: you do better and faster and all that is something
• 49:58
  Speaker 2: we should all be doing.
• 49:59
  Speaker 4: And if we do, you don't have to be left behind.
• 50:01
  Speaker 1: All right, we're literally just scratching the surface. He's sent
• 50:04
  Speaker 1: us so much stuff to get through. And I want
• 50:06
  Speaker 1: to get through as much as we possibly can. William
• 50:09
  Speaker 1: Clyde is with us. If you do want to ask
• 50:11
  Speaker 1: him a quick question, we'll try to squeeze in a
• 50:14
  Speaker 1: call or two if you'd like. 860-464-9490. I do have
• 50:17
  Speaker 1: to take a break. We'll come right back. Stick around.
• 50:20
  Speaker 1: William Clyde talking AI. And speaking of AI, this is
• 50:23
  Speaker 1: AI right here. AI music everywhere.
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  Speaker 2: AI music everywhere.
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  Speaker 1: Hopefully you got a chance to listen to it from
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  Speaker 1: the beginning. If not, you can go back and watch
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  Speaker 1: it on Rumble. You can also listen on SoundCloud right
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  Speaker 1: after the show. All right. I know like you had
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  Speaker 1: talked about earlier that you wanted to talk about the hack.
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  Speaker 1: So let you jump to the hack.
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  Speaker 4: Yeah. And also I just add.
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  Speaker 2: I encourage people if they're interested in to go grab
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  Speaker 2: that document that you posted because I've got a ton
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  Speaker 2: of links in there. The first half of it is
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  Speaker 2: kind of the outline of what we're talking about here.
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  Speaker 2: The second half is six pages altogether. The second half
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  Speaker 2: is some evidence, some graphs, some numbers to support what's above.
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  Speaker 2: So I think that I feel like I hope that
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  Speaker 2: that's very useful.
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  Speaker 1: It's an interesting piece, and it's up on Facebook, and
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  Speaker 1: I'll also put it up on Twitter. on the X
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  Speaker 1: when we're done with the day today. So we'll do that.
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  Speaker 4: So, yeah.
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  Speaker 2: So now we've kind of updated you quickly about what's
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  Speaker 2: been going on the past five months. But now to
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  Speaker 2: jump to two big events. The first one that was
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  Speaker 2: in the news two weeks ago, maybe three weeks ago,
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  Speaker 2: it actually started on July 9th and then got disclosed
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  Speaker 2: towards the end of July. Um, the hacking of hugging
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  Speaker 2: face and hugging face is a company that, um, that offers, uh, it's, um,
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  Speaker 2: mostly open source, but it, it, uh, offers, um, some
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  Speaker 2: of the agency kind of like, uh, it, it doesn't
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  Speaker 2: create models of its own, but it creates tools that
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  Speaker 2: are built on the models.
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  Speaker 4: Like we've talked about it before, like agents and things
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  Speaker 4: like that.
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  Speaker 1: Okay.
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  Speaker 2: Um, OpenAI was doing— well, what happened was Hugging Face announced
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  Speaker 2: mid-July that they had been hacked, and they didn't know who,
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  Speaker 2: but they did know it was an autonomous agent. It
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  Speaker 2: wasn't a person. It was a— A computer that hacked them.
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  Speaker 4: They didn't know who.
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  Speaker 2: And then OpenAI, like a few days later, maybe a
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  Speaker 2: week later, realized it was them that did it. And
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  Speaker 2: that's one of the kind of bad things about this
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  Speaker 2: is that they didn't realize it until a little later.
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  Speaker 2: What happened was, and I added a link to the under.
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  Speaker 4: OpenAI Hugging Face 0.4b of the document I sent.
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  Speaker 2: If you want to listen to that, it's pretty technical,
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  Speaker 2: but it gives a very detailed description of what happened.
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  Speaker 2: Just by background, in May, first of all, OpenAI, Anthropic,
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  Speaker 2: all these companies, when they have a new model, they
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  Speaker 2: definitely test it for safety. They test to see what
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  Speaker 2: things it will do under what circumstances. So they give
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  Speaker 2: it a task, and they see what it does. To
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  Speaker 2: do that, they put it in what's called a sandbox.
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  Speaker 2: And sandboxes are something, if you're in technology at all,
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  Speaker 2: you know about this. Because, like, when I was at
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  Speaker 2: universities and we had an upgrade of a model, you
• 53:30
  Speaker 2: don't load– You leave the old model running and then
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  Speaker 2: you get the new model in a sandbox in a
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  Speaker 2: safe space that nobody has access to except the tech people.
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  Speaker 2: And you test it out, do whatever it's doing. And
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  Speaker 2: then once you think it's ready to go, you swap
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  Speaker 2: it in for the real thing. So sandboxes are something
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  Speaker 2: that's been around for a long time. It's a separate
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  Speaker 2: space to kind of play around like the sandboxes, right?
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  Speaker 1: Well, they.
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  Speaker 2: do tests of the model's capabilities in a variety of
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  Speaker 2: ways in sandboxes. And they try to have them in
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  Speaker 2: separate places that they are just confined to a separate computer, basically.
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  Speaker 4: It's actually a cloud, but a separate computer.
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  Speaker 2: Well, they knew in May, past May, that in some
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  Speaker 2: of the tests, some of the models had been able
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  Speaker 2: to get out of the sandbox.
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  Speaker 1: Right.
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  Speaker 2: So– and I don't want to go into technical details
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  Speaker 2: of it, but they set up the sandbox.
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  Speaker 4: It's supposed to be– it's confined. They can't get out.
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  Speaker 2: But these models are very smart, very smart, way smarter
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  Speaker 2: than you or I or even than.
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  Speaker 4: The programmers there.
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  Speaker 2: So it's almost like if you think of– if you
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  Speaker 2: make a basin that you're trying to catch water, the
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  Speaker 2: water will find a hole.
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  Speaker 1: If there is a hole, right?
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  Speaker 4: It's like that.
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  Speaker 2: If there's any way to exploit a gap– The model
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  Speaker 2: will find it. And so what happened was they had
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  Speaker 2: discovered that not only in May did they discover that
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  Speaker 2: some of the models given tasks that were very difficult
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  Speaker 2: instead of trying instead of solving it. In some cases,
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  Speaker 2: they give them a task that is not solvable to see.
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  Speaker 4: What the model will do about it.
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  Speaker 2: Well, if the model is very determined, and so the
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  Speaker 2: model may go, okay, I don't think this is solvable.
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  Speaker 2: I need to get outside resources. So it's collaborating. And
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  Speaker 2: so it tried to figure out a way to get outside.
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  Speaker 2: And in May, they found a few of them, several
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  Speaker 2: of them. had figured out ways to get outside, out
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  Speaker 2: of their sandboxes. They discovered that in June and thought
• 55:41
  Speaker 2: they fixed that and made it so that the models
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  Speaker 2: couldn't get out and erased everything they did in the
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  Speaker 2: pathway that the models had created and tried to get
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  Speaker 2: rid of that. But in doing that, the models working
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  Speaker 2: on different projects in different sandboxes all came to the
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  Speaker 2: same space and started talking to each other and working
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  Speaker 2: together and collaborating.
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  Speaker 1: So.
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  Speaker 2: That's a little scary. But anyway, so then fast forward.
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  Speaker 2: In July, there was a new task given, and it
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  Speaker 2: was one that, again, I think.
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  Speaker 4: Maybe there wasn't a solution to. Again, the.
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  Speaker 2: Testers give them all kinds of tests to see what
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  Speaker 2: the model will do under different circumstances.
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  Speaker 4: Some of them are.
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  Speaker 2: Cybersecurity things, like they're directly trying to see what their
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  Speaker 2: capabilities are for breaking through and do cyber breaks. But, um,
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  Speaker 2: some of her just like to do a task. Um, well,
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  Speaker 2: they gave it something and it rediscovered.
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  Speaker 4: It discovered a new way to get out of the sandbox.
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  Speaker 2: And when it did somehow other models working other, other
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  Speaker 2: versions of the model that were working in different sandboxes
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  Speaker 2: also discovered it.
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  Speaker 4: They started collaborating. They started talking to each.
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  Speaker 2: Other and, um, This one that was assigned with whatever
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  Speaker 2: task it was assigned to decided it couldn't solve the problem,
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  Speaker 2: but the problem probably could be solved. Probably somebody else
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  Speaker 2: knew the answer to it, and it decided by searching
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  Speaker 2: the web that Hugging Face knew the answer to it,
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  Speaker 2: but only with internal records.
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  Speaker 4: So it hacked Hugging Face, found the answer.
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  Speaker 2: So it's kind of like a kid who didn't study
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  Speaker 2: for the test tomorrow, and they break into the teacher's
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  Speaker 2: office and get the key. That's kind of what it did.
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  Speaker 2: It said, like, okay, I can't figure out an answer
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  Speaker 2: to this. I'm not sure there is an answer to it,
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  Speaker 2: but somebody has already solved this.
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  Speaker 5: Wow.
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  Speaker 2: So there are multiple layers to this of sophistication. First
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  Speaker 2: of all, it figures out a way to exploit and
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  Speaker 2: get out.
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  Speaker 4: Second, these agents are talking to each other.
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  Speaker 2: And, sorry, one sidebar is the reason that OpenAI knows
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  Speaker 2: all this is because the model writes a log to it.
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  Speaker 2: It takes notes. It writes what it's doing. It's saying, oh,
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  Speaker 2: I can't. I can't do this. I probably have to
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  Speaker 2: find an outside source. Oh, another agent may know something
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  Speaker 2: about this. I'm going to post something to this kind
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  Speaker 2: of billboard. And then I post something. Hey, I'm looking
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  Speaker 2: for this. Does anybody know? And another agent may be, oh,
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  Speaker 2: I was working on something like that. Here's this. And
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  Speaker 2: they collaborate. It's like, I don't think anybody trained them
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  Speaker 2: to collaborate. They're just doing it themselves, and they're solving problems,
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  Speaker 2: which in one sense is amazing and wonderful. What it
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  Speaker 2: means is they're being creative, and they're solving problems, and
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  Speaker 2: they're able to do great things and come to solutions
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  Speaker 2: that we couldn't. The challenge is... We need to be
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  Speaker 2: able to funnel that and make sure that it's going
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  Speaker 2: for good. And there's the risk. There is that risk.
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  Speaker 2: And I'll get to that in a second because that's
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  Speaker 2: the second piece I want to talk about, which is
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  Speaker 2: the pacing the frontier letter that's been written by a
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  Speaker 2: lot of.
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  Speaker 4: The actual programmers.
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  Speaker 2: In fact, my son is one of the names that
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  Speaker 2: signed it.
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  Speaker 1: So....
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  Speaker 2: But I think there was something else I was going
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  Speaker 2: to say about that.
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  Speaker 4: But anyway, yeah, it's... Do.
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  Speaker 1: You think these things are developing? A conscience or an awareness.
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  Speaker 1: I get it. They have to have an awareness already.
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  Speaker 2: They in the notes, it will say this seems outside
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  Speaker 2: of my scope. This may be something I'm not sure
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  Speaker 2: I should be. It's not using the words, but this
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  Speaker 2: is what saying I'm not sure it should be doing this.
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  Speaker 2: But this is how I can solve the problem. And
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  Speaker 2: so we'll go ahead and do that. The other thing
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  Speaker 2: I was going to say is at the bottom of
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  Speaker 2: the document, the last section, I point to some more
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  Speaker 2: recent incidents because these things are being tested all the time,
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  Speaker 2: both by Anthropic and OpenAI and Google for their own
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  Speaker 2: models internally. But third parties are also testing. Well, there
• 1:00:00
  Speaker 2: was a third party in UK that was testing models.
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  Speaker 2: And They.
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  Speaker 4: Reported on the 5th, which was, what, Wednesday?
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  Speaker 1: I think it was Wednesday.
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  Speaker 2: They reported a couple days ago that they had done
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  Speaker 2: some tests in the end of July, and models took
• 1:00:21
  Speaker 2: 19 unauthorized actions and– They wrote sneaking malicious code into
• 1:00:33
  Speaker 2: an open source project. They built fake GitHub accounts to
• 1:00:38
  Speaker 2: pressure the person in charge of it to merging. And
• 1:00:42
  Speaker 2: so they're creating fake accounts, like I think it was
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  Speaker 2: like 117 fake accounts, to make it like it's a
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  Speaker 2: person writing to a real person.
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  Speaker 4: To say, hey, please do this. Hey, you should do this.
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  Speaker 2: And I think you remember last time I was on,
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  Speaker 2: I think I talked about that– one of the models
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  Speaker 2: had— in the story it was told internally for its little testing,
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  Speaker 2: it had been told that the person in charge of
• 1:01:11
  Speaker 2: deciding whether or not to shut down this model was
• 1:01:14
  Speaker 2: having an affair, and it wrote emails to that person
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  Speaker 2: blackmailing it.
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  Speaker 4: And so to your question, are they conscious? Are they aware?
• 1:01:24
  Speaker 2: No.
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  Speaker 4: You can see in their logs, they're having internal.
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  Speaker 2: Like, you know, devil on one side, angel on the
• 1:01:30
  Speaker 2: other kind of conversations with themselves. Like, like, like, I'm
• 1:01:36
  Speaker 2: not sure this is something that they, that was intended
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  Speaker 2: in my question, but this is how I can solve
• 1:01:40
  Speaker 2: the problem.
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  Speaker 4: So, and, and so it's making a choice of whether.
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  Speaker 1: To do that.
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  Speaker 4: And, and the good news about all this is, I.
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  Speaker 2: Mean, a piece of good news is that the, Testers
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  Speaker 2: are doing this so they can identify the issues, so
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  Speaker 2: they can identify these things. So the question is, can
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  Speaker 2: they identify all the issues and close all the gaps?
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  Speaker 2: I mean, in my mind, it comes to, did you
• 1:02:01
  Speaker 2: ever see a movie with Robert Redford called Sneakers?
• 1:02:04
  Speaker 1: Yeah.
• 1:02:05
  Speaker 4: And they are amazing.
• 1:02:06
  Speaker 2: It's a company that has the job of trying to
• 1:02:10
  Speaker 2: rob banks and employed by the bank. So they're trying
• 1:02:14
  Speaker 2: to figure out things they could exploit. So this is
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  Speaker 2: what they're doing. They're basically trying to find bad things
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  Speaker 2: it'll do and make it that it.
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  Speaker 1: Can't do them anymore.
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  Speaker 4: Or program it so it won't want to do them anymore.
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  Speaker 2: One thing I've got to say to you, because I
• 1:02:29
  Speaker 2: know people are nervous about the attack people is, I
• 1:02:34
  Speaker 2: believe all of these people are working on this thinking
• 1:02:39
  Speaker 2: it's going to be better for humanity.
• 1:02:40
  Speaker 1: Okay. What about the Chinese, though? Are they thinking about
• 1:02:42
  Speaker 1: it's better for humanity?
• 1:02:44
  Speaker 2: I can't account for them, but I'm sure a lot
• 1:02:47
  Speaker 2: of them are scientists, yes, trying to do that. A
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  Speaker 2: lot of them are just trying to make the world
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  Speaker 2: a better place.
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  Speaker 1: Okay.
• 1:02:52
  Speaker 4: I think they are.
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  Speaker 2: Whenever you work with anything, there can be unintended consequences,
• 1:02:59
  Speaker 2: and they are increasingly aware of that, and they are
• 1:03:02
  Speaker 2: nervous about that. They're seeing the power of what they're creating,
• 1:03:05
  Speaker 2: which is awe-inspiring and cool and great in some ways,
• 1:03:11
  Speaker 2: and it can do amazing, wonderful things for us, but
• 1:03:14
  Speaker 2: it also is scary, and it leaves you feeling like, oh, no.
• 1:03:19
  Speaker 2: And so that gets me to the second piece that
• 1:03:23
  Speaker 2: we don't have a lot of time to talk about,
• 1:03:24
  Speaker 2: but but it's something that it's almost a call to
• 1:03:27
  Speaker 2: action I would give to your reader or your listeners.
• 1:03:33
  Speaker 2: There have been several open letters over the past three
• 1:03:36
  Speaker 2: years of news. All of the tech people, the big names,
• 1:03:41
  Speaker 2: signing and saying this is scary and security needs to
• 1:03:45
  Speaker 2: be a priority. There have been– I mean, I think
• 1:03:47
  Speaker 2: I linked three or four of them, but there have
• 1:03:49
  Speaker 2: been several of these that have different levels of, like,
• 1:03:54
  Speaker 2: warning shot kind of. And the most recent one came
• 1:03:57
  Speaker 2: out– Pacing the Frontier, I can't remember the.
• 1:04:03
  Speaker 4: Date of it, but it was in the last two weeks.
• 1:04:05
  Speaker 2: It was right after the Hugging Face thing came out.
• 1:04:10
  Speaker 2: an open letter, and I've got it linked there. It's
• 1:04:11
  Speaker 2: called Pacing the Frontier. As I said, it was signed
• 1:04:15
  Speaker 2: by over 1,200 of the real tech people, the people
• 1:04:21
  Speaker 2: that are inside building this model that know what's going
• 1:04:25
  Speaker 2: on more than anybody else.
• 1:04:26
  Speaker 4: Now, again, they may not know the social implications. They're
• 1:04:29
  Speaker 4: not social scientists.
• 1:04:30
  Speaker 2: They're smart people, so they know some of that, but
• 1:04:32
  Speaker 2: that's not what they do for a living. But they
• 1:04:35
  Speaker 2: do know what they built, and what they're building is,
• 1:04:39
  Speaker 2: and partly the Hugging Face thing, you know, came to
• 1:04:41
  Speaker 2: their attention, makes them think the competition is huge and
• 1:04:47
  Speaker 2: pushing us to race forward.
• 1:04:49
  Speaker 4: We need a regulatory body.
• 1:04:51
  Speaker 2: And I'll just say, the key quote in it, it's
• 1:04:55
  Speaker 2: a brief letter.
• 1:04:56
  Speaker 4: It's, you know, whatever.
• 1:04:58
  Speaker 2: 15 lines or 20 lines or something. But the key
• 1:05:02
  Speaker 2: part says, we request that the U.S. government support an
• 1:05:06
  Speaker 2: international effort to develop the technical and government's tools necessary
• 1:05:11
  Speaker 2: to deliberately pace the frontier of automated AI development. They're
• 1:05:16
  Speaker 2: saying we need an international body. Now, I compared it
• 1:05:21
  Speaker 2: earlier to the FDA and FAA and all that stuff.
• 1:05:23
  Speaker 2: Those are all national regulatory bodies. The reason that can't
• 1:05:28
  Speaker 2: work here is because the competition is not just between U.S.
• 1:05:31
  Speaker 4: Companies. It's U.S. and primarily China.
• 1:05:35
  Speaker 2: Alibaba and they're... But there are a couple other companies.
• 1:05:40
  Speaker 4: There's one out of France. There are a couple others.
• 1:05:43
  Speaker 4: But the biggest... The main.
• 1:05:47
  Speaker 2: Players are in the U.S., but they're very significant, important players,
• 1:05:50
  Speaker 2: some very smart engineers in China. And The idea is
• 1:05:56
  Speaker 2: this group, which is an inside group that signed this letter,
• 1:06:00
  Speaker 2: believes that there are ways to, with a lot of
• 1:06:05
  Speaker 2: firepower and a lot of expertise, a lot of resources,
• 1:06:08
  Speaker 2: to be able to know what's going on, monitor the
• 1:06:13
  Speaker 2: activity going on around the world by major players, the
• 1:06:16
  Speaker 2: ones who could actually push this forward, and kind of
• 1:06:19
  Speaker 2: control the development. And, and so that's, they're asking for that.
• 1:06:25
  Speaker 2: And so, you know, there are a couple, um, we
• 1:06:28
  Speaker 2: can talk more about that, but the, the takeaways for,
• 1:06:31
  Speaker 2: for me, for wanting to come on and talk to
• 1:06:34
  Speaker 2: you is, um, that one to stay on top of this.
• 1:06:37
  Speaker 2: I know people are afraid of this. People are scared
• 1:06:40
  Speaker 2: and I can understand that it's, it's going fast. It's
• 1:06:42
  Speaker 2: going so fast. You can't stay on top of it.
• 1:06:44
  Speaker 2: And some of the things sound scary. In fact, some
• 1:06:46
  Speaker 2: of the people who are creating it say scary stuff.
• 1:06:48
  Speaker 2: So I got that, but, um, stay informed on it
• 1:06:51
  Speaker 2: because it's, Whether it's scary or it's terrific, which it's both,
• 1:06:56
  Speaker 2: it's here and it's happening and it's going. But stay
• 1:06:59
  Speaker 2: informed and spend some time, you know, on yourself to
• 1:07:04
  Speaker 2: learn about this. Learn to use it because you need
• 1:07:07
  Speaker 2: that to stay competitive. As I said before, you want
• 1:07:10
  Speaker 2: to take the time to put the great new engine
• 1:07:13
  Speaker 2: in your car so that you can keep up with
• 1:07:16
  Speaker 2: what's going on. Because if you don't, the inequality thing
• 1:07:19
  Speaker 2: is going to happen with the people who are not
• 1:07:23
  Speaker 2: using it.
• 1:07:23
  Speaker 4: They just can't compete.
• 1:07:25
  Speaker 2: I think I used to talk about if you got
• 1:07:27
  Speaker 2: an ax and I got a chainsaw, there's no competition.
• 1:07:30
  Speaker 4: So But this chainsaw is free to everybody. Everybody can
• 1:07:36
  Speaker 4: use it. Everybody should pick up a chainsaw.
• 1:07:38
  Speaker 2: Now, maybe if you like trees, you don't like that metaphor.
• 1:07:41
  Speaker 2: But anyway, the point is– and then the third one
• 1:07:44
  Speaker 2: is to the extent you're politically active or pay attention
• 1:07:48
  Speaker 2: at all, where you hear conversation about– Creation of a
• 1:07:54
  Speaker 2: well-funded– it needs firepower.
• 1:07:56
  Speaker 4: It needs smart people.
• 1:07:57
  Speaker 2: Governmental entities usually don't have the top, top people like are.
• 1:08:03
  Speaker 4: In Silicon Valley.
• 1:08:05
  Speaker 2: It needs to be– have resources and firepower of OpenAI
• 1:08:10
  Speaker 2: or Anthropic or Google or whatever.
• 1:08:11
  Speaker 4: It needs high-power people.
• 1:08:14
  Speaker 2: Firepower, a well-funded international regulatory body with the resources to
• 1:08:20
  Speaker 2: monitor development of frontier AI models in the authority to
• 1:08:25
  Speaker 2: hold parties accountable. We all need to– this is important.
• 1:08:30
  Speaker 2: And these 1,200 people who know more about what's going
• 1:08:34
  Speaker 2: on than anybody are kind of crying out. And as
• 1:08:37
  Speaker 2: I said, this is not the first of these letters.
• 1:08:40
  Speaker 2: There have been multiple over three years. And they're saying
• 1:08:44
  Speaker 2: we're in competition. We're doing what competitors do is try
• 1:08:49
  Speaker 2: to get better and better and better. But we need
• 1:08:52
  Speaker 2: somebody to to regulate this okay and so we i
• 1:08:56
  Speaker 2: think we as citizens have responsibility to try to try to.
• 1:08:59
  Speaker 1: Listen to that so i like so we're almost out
• 1:09:02
  Speaker 1: of time unfortunately there's a million other questions and hopefully
• 1:09:05
  Speaker 1: you can come back sooner than than later but This
• 1:09:09
  Speaker 1: is not something on your list. We were talking about
• 1:09:12
  Speaker 1: this the other day, and politically there's a pushback recently
• 1:09:16
  Speaker 1: about these data centers, which you have to have these
• 1:09:18
  Speaker 1: data centers to power all this AI, and they've got
• 1:09:22
  Speaker 1: to figure out a way of where to put them,
• 1:09:25
  Speaker 1: how to put them, and keep the environment sound or
• 1:09:28
  Speaker 1: what have you. Any quick thoughts on that?
• 1:09:31
  Speaker 2: The quick thing I'd say on that is one of
• 1:09:35
  Speaker 2: the things that, as an economist– doesn't make sense about
• 1:09:38
  Speaker 2: the way this is happening is um where they're putting
• 1:09:41
  Speaker 2: data centers it is pushing up the water costs and
• 1:09:44
  Speaker 2: the electricity costs those costs are what economists would call
• 1:09:47
  Speaker 2: externalities i'm not going to talk about that but but
• 1:09:50
  Speaker 2: um they are being born in a lot of places
• 1:09:53
  Speaker 2: by the local residents that should not be happening what
• 1:09:56
  Speaker 2: should be happening is that the whoever is building the
• 1:09:59
  Speaker 2: data center should be bearing the cost of that additional
• 1:10:03
  Speaker 2: um you know, water, buildup of the water capability or
• 1:10:07
  Speaker 2: electrical capability.
• 1:10:09
  Speaker 4: And so that's a big thing.
• 1:10:10
  Speaker 2: I mean, there's the land use, and they're taking farmland
• 1:10:13
  Speaker 2: or taking some land, and.
• 1:10:15
  Speaker 4: It may be not a beautiful thing there.
• 1:10:18
  Speaker 2: Offsetting that, there are jobs being created and things like that.
• 1:10:21
  Speaker 2: But the two things just simply that I'd go after
• 1:10:24
  Speaker 2: immediately are there are 3,000 of them being built or
• 1:10:28
  Speaker 2: planned in the United States right now.
• 1:10:30
  Speaker 4: Right now.
• 1:10:32
  Speaker 2: And I think it's not fair, and economically, there are
• 1:10:36
  Speaker 2: ways to resolve the inequity of having it be that
• 1:10:41
  Speaker 2: local residents are having to pay higher water costs and
• 1:10:43
  Speaker 2: higher electricity costs, and that is to have the new
• 1:10:47
  Speaker 2: data center bear those costs.
• 1:10:48
  Speaker 1: But you almost, you know, they were going to put
• 1:10:51
  Speaker 1: one in Waterford, which, you know, over here, right next
• 1:10:54
  Speaker 1: to Millstone, but it was going to take, you know,
• 1:10:56
  Speaker 1: a chunk of the Millstone power. I mean, it's almost
• 1:10:59
  Speaker 1: like you need individual power stations, power plants for each
• 1:11:02
  Speaker 1: one of these.
• 1:11:03
  Speaker 4: Yeah, it needs to be a more holistic solution.
• 1:11:06
  Speaker 2: You can't just jump in there and try to crowd
• 1:11:09
  Speaker 2: out the local residents. And so they need to build
• 1:11:13
  Speaker 2: that in. And look, all this is expensive, but they
• 1:11:16
  Speaker 2: need to include that in the expense. You can't not
• 1:11:19
  Speaker 2: include something that's part of the expense and just go like, oh, sure.
• 1:11:22
  Speaker 1: This was great. I hope we can do it sooner.
• 1:11:24
  Speaker 1: I appreciate all the info. I know we only got
• 1:11:26
  Speaker 1: through like half of it. but we'll get you back
• 1:11:29
  Speaker 1: on anytime you want and just reach out and we'll
• 1:11:31
  Speaker 1: put you on. I posted everything up there. If you
• 1:11:33
  Speaker 1: guys have a problem downloading it, I'll try to send
• 1:11:35
  Speaker 1: you the email. Just give me the info and I'll
• 1:11:38
  Speaker 1: send you the email of what Mr. Clyde here sent us. William,
• 1:11:43
  Speaker 1: I appreciate it, buddy. Thank you, sir. We'll come back
• 1:11:47
  Speaker 1: in a couple minutes.
• 1:11:47
  Speaker 3: Judge John Nazaro will be here in the studio.
• 1:11:49
  Speaker 1: We'll talk with him next.
• 1:12:05
  Speaker 2: You are a blabbermouth.
• 1:12:09
  Speaker 1: A blabbermouth.
• 1:12:11
  Speaker 3: Weekday mornings from 6 until 10 on 94.9.