October 15, 2025 • 15 mins
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Speaker 1 (00:00):
Out of most of their streaming success.
Speaker 2 (00:02):
Shows Clay and Buck Today at noon on fifty five.
Speaker 1 (00:06):
Karc Ato five Here a fifty five KRCD talk station,
Happy Wednesday. Sadly no judgment of Polatana. But at the
bottom of the are we're gonna hear from Scott Warpin from
the Cincinni enquired by the Council Race in the meantime.
Empower Youamerica dot Orger is where you find all the
empower Use seminar series. They're all wonderful, all very informative,
most notably chat GPT. It's a brand new phenomenon for
(00:29):
most of us out in the world. It's that artificial
intelligence doing the work for us. Michael Mercer is doing
the seminars taking place tomorrow night. You can log in
from home or I think you can show up yes
at the empower U Seminar Classroom three hundred Great Oaks Drive,
or you'll hear Michael talk about chat GPT by way
of background. He's very informed in this obviously this topic.
(00:51):
He is the president of Screen Education, which addresses issues
at the intersection of digital technology and human well being.
We'll get to that, including smartphone addiction. News meet you, bias,
artificial intelligence, thought research seminars, and consultant. He, like most
of us my age, started out with world book encyclopedias
that he spent a decade as an editor and publisher
of college textbooks and another decade in market research before
(01:12):
heading on over to president of Screen Education, got multiple
degrees and again the seminars tomorrow night, beginning at seven pm.
Welcome to the program, Michael. It's a real pleasure to
have you on today.
Speaker 2 (01:23):
Well, thank you, Brian, I appreciate it.
Speaker 1 (01:24):
And an interesting element of your seminar. Now part of
me wants to say, well, if you're using chat GPT,
you're not doing the work and you're not learning anything.
It's like you sit there in front of it with
your mouth open, a little bit of drool coming out
of the corner of your mouth. You let it do
all the work for you, and then you just regurgitate
it back to whatever source you're seeking the information for.
(01:45):
But you have a different viewpoint on this. You can
use it to learn, right.
Speaker 2 (01:50):
So that's the point of my talk is really how
to use chat GPT to teach yourself anything. That's really
the point where I'm coming from with this is I've,
as you sort of alluded to this, I've been a
sort of an autodidactor. I teach myself things all my life,
and I during the COVID I actually spent about thirty
(02:13):
five hours studying MR and A vaccines and how they work.
I really needed to understand them for personal reasons, and
so that was a huge self directed learning project. And
I was sort of shocked because I would talk to
other people, friends and acquaintances about these vaccines and they
knew nothing about it. And I could see that they
had no interest in learning about it. You know, they
(02:34):
almost felt like they couldn't understand it if they tried.
So I realized, like, wow, you know, maybe a lot
of people don't teach themselves things. And then when I
discovered chatbots, I'll tell you, I asked the man I
spent about thirty five hours teaching myself about MR and
A vaccines that if I had a chatbot, I think
I could have cut it to fifteen. You know. Yeah, well,
you know what.
Speaker 1 (02:53):
I have to interject this because we went back and
forth with my son. My son is now thirty one.
He was in the computer engineering department at Ohio State university,
and I think that speaks volumes to his his intellect
because it's tough to get in there. So he spends
about a year and a half and then he drops out.
And what are you doing? You're not paying for it,
Just get the damn degree. I don't want to sit
(03:14):
in front of a computer doing coding. And besides, Mom
and Dad, I can teach it myself. And we're like, well,
well he ended up doing that. He'd got certificates for
computer security. He knows how to code. He did it
all himself. He taught himself, so it can be done.
And I make this point regularly because he convinced us
that he was right. Why spend all the extra money
(03:37):
and resources when all of this material is readily available.
Why would you spend one hundred thousand dollars to get
an art degree when there's countless books on art? You
can self direct and learn all you want to know
about your favorite hobby without having some teacher tell you
how to do it. I think people are paying college
tuition for the structure, the forced obligation to learn right.
Speaker 2 (03:58):
Right right, that's you know what I'm going to do
in the talk is it's broken into three parts. So
the first part, and I feel this is critical for
people who want to teach themselves things right the way
that your son did. The first part, I'm going to
walk through the learning process. So I've broken the learning
process into six steps. You set a goal, you gather information,
you vet the information, then you have to do the
(04:20):
hard work to understand at a deep level that information.
Then you structure it, and then you integrate it into
your current knowledge base. Right. So I'm going to walk
through this self directed learning process so people understand the
process and how it works at each stage. Then I'm
going to give an overview of chatbots, and specifically I'm
(04:41):
going to use chat GPT because it's so popular, right,
but i want to show people, you know, you know,
this is what a chatbot is, this is the interface.
These are the features that are critical and really helpful
in self directed learning. But I think another important thing
is to teach them how these you know, so called
large language models work, because I think if you can
(05:03):
understand how large language models work, you can be more
effective in using chatbots to learn, you know. And then
the third part, I'm going to synthesize the two. Then
I'm going to close off by walking through the each
steps of each of the six steps of learning again
and tying off, how do you know specific ways you
use the chatbot to optimize your learning at each stage. Okay,
(05:25):
So I think it's really going to be helpful for
people to sort of codify this process for people if
they do want to jump in and try to teach
themselves things.
Speaker 1 (05:33):
You know, right, if you have a motivation to teach
yourself something, this is an ideal class to do it
because it is it being the information on whatever topic
you want is out there in the world. So the
key element that I want to focus on just here
for at least a moment, Michael is vetting. You've got
vetting in here, and of course Vetting suggests to me
you need to understand how reliable whatever given source is,
(05:55):
where the source material came from, so you know if
it's some sort of like learned treatise or it's just
made up whole cloth. Because I keep hearing I mean
almost daily, and I'm sure you do as well. Idiot lawyers,
for example, who let chat, GPT or some other AI
program create case law that they don't even bother. Going
back to the original law books, or go to Lexus
and Nexus or West Law to find out if it's
(06:16):
a real case law and behold, it's not. It makes
up stuff. How do you know? How can you vet
what you're reading and know whether it's even real or not?
Speaker 2 (06:23):
Michael, Well, that's a good point, you know, so that
you're getting at the in terms of vetting, that's the
you're right, the information literacy judging whether something is accurate
and correct. Right. So I guess that that's part of
the vetting. And one one way you do this is
I would say, first of all, don't just trust. You
can't blindly trust the chatbot. You can't. So you you know,
you've got to go out and cross reference things. You
(06:46):
can ask it to give you sources and then you
can link to those sources and look at the source
and see if you, in your judgment, it's accurate. Right.
So information literacy and judging the validity and truthfulness of
information is part of the vetting. The other part is
is vetting information in terms of determining what what you
given your goal, right, since you're the teacher, you're setting
(07:09):
the goal, and you have an internal motivation, right, you
want to you want to learn what you're studying for
internal reasons, right, It's not like you're taking a course
and the goal is given to you, right, Right, So
you want to use your intrinsic goals as the guide
post for judging whether or not the information you're you're
finding that could be relevant to the goal is actually relevant.
(07:31):
So you're going to find there are things like, Okay,
it's tangential, I don't really need to understand that at
a deep level given my goal, right. So that's the
other part of vetting. So so it's it's sort of
you know, both of those things, right, Yeah, judging the
relevance but also the validity of the information, and it's
it's all going to like primary sources and checking multiple
sources to make sure it's it's it's.
Speaker 1 (07:52):
Truthful, and having a fundamental knowledge of what a primary
source is also is a helpful thing to have going
into the process, isn't it.
Speaker 2 (08:00):
Well, that's that's true, that's true. Yeah. So but even that,
you know, there's there's a lot of judgment that comes
to that because you could have a primary source, but
it could be biased, like you know, for example.
Speaker 1 (08:12):
Like a scientific consensus Exactly.
Speaker 2 (08:17):
I was going to say a research study going back
to COVID. Right, you could have a research study on
the vaccines or biromectin or whatever it is, right, and
you you have to bring you know, it could be
biased science, right, The people doing the study could could
have been biased, they could have changed data. So you
have to bring some judgment and you know there is
some guesswork in estimating. It's not a perfect process, but
(08:40):
you can do pretty well.
Speaker 1 (08:41):
I think you know.
Speaker 2 (08:42):
So.
Speaker 1 (08:42):
So for example, if I'm interested in, like whether carbon
dioxide is bad for people or something, you're going to
have research studies would suggest it is some sort of
greenhouse gas, and it'll make that conclusion based upon some
other scientific consensus. But then again you can ask it
to provide an alternative viewpoint of that, can you not?
So it would go to other sources?
Speaker 2 (09:03):
Yeah? Perfect, Yeah, perfect point. Yes you can. And that's
see that's the great thing about the chat This is
the thing with the chatbots, right, it's you I basically
look at these chatbots as they're they're expert level tutors
on every subject, right that are available twenty four to seven.
You can access them twenty four to seven and they
can speak to you at any level of detail you want. Right. So,
(09:27):
so what you're doing is through this iterative process I
chat with these chat bots like I'm chatting with a
with a teacher or a person right, right. And what
it's doing is it's continuously with with every iteration of
your conversation, it's continuously refining your it's understanding of your
perspective until it gets to a point where it's it's
(09:47):
what I call mirror, cognitive mirroring or cognitive achieving, cognitive
alignment with with you, right you get?
Speaker 1 (09:57):
Is that you getting an answer you ultimately want, Like
an expert. If I hire an expert as a lawyer,
I'm pretty darn certain I can get that expert to
reach a conclusion that's beneficial to my client. Can you
do that with chat, GPT or other AI resources?
Speaker 2 (10:14):
You can? It's it's through you know, the more it
understands your goal. So what one thing I'm going to
lay out in the talk is how you accelerate through
the process of having it aligned with you cognitively. Right,
Sure you can. So you can almost do like a
brain dump at the beginning of the project, so it
fully understands what you want to do. And this is
the thing, Brian, Once it knows, if it knows you're
(10:36):
working on a project, say like I use chat GPT
to learn about large language models and chatbots for this
for this talk them to give right, And once it
new that, I'm like, Okay, he's working on this presentation.
He wants to understand them, but he wants to understand
them at a way, at a level at which he
can explain them to a layperson, right, And he himself
(10:56):
is not like a tech expert, right, so he has
to understanding of that level. It's it's what you're spying
and saying, here's the here's the information, here's how you
can present it to your audience at a conceptual level
so the average person can understand it. And if you want,
I can create a sly for you, you know, to
incert in your talk. That's what it starts doing. And
(11:16):
so you know, they can be extremely helpful once they
really fully understand what you're doing and what your goal
is and how you're looking at the project. You know,
it's amazing.
Speaker 1 (11:26):
Yeah, I get that, and I can see it. For example,
again going back to my you know my days' is
a litigation attorney. Sometimes you have extraordinarily complex case. You know,
the facts and circumstances and law and elements of it
that you really get used to and you're accustomed to
talking amongst yourselves with your other lawyers. Everybody gets what
you're talking about, you know, but you've got to be
(11:47):
able to explain it to a jury who has no
idea where you're coming from. You got to boil it
down easily, understandable, a story to tell which connects all
the dots, so it makes people that's it sounds me
like what you're accomplishing here.
Speaker 2 (12:01):
That's right. So after the vetting process, once you decide okay,
I need these are the five things I need to
learn to understand this, then the next step in my
learning process is actually understanding it. You know, you won't
fully understanding once you vet it. You still have to
go deep into it and understand it. That's when these
chatbots can be incredible because you can just keep going
back and forth and just keep asking it questions about
(12:26):
every minute thing that you don't understand, and it'll it'll
explain it to you at the level you want to
understand it or you need to understand it. It'll clarify
the micro elements that you're not getting. It'll give you
metaphors that help you under I want to give you
an example. So these large language models, it's really complex stuff.
So I learned a lot more than the average person.
(12:47):
But I'm by no means close to you know, being
a quote tech expert on this, right, But I was
struggling with this for hours, okay, to understand it large
language models. And at some point the chat gave me
an analogy that just crystallized the whole thing for me, right,
And it was trying to explain, well, it's a large
language module. Isn't thinking, it's actually just it's it's using
(13:10):
probability to give you the next likely word in its response.
So it's a probability machine, right, And it gave me
this metaphor it was it said, it's like autocomplete on steroids.
It just right, So that's literally what it's doing. It's
like on your phone, right when you're typing a message
to someone, a text message. It gives you like you're
(13:33):
starting to type the next word, and it gives you
three options to pick one. It's calculating the most likely
next word you're going to use given the context of
what you're typing, right, Well, that's what a chatbot is
literally doing it, but it's infinitely more complex. The calculation
is infinitely more complex. But it's really just a machine.
It's it doesn't you know, it's not thinking, it's not
(13:55):
it's not a person. You know. It's easy to anthropomorphize
these things, right, you really feel like it knows you,
but that Chris lives for me, Like, Okay, it's really
just a machine. It's a probability generating machine.
Speaker 1 (14:08):
Really, and that's that's where the human element is always
going to be critical and going through this exact process
that you're going to be talking about tomorrow night at
seven pm. So yes, it is, and it won't end
your job. AI Michael Mercer, how to teach yourself anything
using chat GTP log in, get registered before you do.
(14:28):
Empower you America dot org register seven PM's log in
time or the time to be a three hundred grede
Oaks driver for the live discussion. It's going to be fascinating, Michael.
I appreciate you doing this and helping to educate us
and obviously giving us some really positive uses for artificial
intelligence when I think most of us are scared that
it's going to end our careers. Michael.
Speaker 2 (14:47):
Yeah, well thanks, I hope it. I hope it helps people,
so I really do.
Speaker 1 (14:50):
So that's what you're all about, Michael, and I appreciate
you doing that. Get some help tomorrow night, seven pm.
Thanks Michael, have a wonderful day, and good luck with
the seminar and folks. And when you get into with
Galaxy concrete coatings, because you're going to
Out of most of their streaming success.
Speaker 2 (00:02):
Shows Clay and Buck Today at noon on fifty five.
Speaker 1 (00:06):
Karc Ato five Here a fifty five KRCD talk station,
Happy Wednesday. Sadly no judgment of Polatana. But at the
bottom of the are we're gonna hear from Scott Warpin from
the Cincinni enquired by the Council Race in the meantime.
Empower Youamerica dot Orger is where you find all the
empower Use seminar series. They're all wonderful, all very informative,
most notably chat GPT. It's a brand new phenomenon for
(00:29):
most of us out in the world. It's that artificial
intelligence doing the work for us. Michael Mercer is doing
the seminars taking place tomorrow night. You can log in
from home or I think you can show up yes
at the empower U Seminar Classroom three hundred Great Oaks Drive,
or you'll hear Michael talk about chat GPT by way
of background. He's very informed in this obviously this topic.
(00:51):
He is the president of Screen Education, which addresses issues
at the intersection of digital technology and human well being.
We'll get to that, including smartphone addiction. News meet you, bias,
artificial intelligence, thought research seminars, and consultant. He, like most
of us my age, started out with world book encyclopedias
that he spent a decade as an editor and publisher
of college textbooks and another decade in market research before
(01:12):
heading on over to president of Screen Education, got multiple
degrees and again the seminars tomorrow night, beginning at seven pm.
Welcome to the program, Michael. It's a real pleasure to
have you on today.
Speaker 2 (01:23):
Well, thank you, Brian, I appreciate it.
Speaker 1 (01:24):
And an interesting element of your seminar. Now part of
me wants to say, well, if you're using chat GPT,
you're not doing the work and you're not learning anything.
It's like you sit there in front of it with
your mouth open, a little bit of drool coming out
of the corner of your mouth. You let it do
all the work for you, and then you just regurgitate
it back to whatever source you're seeking the information for.
(01:45):
But you have a different viewpoint on this. You can
use it to learn, right.
Speaker 2 (01:50):
So that's the point of my talk is really how
to use chat GPT to teach yourself anything. That's really
the point where I'm coming from with this is I've,
as you sort of alluded to this, I've been a
sort of an autodidactor. I teach myself things all my life,
and I during the COVID I actually spent about thirty
(02:13):
five hours studying MR and A vaccines and how they work.
I really needed to understand them for personal reasons, and
so that was a huge self directed learning project. And
I was sort of shocked because I would talk to
other people, friends and acquaintances about these vaccines and they
knew nothing about it. And I could see that they
had no interest in learning about it. You know, they
(02:34):
almost felt like they couldn't understand it if they tried.
So I realized, like, wow, you know, maybe a lot
of people don't teach themselves things. And then when I
discovered chatbots, I'll tell you, I asked the man I
spent about thirty five hours teaching myself about MR and
A vaccines that if I had a chatbot, I think
I could have cut it to fifteen. You know. Yeah, well,
you know what.
Speaker 1 (02:53):
I have to interject this because we went back and
forth with my son. My son is now thirty one.
He was in the computer engineering department at Ohio State university,
and I think that speaks volumes to his his intellect
because it's tough to get in there. So he spends
about a year and a half and then he drops out.
And what are you doing? You're not paying for it,
Just get the damn degree. I don't want to sit
(03:14):
in front of a computer doing coding. And besides, Mom
and Dad, I can teach it myself. And we're like, well,
well he ended up doing that. He'd got certificates for
computer security. He knows how to code. He did it
all himself. He taught himself, so it can be done.
And I make this point regularly because he convinced us
that he was right. Why spend all the extra money
(03:37):
and resources when all of this material is readily available.
Why would you spend one hundred thousand dollars to get
an art degree when there's countless books on art? You
can self direct and learn all you want to know
about your favorite hobby without having some teacher tell you
how to do it. I think people are paying college
tuition for the structure, the forced obligation to learn right.
Speaker 2 (03:58):
Right right, that's you know what I'm going to do
in the talk is it's broken into three parts. So
the first part, and I feel this is critical for
people who want to teach themselves things right the way
that your son did. The first part, I'm going to
walk through the learning process. So I've broken the learning
process into six steps. You set a goal, you gather information,
you vet the information, then you have to do the
(04:20):
hard work to understand at a deep level that information.
Then you structure it, and then you integrate it into
your current knowledge base. Right. So I'm going to walk
through this self directed learning process so people understand the
process and how it works at each stage. Then I'm
going to give an overview of chatbots, and specifically I'm
(04:41):
going to use chat GPT because it's so popular, right,
but i want to show people, you know, you know,
this is what a chatbot is, this is the interface.
These are the features that are critical and really helpful
in self directed learning. But I think another important thing
is to teach them how these you know, so called
large language models work, because I think if you can
(05:03):
understand how large language models work, you can be more
effective in using chatbots to learn, you know. And then
the third part, I'm going to synthesize the two. Then
I'm going to close off by walking through the each
steps of each of the six steps of learning again
and tying off, how do you know specific ways you
use the chatbot to optimize your learning at each stage. Okay,
(05:25):
So I think it's really going to be helpful for
people to sort of codify this process for people if
they do want to jump in and try to teach
themselves things.
Speaker 1 (05:33):
You know, right, if you have a motivation to teach
yourself something, this is an ideal class to do it
because it is it being the information on whatever topic
you want is out there in the world. So the
key element that I want to focus on just here
for at least a moment, Michael is vetting. You've got
vetting in here, and of course Vetting suggests to me
you need to understand how reliable whatever given source is,
(05:55):
where the source material came from, so you know if
it's some sort of like learned treatise or it's just
made up whole cloth. Because I keep hearing I mean
almost daily, and I'm sure you do as well. Idiot lawyers,
for example, who let chat, GPT or some other AI
program create case law that they don't even bother. Going
back to the original law books, or go to Lexus
and Nexus or West Law to find out if it's
(06:16):
a real case law and behold, it's not. It makes
up stuff. How do you know? How can you vet
what you're reading and know whether it's even real or not?
Speaker 2 (06:23):
Michael, Well, that's a good point, you know, so that
you're getting at the in terms of vetting, that's the
you're right, the information literacy judging whether something is accurate
and correct. Right. So I guess that that's part of
the vetting. And one one way you do this is
I would say, first of all, don't just trust. You
can't blindly trust the chatbot. You can't. So you you know,
you've got to go out and cross reference things. You
(06:46):
can ask it to give you sources and then you
can link to those sources and look at the source
and see if you, in your judgment, it's accurate. Right.
So information literacy and judging the validity and truthfulness of
information is part of the vetting. The other part is
is vetting information in terms of determining what what you
given your goal, right, since you're the teacher, you're setting
(07:09):
the goal, and you have an internal motivation, right, you
want to you want to learn what you're studying for
internal reasons, right, It's not like you're taking a course
and the goal is given to you, right, Right, So
you want to use your intrinsic goals as the guide
post for judging whether or not the information you're you're
finding that could be relevant to the goal is actually relevant.
(07:31):
So you're going to find there are things like, Okay,
it's tangential, I don't really need to understand that at
a deep level given my goal, right. So that's the
other part of vetting. So so it's it's sort of
you know, both of those things, right, Yeah, judging the
relevance but also the validity of the information, and it's
it's all going to like primary sources and checking multiple
sources to make sure it's it's it's.
Speaker 1 (07:52):
Truthful, and having a fundamental knowledge of what a primary
source is also is a helpful thing to have going
into the process, isn't it.
Speaker 2 (08:00):
Well, that's that's true, that's true. Yeah. So but even that,
you know, there's there's a lot of judgment that comes
to that because you could have a primary source, but
it could be biased, like you know, for example.
Speaker 1 (08:12):
Like a scientific consensus Exactly.
Speaker 2 (08:17):
I was going to say a research study going back
to COVID. Right, you could have a research study on
the vaccines or biromectin or whatever it is, right, and
you you have to bring you know, it could be
biased science, right, The people doing the study could could
have been biased, they could have changed data. So you
have to bring some judgment and you know there is
some guesswork in estimating. It's not a perfect process, but
(08:40):
you can do pretty well.
Speaker 1 (08:41):
I think you know.
Speaker 2 (08:42):
So.
Speaker 1 (08:42):
So for example, if I'm interested in, like whether carbon
dioxide is bad for people or something, you're going to
have research studies would suggest it is some sort of
greenhouse gas, and it'll make that conclusion based upon some
other scientific consensus. But then again you can ask it
to provide an alternative viewpoint of that, can you not?
So it would go to other sources?
Speaker 2 (09:03):
Yeah? Perfect, Yeah, perfect point. Yes you can. And that's
see that's the great thing about the chat This is
the thing with the chatbots, right, it's you I basically
look at these chatbots as they're they're expert level tutors
on every subject, right that are available twenty four to seven.
You can access them twenty four to seven and they
can speak to you at any level of detail you want. Right. So,
(09:27):
so what you're doing is through this iterative process I
chat with these chat bots like I'm chatting with a
with a teacher or a person right, right. And what
it's doing is it's continuously with with every iteration of
your conversation, it's continuously refining your it's understanding of your
perspective until it gets to a point where it's it's
(09:47):
what I call mirror, cognitive mirroring or cognitive achieving, cognitive
alignment with with you, right you get?
Speaker 1 (09:57):
Is that you getting an answer you ultimately want, Like
an expert. If I hire an expert as a lawyer,
I'm pretty darn certain I can get that expert to
reach a conclusion that's beneficial to my client. Can you
do that with chat, GPT or other AI resources?
Speaker 2 (10:14):
You can? It's it's through you know, the more it
understands your goal. So what one thing I'm going to
lay out in the talk is how you accelerate through
the process of having it aligned with you cognitively. Right,
Sure you can. So you can almost do like a
brain dump at the beginning of the project, so it
fully understands what you want to do. And this is
the thing, Brian, Once it knows, if it knows you're
(10:36):
working on a project, say like I use chat GPT
to learn about large language models and chatbots for this
for this talk them to give right, And once it
new that, I'm like, Okay, he's working on this presentation.
He wants to understand them, but he wants to understand
them at a way, at a level at which he
can explain them to a layperson, right, And he himself
(10:56):
is not like a tech expert, right, so he has
to understanding of that level. It's it's what you're spying
and saying, here's the here's the information, here's how you
can present it to your audience at a conceptual level
so the average person can understand it. And if you want,
I can create a sly for you, you know, to
incert in your talk. That's what it starts doing. And
(11:16):
so you know, they can be extremely helpful once they
really fully understand what you're doing and what your goal
is and how you're looking at the project. You know,
it's amazing.
Speaker 1 (11:26):
Yeah, I get that, and I can see it. For example,
again going back to my you know my days' is
a litigation attorney. Sometimes you have extraordinarily complex case. You know,
the facts and circumstances and law and elements of it
that you really get used to and you're accustomed to
talking amongst yourselves with your other lawyers. Everybody gets what
you're talking about, you know, but you've got to be
(11:47):
able to explain it to a jury who has no
idea where you're coming from. You got to boil it
down easily, understandable, a story to tell which connects all
the dots, so it makes people that's it sounds me
like what you're accomplishing here.
Speaker 2 (12:01):
That's right. So after the vetting process, once you decide okay,
I need these are the five things I need to
learn to understand this, then the next step in my
learning process is actually understanding it. You know, you won't
fully understanding once you vet it. You still have to
go deep into it and understand it. That's when these
chatbots can be incredible because you can just keep going
back and forth and just keep asking it questions about
(12:26):
every minute thing that you don't understand, and it'll it'll
explain it to you at the level you want to
understand it or you need to understand it. It'll clarify
the micro elements that you're not getting. It'll give you
metaphors that help you under I want to give you
an example. So these large language models, it's really complex stuff.
So I learned a lot more than the average person.
(12:47):
But I'm by no means close to you know, being
a quote tech expert on this, right, But I was
struggling with this for hours, okay, to understand it large
language models. And at some point the chat gave me
an analogy that just crystallized the whole thing for me, right,
And it was trying to explain, well, it's a large
language module. Isn't thinking, it's actually just it's it's using
(13:10):
probability to give you the next likely word in its response.
So it's a probability machine, right, And it gave me
this metaphor it was it said, it's like autocomplete on steroids.
It just right, So that's literally what it's doing. It's
like on your phone, right when you're typing a message
to someone, a text message. It gives you like you're
(13:33):
starting to type the next word, and it gives you
three options to pick one. It's calculating the most likely
next word you're going to use given the context of
what you're typing, right, Well, that's what a chatbot is
literally doing it, but it's infinitely more complex. The calculation
is infinitely more complex. But it's really just a machine.
It's it doesn't you know, it's not thinking, it's not
(13:55):
it's not a person. You know. It's easy to anthropomorphize
these things, right, you really feel like it knows you,
but that Chris lives for me, Like, Okay, it's really
just a machine. It's a probability generating machine.
Speaker 1 (14:08):
Really, and that's that's where the human element is always
going to be critical and going through this exact process
that you're going to be talking about tomorrow night at
seven pm. So yes, it is, and it won't end
your job. AI Michael Mercer, how to teach yourself anything
using chat GTP log in, get registered before you do.
(14:28):
Empower you America dot org register seven PM's log in
time or the time to be a three hundred grede
Oaks driver for the live discussion. It's going to be fascinating, Michael.
I appreciate you doing this and helping to educate us
and obviously giving us some really positive uses for artificial
intelligence when I think most of us are scared that
it's going to end our careers. Michael.
Speaker 2 (14:47):
Yeah, well thanks, I hope it. I hope it helps people,
so I really do.
Speaker 1 (14:50):
So that's what you're all about, Michael, and I appreciate
you doing that. Get some help tomorrow night, seven pm.
Thanks Michael, have a wonderful day, and good luck with
the seminar and folks. And when you get into with
Galaxy concrete coatings, because you're going to
Brian Thomas News
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