Welcome to the Innovation Conversation, a podcast
about innovators, both in business and real life.
Hosted by myself, Ricardo Rescual and Harry McCona.
Today's episode is sponsored by Hyperskill. Hyperskill
is a learning and training platform that enables
people from all over the world to learn new tech
skills. If you're looking to learn new tech skills,
this is the platform to choose. You can find
out more about them on hyperskill .org. Today
we are joined by Elon Buckner. one of the godfathers
of AI. Ellen, thank you so much for being here
and being one of our guests in the podcast. If
you'd like to introduce yourself to the audience,
please. Sure, let's see. I've had about a 30
-year career. I co -founded and sold a software
company to Thomson Reuters. I was a hedge fund
portfolio manager. I built a practice selling
AI to asset managers, consulting practice. I
spent three, four years in big tech at Microsoft
and Google. I was most recently head of AI at
a company called Factset. And just recently left
about a month, month and a half ago to explore
a startup project. I have so many questions lined
up, it's absolutely crazy. So one of the things
we normally like to ask in the podcast, it's
about your own journey as an entrepreneur. So
how hard was it, because you sold the company
a couple of years ago, so how hard was it to
get started, get funding, get any funding? So
do you want to tell us a bit more about that
journey? Because you are a very successful entrepreneur,
right? Not everyone can actually go through an
exit and an exit to Thompson. Thompson writer,
right? So it's it's not an easy thing. So you
want to tell us a bit more about that? Thank
you, Ricardo. You know, every every journey,
entrepreneurial journey that I have is completely
different. I haven't cracked the code yet. But
I can tell you about my first one. And it was
it was pretty amazing. I was I was a couple of
years out of college. And I got together with
a few a few contacts through Family Connection.
and they were just getting started. It was basically
me and maybe one or two other co -founders. We
were just in an empty office and we were trying
to figure out what to do. We started out bootstrapping.
The bootstrapping recipe that I'm familiar with
is to do consulting. Back then, my background
was in web design. I had worked for this early
web design leader called agency .com. They did
the first website for American Express and for
Itachi and for a few other major brands. And
my partner came from Microsoft. He was pretty
senior in the consulting organization there.
And our idea was that we would make something
that merges the beauty of web design and the
software depth of you know, the Microsoft way
of building software. This was back in like 1994,
95. And we would try to kind of build websites
that are not just skin deep, but actually functional.
And that worked out pretty well. You know, we
got the first few clients through just outreach
to our networks. And then we actually connected,
we partnered with the Microsoft consulting organization,
which Just by way of background, back then and
still now, consulting is a very small part of
Microsoft's business. They don't really especially
like to do consulting. It's less profitable than
building software. Back then, demand for Microsoft
was booming just after Windows 95 was released
and all this other stuff. The consulting organization
in New York, was just getting hammered. There
was just way, way too many requests. And so we
were like the Statue of Liberty. There's a plaque
on the Statue of Liberty that says, give me your
poor and wretched masses. So we said, give me
all your clients that don't pay the bills. They
have unreasonable expectations. They are paying
to work with, there's scope creep, all the ones
that you don't like working with, and you will
never hear from them again. That was our pitch.
And it worked. We got a couple of referrals from
Microsoft Consulting, and we took care of them.
And that became kind of the early start to our
business. And then over time, it turned out that
a couple of our clients requested substantially
the same thing. And that thing was... Anyway,
so it was my role to... I basically, I noticed
it, I wrote a memo about it and I said, you know
what, we can keep doing consulting but it would
be even better if we had a product because that
would be a nice compliment to our business and
it would be really cool to build it and it would
be profitable. And so I guess became the product
person and I took that product from the memo
to where it became something like 70 % of the
revenue of the company and the reason why we
got acquired. that product would you know it
would now be called social networking but back
then there's no such thing that label didn't
exist so we called it Bolton boards or community
and there's also no software as a service we
shipped it as a CD. I remember those, I remember
CD -ROMs. That's right so you pop the CD on your
server and you get all these features and it
was a lot cheaper than having to sort of build
those things yourself. Like the moment that we
hit real sort of product market fit, it was kind
of interesting because, you know, we were, it's
not that we were limping along, but we were chugging
along, it wasn't anything special. And then,
you know, the dot com wave hit, all these companies
raised money. And you raise money, the VC tells
you there's a checklist of things you have to
do. And usually, Number two or three item on
that checklist is build a community around your
website or around whatever you do. You need a
community around. And so back then, there was
just no software to do that. And our pitch to
all of these entrepreneurs was we'll help you
take number three off your checklist and you'll
spend, say, a quarter of a million dollars instead
of one million dollars. And you'll spend like
30 days instead of six months to build it. It's
going to work better than whatever you're going
to build in six months. It was super expensive,
right? Yeah, it was enterprise -grade software,
and it was built to scale. So some of our clients,
our software powered... When CNBC launched their
website, their first website, and they had discussions
about stocks, that was using our software. So
it was maybe 20 ,000 discussion boards about
each security. When Healthy on WebMD launched
and they had discussions with doctors online
that was using our software. So we tried to build
software that was really high quality, that would
scale quite a bit, would be fast. So that's an
incredible story because I think people can only
aspire to have been there when it was kind of
exploding, right? So just before the dot -com
and then catching all the dot -com, and then
the massive explosion that happened and then
everyone would kind of I wouldn't say started
having a personal computer but they did start
having access to the internet and started using
the internet quite a lot right in the beginning
of 2000 so it's really the time to be alive I
guess and how right now I know you're quite active
in the AI how did you transition from you know
having your own company then selling the company
and then how do you progress towards AI because
It's not new for you. You haven't been in the
space for much, much longer than anyone else
talking about it. So how did it happen? I got
my start working on AI about 20 years ago or
so. And I was working for this consulting company
that was in two lines of business. One of them
was management consulting, strategy consulting.
They recruited me right out of business school
for that kind of business. And the other line
of business was what they called data mining.
And it turned out that they were, you know, we
were okay at strategy consulting. We would compete
with, I don't know, McKinsey, Bain, et cetera.
We were a little bit cheaper. But the work that
this company was doing in data mining was five,
10 years ahead of its time. And so I was hired
for business number one, and I switched to business
number two as soon as I could because I was just
shocked and amazed at what they were doing. And
back then, there were no language models. The
work was done in SAS. And everything was really
slow. I started building marketing and risk models
for one of our biggest clients was American Express.
So American Express, it's not that they didn't
use any math. It's that before we came on the
scene, they would use, let's say, to make a decision
about whether to give you a line of credit or
not, they would use a really simple model, like
linear regression or logistic regression or something
like that. And we came in in the early aughts,
early 2000s, and we basically brought forward,
so linear regression was invented, I don't know,
in 18 whatever 1870s 1860s was used by some statisticians
maybe even older than that logistic regressions
from the 1960s and American Express in like in
the year 2000 they were using like 40 to 140
year old technology and we came in and we proposed
new modeling techniques that had been invented
in like 1998 and so it was it was like shooting
fish in a barrel it was just It was bringing
a tank to a knife fight. It was completely unfair.
The new techniques worked way better than the
new regression. So they were able to get much
better statistical results for all sorts of decisions
like who should get credit, how much credit should
they get, who do you target the marketing proposal
to, who should get to the front of the queue
when they call for help, all sorts of resource
allocation decisions. It was an eye -opener for
me. I was just, I mean, I was talking to customers.
I was during the day and I was learning the math
at night and I was having a lot of fun. And then
it turned out that the business of strategy consulting,
at least my perspective of it, shifted, and the
perspective of my clients, shifted from the traditional
management consulting is top -down. Your client
asks you the big question, what should our strategy
be over the next five years? And you start by
researching the world, researching the market,
researching this client. And you identify a couple
of themes or a couple of really big ideas. And
then you drill down into how to do them. And
you drill down into what do they mean for this
business and for that business and for the third
business. And then you translate that into kind
of a marching orders, like how do you execute
it month by month, et cetera. So that is, to
me, that is like classic top down pyramid principle
management consulting. And I found that the paradigm
had shifted from that to sort of bottom up strategy
consulting. What is bottom up strategy consulting?
You don't start by asking like big questions
out of Wikipedia or out of like secondary research.
You start by interrogating the data. What does
the data say? And the data will, so first you
figure out, you collect the data if you don't
have it, or you buy it. And you interrogate it.
And then you, you know, the data gives you some
hypotheses, you validate them. Once you have
some hypotheses, then you do the rest of it.
Figure out, you know, how to use them. And I
found that model of consulting to be so much
more satisfying than doing sort of top -down
research, because when I would get questioned
on something, I'd have backup, there'd be some,
you know, I'm a numbers guy, there'd be some
scientific basis for what I'm saying. Now it's
not always the right, it's not the only right
answer, it's not the only way to do it, but it's
a way that really worked for me and it worked
for more and more of my clients and so I learned
that way of thinking at this company and then,
you know, after the company, that the company
grew, got acquired, I left and I started doing
some of my own consulting and this was the way
that served me. But you know, Ricardo, I've been
doing this for 20 years and I have never seen,
like what's been happening in AI over the last
year has just been completely different from
the last, the 19 years preceded that. I was just
about to ask you about that because it feels
that people... You know everyone's talking about
AI now and rightfully so but they don't actually
realize there has been a lot of growth up until
this stage right now is just the point is just
the tip of the iceberg there's actually quite
a big chunk of ice underneath you know the waves
so I was just about to ask you what do you think
is happening now how do you see this how impactful
do you think the current evolution of AI is for
for everything that we do? You know I can tell
you that the feeling that I get from being in
this moment, I feel really fortunate. And it's
very similar to the feeling that I remember having
in like 1995 working in an internet company.
I mean, it's really exciting. And at the same
time, it feels so, so early. It feels like we're
trying to build these things. We're excited about
these new capabilities. But there's so much left
to do. There's just this wide, wide open space,
and we're just at the tip of the iceberg. It's
not even the first inning. It's like the first
five minutes of the game. That's what it feels
like to me. But in terms of what actually happened,
I don't have an especially contrarian view. I
think the fact that ChatGPT is the fastest growing
product in history and suddenly unlocked all
of these capabilities and showed that you could
just You could just throw some more data and
compute at this problem and get a magic moment.
And now that toothpaste is out of the tube and
lots of other people are able to replicate parts
of it. It's very, very exciting. It feels like
to me, it feels at least as impactful as the
creation of the internet. And maybe at least
as impactful as maybe even bigger than that.
Maybe it's electricity, maybe it's fire. but
I'm quite quite optimistic about it. I think
it's going to be a new revolution, the same way
we had all these revolutions throughout history.
I think we're at that stage where everything's
going to change and rightfully so and for the
best. I was listening to a famous podcast the
other day and he was saying it's the same change
we watch when people transition from having horses
everywhere to having automobiles. And that happened
overnight, right? It was night and day. And I
think that's probably what's going to happen
with this type of AI. Shouldn't we be concerned?
Because there's a lot, you know, if you read,
I don't know, those type of weird newspapers
and say, Oh my God, AI is coming to take your
job in this. But to be honest, I think we're
at that stage where it's actually quite good.
But should we be concerned? What do you think?
Yeah, it's a really good question. I actually
guess that a lot, Ricardo. So I think that there
are there are two future scenarios that could
cause concern. And I think that they're actually
very, very different from each other. And one
really is or assuming one isn't. So the first
one is AI is gonna take my job. That is a very
concerning future scenario. The second one is
AI is gonna take my freedom. So I actually think
that the first scenario where AI is gonna take
my job That is, it looks really concerning, it
sounds really scary, but I actually think that
that is the utopian scenario. There are a lot
of jobs that I wish AI would take. There are
a lot of people that are doing jobs that are
just gonna be better done by a computer, and
they're not gonna be jobs for humans anymore.
Those humans are gonna be much happier not doing
those jobs. I think also that when people are
looking at that first scenario of AI is going
to take my job, they stop visualizing it at the
moment that the job is lost. But I don't think
they fully appreciate all of the knock -on effects.
So if AI takes all of these jobs, that means
that it's going to be able to do these jobs better
and cheaper. That means that the things that
these jobs produce are going to become so much
better and cheaper. So imagine that you need
a proofreader, or you need a lawyer, you need
an editor for this podcast, or a booker to help
you find guests so you can do a little bit better
than me next time. I thought we were going to
do any better than you, and I think we've reached
the pinnacle of the highest quality guests ever.
Thank you, Ricardo. But you can imagine how,
as an entrepreneur, you consume all of these
services. Maybe you do them yourself, maybe as
you grow, you'll decide to outsource them. So
today, your option is basically outsource it
to a human and hopefully they're good at what
they do. And imagine that in that future, and
maybe this future is not so far away, you can
actually outsource it to a machine. That machine
does a really good job of booking guests for
you. That means that there's going to be the
quality of your podcast goes up, the cost of
producing it goes down. You get to keep more
money from All the other sources of revenue that
you have the reason why you do this podcast whether
it's advertising or you know your other businesses
and so All the services that you consume get
cheaper. You will feel richer. You will be richer
And it's not just you it's like everybody that's
consuming all of these white -collar services,
you know professional services architects and
lawyers and designers and programmers and all
these things become cheap so To me, if you zoom
out on that society, it means that all the things
that we need become really cheap. So we will
feel very rich. Just imagine you're now a billionaire
and all these things that you want to buy, they
don't mean anything. The prices don't mean anything
to you. You can afford as much as you want. And
so I think that that's a world where there's
huge deflation. The prices of lots of goods and
services drop because the AI is doing them more
efficiently. If there's so much deflation, that
means basically we all feel richer, even if we
don't make the numbers might not be higher. It's
not like my income went up, but my expenses went
down. And so I feel richer and I am richer. And
I think in that world, just fewer people need
to work. So in that world, I think that those
people who lost their jobs, maybe they'll find
other jobs, you know, developing, you know, something
that's higher value. Some of them will become,
you know, maybe engineering. Instead of being
a lawyer, you might be an engineer training law
chatbots or something like that. But it's not
necessarily like not everybody's going to switch.
Some people will become artists because whatever,
you know, basically whatever change they have
left in their pocket is enough to live on. And
as a society, I also think that we'll be able
to afford to support these people because we
will have so much because all these things become
cheaper. So I think that world is a world where
there's going to be something like universal
basic income and we'll just be able to take care
of all these people. It's not going to be a problem.
That is one of those that you never know how
it's going to go, right? But I was just thinking
about something that people being scared about
all this transformation and how it's going to
impact. I think people fail to realize that they
can actually upskill themselves by using AI.
For example, think about tutoring and you're
in school, you're trying to learn something,
the teachers are not that good. Nowadays, you
can probably go on YouTube, you can probably
go on Google and find the right information,
but it never really does explain it to the level
detail you need to. However, on ChatGPT, it will
tell you exactly what you need to do, how you
need to do it. It just opens up possibilities,
right? It's a bit like having access to books
in the 15th century for the printing press You'll
be the same thing the same change, right? So
it's really like that regard I would say it's
like going from a world where you have access
to books To a world where you have access to
a tutor like a really good tutor that knows you
The tutor knows what you like and what you don't
like, you know, whether you like maybe you like
learning by reading or by listening or by watching
things. And it knows what you're strong at and
what you're weak at. And it basically helps you.
It's a personalized tutor. So that personalized
tutor is, you know, it's very expensive in the
pre -AI world. Only a few people can afford one.
But in the post -AI world, you know, everybody
could, you know, learn that way and yeah, can
be very effective. Now we were talking about
some of the dangers of AI which is also a very
hot topic So what do you think will be like in
terms of the government's using it and every
being? Everyone being repressed and we have killer
robots walking down the street, which by the
way, it's completely People are absolutely crazy
when I say that but what do you think? Those
are some of the things we should be concerned
about because there is quite a lot of capabilities
and I know some of it But I'm pretty sure you
know a lot more about it than I do. Should we
be concerned about it or not at all? You know,
Ricardo, I may be one of those crazy people.
I am pretty concerned about it, actually. So
when we talked about the two scenarios before,
where the first scenario is AI takes my job,
and the other scenario is AI takes my freedom,
I'm really, really worried about that scenario.
There's a couple of different ways that AI can
be used to take our freedom. No, the simplest
way to think about it is the like the terminator
scenario. So we all we've all seen the movies,
you know, approximately, you know, approximately
every future science fiction story about AI is
a disaster story. And it's it's really scary.
And working with this technology, I cannot tell
you that it's like there's no way for it to happen.
Like I cannot I can't push that probability down
to zero. And it's it's very, very scary. Now,
it's not like, you know, I'm not losing sleep
over it, but I think that there's, you know,
there's a real chance that it's called takeoff,
where the capabilities of AI, you know, they
kind of grow and grow and grow, and then they
suddenly take off at a rate that is just too
fast for the scientists to contain. I think that
is, it's a real risk. I'm worried about it. And
also, you know, even if you ignore takeoff, even
if takeoff is too science fiction to think about,
AI is the kind of technology where it's really
asymmetrical. It's not like nuclear power, for
example. So, you know, if you're worried about
nuclear proliferation, to create a nuclear bomb
requires the resources of a nation state. It's
incredibly difficult. You need to set up this
enrichment program. You need really high -grade
scientists and equipment and all these. You have
to buy these things that are not available for
sale. And so it takes so much money and so much
time that only a few countries in the world have
been able to do it. And those countries have
been able to contain this technology to some
extent. It's not perfect either. AI is not like
that. AI, as an individual, you can have a breakthrough.
Like today, we're not too late. We're early enough
in the process where an individual can publish
a paper and invent something that nobody's ever
thought of. And that thing significantly increases
the capabilities of the state of the art of what
you can do with AI. I can give you lots of examples
of papers like that. But from a risk perspective,
just imagine that a single scientist could invent
something that makes I don't know, that makes
nuclear bombs more destructive or more attainable.
That would be scary, right? So with AI, it's
not just that an individual can create a breakthrough
to improve, to increase the power. It's also
that training these large models and all of the
infrastructure around AI is getting cheaper at
a very, very fast rate. Yeah, so it's really
asymmetrical. By the way, I should mention, these
ideas are not mine. I read a book that I'd like
to recommend to you and your viewers. The book
is called The Coming Wave. It's written by Mustafa
Suleiman, who is one of the co -founders of DeepMind,
Google DeepMind. And it's mostly a book about
what can go wrong. 10 % of the book are about
what we can do about it Yeah, yeah, so so it's
a it's a really it's a really interesting book
in the last chapter of that book he talks about
a framework for For defending against these these
problems and it's You know, I'm not going to
do it justice, but it's it's these concentric
circles It's the way the way that you design
any kind of security system is not a single barrier
or single line of defense, but many. So that
if you breach the external line of defense, you
have the internal one, you have the internal
one. It's like a bullseye. And so, again, I don't
remember all of them, but one of them starts
very, very close to the researchers. And it basically
says that every model should have a built -in
auditing system that describes what the model
does and is available to not just the team researching
it, but to other people that want to inspect
that model. So it's kind of like, you know, you
should be able to have like a little diagnostic,
like you have a diagnostic port on your car.
You know, you can plug in a USB or something.
The car will tell you. All cars have it since
then. All cars. Right. That's right. So the car
will tell you kind of how it's feeling, you know,
if some things are rusty, some things are according
to spec or not. So what he suggests is there
should be, and it's a standard port, like the
same USB thing will work on any car and can read
data and say cars have standardized on this.
So he's suggesting that should be a diagnostic
port on AI models. Whether that model is built
by OpenAI or Anthropic or by WeChat, there should
be a standard way to inspect them. Another wider
sort of circle that he talks about is that all
AI labs should run and publish their test results
in a way that in a public place so that individual
researchers can inspect those results and spot
any kind of problem. So there would be like some
kind of protocol, they publish it, and you and
I can go check that removed data and see if we,
you know, and that's transparency. So he basically
has like, you know, six or seven or eight of
these concentric circles and they go all the
way from the individual team up to something
that requires the society to make an investment.
But I hope some of these things come true. I
hope that these mechanisms get adopted. How do
you prevent certain states from developing capabilities
like this? Is there a way of controlling it or
not at all? Because right now, as you're talking
about nuclear nuclear technology, and we know
there are certain constraints about getting uranium,
getting plutonium, then reaching them, and we
can track that by satellite, saying, okay, you
have this, you came from that source, so forth,
so on. How do we stop countries like, I'm going
to give North Korea, I hope I never go to North
Korea because then I won't be allowed in, I'll
probably get stuck there, but how do we prevent
countries like North Korea from creating capabilities
that would So how do we solve that? Yeah, it's
a serious question, Ricardo. I don't have an
answer. I think that the only way to compel nation
states to do something is through some kind of
an international treaty and political pressure.
There's no magic bullet here. Some of these things
require very, very broad agreement and broad
coalitions to make something happen, but not
all of it. So there are some things that we can
just start doing the right thing locally. And
there are some things that just will require
massive agreement and will probably take a while.
In that sense, I think that this problem is not
unlike the environmentalist movement. We have
to take care of our planet. And how do we force
the worst polluter to stop polluting? it's going
to be really hard to force the worst polluter.
But it doesn't mean that we should just like
throw up our hands and say, well, if China is
going to keep polluting in, you know, such and
such province, it means that I don't have to
worry about the environment at all. So you kind
of you take whatever steps you can. You start
with your own bed, right? You make your bed,
keep your, you know, you lower your own carbon
footprint, think personally, and then you think
about your circle of friends. your local community
and kind of grow from there but then the question
would be because we can always the way we present
ourselves and the way we organize ourselves it
is done in respect with our values right and
much more so however when we are living in a
global society the other fellow might not have
the same values and they might respect the same
thing so it's a bit like going to war When you
do go to war, you need to be aware that your
enemy might not have the same rules of engagement.
They will not comply with the Geneva Convention,
for example. So they'll fight in a very dirty
way. How do we stop this from happening? It creates
this dilemma. It's going to be tricky, no? Yeah,
it's definitely going to be tricky, Ricardo.
I wish I had a quick answer for you. But I think
that the stakes of solving this with AI are very,
very high. Because if we don't get it right in
warfare, then the risk is that there's going
to be a war that doesn't follow the rules and
it's really going to hurt the combatants in that
war. If we don't get it right in AI, the risk
is that there is AI takeoff or an AI weapon and
it just wipes us out. I mean, I think it's an
existential risk for the planet. It's not unlike
global warming. Question on that. So there is,
I guess, a gap right now between the online space
and the actual physical capabilities of AI, right?
We don't have robots yet. Do you think all these
bad nation states will be able to produce, for
example, killer robots or have that enough technology
to actually disrupt this fully or resume very,
very far away? Because if we look at that company,
what's it called? Boston Dynamics? Is it Boston
Dynamics? All those advanced robots? So when
I think of, okay, let's incorporate AI here,
it's actually quite powerful. But then I also
know that the country's not having it. So that
makes me feel a little bit safer at night. Do
you think that that transition will be easy or
not? No, it definitely won't be easy and also
I think we're I'm getting a little bit away from
my expertise. So I Most of the work that I've
been doing has been for Commercial AI, you know
in the business world and it's mostly been with
text So I haven't had a lot of personal experience
with robots for weapons But I can tell you that
you know Autonomous weapons AI weapons that have
the, they can actually make the decision to pull
the trigger. They exist. They, you know, several
nations have them, including the US. And it's
a really, it's a really scary thing. And there's,
there's this, you know, the arms race is pushing
a lot of the participants to be ever less careful
and put ever more powerful weapons into the field.
That's the way it's always been. But Yeah, it's
a very scary kind of race here and I hope that
we pull back from Brick. So on that note about
not arms race or anything like that but about
AI and technology, I know you're also a mentor
for Techstars. I was just going to ask you, do
you think that a startup can still exist without
AI on something that they do or that's completely
off? Everything needs to be around AI. I heard
a recent statement from a venture capitalist.
I think it was in Sequoia or maybe A16Z or one
of those large funds. And they said that over
90 % of incoming pitches are AI related. So I
guess it's possible, but pretty slim. I think
part of it is supply and demand. There's a lot
of capital. Looking for AI ideas and there are
a lot of entrepreneurs that are trying to be
where the capital is going Yeah, that makes sense,
but would you so? Because I know you also teach
people when they help them out So what advice
would you give to an entrepreneur just launching
their startup in terms of incorporating AI into
their idea? I Think that AI is a tool it helps
you achieve certain things. It helps you maybe
get where you're going, but it doesn't help you
decide where you're going. It's not a destination.
It doesn't produce value by itself. It helps
you produce the value that you want to produce.
So it's a means to an end. It's technology. It's
not a product. If that makes sense. So my advice
to the entrepreneur, you know, if the entrepreneur
tells me, you know, actually, you know, I recently
had this I had, you know, I had a startup founder
and told me, look, I, you know, I built this
AI based product. And it's really cool. It has
all these technologies in it. And I'm having
like a lot of trouble selling it, you know, it's
not really getting the kind of pick up the market
traction. that I'm looking for. So what should
I do? Should I maybe raise some money, maybe
lower my price, maybe fix my ad, maybe I should
take on a partner? How do I fix it? And the problem
with that question is that users don't really
care if you're using AI or not. Maybe investors
do, but users don't care. Users have certain
pain points, and as entrepreneurs, it's our job
to fix those pain points using whatever legal
means we can come up with. And it just so happens
that a lot of problems could probably be fixed
with the application of these new capabilities
that just got unlocked. But the user, again,
the user doesn't care whether we're using a new
way to fix it or an old way to fix it. They just
care that it's fixed. So the advice of the entrepreneur
is Before you decide that you want to build something
with AI, talk to users and make sure that you're
building something that they would want. And
then you figure out how to build it. It makes
a lot of sense. In terms of raising investment,
because I know you're also in space, how hard
do you think it is right now to raise investment
overall? because here for example in UK a lot
of people are complaining oh my god it's been
so hard and no one's investing you know money's
really tight we know for a fact that in the US
you know rounds are at least five times bigger
than in the UK which is great you know our minimum
you know round is 250k and that's really a lot
of money because in the US it's around a million
so how is that working what's the current status
okay so there's two questions there there's the
US versus UK or US versus other countries And
there's also how hard is it now versus how hard
was it before. So for the second question, I
think that valuations for private companies,
for startups have generally come down in the
US over the past like maybe six months, 12 months.
And you can see that in a lot of investors that
have sort of mark to market accounting. They
have taken down the marks of their private investments.
And it's also, you know, it's more difficult
to raise money now than it was maybe six or 12
months ago. Not necessarily a bad thing. It was
just like such a mania going on. But it's still,
you know, there's still a lot of VC investments.
There's still a lot of VCs that have dry powder
and there's still a lot of capital looking for
AI opportunities. In terms of the US versus other
countries, it's a really good question and I
don't have a lot of expertise there, but there's
something special about the Bay Area ecosystem
and what they've created over the past 30, 40,
50 years. I know that a lot of other countries
have tried to replicate it and it's been elusive.
It's not that nobody else has succeeded, but
the scale is, you know, it's tough to replicate.
I can't tell you that I know exactly what it
is, but, you know, something about the physical
proximity of a couple of universities and all
of these capital providers, it's like a magnet,
it's like a self -reinforcing system and it seems
to work. I also think that, you know, there's
something in... There's something about cultures
that are just different. Something about the
value of the individual versus the value of a
group and the value of society. The US makes
different choices than other countries do, and
those choices have pluses and minuses. Maybe
the entrepreneurial ecosystem is a plus, but
hey, we have one of the most expensive healthcare
systems in the world. to a lot of other people
who live in a lot of other countries. It's crazy
that you have to go shopping for dentists and
you have to like haggle with your pharmacist
about how much to pay for a medication. But that
happens in the US all the time and it doesn't
happen in any other advanced economy. So there's
definitely trade -offs. That's always a big shock.
Our second friend of mine who travels to the
US. He also has family there. We're talking about
Azomorpozol, which is the medicine you take through
to the stomach protector. And he was saying I
had to get some prescription there in the States
and he was like $700. Whereas in here, I literally
can go to my supermarket and buy it and it'll
be two pounds. So very, very cheap. It's a bit
of a shock. Another question I have is Would
you advise someone coming in from Europe and
say, you know what, just go to the US and try
and raise some funds there? Or do you think automatically
they'll be shut down and say, oh, where are you
coming from? The UK, France, whatever, Germany.
Yeah, we don't tend to invest in companies because
it's illegal minefield or we don't trust you
to do things the right way. You know, I don't
think that switching countries is the right move
for most entrepreneurs. I think that The biggest
problems are around building something that people
want. It's achieving product market fit. If you
are able to achieve product market fit, the capital
will come to you, even if it has to come overseas.
So I think that over the past 20, 30 years, I
think, you know, even if you look at US capital,
that there's just a lot more investment overseas
and, you know, that they're looking for deals
in much, much bigger places. certainly broader
than the Bay Area. And I think that concentration
is decreasing, it's diffusing. I know that there's
not as much capital available to entrepreneurs
in more conservative countries. But I think that
if you, let's say if you're in... If you're in
France, if you're in Germany, if you're in the
UK and you have developed a product that has
good traction that users really want, I think
that you can raise the capital without moving.
You may not be able to raise it from local investors
that are down the street, but I think that it
is possible to do. This is going to be a very
tricky question, I realize that. If you had just
one piece of advice to give to an entrepreneur,
what would that be? Build something people want
Yeah, that's that's because I think Sometimes
you meet a lot of people who are building this
fantastic idea in their mind and then they realize
actually no one wants this what I'm gonna do
with it and the same happens quite often with
software companies where they build this product
that they think the market's really gonna need
and that they didn't hear in the market and the
market say why did you spend a couple million
here because that's not for us that's No one's
going to use it. As we're closing to the end
of our podcast, if people want to reach out to
you, how can they do so? Yeah. So the best way
to reach me is on LinkedIn. It's Alan Bachman,
A -L -O -N -B -O -C -H -M -E -N. And just drop
me a note. I respond to everybody that reaches
out to me. Thank you so much, Alan. Thank you
so much for your time today. It's been super
insightful. Thank you, Ricardo. Take care. Let
me just.