Latest / Financial Survival Network / The Crime-Fighting Sidekick: How AI is Strengthening the Justice System - Terence Mills #6132

Transcript

The Crime-Fighting Sidekick: How AI is Strengthening the Justice System - Terence Mills #6132 · Financial Survival Network

• 0:00
  Speaker 1: And we find that it's happening a lot today. We're
• 0:03
  Speaker 1: stopping people from going through the airport in the street
• 0:07
  Speaker 1: in the UK, we're identifying people before they commit the crime.
• 0:13
  Speaker 1: And while it might be an interesting debate about personal privacy,
• 0:19
  Speaker 1: is the debate really one that we want to be
• 0:21
  Speaker 1: having when we're in an airplane and we're wondering is
• 0:25
  Speaker 1: there someone who's going to do something bad on that plane?
• 0:29
  Speaker 2: You're listening to Carrie Let'sa's Financial Survival Network where you
• 0:32
  Speaker 2: get valuable information you just can't find anywhere else to
• 0:37
  Speaker 2: thrive in today's trying times. You need the Financial Survival
• 0:41
  Speaker 2: Network now more than ever. Go to Financial Survivalnetwork dot
• 0:45
  Speaker 2: com and get your free newsletter and gift. Financial Survival
• 0:50
  Speaker 2: Network now more than ever.
• 0:56
  Speaker 3: And welcome you are listening to and watching the Financial
• 1:00
  Speaker 3: Survival Network. I'm your host, Kerrie Let's Well. AI is
• 1:04
  Speaker 3: all the buzz? Is it all it's cranked up to be?
• 1:07
  Speaker 3: Can you actually profit from it now? Or do you
• 1:10
  Speaker 3: have to wait for this golden era of AI technology
• 1:14
  Speaker 3: to permeate everything? How big a deal is it? AI
• 1:18
  Speaker 3: Expert is on with us now, Terrence Mills, Terence, Hey,
• 1:23
  Speaker 3: you're the guy, CEO and innovator of AI solutions. So
• 1:28
  Speaker 3: let's talk some solutions here. A is a real threat
• 1:34
  Speaker 3: to the workforce of humanity. Here we're all going to
• 1:38
  Speaker 3: be sitting around getting our guaranteed basic income and assuming
• 1:43
  Speaker 3: the answer is no that, how can I use it
• 1:46
  Speaker 3: now in my existing business to better improve my productivity
• 1:51
  Speaker 3: and my work product Yeah. AI is not going to
• 1:54
  Speaker 3: take over the world. Robots are not going to step
• 1:57
  Speaker 3: in and take our jobs. This is not what AI
• 2:02
  Speaker 3: is about. AI today also can't understand very much other
• 2:07
  Speaker 3: than what we teach it. So based on what we know,
• 2:13
  Speaker 3: AI will know and in business today, we really build
• 2:17
  Speaker 3: AI for the purposes of solutions solving problems that are
• 2:23
  Speaker 3: real business problems that maybe humans don't do very well.
• 2:27
  Speaker 3: So Carrie, you and I can have these types of conversations,
• 2:30
  Speaker 3: really well intimate discussions.
• 2:32
  Speaker 1: Machines can't. On the other hand, us as humans don't
• 2:37
  Speaker 1: have the ability to go ahead and pull stuff out
• 2:40
  Speaker 1: of a database at random, We don't have the ability
• 2:45
  Speaker 1: to term things that can just happen in a split second.
• 2:50
  Speaker 1: Machines can make those decisions, and they can do those
• 2:54
  Speaker 1: things better than humans. So if we're solving a business problem.
• 2:58
  Speaker 1: The answer is, yes, we have a lot of work
• 3:01
  Speaker 1: yet to do. But makes sense.
• 3:03
  Speaker 3: Okay, so it's an aid, But if you listen to
• 3:08
  Speaker 3: Elon Musk, it really sounds like this thing is going
• 3:14
  Speaker 3: to basically take over Maybe not so much like, but
• 3:20
  Speaker 3: I don't know. I'm sure you saw that demo of
• 3:25
  Speaker 3: the robot handing the guy an apple, putting the dishes,
• 3:30
  Speaker 3: the dirty dishes in the sink, and all that stuff.
• 3:34
  Speaker 3: It seemed pretty real.
• 3:36
  Speaker 1: Oh, it's real, all right. But as I said before,
• 3:40
  Speaker 1: the robot can only do what we teach it to do.
• 3:43
  Speaker 1: And do we think that it's going to take over
• 3:45
  Speaker 1: the world. I don't think so. At this time. We
• 3:48
  Speaker 1: have a lot of work to do before AI can
• 3:52
  Speaker 1: think on its own, before robot can think to put
• 3:56
  Speaker 1: the dishes away, or to clean the dishes or hand
• 3:59
  Speaker 1: me apple if I don't tell it to do that. AI, though,
• 4:03
  Speaker 1: on the other hand, does have some threats that are valid.
• 4:08
  Speaker 1: So in the UK we're very concerned about AI taking
• 4:12
  Speaker 1: pictures of general public, both when they enter the airport
• 4:17
  Speaker 1: also when they're walking down the street, and there's a
• 4:20
  Speaker 1: lot of debate about that as well. So based on
• 4:24
  Speaker 1: the current state of AI and where we have to go.
• 4:28
  Speaker 1: We have a lot of work to do. But ethical AI,
• 4:31
  Speaker 1: which is what I think that everyone's talking about now,
• 4:35
  Speaker 1: is really very important to us.
• 4:38
  Speaker 3: Okay, so where do you think AI holds the most promise?
• 4:42
  Speaker 1: I think AI holds the most promise in solving business
• 4:46
  Speaker 1: problems that humans can't solve. Today. We do it a
• 4:49
  Speaker 1: lot in healthcare. As an example, we're bringing doctors and
• 4:54
  Speaker 1: patients closer together by using AI to pull out the
• 4:59
  Speaker 1: risks that are in health insurance claims so that we
• 5:03
  Speaker 1: can pay person providers so that they can focus on patients.
• 5:09
  Speaker 1: And that is solving a really big business problem.
• 5:13
  Speaker 3: Okay, what about the concept of like having one pilot
• 5:18
  Speaker 3: cockpits because AI is going to handle all the other stuff.
• 5:21
  Speaker 3: It doesn't sound like a real good thing to me,
• 5:24
  Speaker 3: but in Europe they're actually going ahead to experiment with it.
• 5:28
  Speaker 1: Well, we have the same thing in self driving cars
• 5:31
  Speaker 1: and in that debate, and in that debate we wound
• 5:34
  Speaker 1: up to find that if cars can drive better than humans,
• 5:39
  Speaker 1: is it a bad plan? I agree with what you're saying.
• 5:43
  Speaker 1: Do you want to be in the sky? Well, this
• 5:47
  Speaker 1: is something that we think about, but it's very possible
• 5:51
  Speaker 1: that AI can fly a plane better than a human.
• 5:54
  Speaker 1: I think the question mark is, though, what happens when
• 5:58
  Speaker 1: something goes wrong, either in a car or in a plane.
• 6:02
  Speaker 1: These are stark contrasts to humans and their ability to react.
• 6:07
  Speaker 1: We remember when Sully landed the plane on the Hudson,
• 6:12
  Speaker 1: and the big thing there was, Yeah, well, you can't
• 6:17
  Speaker 1: debate what I did because I'm a human. I'm not
• 6:20
  Speaker 1: a machine, and as a human we react to certain situations.
• 6:25
  Speaker 1: As a machine, it doesn't react, it does what it's
• 6:29
  Speaker 1: told to do. And this is the stark contrast. That's interesting.
• 6:33
  Speaker 3: Yeah, well, if only all my employees did what they
• 6:36
  Speaker 3: were told to do, the world would be a wonderful place, right.
• 6:40
  Speaker 1: I think that's right.
• 6:42
  Speaker 3: So, but things like when you're dealing with you mentioned
• 6:47
  Speaker 3: airport security. All right, so the AI you can basically
• 6:52
  Speaker 3: go through every passenger's information, everything that's ever been done
• 6:57
  Speaker 3: about them, and figure out whether they're a threat or not.
• 7:00
  Speaker 3: Maybe we could do away with these ridiculous security theater
• 7:04
  Speaker 3: and all these airports. I think that that's right. I
• 7:06
  Speaker 3: think it's on its way there.
• 7:08
  Speaker 1: I mean today when I walk into La Guardia Airport
• 7:12
  Speaker 1: and I have to go to a gate. It's taking
• 7:14
  Speaker 1: my photograph. I have to stand in front of a camera.
• 7:17
  Speaker 1: I have to have a retinal scan, and here I
• 7:20
  Speaker 1: am yes on Terence Mills. Right, you can go through.
• 7:24
  Speaker 1: We're definitely moving in the right direction and we can
• 7:27
  Speaker 1: get a lot of bad actors out of the playing field,
• 7:30
  Speaker 1: so to speak. If we're using this technology for good.
• 7:34
  Speaker 1: I think the difference in the argument is can we
• 7:37
  Speaker 1: use it for good all good? Or is there places
• 7:41
  Speaker 1: where bad actors can come into play and use it
• 7:44
  Speaker 1: for bad things as well. That's still a current debate
• 7:47
  Speaker 1: that we're having. All right, So what about pre crime?
• 7:50
  Speaker 3: All right, we have enough data on criminals and crimes
• 7:55
  Speaker 3: that basically, you know, it's getting to the Tom Cruise
• 8:00
  Speaker 3: movie Minority Report, but with a difference that it can
• 8:04
  Speaker 3: accurately in many cases most of them predict who's at
• 8:08
  Speaker 3: risk of committing crimes.
• 8:09
  Speaker 1: It'll be solving crimes. So too well, it ends absolutely
• 8:14
  Speaker 1: without a doubt, and we find that it's happening a
• 8:18
  Speaker 1: lot today. We're stopping people from going through the airport
• 8:22
  Speaker 1: in the street in the UK, we're identifying people before
• 8:26
  Speaker 1: they commit the crime. And while it might be an
• 8:30
  Speaker 1: interesting debate about personal privacy. Is the debate really one
• 8:36
  Speaker 1: that we want to be having when we're in an
• 8:38
  Speaker 1: airplane and we're wondering, is there someone who's going to
• 8:42
  Speaker 1: do something bad on that plane? If we can stop
• 8:45
  Speaker 1: these things, that's the other side of the argument, and
• 8:48
  Speaker 1: it's a good argument to be having. It's an interesting
• 8:52
  Speaker 1: place to be right now.
• 8:54
  Speaker 3: Yeah. I mean really, even before AI came into focus,
• 9:00
  Speaker 3: they were working on this in Chicago and a few
• 9:02
  Speaker 3: other cities where feeding they were like solving serial killer
• 9:08
  Speaker 3: cases with big data. I mean, AI is just big
• 9:12
  Speaker 3: data on steroids pretty much. Right.
• 9:15
  Speaker 1: It is big data, but there are other tools of
• 9:17
  Speaker 1: that data that need to be put into motion in
• 9:21
  Speaker 1: order to work. We have these big terms like machine
• 9:26
  Speaker 1: learning and natural language processing. I fear that no one
• 9:31
  Speaker 1: really yet understands all of this stuff, and the common
• 9:34
  Speaker 1: person walking the street has no idea what I just said.
• 9:38
  Speaker 1: I think it's important to recognize that tools of AI
• 9:44
  Speaker 1: need to come together to build a solution in an
• 9:48
  Speaker 1: interesting way, to solve a problem. When you're talking about
• 9:52
  Speaker 1: solving crimes, you're solving a problem. When we're talking about healthcare,
• 9:57
  Speaker 1: we're identifying business problems that maybe a one trillion dollar spend.
• 10:02
  Speaker 1: These are big, big items. Whether it's on the personal
• 10:06
  Speaker 1: side or whether it's on the healthcare side or any
• 10:09
  Speaker 1: other business that may be regulatory in nature, this is
• 10:13
  Speaker 1: a big deal.
• 10:15
  Speaker 3: So I tried to get to chat EPT to analyze
• 10:19
  Speaker 3: the twenty twenty five US budget and cut out twenty
• 10:24
  Speaker 3: five percent, and they just wouldn't do it. I mean,
• 10:28
  Speaker 3: maybe I'm not right in the right query, but it
• 10:30
  Speaker 3: gives me some nonsense here, a gobbledegook that you know,
• 10:35
  Speaker 3: it never really did the analysis on its own, you know,
• 10:39
  Speaker 3: tells me is we need to raise taxes from twenty
• 10:43
  Speaker 3: one to twenty eight percent for the corporate alternative minimum
• 10:48
  Speaker 3: income tax. We need to tax the rich more with
• 10:52
  Speaker 3: a twenty five percent minimum tax on wealth for individuals.
• 10:57
  Speaker 3: And that this isn't this is like raising the this
• 11:03
  Speaker 3: is this is not lowering the water. This is raising
• 11:07
  Speaker 3: the bridge here and then additional taxes, medicare taxes, and
• 11:11
  Speaker 3: net investment income. And then it found that it could
• 11:16
  Speaker 3: save nine hundred and twenty one billion by reducing discretionary
• 11:22
  Speaker 3: spending growth. This thing is talking here like terrence, like
• 11:25
  Speaker 3: a politician.
• 11:27
  Speaker 1: Yes, well, JATGBT while is a really innovative tool and
• 11:33
  Speaker 1: leap forward. It has also gotten a lot of recognition
• 11:38
  Speaker 1: from the common person walking down the street, hasn't it?
• 11:42
  Speaker 1: And we understand that it has some capabilities, that those
• 11:48
  Speaker 1: capabilities are more technical in nature, and its ability to
• 11:51
  Speaker 1: learn data and to understand it, which is interesting. It's
• 11:56
  Speaker 1: equal abilities to do what we call hallucinate. Another big
• 12:00
  Speaker 1: word that people don't really understand is to say things
• 12:05
  Speaker 1: that aren't true but yet presented as fact. That's what
• 12:09
  Speaker 1: you just read to me, and that kids, my tasn't
• 12:12
  Speaker 1: always doing. It's very similar to that. That's right.
• 12:18
  Speaker 3: Yeah, So I'm gonna I guess I didn't do a
• 12:20
  Speaker 3: good enough query. So I'm telling it now to eliminate
• 12:23
  Speaker 3: all tax increases, focus on spending cuts only, and especially
• 12:29
  Speaker 3: corporate welfare. Let's see what it comes up with now.
• 12:34
  Speaker 3: But you know, like you say, it's garbage in, garbage out.
• 12:37
  Speaker 1: It can only it's always read to be that it.
• 12:39
  Speaker 3: Can only find a trillion dollars here, man, I could
• 12:41
  Speaker 3: do better than this, and it's only we could say
• 12:45
  Speaker 3: two to three hundred billion on healthcare. I mean it's
• 12:50
  Speaker 3: nonsense here, right, It's really nonsense. So yes, it really
• 12:55
  Speaker 3: solve the generational problems that we're facing. We still need
• 12:59
  Speaker 3: human put for that, right absolutely, And that's what I
• 13:03
  Speaker 3: was meaning.
• 13:04
  Speaker 1: We can have these discussions a lot easier than others
• 13:09
  Speaker 1: than a machine can, and so we should keep having
• 13:13
  Speaker 1: these discussions. Hey, what's the best use you've found for
• 13:17
  Speaker 1: AI so far? Hey, for us, it has been healthcare.
• 13:21
  Speaker 1: Healthcare is sixteen to eighteen percent of GDP, whose ever
• 13:26
  Speaker 1: numbers you believe on a Monday, And based on that,
• 13:30
  Speaker 1: we have an understanding that there are a lot of
• 13:32
  Speaker 1: problems in our healthcare system and the ability to solve
• 13:36
  Speaker 1: those problems. Machines can do it extraordinarily well, but it
• 13:40
  Speaker 1: is not at the risk of weeding out people's jobs
• 13:46
  Speaker 1: in healthcare. We need more doctors, we need more nurses.
• 13:50
  Speaker 1: It is not going to overtake this industry. But it's very,
• 13:54
  Speaker 1: very important to understand that it can solve some problems,
• 13:59
  Speaker 1: to live interesting data and help replake decisions. And that's
• 14:04
  Speaker 1: what we seek to do while driving down costs, which
• 14:08
  Speaker 1: is a big part. At the chat. GPT may not
• 14:10
  Speaker 1: be able to tell you where that is.
• 14:12
  Speaker 3: Well, it gave me some programs to cut here now
• 14:15
  Speaker 3: that I said specific instances, it wants to cut out
• 14:19
  Speaker 3: the F thirty five Joint Strike Fighter program. That'll take
• 14:23
  Speaker 3: two hundred billion overseas military bases procurement reform, so we
• 14:29
  Speaker 3: save five hundred to six hundred billion right there. I mean, man,
• 14:33
  Speaker 3: if we could just get rid of the politicians and
• 14:36
  Speaker 3: let the AI go to work, we could actually accomplish something.
• 14:40
  Speaker 1: They may be concerned about that, and that might be
• 14:42
  Speaker 1: part of the problem.
• 14:44
  Speaker 3: I mean, that's what we got to do here. We
• 14:45
  Speaker 3: got to get rid of our ruling class and just
• 14:49
  Speaker 3: get AI in there. Because there is zero intelligence in Washington, DC.
• 14:54
  Speaker 3: It's actually negative I think. I mean Corfrid welfare. They're
• 14:57
  Speaker 3: talking four hundred billion agricultural subsidies XM bank. I mean,
• 15:04
  Speaker 3: it's it's insane here, and we barely scratch the surface.
• 15:08
  Speaker 1: Man.
• 15:08
  Speaker 3: I think with a few more queries I could get
• 15:11
  Speaker 3: us into surplus territory here. And it reminds me of
• 15:14
  Speaker 3: that movie Dave where he sat down and did basic
• 15:18
  Speaker 3: math on a pad and man did managed to come
• 15:21
  Speaker 3: up with one point five trillion, and stats like chat
• 15:24
  Speaker 3: GPT can do it a little bit quicker. Remember the
• 15:27
  Speaker 3: Grace Commission, Oh sure, they were only back then the
• 15:31
  Speaker 3: deficit was nothing and they were looking at two hundred
• 15:33
  Speaker 3: and fifty billion a year, which none of it ever
• 15:36
  Speaker 3: got implemented because that's not the way Washington, DC works.
• 15:40
  Speaker 3: But now the genie is out of the bottle. Me
• 15:43
  Speaker 3: sitting at my desktop and do a better job managing
• 15:46
  Speaker 3: the economy than the people who are, like, you know,
• 15:50
  Speaker 3: responsible for it.
• 15:51
  Speaker 2: Right.
• 15:52
  Speaker 1: Yeah, I think CHATCHPT doesn't collect a paycheck and CHATCHPT
• 15:57
  Speaker 1: doesn't have other interests, and so there you go.
• 16:01
  Speaker 3: Yeah, well, you know, I think the what was it
• 16:06
  Speaker 3: they said, Samuel Colt made all men equal? Lenny created
• 16:11
  Speaker 3: the revolver, right, the forty five calibery revolver, the forty
• 16:15
  Speaker 3: five And maybe chat GPT will make everybody's IQ the
• 16:21
  Speaker 3: same now, either for the better or for the worse.
• 16:24
  Speaker 1: Here, Terrence, that one may be for the worst, but
• 16:28
  Speaker 1: we'll see what happens.
• 16:29
  Speaker 3: Hey. Three things that everybody who is listening to or
• 16:34
  Speaker 3: watching this show can do with AI right now to
• 16:37
  Speaker 3: make their lives better.
• 16:39
  Speaker 1: Yeah, that's an important one. If we want to use
• 16:43
  Speaker 1: AI in order to lower our own expenditures in the household,
• 16:48
  Speaker 1: we can do that. We may have to give interesting
• 16:51
  Speaker 1: queries to chat GPT as an example, but we can
• 16:55
  Speaker 1: lower the amount of expanse on food items. We can
• 16:58
  Speaker 1: lower the amount of events on fuel just by going
• 17:02
  Speaker 1: and trending, which it's capable of doing, of where the
• 17:05
  Speaker 1: lowest costs are. Now, I'm not too sure that humans
• 17:09
  Speaker 1: will drive an extra fifteen miles to get a lower
• 17:12
  Speaker 1: gas rate. However, chat GBT, unfortunately that's the case. So
• 17:20
  Speaker 1: I think that what's really happening, though, is chat GBT
• 17:24
  Speaker 1: is always around us. Not just that, but AI is
• 17:29
  Speaker 1: around us in general doing things that we didn't know
• 17:33
  Speaker 1: it was doing. So when we're using our phone today,
• 17:37
  Speaker 1: Siri or any version of Siri is out there queerying
• 17:43
  Speaker 1: the data of the world in order to give us
• 17:46
  Speaker 1: an answer to a common question. And sometimes the questions
• 17:51
  Speaker 1: can be complex and the answer is more complex, but
• 17:55
  Speaker 1: it's still giving us information today that we never thought
• 17:58
  Speaker 1: we could put our hands on, and so for that,
• 18:02
  Speaker 1: we use it daily and it's always around us all
• 18:06
  Speaker 1: the time. So in a lot of cases we like that.
• 18:10
  Speaker 1: In some cases we don't want advertisements right away for
• 18:14
  Speaker 1: goods that we looked at online, but that's the world
• 18:18
  Speaker 1: that we now live in, and we hope that it's
• 18:20
  Speaker 1: all for good instead of it being or turning bad
• 18:23
  Speaker 1: in some way with a bad actor.
• 18:26
  Speaker 3: Hey, good news here I found additional savings for us. Here.
• 18:29
  Speaker 3: We're making a progress. Just while I'm talking to you.
• 18:33
  Speaker 3: We've solved most of the federal budget. Postal Service reform
• 18:38
  Speaker 3: cut losses by reforming USPS operations one hundred billion federal
• 18:43
  Speaker 3: property sales. I think we can it says fifty billion.
• 18:47
  Speaker 3: I'll bet we can find half a trillion there. It
• 18:50
  Speaker 3: is asinal grants reform, endowment taxes. All right, that I
• 18:55
  Speaker 3: like a lot, because why should Harvard have eighty five billion?
• 18:59
  Speaker 3: You know, I save two trillion dollars in literally five minutes.
• 19:04
  Speaker 3: I mean, right, you're doing pretty good, Jared, Now, okay,
• 19:08
  Speaker 3: So that's cutting costs. And we can use chat GPT
• 19:11
  Speaker 3: feeding your budget somehow. I guess you would do a
• 19:15
  Speaker 3: list of everything, but it would have to know what
• 19:17
  Speaker 3: you bought too. But what about making more money? How
• 19:21
  Speaker 3: do we use it to make more money?
• 19:22
  Speaker 1: Well, I think that the big firms on Wall Street
• 19:26
  Speaker 1: figured that out a long time ago, and they're taking
• 19:31
  Speaker 1: the common person out of the trading game, and that's
• 19:35
  Speaker 1: how they're making more money. I think that there are
• 19:39
  Speaker 1: a number of business examples like that where it's working
• 19:44
  Speaker 1: in that vein. But you know, like I said, the
• 19:48
  Speaker 1: common person walking the street experiences it more than it does.
• 19:54
  Speaker 1: Put it to use as an example.
• 19:56
  Speaker 3: Okay, well I'm buying it. So give us the important
• 20:00
  Speaker 3: and stuff. How we connect with you on the web, websites,
• 20:03
  Speaker 3: all that stuff which you will find in the show
• 20:06
  Speaker 3: notes of course on Financial Survival Network dot com. That is,
• 20:10
  Speaker 3: if the AI note taker does what it's supposed to do,
• 20:13
  Speaker 3: which it doesn't always do, tell us how we connect
• 20:17
  Speaker 3: with you.
• 20:18
  Speaker 1: Yeah, I can be reached at view duu dot com
• 20:24
  Speaker 1: and then can also be reached via LinkedIn and my
• 20:28
  Speaker 1: LinkedIn profile which is Terrence spelled with one R and
• 20:33
  Speaker 1: a mills m I L L.
• 20:34
  Speaker 3: S excellent And like I said, it's in the show
• 20:37
  Speaker 3: notes this interview on Financial Survival Network dot com. Make
• 20:41
  Speaker 3: sure while you're there you sign up for your free
• 20:44
  Speaker 3: newsletter also our sister site, Inflation dot Cafe to find
• 20:49
  Speaker 3: out the latest ways the government is diminishing your purchasing power,
• 20:55
  Speaker 3: which is an ongoing process just like AI. And if
• 20:59
  Speaker 3: you've got a question comment for Terrence or myself, shoot
• 21:02
  Speaker 3: me an email k L at Carrie LUTs dot com.
• 21:05
  Speaker 3: Terrence absolute pleasure. We are good. Definitely, you're our go
• 21:08
  Speaker 3: to guy for AI. We will have you back on
• 21:11
  Speaker 3: the show.
• 21:11
  Speaker 2: Thanks very much, Thanks for listening to Carrie Letz's Financial
• 21:15
  Speaker 2: Survival Network, your solution to today's trying times. For the latest,
• 21:20
  Speaker 2: go to Financial Survivalnetwork dot com. Financial Survival Network now
• 21:26
  Speaker 2: more than ever,