Episode Transcript
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Speaker 1 (00:00):
Out of most of their streaming success shows Clay and
Buck Today at noon on fifty five KARC.
Speaker 2 (00:09):
Height No.
Speaker 1 (00:10):
Five here fifty five KRCD talk Station Happy Wednesday. Sadly
no judgenten 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 most of
us out in the world. It's that artificial intelligence doing
(00:32):
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 Use 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. He's the
president of Screen Education, which addresses issues at the intersection
(00:55):
of digital technology and human well being. We'll get to that,
including smartphone addiction, news, meat, bias, artificial intelligence, thought research, seminars,
and consultant. He, like most of us my age, started
out with World book Encyclopedias. Then he spent a decade
as an editor and publisher of college textbooks and another
decade in market research before heading on over to president
of Screen Education, got multiple degrees and again the seminars
(01:17):
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 3 (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 and 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 esked themate. 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.
Speaker 2 (02:52):
You know.
Speaker 1 (02:52):
Yeah, well, you know what. 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
(03:13):
damn degree. I don't want to sit in front of
a computer doing coding. And besides, Mom and Dad, I
can teach it myself. And we're like, well, well, and
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
(03:34):
was right. Why spend all the extra money 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.
Speaker 3 (03:57):
Right 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
(04:17):
gather information, you vet the information, then you have to
do the hard work to understand at a deep level
that information. Then you structure it, and then you integrate
it into your.
Speaker 2 (04:28):
Current knowledge base. Right.
Speaker 3 (04:30):
So I'm going to walk through this self directed learning
process so people understand the process and.
Speaker 2 (04:35):
How it works at each stage.
Speaker 3 (04:37):
Then I'm going to give an overview of chatbots, and
specifically I'm 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
(05:00):
large language models work, because I think if you can
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 you know specific ways
(05:21):
you use the chatbot to optimize your learning at each stage. Okay,
So I think it's really going to be helpful for
people to sort of 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 3 (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.
Speaker 2 (06:32):
Is accurate and correct. Right.
Speaker 3 (06:34):
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.
Speaker 2 (06:40):
You can't blindly trust the chatbot. You can't.
Speaker 3 (06:42):
So you you know, you've got to go out and
cross reference things. You 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 it's accurate.
Speaker 2 (06:52):
Right.
Speaker 3 (06:54):
So information literacy and judging the validity and truthfulness of
information is part of the vetting.
Speaker 2 (06:59):
The other part is.
Speaker 3 (07:01):
Is vetting information in terms of determining what what do
you given your goal?
Speaker 2 (07:07):
Right?
Speaker 3 (07:07):
Since you're the teacher, you're setting 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
(07:29):
relevant to the goal is actually relevant. 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
(07:51):
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.
Speaker 3 (08:03):
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.
Speaker 1 (08:10):
Like you know, for example, like a scientific consensus.
Speaker 3 (08:16):
Exactly 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, that the people doing the study
could could have been biased, they could have changed data.
Speaker 2 (08:32):
So you have to.
Speaker 3 (08:34):
Bring some judgment, and you know, there is some guesswork
in estimating. It's not a perfect process, but you can
do pretty well.
Speaker 2 (08:41):
I think you know. 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 3 (09:03):
Yeah, perfect, Yeah, perfect point.
Speaker 2 (09:05):
Yes you can.
Speaker 3 (09:06):
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.
Speaker 2 (09:26):
Right.
Speaker 3 (09:27):
So, 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.
Speaker 2 (09:46):
It gets to a point where it's it's what I.
Speaker 3 (09:48):
Call mirror, cognitive mirroring or cognitive achieving cognitive alignment with
with you.
Speaker 1 (09:55):
Right that you get 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.
Speaker 3 (10:14):
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 do you accelerate through the process
of having it.
Speaker 2 (10:23):
Aligned with you cognitively? Right? Sure you can.
Speaker 3 (10:26):
So you can almost do like a brain dump at
the beginning of the project. So it fully understands what
you want to do.
Speaker 2 (10:33):
And this is the thing, Brian.
Speaker 3 (10:34):
Once it knows, if it knows you're working on a project,
say like I use chat GPT to learn about large
language models and chet bots for this, for this talk
I'm 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 understand them at a way, at a
level at which he can explain them to a layperson, right,
(10:55):
And he himself is not like a tech expert, right,
so he has.
Speaker 2 (10:57):
To understand that of that level.
Speaker 3 (10:59):
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 exert in your talk.
Speaker 2 (11:15):
That's what it starts doing.
Speaker 3 (11:16):
And so you know, they can be extremely helpful once
they really fully understand what you're doing and what your
goal is and.
Speaker 2 (11:23):
How you're looking at the project. You know, I under
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 and 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.
Speaker 3 (12:02):
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 every
(12:26):
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.
Speaker 2 (12:40):
You an example.
Speaker 3 (12:41):
So these large language models, it's really complex stuff. So
I learned a lot more than the average person. 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
(13:01):
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 probability to
give you the next.
Speaker 2 (13:12):
Likely word in its response.
Speaker 3 (13:14):
So it's 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 starting to type the next word, and it gives
(13:34):
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 at three hundred Great
Oaks Driver for the live discussion. It's going to be fascinating.
Speaker 2 (14:36):
Michael.
Speaker 1 (14:36):
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 3 (14:47):
Yeah, well thanks, I hope, 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 gonna
Out of most of their streaming success shows Clay and
Buck Today at noon on fifty five KARC.
Speaker 2 (00:09):
Height No.
Speaker 1 (00:10):
Five here fifty five KRCD talk Station Happy Wednesday. Sadly
no judgenten 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 most of
us out in the world. It's that artificial intelligence doing
(00:32):
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 Use 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. He's the
president of Screen Education, which addresses issues at the intersection
(00:55):
of digital technology and human well being. We'll get to that,
including smartphone addiction, news, meat, bias, artificial intelligence, thought research, seminars,
and consultant. He, like most of us my age, started
out with World book Encyclopedias. Then he spent a decade
as an editor and publisher of college textbooks and another
decade in market research before heading on over to president
of Screen Education, got multiple degrees and again the seminars
(01:17):
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 3 (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 and 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 esked themate. 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.
Speaker 2 (02:52):
You know.
Speaker 1 (02:52):
Yeah, well, you know what. 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
(03:13):
damn degree. I don't want to sit in front of
a computer doing coding. And besides, Mom and Dad, I
can teach it myself. And we're like, well, well, and
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
(03:34):
was right. Why spend all the extra money 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.
Speaker 3 (03:57):
Right 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
(04:17):
gather information, you vet the information, then you have to
do the hard work to understand at a deep level
that information. Then you structure it, and then you integrate
it into your.
Speaker 2 (04:28):
Current knowledge base. Right.
Speaker 3 (04:30):
So I'm going to walk through this self directed learning
process so people understand the process and.
Speaker 2 (04:35):
How it works at each stage.
Speaker 3 (04:37):
Then I'm going to give an overview of chatbots, and
specifically I'm 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
(05:00):
large language models work, because I think if you can
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 you know specific ways
(05:21):
you use the chatbot to optimize your learning at each stage. Okay,
So I think it's really going to be helpful for
people to sort of 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 3 (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.
Speaker 2 (06:32):
Is accurate and correct. Right.
Speaker 3 (06:34):
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.
Speaker 2 (06:40):
You can't blindly trust the chatbot. You can't.
Speaker 3 (06:42):
So you you know, you've got to go out and
cross reference things. You 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 it's accurate.
Speaker 2 (06:52):
Right.
Speaker 3 (06:54):
So information literacy and judging the validity and truthfulness of
information is part of the vetting.
Speaker 2 (06:59):
The other part is.
Speaker 3 (07:01):
Is vetting information in terms of determining what what do
you given your goal?
Speaker 2 (07:07):
Right?
Speaker 3 (07:07):
Since you're the teacher, you're setting 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
(07:29):
relevant to the goal is actually relevant. 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
(07:51):
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.
Speaker 3 (08:03):
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.
Speaker 1 (08:10):
Like you know, for example, like a scientific consensus.
Speaker 3 (08:16):
Exactly 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, that the people doing the study
could could have been biased, they could have changed data.
Speaker 2 (08:32):
So you have to.
Speaker 3 (08:34):
Bring some judgment, and you know, there is some guesswork
in estimating. It's not a perfect process, but you can
do pretty well.
Speaker 2 (08:41):
I think you know. 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 3 (09:03):
Yeah, perfect, Yeah, perfect point.
Speaker 2 (09:05):
Yes you can.
Speaker 3 (09:06):
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.
Speaker 2 (09:26):
Right.
Speaker 3 (09:27):
So, 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.
Speaker 2 (09:46):
It gets to a point where it's it's what I.
Speaker 3 (09:48):
Call mirror, cognitive mirroring or cognitive achieving cognitive alignment with
with you.
Speaker 1 (09:55):
Right that you get 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.
Speaker 3 (10:14):
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 do you accelerate through the process
of having it.
Speaker 2 (10:23):
Aligned with you cognitively? Right? Sure you can.
Speaker 3 (10:26):
So you can almost do like a brain dump at
the beginning of the project. So it fully understands what
you want to do.
Speaker 2 (10:33):
And this is the thing, Brian.
Speaker 3 (10:34):
Once it knows, if it knows you're working on a project,
say like I use chat GPT to learn about large
language models and chet bots for this, for this talk
I'm 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 understand them at a way, at a
level at which he can explain them to a layperson, right,
(10:55):
And he himself is not like a tech expert, right,
so he has.
Speaker 2 (10:57):
To understand that of that level.
Speaker 3 (10:59):
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 exert in your talk.
Speaker 2 (11:15):
That's what it starts doing.
Speaker 3 (11:16):
And so you know, they can be extremely helpful once
they really fully understand what you're doing and what your
goal is and.
Speaker 2 (11:23):
How you're looking at the project. You know, I under
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 and 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.
Speaker 3 (12:02):
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 every
(12:26):
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.
Speaker 2 (12:40):
You an example.
Speaker 3 (12:41):
So these large language models, it's really complex stuff. So
I learned a lot more than the average person. 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
(13:01):
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 probability to
give you the next.
Speaker 2 (13:12):
Likely word in its response.
Speaker 3 (13:14):
So it's 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 starting to type the next word, and it gives
(13:34):
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 at three hundred Great
Oaks Driver for the live discussion. It's going to be fascinating.
Speaker 2 (14:36):
Michael.
Speaker 1 (14:36):
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 3 (14:47):
Yeah, well thanks, I hope, 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 gonna
Brian Thomas News
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