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Speaker 1: Out of most of their streaming success.

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Speaker 2: Shows Clay and Buck Today at noon on fifty five.

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Speaker 1: Karc Ato five Here a fifty five KRCD talk station,

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Speaker 1: Happy Wednesday. Sadly no judgment of Polatana. But at the

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Speaker 1: bottom of the are we're gonna hear from Scott Warpin from

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Speaker 1: the Cincinni enquired by the Council Race in the meantime.

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Speaker 1: Empower Youamerica dot Orger is where you find all the

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Speaker 1: empower Use seminar series. They're all wonderful, all very informative,

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Speaker 1: most notably chat GPT. It's a brand new phenomenon for

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Speaker 1: most of us out in the world. It's that artificial

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Speaker 1: intelligence doing the work for us. Michael Mercer is doing

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Speaker 1: the seminars taking place tomorrow night. You can log in

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Speaker 1: from home or I think you can show up yes

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Speaker 1: at the empower U Seminar Classroom three hundred Great Oaks Drive,

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Speaker 1: or you'll hear Michael talk about chat GPT by way

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Speaker 1: of background. He's very informed in this obviously this topic.

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Speaker 1: He is the president of Screen Education, which addresses issues

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Speaker 1: at the intersection of digital technology and human well being.

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Speaker 1: We'll get to that, including smartphone addiction. News meet you, bias,

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Speaker 1: artificial intelligence, thought research seminars, and consultant. He, like most

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Speaker 1: of us my age, started out with world book encyclopedias

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Speaker 1: that he spent a decade as an editor and publisher

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Speaker 1: of college textbooks and another decade in market research before

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Speaker 1: heading on over to president of Screen Education, got multiple

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Speaker 1: degrees and again the seminars tomorrow night, beginning at seven pm.

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Speaker 1: Welcome to the program, Michael. It's a real pleasure to

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Speaker 1: have you on today.

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Speaker 2: Well, thank you, Brian, I appreciate it.

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Speaker 1: And an interesting element of your seminar. Now part of

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Speaker 1: me wants to say, well, if you're using chat GPT,

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Speaker 1: you're not doing the work and you're not learning anything.

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Speaker 1: It's like you sit there in front of it with

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Speaker 1: your mouth open, a little bit of drool coming out

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Speaker 1: of the corner of your mouth. You let it do

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Speaker 1: all the work for you, and then you just regurgitate

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Speaker 1: it back to whatever source you're seeking the information for.

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Speaker 1: But you have a different viewpoint on this. You can

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Speaker 1: use it to learn, right.

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Speaker 2: So that's the point of my talk is really how

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Speaker 2: to use chat GPT to teach yourself anything. That's really

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Speaker 2: the point where I'm coming from with this is I've,

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Speaker 2: as you sort of alluded to this, I've been a

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Speaker 2: sort of an autodidactor. I teach myself things all my life,

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Speaker 2: and I during the COVID I actually spent about thirty

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Speaker 2: five hours studying MR and A vaccines and how they work.

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Speaker 2: I really needed to understand them for personal reasons, and

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Speaker 2: so that was a huge self directed learning project. And

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Speaker 2: I was sort of shocked because I would talk to

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Speaker 2: other people, friends and acquaintances about these vaccines and they

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Speaker 2: knew nothing about it. And I could see that they

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Speaker 2: had no interest in learning about it. You know, they

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Speaker 2: almost felt like they couldn't understand it if they tried.

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Speaker 2: So I realized, like, wow, you know, maybe a lot

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Speaker 2: of people don't teach themselves things. And then when I

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Speaker 2: discovered chatbots, I'll tell you, I asked the man I

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Speaker 2: spent about thirty five hours teaching myself about MR and

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Speaker 2: A vaccines that if I had a chatbot, I think

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Speaker 2: I could have cut it to fifteen. You know. Yeah, well,

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Speaker 2: you know what.

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Speaker 1: I have to interject this because we went back and

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Speaker 1: forth with my son. My son is now thirty one.

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Speaker 1: He was in the computer engineering department at Ohio State university,

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Speaker 1: and I think that speaks volumes to his his intellect

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Speaker 1: because it's tough to get in there. So he spends

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Speaker 1: about a year and a half and then he drops out.

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Speaker 1: And what are you doing? You're not paying for it,

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Speaker 1: Just get the damn degree. I don't want to sit

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Speaker 1: in front of a computer doing coding. And besides, Mom

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Speaker 1: and Dad, I can teach it myself. And we're like, well,

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Speaker 1: well he ended up doing that. He'd got certificates for

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Speaker 1: computer security. He knows how to code. He did it

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Speaker 1: all himself. He taught himself, so it can be done.

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Speaker 1: And I make this point regularly because he convinced us

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Speaker 1: that he was right. Why spend all the extra money

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Speaker 1: and resources when all of this material is readily available.

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Speaker 1: Why would you spend one hundred thousand dollars to get

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Speaker 1: an art degree when there's countless books on art? You

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Speaker 1: can self direct and learn all you want to know

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Speaker 1: about your favorite hobby without having some teacher tell you

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Speaker 1: how to do it. I think people are paying college

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Speaker 1: tuition for the structure, the forced obligation to learn right.

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Speaker 2: Right right, that's you know what I'm going to do

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Speaker 2: in the talk is it's broken into three parts. So

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Speaker 2: the first part, and I feel this is critical for

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Speaker 2: people who want to teach themselves things right the way

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Speaker 2: that your son did. The first part, I'm going to

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Speaker 2: walk through the learning process. So I've broken the learning

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Speaker 2: process into six steps. You set a goal, you gather information,

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Speaker 2: you vet the information, then you have to do the

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Speaker 2: hard work to understand at a deep level that information.

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Speaker 2: Then you structure it, and then you integrate it into

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Speaker 2: your current knowledge base. Right. So I'm going to walk

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Speaker 2: through this self directed learning process so people understand the

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Speaker 2: process and how it works at each stage. Then I'm

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Speaker 2: going to give an overview of chatbots, and specifically I'm

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Speaker 2: going to use chat GPT because it's so popular, right,

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Speaker 2: but i want to show people, you know, you know,

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Speaker 2: this is what a chatbot is, this is the interface.

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Speaker 2: These are the features that are critical and really helpful

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Speaker 2: in self directed learning. But I think another important thing

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Speaker 2: is to teach them how these you know, so called

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Speaker 2: large language models work, because I think if you can

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Speaker 2: understand how large language models work, you can be more

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Speaker 2: effective in using chatbots to learn, you know. And then

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Speaker 2: the third part, I'm going to synthesize the two. Then

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Speaker 2: I'm going to close off by walking through the each

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Speaker 2: steps of each of the six steps of learning again

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Speaker 2: and tying off, how do you know specific ways you

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Speaker 2: use the chatbot to optimize your learning at each stage. Okay,

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Speaker 2: So I think it's really going to be helpful for

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Speaker 2: people to sort of codify this process for people if

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Speaker 2: they do want to jump in and try to teach

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Speaker 2: themselves things.

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Speaker 1: You know, right, if you have a motivation to teach

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Speaker 1: yourself something, this is an ideal class to do it

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Speaker 1: because it is it being the information on whatever topic

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Speaker 1: you want is out there in the world. So the

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Speaker 1: key element that I want to focus on just here

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Speaker 1: for at least a moment, Michael is vetting. You've got

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Speaker 1: vetting in here, and of course Vetting suggests to me

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Speaker 1: you need to understand how reliable whatever given source is,

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Speaker 1: where the source material came from, so you know if

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Speaker 1: it's some sort of like learned treatise or it's just

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Speaker 1: made up whole cloth. Because I keep hearing I mean

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Speaker 1: almost daily, and I'm sure you do as well. Idiot lawyers,

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Speaker 1: for example, who let chat, GPT or some other AI

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Speaker 1: program create case law that they don't even bother. Going

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Speaker 1: back to the original law books, or go to Lexus

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Speaker 1: and Nexus or West Law to find out if it's

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Speaker 1: a real case law and behold, it's not. It makes

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Speaker 1: up stuff. How do you know? How can you vet

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Speaker 1: what you're reading and know whether it's even real or not?

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Speaker 2: Michael, Well, that's a good point, you know, so that

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Speaker 2: you're getting at the in terms of vetting, that's the

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Speaker 2: you're right, the information literacy judging whether something is accurate

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Speaker 2: and correct. Right. So I guess that that's part of

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Speaker 2: the vetting. And one one way you do this is

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Speaker 2: I would say, first of all, don't just trust. You

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Speaker 2: can't blindly trust the chatbot. You can't. So you you know,

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Speaker 2: you've got to go out and cross reference things. You

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Speaker 2: can ask it to give you sources and then you

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Speaker 2: can link to those sources and look at the source

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Speaker 2: and see if you, in your judgment, it's accurate. Right.

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Speaker 2: So information literacy and judging the validity and truthfulness of

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Speaker 2: information is part of the vetting. The other part is

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Speaker 2: is vetting information in terms of determining what what you

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Speaker 2: given your goal, right, since you're the teacher, you're setting

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Speaker 2: the goal, and you have an internal motivation, right, you

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Speaker 2: want to you want to learn what you're studying for

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Speaker 2: internal reasons, right, It's not like you're taking a course

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Speaker 2: and the goal is given to you, right, Right, So

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Speaker 2: you want to use your intrinsic goals as the guide

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Speaker 2: post for judging whether or not the information you're you're

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Speaker 2: finding that could be relevant to the goal is actually relevant.

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Speaker 2: So you're going to find there are things like, Okay,

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Speaker 2: it's tangential, I don't really need to understand that at

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Speaker 2: a deep level given my goal, right. So that's the

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Speaker 2: other part of vetting. So so it's it's sort of

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Speaker 2: you know, both of those things, right, Yeah, judging the

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Speaker 2: relevance but also the validity of the information, and it's

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Speaker 2: it's all going to like primary sources and checking multiple

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Speaker 2: sources to make sure it's it's it's.

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Speaker 1: Truthful, and having a fundamental knowledge of what a primary

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Speaker 1: source is also is a helpful thing to have going

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Speaker 1: into the process, isn't it.

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Speaker 2: Well, that's that's true, that's true. Yeah. So but even that,

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Speaker 2: you know, there's there's a lot of judgment that comes

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Speaker 2: to that because you could have a primary source, but

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Speaker 2: it could be biased, like you know, for example.

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Speaker 1: Like a scientific consensus Exactly.

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Speaker 2: I was going to say a research study going back

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Speaker 2: to COVID. Right, you could have a research study on

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Speaker 2: the vaccines or biromectin or whatever it is, right, and

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Speaker 2: you you have to bring you know, it could be

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Speaker 2: biased science, right, The people doing the study could could

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Speaker 2: have been biased, they could have changed data. So you

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Speaker 2: have to bring some judgment and you know there is

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Speaker 2: some guesswork in estimating. It's not a perfect process, but

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Speaker 2: you can do pretty well.

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Speaker 1: I think you know.

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Speaker 2: So.

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Speaker 1: So for example, if I'm interested in, like whether carbon

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Speaker 1: dioxide is bad for people or something, you're going to

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Speaker 1: have research studies would suggest it is some sort of

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Speaker 1: greenhouse gas, and it'll make that conclusion based upon some

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Speaker 1: other scientific consensus. But then again you can ask it

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Speaker 1: to provide an alternative viewpoint of that, can you not?

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Speaker 1: So it would go to other sources?

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Speaker 2: Yeah? Perfect, Yeah, perfect point. Yes you can. And that's

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Speaker 2: see that's the great thing about the chat This is

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Speaker 2: the thing with the chatbots, right, it's you I basically

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Speaker 2: look at these chatbots as they're they're expert level tutors

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Speaker 2: on every subject, right that are available twenty four to seven.

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Speaker 2: You can access them twenty four to seven and they

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Speaker 2: can speak to you at any level of detail you want. Right. So,

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Speaker 2: so what you're doing is through this iterative process I

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Speaker 2: chat with these chat bots like I'm chatting with a

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Speaker 2: with a teacher or a person right, right. And what

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Speaker 2: it's doing is it's continuously with with every iteration of

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Speaker 2: your conversation, it's continuously refining your it's understanding of your

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Speaker 2: perspective until it gets to a point where it's it's

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Speaker 2: what I call mirror, cognitive mirroring or cognitive achieving, cognitive

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Speaker 2: alignment with with you, right you get?

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Speaker 1: Is that you getting an answer you ultimately want, Like

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Speaker 1: an expert. If I hire an expert as a lawyer,

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Speaker 1: I'm pretty darn certain I can get that expert to

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Speaker 1: reach a conclusion that's beneficial to my client. Can you

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Speaker 1: do that with chat, GPT or other AI resources?

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Speaker 2: You can? It's it's through you know, the more it

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Speaker 2: understands your goal. So what one thing I'm going to

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Speaker 2: lay out in the talk is how you accelerate through

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Speaker 2: the process of having it aligned with you cognitively. Right,

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Speaker 2: Sure you can. So you can almost do like a

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Speaker 2: brain dump at the beginning of the project, so it

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Speaker 2: fully understands what you want to do. And this is

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Speaker 2: the thing, Brian, Once it knows, if it knows you're

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Speaker 2: working on a project, say like I use chat GPT

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Speaker 2: to learn about large language models and chatbots for this

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Speaker 2: for this talk them to give right, And once it

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Speaker 2: new that, I'm like, Okay, he's working on this presentation.

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Speaker 2: He wants to understand them, but he wants to understand

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Speaker 2: them at a way, at a level at which he

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Speaker 2: can explain them to a layperson, right, And he himself

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Speaker 2: is not like a tech expert, right, so he has

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Speaker 2: to understanding of that level. It's it's what you're spying

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Speaker 2: and saying, here's the here's the information, here's how you

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Speaker 2: can present it to your audience at a conceptual level

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Speaker 2: so the average person can understand it. And if you want,

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Speaker 2: I can create a sly for you, you know, to

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Speaker 2: incert in your talk. That's what it starts doing. And

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Speaker 2: so you know, they can be extremely helpful once they

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Speaker 2: really fully understand what you're doing and what your goal

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Speaker 2: is and how you're looking at the project. You know,

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Speaker 2: it's amazing.

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Speaker 1: Yeah, I get that, and I can see it. For example,

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Speaker 1: again going back to my you know my days' is

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Speaker 1: a litigation attorney. Sometimes you have extraordinarily complex case. You know,

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Speaker 1: the facts and circumstances and law and elements of it

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Speaker 1: that you really get used to and you're accustomed to

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Speaker 1: talking amongst yourselves with your other lawyers. Everybody gets what

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Speaker 1: you're talking about, you know, but you've got to be

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Speaker 1: able to explain it to a jury who has no

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Speaker 1: idea where you're coming from. You got to boil it

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Speaker 1: down easily, understandable, a story to tell which connects all

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Speaker 1: the dots, so it makes people that's it sounds me

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Speaker 1: like what you're accomplishing here.

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Speaker 2: That's right. So after the vetting process, once you decide okay,

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Speaker 2: I need these are the five things I need to

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Speaker 2: learn to understand this, then the next step in my

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Speaker 2: learning process is actually understanding it. You know, you won't

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Speaker 2: fully understanding once you vet it. You still have to

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Speaker 2: go deep into it and understand it. That's when these

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Speaker 2: chatbots can be incredible because you can just keep going

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Speaker 2: back and forth and just keep asking it questions about

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Speaker 2: every minute thing that you don't understand, and it'll it'll

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Speaker 2: explain it to you at the level you want to

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Speaker 2: understand it or you need to understand it. It'll clarify

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Speaker 2: the micro elements that you're not getting. It'll give you

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Speaker 2: metaphors that help you under I want to give you

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Speaker 2: an example. So these large language models, it's really complex stuff.

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Speaker 2: So I learned a lot more than the average person.

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Speaker 2: But I'm by no means close to you know, being

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Speaker 2: a quote tech expert on this, right, But I was

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Speaker 2: struggling with this for hours, okay, to understand it large

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Speaker 2: language models. And at some point the chat gave me

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Speaker 2: an analogy that just crystallized the whole thing for me, right,

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Speaker 2: And it was trying to explain, well, it's a large

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Speaker 2: language module. Isn't thinking, it's actually just it's it's using

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Speaker 2: probability to give you the next likely word in its response.

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Speaker 2: So it's a probability machine, right, And it gave me

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Speaker 2: this metaphor it was it said, it's like autocomplete on steroids.

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Speaker 2: It just right, So that's literally what it's doing. It's

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Speaker 2: like on your phone, right when you're typing a message

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Speaker 2: to someone, a text message. It gives you like you're

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Speaker 2: starting to type the next word, and it gives you

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Speaker 2: three options to pick one. It's calculating the most likely

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Speaker 2: next word you're going to use given the context of

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Speaker 2: what you're typing, right, Well, that's what a chatbot is

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Speaker 2: literally doing it, but it's infinitely more complex. The calculation

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Speaker 2: is infinitely more complex. But it's really just a machine.

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Speaker 2: It's it doesn't you know, it's not thinking, it's not

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Speaker 2: it's not a person. You know. It's easy to anthropomorphize

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Speaker 2: these things, right, you really feel like it knows you,

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Speaker 2: but that Chris lives for me, Like, Okay, it's really

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Speaker 2: just a machine. It's a probability generating machine.

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Speaker 1: Really, and that's that's where the human element is always

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Speaker 1: going to be critical and going through this exact process

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Speaker 1: that you're going to be talking about tomorrow night at

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Speaker 1: seven pm. So yes, it is, and it won't end

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Speaker 1: your job. AI Michael Mercer, how to teach yourself anything

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Speaker 1: using chat GTP log in, get registered before you do.

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Speaker 1: Empower you America dot org register seven PM's log in

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Speaker 1: time or the time to be a three hundred grede

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Speaker 1: Oaks driver for the live discussion. It's going to be fascinating, Michael.

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Speaker 1: I appreciate you doing this and helping to educate us

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Speaker 1: and obviously giving us some really positive uses for artificial

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Speaker 1: intelligence when I think most of us are scared that

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Speaker 1: it's going to end our careers. Michael.

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Speaker 2: Yeah, well thanks, I hope it. I hope it helps people,

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Speaker 2: so I really do.

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Speaker 1: So that's what you're all about, Michael, and I appreciate

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Speaker 1: you doing that. Get some help tomorrow night, seven pm.

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Speaker 1: Thanks Michael, have a wonderful day, and good luck with

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Speaker 1: the seminar and folks. And when you get into with

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Speaker 1: Galaxy concrete coatings, because you're going to