The Future of Generative AI: Insights with David Clinton

Miko Pawlikowski hosts an engaging conversation with David Clinton, author of 'The Complete Obsolete Guide to Generative AI' and numerous technical books. They delve into the significance of generative AI, its current impact, and its potential to revolutionize various fields. Clinton shares his extensive experience as an author, discussing the rapid evolution of AI and its implications for traditional publishing, technical writing, and more. The discussion also explores broader topics, including AI's role in content creation, potential effects on industries like accounting and publishing, and the future of AI technology. Throughout, there's a focus on the blend of technology and creativity, the importance of adaptation, and contemplation on what the widespread adoption of AI means for society at large.

00:00 Welcome to Hockey Stick: The Generative AI Revolution

00:22 Meet David Clinton: A Serial Author in the Tech World

00:41 The Impact of Generative AI on Technology and Life

00:58 David Clinton's Prolific Writing Career and AI's Role

05:13 Generative AI: Transforming Industries and Professions

09:11 The Future of AI: Opportunities, Challenges, and Predictions

24:08 Generative AI vs. Traditional Technologies: A Comparative Analysis

26:36 Exploring Alternatives in AI and the Future of Search Engines

29:55 Elon Musk's Ventures and the Future of AI

32:18 Exploring the Timeliness of Technological Predictions

32:33 Why Now? The Sudden Surge in AI and Technology

33:18 The Integration Revolution: From Discrete Tools to AI Agents

35:05 The Role of Data Availability in AI Advancements

36:26 The Legal and Ethical Quandaries of AI Development

43:29 The Practical Uses and Limitations of Generative AI

52:51 The Future of AI: AGI, Quantum Computing, and Regulation

57:05 Reflecting on the Journey: AI's Impact on Content Creation

01:00:49 Navigating the New Era: AI's Role in Writing and Publishing

I'm Miko Pawlikowski, and this is Hockey Stick.

Generative AI is eating the world just like software and

the internet did before it.

Probably everything you read and see today is at least in part

generated or touched up by AI models.

Revolutions tend to happen fast, but this one feels faster

than anything I've seen before.

Today, I'm joined by David Clinton, the author of the playfully named book" The

Complete Obsolete Guide to Generative AI".

He's a serial author of technical books, including titles like

"Linux in Action", "Linux Security Fundamentals", "Ubuntu Linux Bible",

"AWS Study Guides", and more.

When interrogated, he admitted to a dozen titles.

In this conversation, we'll cover why Gen AI, not to be confused with

Gen X, is such a big deal, why it's happening right now, what breakthroughs

made it possible, and how you too can incorporate it in your life right now.

And become more productive right away.

Welcome to this episode and please enjoy.

David, before I even met you, you've already given me a lot of trouble, because

for most of my guests I can more or less describe them in three sentences.

With you, on the other hand, I started looking up the books that you

wrote, and I can't even count them.

And, spoiler alert, David, I'm not sure he knows himself, because in one of

the chapters of his book, we're going to talk about, "The complete obsolete

guide to generative AI", he's asking ChatGPT to count the books that he's

written and ChatGPT doesn't know either.

So David, how many books have you written at this stage?

it depends.

Are you talking about the books under this name or under other names?

wow.

Okay.

Including your all other alter egos.

Yeah, but at least the ones with my own name, David Clinton,

various editions, maybe a dozen.

"Linux in action".

"Linux security fundamentals", Ubuntu Linux Bible".

I think you co-authored that one.

And there's a lot of study guides as well.

the Wiley study guides.

By the way, being a Wiley author, makes me a colleague of Herman

Melville, the author of "Moby Dick", because Herman Melville's publisher

was John Wiley himself 200 years ago.

The company somehow has survived 200 years.

And the chairman is still a Wiley.

It's Jesse Wiley now it's absolutely amazing how they've

survived and managed to adjust.

There wasn't a lot of AWS, training content necessary, required back

in the 1820, but, they seem to have adjusted and found new places.

However, maybe near the end of this run, because one of the, niches,

that generative AI is already eating is, technology training books wide

by a technology training book.

if, GPT can tell you exactly what you want to know right now.

Wow.

So that's reason enough to go via Wiley.

Did you prefer Wiley to Manning?

What's your favorite publisher at this stage?

They're very different.

and I like them both, each in their own way.

Manning is very demanding from an editorial process perspective.

And they take a long time on everything.

A long time.

That's why the book is called "Obsolete...".

they're good.

They put out a great product.

Wiley has a much lighter hand from an editorial perspective.

and, they have, excellent connections in the industry as much as possible

to move books in large numbers, and they're a solid, reliable company.

But they each have their value and each have the things they do best.

before I even opened the book, from the title I got the hint that it was going

to be a fan book, "The ,Obsolete Guide".

by the way, I'm still not sure how you passed that by the Manning

editorial team and how did they

too, they loved it right away, actually, I was really surprised I

threw that out I was angry with them.

They were taking so long.

So I just threw that title out and they actually bought it and they went with it.

that's remarkable.

So why did you write this book?

I read the book and, you basically put in there a legend slash myth, about

how they effectively told you to stop pestering them about using generative AI

and just write a book about it already.

is that the short version of what happened?

it's close enough, as far as I can remember.

we've had a good relationship for many years and, they've sometimes

asked me to do things I didn't want to do, and sometimes I've pitched

ideas to them they didn't want.

this one we were talking about on and off over a year, we were talking

about generative AI in different contexts, and then, they wanted to

invest heavily in generative AI as far as their books and other content.

They didn't want to get left behind, which is a very smart decision.

So a year ago, they were looking at publishing 10, 15, 20 books in

general topic of generative AI.

And they knew I was someone who thought a lot about it, so they

were pushing me to do something.

and I was pushing them to go away because I didn't think they could move

fast enough for this particular market.

somehow, I don't remember exactly how, but we latched on to this

project and, so far it's sold relatively well in its pre-MEAP sales.

sold about 1100 copies, so far.

And this is, before it's published and before it hits Amazon.

we can always, we can always hope.

And, but I'm not disappointed.

The process, has been reasonable, if way too long.

let's jump to the main question then.

why is generative AI such a big deal at the moment?

It's upending everything.

almost everything.

There are people who do things with their hands, who build the world

and keep the world going, they're in an excellent position and they're

still keeping the world going.

But everybody else is at risk.

but then again, 200 years ago, in the Industrial Revolution, we had the

same fears that there were certain mechanical tools and processes were

genuinely predicted and incorrectly predicted to be about to replace

the vast majority of labor.

And what would all those laborers do?

But it actually worked out quite well.

there wasn't mass starvation as a result of the industrial revolution.

There are other issues, political issues, but not the industrial revolution issues.

And, the economy and the market somehow reached an equilibrium and settled.

and as, progress has been significant in the last 200 years, probably

we're going to see something similar.

There's going to be huge upheaval.

Generative AI can do things that highly skilled people were necessary for 5

years ago, and are no longer necessary.

the things I do, I never truly understood why people bought my books.

like "AWS Solutions Architect Study Guide".

where did they think I got my information for writing the book?

I got it from the internet, right?

Like everybody else.

And if I could have gotten it from the internet, why doesn't everybody else?

I'm not saying you shouldn't buy the book, of course you should.

But, I just don't understand why.

if you're just willing to invest a little bit of research time,

you can get everything I got.

I'm gonna be replaced.

At least that part of what I do.

And, it's scary.

For good reason.

And it's, exciting.

And it is a big deal.

I don't think much of the hype is oversold.

This really is a big change.

When you were talking about construction site, I just remembered, I saw the

video on the internet and hopefully it's true and not AI-generated, but it

was basically a construction site with the scaffolding with a big banner on it

saying "ChatGPT finish this building".

they have experimented, I think, successfully already

with, print-on-demand houses.

where they can actually layer, a layer after layer of a construction material to

build the walls and even the ducting and some of the wiring for a house in a day.

it's interesting that you should mention that, because I think 3D printing, and I

will include the housing printing in that category, held such a premise not that

long ago, maybe a decade and a half ago when we were picturing everybody printing

anything, like in the sci-fi movies, when you just download something and then

you click it and a minute later you get an object, physical object, people were

talking about how It's going to be so dangerous because people can just download

a plan for a gun and print it at home, or they can do, replicas of things that

will be indistinguishable from truth.

But somehow that didn't really happen.

what I actually see people printing is parts for their, drones when they have

to go through quite a lot of propellers when they're racing them and, the

mandatory figurines that everybody prints when they actually buy a 3D printer

initially, and not an awful lot more.

So how do we know that?

Why are we so sure?

And that seems to be prevailing that the AI revolution that we're

seeing is different from that.

first I wouldn't say that, that, 3d printing is dead.

You're right.

it's, dormant.

but I think it is happening probably in niche areas where

it's making a difference.

they are printing, 3D guns, they're just not advertising it because in

many jurisdictions it's illegal.

I think that's happening probably more than we'd like.

so it's there and it'll find a niche, it'll probably find a market somehow.

However, AI I think is different, that's not to say that it's going to play out

exactly the way we think it will now.

but markets will discover, the value of AI in ways that

probably we haven't anticipated.

it's so broad and potentially complex, it won't be ignored.

There are too many creative people and imaginative people

who are focused on it now, that I can't imagine that substantially

transformative things won't happen.

I can't tell you what they'll be necessarily, I can guess.

but I can't believe that it won't happen.

This is a tool that's far too valuable to be ignored.

But, hey, I've been wrong before.

In fact, if you ever want to know how to anticipate the results of an election,

just ask me what I think, who I think is gonna win, and go the other way.

Because I'm always wrong in my predictions.

So you hinted a little bit at one group of people that you expect

to be particularly affected.

And you included yourself in the technical writing.

And I think to a certain extent I'm ready to agree with you.

Probably the ChatGPT version of, technical documentation is going to

be equally dry as the majority of the documentation that I come across myself.

Who do you think, who else, is at the highest, end of the possible, affection

of, their livelihoods effectively.

I wouldn't want to be a young accountant.

what accountants do is easily replicable by AI right now, and certainly in

the next few years, they, mentally process a lot of numbers and trends.

And of course there are a lot of accountants, different

accountants do different things.

They have different tasks.

But at core, they're processing data, whether it's financial data, or sales

data, and they're trying to, number one, organize it, so that they can

file their quarterly filings and their tax filings and everything, so they're

trying to organize the information, but also the higher level accountants

are anticipating where are these trends are going to affect their company,

the company they're working for.

And those are things that AI does exceptionally well already, and

it's only going to get better.

And when the time comes that they'll be integrating, accounting

processes into AI systems.

I think accountants will be looking for new work.

Another thing, I read an article last week by, the owner of a small

Canadian publisher, Sutherland House.

He wrote about a conference of publishers he was at sometime before, and they

had an AI specialist, whatever that is.

I guess that's me, I don't know.

And talking about how their industry was going to be changed.

And they spoke about things like, AI translation.

this publisher likes the idea of taking excellent European books or

books from all over the world that aren't written in English and have

proven themselves as popular and successful books in their languages.

But he said that translating them is expensive.

hiring a good literary translator Is not cheap and it's not cost

effective in his publishing model.

But, feeding the manuscript to an AI translator will get

you 80% of the way there.

And then you hire a genuine human translator to fix it, to get the last

20%, but it's gonna be much cheaper.

So those are things that are changing, but the AI specialist at this conference

then said, one thing, he said, you can say goodbye to all your interns.

And then the crowd, apparently the audience started screaming and shouting.

that upset a lot of people.

But it's probably true.

An intern at a publishing company, their job is to make all the

connections and do all the grunt work that the executives don't want

to do or haven't got the time to do.

And that's exactly the type of work, the moving information, making appointments,

making connections - that's exactly the sort of work that an AI can do well,

or will be able to do well soon enough.

So that junior knowledge worker is at risk.

And of course the problem there is that they, the new talent comes into the

publishing world through the interns.

They get interns fresh out of college and they train them up.

they get them to the point where they're.

capable of doing bigger things.

And if you wipe out the intern program, then you're wiping

out your feed of new talent.

That's disruptive.

But, how we got a publishing company justify or a government for that

matter, justify hiring hundreds of thousands of junior managers, if that

can all be replaced with software.

Let me challenge you a little bit on two aspects of that.

First of all, it's not particularly difficult to get any of these models

really to trip on basic arithmetics.

Like it's gotten a little bit better now GPT-4 that actually uses a calculator

instead of trying to, do the arithmetics in it's head, but it's still not

particularly hard to formulate it in a way that it doesn't trigger that and

gives you a demonstrably false answer.

I think you gave a few examples of that, from prior versions in the

book as well when you were asking about, a population, that's the

closest to the median in the list

can't remember.

Yeah, it's been a long time since I wrote it, but you're right,

definitely there have been problems.

Yeah,

So that makes me think that this is still better suited for situations

where you've got a lot of groundwork.

Like you said, the translation, for example, you can get it to be 90% good

and then get someone to do the last 10% and you save yourself 90%of the cost.

Great.

but is that going to work the same way with the accounting?

Can you get the accounts to be 90% good and then get

someone to check the last 10%?

Possibly.

I don't see why not.

they do have auditors for a reason, and they can just, adjust the role

of your company auditor to be looking over the shoulder of the AI rather than

all the, junior accountants possibly, it's hard to know how it'll play out.

But also as far as the errors go,

GPT and other AIs are prone to certain types of errors and they're working on

them, but, my experience with, let's say, I feed now, really large spreadsheets

and 400 page, corporate filings.

I'll feed them to GPT and, I'll get into look for anomalies and add up all the line

items related to this issue or that issue.

Basically doing SQL, requests on it.

it's very good and then I'll usually check it up.

I'll usually confirm, I'll load it up into, into Python and

Pandas and do my own searches.

and recently it's been pretty much always right.

I think the hallucinations are disappearing.

They've probably not gone completely.

And, we're gonna have fun still.

But I think they've turned a corner, I think, in that field.

With the exception, of course, of Google Gemini, which is a complete

and utter disaster, because they knew what they were doing.

everything I've read from insiders, they knew exactly what

they were building with Gemini.

It was a political indoctrination tool, and it was not there to

aid humans, but to guide humans.

Maybe they're right, maybe they're wrong, but it wasn't what they advertised it as.

And, I think at this point still Gemini is pretty much

unreliable for anything serious.

But, we've discovered that.

Maybe it would be true of other engines also.

And maybe in time we'll show that we were too harsh on Gemini, but at least

at this point, if I could back up a bit, 10 years ago, I was working for

some, I was involved with some startups and there's something about the startup

culture that I really appreciated.

I thought was very positive: when a customer would leave, an

angry customer would leave or an angry employee would leave.

Very often the startup culture meant that they would beg the customer or the

employee, tell us what we did wrong.

you're leaving, fine, we're sorry to see you go, wish you the best,

but just tell us what we did wrong.

We want to improve.

And I saw this more than once.

CEOs would send email blasts to the whole company.

"This is a problem somebody just reported.

I want it fixed in 48 hours".

They love to hear criticism, they wanted to improve.

It was a culture of openness and it's all about money, of course, but okay.

What's wrong with incentives?

there was a real culture of change.

I think a lot of startups from 20 years ago, like Google, have lost that.

Whether they want it or not, they can't do it.

They're so ossified.

They're so big.

They're so impenetrable.

And they're so enslaved to processes that they can't change even if they wanted to.

And they couldn't really genuinely hear criticism, even if they wanted to.

It's just, it's a shame.

I think it's probably a natural process of all organizations.

we know how governments work.

The large organizations are very hard to improve when things go wrong.

but it's a shame that to some degree we've lost that culture.

And I think, that leads to huge mistakes like Gemini.

there will be a shaking out of the industry that some

will do better than others.

So some AIs are going to improve and probably become steadily more

and more astounding and some aren't.

And, it'd be interesting to see which.

Google is such an interesting topic, and you're obviously not

the only one person saying that.

I've read, at this stage, dozens of former employees, or even current employees,

complaining about the same thing, that it's by no means anymore a startup.

And, that's, to a certain extent, normal.

Their size, their influence, people complain about the same things

like them killing projects and replacing them with the same thing

and renaming and rebranding and, completely not listening to customers.

But I think that Gemini, or in general, the AI, situation at

Google is, So interesting because they were at the forefront of that.

They spent a lot of money acquiring researchers, acquiring assets,

they were there from the ground up

It's wild.

And it reminds me of Kodak.

Kodak owned photography for almost a century, I don't know, 60, 70 years.

And they worked on digital photography.

They didn't ignore it.

I think they built one of the first digital cameras.

They were certainly in the first few.

And they did not ignore the technology.

But somehow, they couldn't pivot.

And they just didn't build a product that the market wanted.

And where's Kodak now?

So Google's sitting on a lot of cash right now, they invested probably

more than anyone in AI, and probably did ground breaking work which we're

using now, but, where are they?

there are other companies that are by no means startups and

they don't move very fast.

But for example, at this stage at least Microsoft's investments seem

so much better in that respect.

They basically more or less bought themselves OpenAI, by

the accounts of many people.

And they're integrating that like crazy into everything at the moment.

And where were they when Google was investing that, a decade ago?

There is, this document, internal memo that I don't think

we still know who wrote that.

It leaked about a year ago and it was called something around "We Have No Moat".

And neither does OpenAI, and I think the points that they were raising in

there, whoever wrote that, are, they basically materialized a hundred percent.

They were talking about how, all the things that Google is planning and hoping

to achieve, like running the LLMs, on your phone, that's already happening.

things like, scaling multimodality, today, this is all over the place, but the open

source picked it up and ran with it.

And obviously a big part of that is Facebook, leaking accidentally

their model, to, at least in my version of events to undermine a

little bit the hegemony potentially.

and give people alternative, but the open source models just run away

with that and there's no going back.

and then things like, cheap fine tuning with LoRA and later

QLoRA, all of those things are making it even more so than that.

Prophetic, memo, announced a year ago, And I just found it crazy that you can,

waste your initial advantage so badly.

Although it's interesting that I don't have the sense that there's a huge uptake

on truly open source and private LLMs.

I'm not sure how many people are doing it for themselves.

Yeah, of course, NVIDIA is selling a lot of GPUs to the people who

are doing this in their houses.

But I still see OpenAI and perhaps Anthropic.

Are still attracting a lot of customers.

And I have no numbers, but I suspect they have a large majority of the

market, for generative AI is going through those portals rather than

people doing it on their own.

So while it is available, there are LLMs you can build on your own.

I'm not sure how popular it is.

I remember a study, that was querying people about how

many models they're using.

And I think the most popular answer was either two or three different models.

And one of them was OpenAI, and one of them was local.

And I think the local It's easy to picture people hacking away in their

garages and, kind of movie-style Hollywood hacker, kind of thing, but what

I think is actually happening is that, In addition to using, OpenAI's models

primarily because they still got the biggest, chunk of the market, to do the

kind of workhorse thing and get projects started to get something off the ground

quickly, people are at least looking and investing into getting something that

they have some kind of control over.

And you can pick like a Mixtral you can pick, even a LLAMA, and if you're

using that for a particular use case that you can test, to an extent that

is actually feasible at the moment.

and you can look into how it's, behaving on your data in your, on your hardware

That gives you.

A massive advantage, like nobody can pull a rag from under you.

You download that, and initially the licenses were a little bit funny, and

you had to apply and do things like that, but now a lot of those models

are Apache 2.0, I think it's not necessarily a question of either/or,

it's more of a different use cases, make some of those options preferable.

If I was starting a startup and I wanted to get something

off the line very quickly.

It's like an obvious choice to get one of the APIs pay a few cents

per thousand tokens and get it off.

But as soon as you would like to make it, a permanent feature, and have any

control, I think, the local models really help hold a lot of progress.

We'll see obviously where it goes, but, I think that's how

I would describe it today.

jumping back to, my second challenge to you, I wanted to compare, the

generative AI that we're seeing today to self driving cars.

And, I think I remember the self driving wars of, what was it, mid 2010s,

when they were offering, researchers, multimillion dollar packages and

stealing research from each other and Waymo and Uber and everybody.

they got it to a point where it was, like, 90-something percent

good, but that wasn't enough, right?

It has to be effectively superhuman quality for people to get over the fact

that there's no one behind the wheel.

Why do we think that generative AI is not going to suffer from the same problem?

First of all, sometimes the stakes aren't as high with a self driving car.

You could be killing people if you make a mistake.

And that's definitely a threshold.

You don't want to slip underneath.

whereas generative AI, a lot of it, maybe most of it is just, 'okay,

so it gets a little math wrong'.

It's not going to kill anyone.

that may be part of it.

the second thing is that, generative AI is coming at us

from so many different directions.

And only one has to succeed and become the next, killer app or whatever.

whereas, self driving cars are self driving cars.

That's all they do.

And you either succeed as a self driving car or you don't.

by the way, I think self driving cars are probably gonna make it.

And they are still making progress.

I think in Las Vegas, they now have the Waymo taxis are actually on the

street running in real time, I think.

so that is eventually going to happen.

of course, 6-7 years ago, they were predicting that all transport

trucks would be, driverless by the year 2020, or whatever.

but then again, having said that, when I was in high school, my

geography teacher told us about the Club of Rome predictions.

This is, by the way, back in the, late 70s.

So the Club of Rome predicted that the world would run out of gold and platinum

by the late 1980s and would run out of, petroleum by like a 1990 or so, and

would run out of food by about 1995.

I guess that didn't happen.

maybe some of these predictions aren't to be taken that seriously either.

I do think that generative AI has a much better chance of pushing

through obstacles simply because There's so many ways it could go.

And there's so many, so many possible happy endings.

would you venture your best bet of what's going to be the

real killer app coming first?

I would say that Google with their their lack of a moat is a good target

in the sense that internet search, may disappear as a business model and as a

use case, simply because, augmented AI search is probably going to be better.

The, last three, four months, I think I've had a, ChatGPT+ subscription.

I bit the bullet and did it.

And I'm happy I did because it's pretty amazing.

So when I ask, ChatGPT+ to find some current information, it'll

activate Bing and go search.

So that's only going to get better.

And with the power of AI itself, married to the ability to search

under the hood, the entire internet.

Why do I need, Google search anymore?

A search engine has been the way we organize the world for the last,

15 years, 20 years, I don't know.

Okay.

And it's the way we think.

When you go to the internet, your thought was "let's go to a search

engine and get there that way".

It may not be rational to use that in a year or so.

so I would say that would be a big upheaval.

Because it's not just Google that's gonna be a victim of this.

Every person who's ever optimized his website for SEO,

that advantage will disappear.

That'll be hugely disrupting.

certainly.

wouldn't even know how to approach building a website anymore.

Because, your mind is set.

you optimize for SEO.

But, maybe not.

Yeah, it's crazy to think how much we rely on Google, so many people rely

on their SEO for their livelihoods.

And like you said, obviously you have to optimize for SEO,

otherwise nobody will find you.

So you have no traffic, so you earn no money.

but Last time I checked, or I vaguely remember, I think about 80% of Google's

income was still coming from ads, and lately, I don't know if it's just me

thinking about it more than before, but I started noticing that most of, my first

page, it's basically ads at this moment, so I do wonder, in the back of my head,

if they just assumed that was gonna die.

So they have to like ramp up and make as much money as possible right now

Squeeze whatever they can out.

Maybe.

Have you, have you tried?

Yeah.

Yeah.

for them, and it's scary for everyone who relied on ads.

Yes.

the rudimentary version of that you can use like GPT or premium or whatever.

There is a thing I've tried called Perplexity, full disclosure, no,

connection to them whatsoever.

How did you find that?

as far as, simple questions, code, if I asked for code or if I, asked for,

a thinking question, it's been close.

It was close to GPT.

I haven't used it for a couple of months regularly, but, I was impressed.

It didn't have the extra functionality of GPT+, So you couldn't upload a document

and have it analyze the document, but as far as just talking with it, it was

fairly close, as is Claude by Anthropic.

for some reason in Canada, they didn't fully release it even yet completely,

but that much Claude I'm allowed to use in Canada, I found it to be,

definitely comparable to, to GPT.

I don't know how you feel about Elon Musk, but have you tried Grok and the X AI

No, I haven't tried it yet.

by the way, I love watching Elon Musk.

He's so much fun.

and the guy is, controversial, he's crazy.

but that's all part of the fun, right?

he's done things with SpaceX that are just so exciting.

what every nerdy kid would have wanted to become.

He's doing it.

He's living the life.

Yeah.

so now when I test a new chatbot, I'm bored very quickly because I've,

talked to them to death before, but Grok is differentiated by being,

the opposite of safe and boring.

So you can get it to say a lot of things very easily and, Even when

you try, it's not gonna give you like this boring, dry, answer.

Which is, at the very minimum, refreshing.

And they actually open sourced, the model, recently.

On what seemed like Elon Musk's complete whim, one day, to look better than OpenAI.

Alright.

a surprise, who saw that coming?

That Elon Musk would have a whim?

from what I remember, it's a mixture of experts architecture that was 300 and I

want to say 20 or 40 billion, parameters.

So despite being only 25 percent weights active at a time, you're

still not going to be able to run it on anything anybody has at home.

but you can talk to that if you've got, X premium or whatever, if you give Elon Musk

money, which is an interesting sidequest.

Which also reminds me, speaking of Elon Musk, I think another

whim, on the 8th of August, we're supposed to see the Robotaxi.

the speculation is that he was, working on, Model 2, or whatever the cheapest

version of Tesla is supposed to be.

And, he internally killed it to push for the self driving taxi

that doesn't even have a steering wheel or anything like that.

And then Reuters wrote something about how, the, that model was dead

based on people's, leaked opinions.

He called them liars.

Something happened.

And the next day it's Oh, we're going to unveil Robotaxi in a couple of months.

So trademark, Musk, PR, version, but I am curious whether it's going to

be svaporware or whether we're going to see anything substantial on that.

with his track record, the odds are pretty good.

Of course, you have to be careful where you tell it to take you, because

you may end up on Mars or something.

I guess the caveat to that is that the track record of delivery.

Yes.

But the track record of timelines, is usually a few

years skewed, but, we'll see.

Anyway, Before I get asked to go on a grand tour of the different, use

cases that you discuss in your book, and I think a lot of people might

find it valuable, and, they'll just go and buy your book right away,

I wanted to also touch base very quickly on Why it's all happening now?

Because a lot of these ideas, if not all of them, are decades old.

what happened?

Why is it happening now?

Is it all thanks to gamers and crypto miners?

partly, it's certainly technology, gains have been significant

in the last five years.

and, Moore's Law is always shaky, it's about to break,

because we're moving too fast.

But, I think the big thing is integration.

Whereas 3-4 years ago, you could do, image segmentation, let's

say, using a deep learning model.

You could do it three years ago, five years ago, ten years ago,

probably, but it was a discrete tool.

You could use it for that and only that, and don't try to

integrate it with anything else.

what's happened now is that we can integrate, let's say, the entire

internet with the generative AI model and an engine and then integrate

that with the way you work and think.

So I can talk to it.

I can type to it.

I could plug it into my company is and its workflow and have it manage things for me.

I think that's a big deal.

We're starting to see, I guess, the first stages of AI agents, which is, it's going

to push us a lot further I would imagine.

I ask an AI a question, I don't know, about my business, I want to launch

a Twitter campaign to promote my new product, and so it'll tell me how to

do it, but I say, be my agent, now go do it, and, people have done this

already, actually, people have connected Twitter accounts to a GPT and actually

had it manage their social media.

probably a huge improvement in most cases over the real thing, but I don't

know there's an accident, you make a claim to your car insurance company.

the AI could manage the insurance processing, it'll contact the underwriter.

And it'll collect all the details of the accident and what the insured property

was and send those to the underwriter and the underwriter will send back

an answer and it'll go to the bank and it could actually handle complex

processes, independently and reliably, at some point reliably at any rate.

So this integration and then the next step integration with creating agents,

I think has been a big game changer.

it's taken a lot of discrete technologies and brought them together

into something a whole lot bigger.

Would you say that the datasets available also played a role?

I

yeah, and not only, have they been getting, oh, taken as one of the

projects I'm involved it would seem on the surface to be really unrelated

to anything I've done before.

I have a, substack called the Audit, where I write about, policy

analysis in Canadian politics.

It's not something most people even in Canada are interested in, and

certainly not outside Canada, but, the underlying premise of the site and of

almost everything I write there, is that governments and institutions make

an amazing amount of that data freely available, so almost everything that goes

on in Canada's parliament has always been recorded in a document called Hansard,

but now it's all available, and not only available online in, digital format,

but it's now, sadly JSON rather than CSV mostly, but it's available in a format

that you can actually work with, and you could do a deep data analysis with it.

So governments on all levels, all over the world, almost,

are producing a ton of data.

As are various types of institutions.

And that data is all becoming available.

It's all becoming available, through APIs and, in automated context.

So yes, that has made a huge difference and it's going to make

a much, much bigger difference.

the further we go on this line.

think there is also a slightly more nefarious, or I guess, gray area

to that, which is, exemplified in this massive lawsuit against OpenAI

from, the New York Times, I think.

That alleges that they should, be compensated for the demonstrable

fact that their model that's bringing them billions of dollars was actually

trained on, the body of work that they've accumulated over decades.

it's interesting because it seems to be very divisive.

A lot of people say, 'oh, If I read the articles and I write something, you're

not going to chase me', which is fair.

A lot of them say that, if we allow OpenAI to go with that, and then the next ones

can't do that, they get unfair advantage.

There's a lot of facets to that, and I'm curious, personally,

which way it's going to sway.

A lot of people don't like the copyright law right away,

which is also understandable.

but I am curious, how that's going to play out, whether going forward,

things will continue getting more open or whether it's going to be the

opposite, because even before the ChatGPT revolution, I want to say.

places like Reddit, for example, were guarding what effectively is their IP from

Google, because they don't want Google to serve you ads and get paid for that.

They'd rather you came onto their platform and clicked on their

ads, to prop their business.

do you have a firm opinion whether, which way you expect this to go?

These are tough questions, obviously.

I appreciate copyright protections.

I'm a writer.

And I create courses, and I create books and content, and

I appreciate being protected.

And if I wasn't protected, arguably, I wouldn't be able to

write and create this content.

In my particular case, that probably wouldn't be true, because thousands of

people have copies of my books illegally.

on the dark web and it doesn't really hurt my business that much because my customers

buy through normal channels and, it's really hard to market my stuff illegally.

but nonetheless, creators should be protected because they have

to be incentivized to create.

On the other hand, there's only a certain distance you can push that.

I've heard the argument in the New York Times case that New York

Times authors Generally learn to write by reading Ernest Hemingway.

Does that mean that the Ernest Hemingway estate has a claim against

the New York Times writers for a portion of their intellectual property.

no one's going to say that when it's a question of training.

If it was taking content or taking ideas, okay, that's would seem to be a clear

copyright violation, but when it's a question of training, I've heard the

argument that, that's not a violation.

everybody trains on something, the whole purpose of content is to train people,

how to read and write and think And of course we want people to learn from us.

And of course you expect that and you can't prevent that.

If you're going to put something in the public domain, you have to expect

that people are going to use it.

so these are tough questions.

it's, going to be hard to find a balance.

I don't know, how it's going to play out.

The odds are, technology will probably win.

I have never seen technology lose for better, for worse.

I guess we have seen technology lose.

And you think of.

the, nuclear energy industry, it lost in a lot of countries, like Germany.

the, nuclear energy genuinely has produced, the carbon neutral

energy, expensive but clean energy for decades and decades.

There have been a few accidents, tragically, but, by and large, the

energy has been clean, relatively affordable, and has many upsides and no

downsides, and yet, the technology has been rejected in certain jurisdictions.

so I guess technology can lose, but by and large it doesn't.

So if I would have to bet money, I would bet against the New York Times, I

would bet, with technology, prevailing.

in other words, the use of, of AI expanding.

I like both your example and your counterexample and it's probably because

I've been watching, on Netflix, Lincoln Lawyer for last couple of evenings.

so I want to say it also has to win in the court of public opinion.

and that might actually be more tricky than, anything else.

The point that you make in your book about open research on that and how that

accelerated this, there's been obviously open research by some people who strongly

believe that in that there was a research behind a cluster, but would you like to

describe briefly what you meant in the book when you said that this, Cambrian

explosion of generative AI that we're looking at right now is in part made

possible by the open nature of research.

as I think Linus Torvald said in the context of open source software,

many eyes make problems lighter.

That is, the more people who are reviewing your research and trying to replicate

your research, the greater the chance you're going to find problems faster

and improve things better and faster.

that was the premise of peer reviewed medical studies, which, of course,

is apparently how it's collapsed and is in complete shambles now.

But, in the open source world, and, particularly in a lot of

the early research into AI, there was a spirit of collaboration.

And much of what was created was put into the public domain and was shared and

commented on and, improved as a result, and there was a lot of money invested.

but there were an awful lot of people involved in the research.

And they're, as far as I understand, I have to be careful what I say.

I can't talk about too many details.

One, because I'm ignorant.

And two, because someone, actual pioneer in the AI research world, read my book,

"the, obsolete guide to, generative AI", Manning thought it was a good idea to send

it to him, just to see what he thought.

And, the appendix at the end, which also includes a brief history of

the AI developments, he really didn't like, and he felt that I

had misrepresented, a lot of the pioneers and the specific, processes

in advancing various AI technologies.

One step at a time, he felt got it all wrong.

He was an insider.

He was involved in a lot of the original research.

So the problem is, he's probably right.

Yeah, he's probably more, a lot more accurate than I am.

I'm not 100 percent sure how to take it though.

this was a complex history with personalities, and sometimes

personalities that didn't get along well with each other.

This is the academic world, after all, where you can't become a

great academic unless you don't get along well with people, it seems.

so I'm not going to go into any detail about, how exactly it happened, and

who were the big movers and shakers, but it did happen, and a lot of it was

done in an open, collaborative format.

So are you going to keep the brief history in the appendix, or are you going to

we are updating it.

because again, he has a lot of credibility.

from your description, there's probably about five people, that

said that I could place in that role.

I'm curious.

But let's leave it at that.

I promised, people a little bit earlier that we'd go through a little,

tour of the different use cases.

for anybody who's going to now go and put the money on Manning's website

to receive goods in exchange, the book is very hands-on, it doesn't

waste too much time, explaining how these things work under the hood.

It goes more into "oh, here's how you play with it, here's what you can do,

let your imagination run, go crazy.

it will help you become more productive, the way that it did, to the author".

If we were to pick maybe three or five most favorite examples of you that

you covered there and that you think, provide the best bang for your buck

experience, which ones would you go with?

I'd say the one that excited me the most when I did it was

using the tool called AutoGPT.

That was an API tool you have the open ai, API tool, key.

And you would feed.

the tool with a set of detailed instructions.

I want you to go out, research this on the internet, then take the outcome

and, distill it this way, and then I want you to draw a conclusion

about this and calculate that.

You get the detailed instructions, it will go out and search the

internet, get information, gather it, come back and iterate over

many steps, give you an answer.

That was really exciting.

The downside is it was a complete failure.

the technology, as far as I know, more often than not, it just

goes into these, death spirals.

It loops over and over again, the same iteration over and over, it never stops,

just keeps costing you more money.

however, the few times I actually did get it to work, I was considering

whether to create a course on Udemy on a particular, LPI, Linux Professional

Institute, certification that was relatively new, and I wanted to know

how popular is that certification?

How likely is it that users are going to want to buy my course,

and then take that certification?

So I had it, go out and research the popularity based on social media posts

and based on Internet evidence, assess the popularity of this technology

versus three other technologies, which I knew how popular they were.

I had a good sense of how effective they were.

and it spent, 45 minutes or so and about, $2 of my money or something

like that, and, came back with a coherent and a numeric answer.

I said, "you're on a scale of one to a hundred.

How would you rate the popularity of each of these four technologies,

or these four certifications?"

And it came back with a good answer.

May even have been correct.

So I thought that was fantastic.

that's going to change the world.

it may change the world, but it won't be AutoGPT that does it.

But yes, that's a type of agent that I think has a lot of potential.

I'm not sure exactly whether they'll get it right, but it'll,

someone's going to get that right.

I have to say I'm not impressed with the AI music and video yet.

everyone else seems to be, but, we have 300 years of all the world's

music on Spotify available 24/7, right?

Do you really think that AI is going to make something better?

it may make good stuff, but there are millions of pieces of music that I've

never listened to that are probably excellent, probably outstanding,

but I just don't need enough time.

So do we really need more music, even if it is good?

and what makes good music?

I don't know.

So AI music, I'm absolutely not impressed with yet.

Okay, everybody skip the music chapter.

It was just a music paragraph, actually, if I remember correctly,

there's this one paragraph, AI video.

the OpenAI tool SORA.

which is producing these 30 second clips of video.

Also, it's ho hum.

I don't know.

they're obviously AI.

They're nice.

They're visually attractive.

But, show me something with a little more substance.

I'm really not there yet.

but, who knows?

Things change.

AI voices, by the way.

Voice cloning.

is something that a number of companies have been offering for quite some time,

and OpenAI just announced they have their new voice cloning tool, from 10 seconds

of your recorded voice, they can then reproduce your voice reading anything.

No one's shown it to me yet.

I'll believe it when I see it.

In other words, can they produce voice that won't be recognizably machine?

I think that's very high bar because so much goes into this little

hints and the tempo and everything.

But I do think that there's been a massive improvement in

that you can listen to that.

you're not going to be fooled into thinking that it's a real person.

but your ears are not going to fall off after at the end of it, there's

a lot of websites that integrate that to, have the audio instead of

reading through a longer article.

And I find myself using that a little bit more than I did before.

for example, if I need to do something else, I can just put it down and

listen to the article a little bit, if it was a podcast episode.

However.

That's not gonna fool me.

I think that transcription, on the other hand, is getting closer to

basically as good as it's gonna get.

because, we're using that in a couple of projects.

For example, my brother and I, we run a series of technical conferences.

And people submit their talks, and it's a lot of, subscriptions to make.

We initially tried to get them done by hand, and that was just not gonna happen.

we integrated that with Assembly AI right now, and it's about 90, I

don't know, maybe 5 percent good?

To the point that, the things that it doesn't get very well sometimes

is things like names of things.

But it's good enough that mostly you can ignore the mistakes at this stage.

So I think that's going pretty good.

on the image and video thing, I think I would agree that people started

talking about how Hollywood was going to fall because SORA could generate

30 seconds of a coherent image.

There was a lot of excitement about that.

There was a project called Pika Labs, I think, before that,

and that also could generate 30 seconds or something like that.

Some of them looked funny.

Some of them looked like a very low budget animation from the 2000s, and

some of them just looked rubbish.

but the one, one exception to that, I think is I remember when I went

back to using midjourney after I initially tried it and wasn't

impressed and it just started.

lIke 'killing it'.

I think it might have been about a year ago or something like that.

I went back and I started generating some images.

I was just so impressed how good they were.

they had all the fingers and no additional

right number of fingers,

Yeah, and the faces and, and people started coming up with this tricks on

how to generate like consistent faces.

If you wanted to generate multiple pictures of your character, I think

it comes out of the box with that now.

for everybody I talked to replaced stock images.

Instead of going and paying for a stock image, you can get a custom one and you

can ask it to tweak it until you like it.

And so for this like going back to what you said, generative AI versus,

self driving cars, when the stakes are lower and you can accept some

problems, it's working well enough that it's just replacing that.

In terms of music, that's a little awkward.

All of the music, for this podcast is AI generated.

It can be good, I probably won't listen to the music of

this podcast hours and hours on

Oh yeah.

It's about 15 seconds, so it should be okay.

But

for that purpose it's great, but I don't think it's going

to replace people's playlists,

no, I don't think so.

Unless you're talking about the actual playlist, algorithm, because I think

Spotify has been very loud about how they're going to replace your playlist

and basically get AI to find the songs that you, they think you're going to like.

Facebook or whatever social media is keeping you

algorithmically, hooked to that.

And that, I believe they might be onto something.

There's probably, an optimal algorithm that can get you hooked and, addicted,

to as many songs as possible.

there's also that.

for anybody else who wants to, get the nitty gritty of how to,

actually play with all these things and test it for yourselves, there

is a sequence of chapters on all of these things and more, including

as well as what we covered, things like code and, talking to documents.

I think there is a little example where David is getting some kind

of AI to talk to a PDF containing Tesla's financial statement and

it's actually working very well.

So there's that.

it's gotten a lot better since, especially with the GPT+, a lot of barriers

have fallen, with my writing from the audit side, I'm able to do things.

in an hour that a traditional journalist would have taken a week

or two if you could do it at all.

But I'm doing it because of AI's, and GPT's incredible processing powers.

yeah, thank you gamers.

If it wasn't for you, we have never gotten Nvidia to make all those GPUs.

as you can probably imagine, I'm not going to let you off the hook before I

try to squeeze your wild prediction about things like AGI and things like regulation

and things like quantum computing and where you think that is going.

So maybe let's just bite the bullet and go there.

AGI.

I'm not sure exactly how we'll measure it, because there's so many

things that GPT, for instance, does so much better than I could ever do.

and faster.

Big Blue, beat Kasparov in chess, right?

So that was one discrete task, which is a very complicated task.

That's already 20 years old or something in that area.

but there are many things that GPT can do infinitely faster than I can.

is that AGI yet?

I'm not sure how we define it.

I think it's, inevitable.

My humble opinion is that AGI, if not now, certainly in the next couple of

years, I would imagine is inevitable.

Is it a good thing or a bad thing?

Personally, I don't stay up at night worrying about the AGI apocalypse.

that the, AI is going to, push off the shackles of humanity and

take over and destroy us all.

But, hey, who knows?

In any case, betting against it's not going to make any money because

you won't be here to collect.

so as far as AGI, I think it's inevitable, if not now, soon.

as far as, quantum computing, I don't, I've read a lot about, I've

read some about quantum computing.

I know that, I have a very vague understanding of what makes it different,

and how it'll be so compute intensive.

it could be that quantum computing will solve the energy

problem that AI is facing.

Maybe.

That is, Platforms, like OpenAI, require thousands of CPUs chugging

away in data centers, and some of them require their own nuclear energy

generators just to keep them alive.

There isn't enough electricity in the world being generated

to keep this stuff running.

And, of course, they're adding on, the electric cars, that are all supposed

to be fed from the electrical grid.

And there isn't enough electricity.

And the chairman of Toyota and Elon Musk also both warned that if every car sold

in 2030 is an EV, we are not going to have enough electricity to run it and to

power your shaver, there isn't enough, so we're coming to a crisis probably soon.

quantum computing, if it scales up fast enough, might be more efficient

from an energy perspective and might head off that crisis that they'll

still be able to exponentially grow the compute base of these platforms

and have enough energy to feed them.

Possibly.

That's, it's a complete guess and don't take it all seriously, but it's possible.

the downside, the real downside of quantum computing, of course, is that all our

passwords will be assumed to be broken.

Because the, the RSA algorithm will probably be cracked fairly quickly once

quantum computing becomes commercial.

if someone had, penetrated your, private website or your private, data, 2-3 years

ago and saved the data archives, unable to get to it because it's encrypted

because of course you use good passwords.

but once the quantum computing allows us to crack the RSA algorithm, they can

retroactively access everything that they've saved, because it's all behind

a, an encryption that can be broken that it has or will have been broken.

Okay, that's a possibility.

As far as regulation goes, as I wrote in the book, I believe,

this can't be regulated.

governments can jump up and down and kick and, scream as they always do.

and pass legislation that, severely restricts the, developments in AI.

It's not gonna change much, because it's out in the open.

It's out in the wild.

People will do with it what they want.

The market will do with it what it wants.

some have argued, as you probably read, OpenAI's requests for government

regulation might just be, a subtle attempt at, at locking in the market.

since it's on top, once the market is regulated, no one else will

be able to enter the market once they're, on top, they'll stay on top.

So some have interpreted it that way, as I'm sure you probably read.

but I don't think it's practical.

Some things can't be regulated.

it wouldn't be the first time.

I remember a certain Zuckerberg, pleading a very similar case

Fai enough.

I wanted to do one more thing before I let you off the hook.

I found your chapter, I think it was chapter 11 where you presumably

got some friends, who happened to be experts in, in AI and you asked them

a series of interesting questions like, "what were the problems", "what

were the biggest surprises", what do you actually use the most, and

all of that, what were the biggest unexpected items that you sell them?

you know, you obviously went with some presumptions of what

you were going to see there.

I'm curious what you got that you didn't sign up for.

That's an interesting question.

And sadly, I can't remember the details well enough.

I appreciate it.

I do.

The answers were great.

And I was, it added a lot to the book, I think.

But sadly, I can't remember them in detail.

I didn't, it was, I have to say that I was expecting some more embarrassing,

step on a rake incidents than I got.

Cause I've had plenty of step on a rake incidents myself.

I'll tell you an example.

I'll come out in the open and tell you one of my, I guess you can call it

a failure, but it was an experiment.

Early on when possibly before GPT-3 came out, I I started with OpenAI.

I believe it was still GPT-2.

I'm not sure they called it that, but I don't remember

now, but it was before GPT-3.

right at the very beginning, I I experimented to see how it would, generate

written content, technology content.

So I I conversed with it back and forth and got from it,

the content for five books.

One was on, low code.

another was on, a couple of security topics.

I don't even remember.

And I assembled all the content and I edited it to, to give it some

coherence and give it a narrative and a flow and I published them.

And I, I just want to see what would happen.

Can I effectively in two hours, I went from zero to up on Amazon Kindle.

I wanted to see if there was a business model.

so first of all, I'm not the only one who had that thought, right?

So Amazon is now flooded with literally millions of such books

and most of them are trash, and most of them you can tell pretty quickly

are trash and people avoid them and the market is correcting for that.

Amazon asks you now, whenever you upload a new book to Kindle,

they ask you, was this, or.

was all or most of this book generated by, an AI.

So they want to know.

They're not penalizing you yet, but they want to know, and it's a fair question.

these four or five books, I did publish them.

I'm not embarrassed by them, because I think the content is useful and helpful.

I think it's genuinely helpful content.

I read through it all, and I don't think there are any mistakes there.

I don't think there's anything misleading there.

But it's cheap.

It's not something I'm particularly proud of.

But I did it, it was an experiment, and I, I think the whole thing

took me two weeks, all five books.

Tempting and interesting.

So they ask whether 50% or more of the book was generated.

Something like that, it was a substantial amount of the book

generated by AI, maybe the word they use is substantial, I don't remember.

they're facing this problem, they have to figure out a way to deal with it.

Their platform is being flooded with this garbage.

Yeah.

Although even with, legitimate books, I would expect that very

close to 100% has some percentage that was at least rephrased

You have to be crazy not to.

it can make you so much more efficient and more accurate, as

long as you use it carefully, and as long as you don't abuse it.

The sum of my book, "the, obsolete guide to generative AI", 10% maybe?

20%?

I don't know.

is, is AI generated?

I

a good, path to do a newer revisions.

You just, regenerate the book with a newer AI.

that's possible.

actually, Manning and I were talking about that, a lot of their authors

are not English as a first language.

There are foreign language speakers, primarily great technologists,

good authors, but English is not their first language.

So they have a lot of problems sometimes getting a manuscript from,

the author's computer to a publishable state in English, and they'll invest

a lot of money in that sometimes.

So they wondered, and we were playing around with the idea

of feeding chapter by chapter.

Into, GPT and then getting it to revise the book, to rewrite the chapter,

I don't know if they ever used it.

I gave them a couple of, proof of concept experiments.

I'm not sure they ever actually applied it or not, but it's an

interesting idea, certainly.

at this rate, we're just going to end up with, everything touched or rephrased or

rewritten by AI, Going back to what you said about SEO, there are so many people

really banking on spitting out so much content, generating entire websites just

to capture some of the traffic with AI, which sadly means that the era of someone

having a website about something that they're interested in and that being,

found is just gone by now, I think.

how that's going to fall out.

I don't know what's going to happen To the accessibility of the internet,

that I don't want to predict.

yeah, it's weird, when I speak to different people, I feel very different.

for example, I was speaking to a friend and, about how people rewrite their

text with ChatGPT and technically they wrote it, but not really.

yeah, it's generated by AI.

Almost exactly what you were describing about getting a chapter and getting

it to be more English first language.

and, the argument was, would you also tell me to not use

autocorrect or like a dictionary

that's cheating, which kind of shut me up.

And I've used that argument since on the other side, and that made me feel, "okay,

that's, that's probably a silly argument.

But then on the other hand.

I wonder if people who sell cars and they were like, Oh, no, we

like our horses and what's going to happen to all these horses.

And no, this is cheating.

It runs on petrol.

It doesn't even have to stop and drink water.

Whether I'm one of those people, sometimes when I speak to my friends,

it's weird times we're in, isn't it?

Yeah.

thinking back, 10 years to how workday went and the tools I'd use and my

first book I wrote, 35 years ago.

was, probably before you were born, possibly.

I wrote it as I mentioned somewhere, I wrote it on paper with a pen.

And, you write differently.

When I wrote, on a typewriter, you write differently, cause there's

no correct, now forget about autocorrect, there's no correct at all.

See you're stuck with the version you have, okay, you could

use that, what was it called?

you probably don't remember.

They used to have this.

Correcto type, I think it was called a little tool.

You could add a little white ink over a mistake in a typewriter.

it was kludgy and you just had to get it right the first time.

I've seen it round the time that word processes became popular 25 years ago,

some editors, one editor in particular said that she can always tell a

manuscript that was written on a computer.

Because there'll be far more stupid mistakes.

On a typewriter, when you're nervous and you can't correct it, you think

about it very carefully before you type.

On a computer, you, nah, just go back and get it later.

And you usually don't.

that's from the typewriter to the, word processor stage.

But from the word processor stage to, AI, the changes are going to be, are

going to be fundamental and remarkable.

Heh

who, wants to go and jump the book, once again, it's called "the complete obsolete

guide to generative AI", it's available at manning.com and it's got a lot of humor.

And if you don't mind, I'm just going to quote you on what you just described.

The book says.

Let me give you some context: I'm a lot older than you might think.

I wrote my first book on sheets of paper using a pen.

It may have been a very old technology, but it was solar-powered.

it was only useful when I opened the window or turned the lights on.

That's the kind of humor that you're going to get in droves, when you read through,

David's book, David, thank you so much.

This was absolute pleasure.

Hopefully, next time we speak, we are both not replaced by AIs, or

maybe we are, and it's actually going to be a better conversation.

Or maybe we are already.

How do you know that these aren't, avatars, and deep fakes?

But, I think you're real, and I'm fairly confident I'm real.

and I, as a real person, I enjoyed this, this conversation, and I'm

looking forward to seeing where it goes.

and so did I, at least in this version of the simulation.

Thank you.

See you next time.

Take care.

Thanks a lot.

Thanks.