January 24, 2024 • 44 mins
Mark shares a Leadership in Action interview with acclaimed tech entrepreneur and AI advocate, Luis Cortez of Red Hat, who shares his first-hand experiences and insights on the transformative potential of artificial intelligence in fueling business growth and driving innovation!
This episode was originally heard on Leadership in Action.
Unleashing the Power of Respect: The I-M Approach by Joseph Shrand, MD
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:02):
Welcome to Elements of Styles, the business podcast that trades in scarce thinking
for community, conversation, and ideas in abundance.
Each week, I, Mark Stiles, sit with professionals and entrepreneurs,
both local and global, and learn how they each add value to their communities,
their partners, and their teams. Please enjoy.
(00:23):
Hey, folks, we're going to mix it up a little bit today. Recently,
I was asked by the Boston chapter of Entrepreneur's Organization to host their podcast.
That podcast is called Leadership in Action.
Check it out. Here is an episode that I recently hosted.
Hey, folks, welcome back to Leadership in Action, your podcast for your chapter
(00:45):
of EO here in Boston, Massachusetts.
Very excited to have our guest today.
He is a passionate serial entrepreneur and marketing executive.
He's been a member with EO for over 15 years.
He served as president in his native Barcelona chapter, as well as here in our Boston chapter.
(01:10):
He co-founded and grew Palamita Technologies,
as a co-CEO while leading marketing and sales, and turned it into a worldwide
leader in business Business Process Management Software,
which was then acquired by Red Hat, now IBM, in 2012.
(01:30):
Co-founded B Combinator, the leading accelerator and startup investor in Southern
Europe for B2B and B2C SaaS, AI and generative AI startups.
We're going to talk a lot about that. He's also the leader of the artificial intelligence MyEO,
(01:51):
AI group in all of EO, where over 850 entrepreneurs learn and thrive with AI.
Did I mention who this was? This is none other than Luis Cortez.
Welcome to the podcast, Luis.
Thank you. Thank you. Thank you, Mark.
(02:12):
Thank you for that welcoming intro. I hope I did it. I'm so excited to be here
talking about all these with all my brothers and sisters in Yale.
And yeah, you did a great job. That was a lot of research on my LinkedIn profile.
I hope so. I hope I did you the honor because you are a huge contributor here in the Boston chapter.
And I want to honor and respect that.
(02:36):
So as we begin with all of our podcasts, we ask the same question.
What is the most valuable lesson you've learned while running a business?
Oh, wow, that's, that's, that's great. That's a great question.
You know, probably one of my favorites is that big problem is nothing more than
(03:00):
a small problem that wasn't properly handled at the time.
And I see this over and over.
You know, sometimes you have, you know, it can be anything.
Thing could be person that consistently doesn't
have good results even though
they say they are doing what they
(03:21):
love and everything and for some reason at some point they didn't get
the right enablement or they were put in a they're the right person but they're
not sitting in the right seat of the bus right and that should have been fixed
like two years ago instead of everybody trying to make it go for like two years
of misery if you will right so yeah i don't know where i read that or who I
learned it from. I'm grateful for that lesson.
(03:43):
But yeah, that's one of the many things that I think I've learned while building a business.
So how do you teach that lesson? That's so very important lesson.
Well, you know, sometimes we are just, my experience at least,
right? It's so many things happening at the same time.
So many decisions. We entrepreneurs work more in our business instead of on our business, right?
(04:06):
As we say. Okay, so stepping from time to time and taking a look at,
you know, we are dismissing this because it looks like it's not important,
but if this continues like this, where is it going to be like six,
12 months from now, right?
So trying to a little bit to project something like that, that can help identify those problems.
And, you know, the time when someone or a group is like,
(04:29):
I wouldn't say complaining, but definitely making a deal about something that
something needs to be tackled right there, right now.
Right. Otherwise, you know, you're risking letting it grow under until it's
just this big, ugly pink elephant that is in the room. Right.
Little, little problems become big problems. Right. So pulling back, what's the symptom?
(04:50):
What's really, what's really at issue here? pay attention
keep your antenna up for those those signals
and uh address nip it in the
bud as they say yes and
yeah don't don't don't be lazy trying you know hoping that things will kind
of sort out by themselves i'm talking talking by experience i've made i'm guilty
(05:14):
i'm the most guilty entrepreneur in the planet for letting things pester so
it's not that i do any but at At least, you know,
sometimes it's like, is this going to become a big problem?
And should we kind of tackle it right now?
That's what we do. We share experiences, right? That's all we can do.
And no, I'm with you on that. Are there any AI solutions to avoid that?
(05:37):
It's a nice segue for you. Exactly.
Well, you know, you can train bots with all sorts of documents and things out there.
It's very easy to do these days. so you're actually getting a system that will help you with that.
I haven't seen one for that, but I don't think it would be too complicated to
come up with a question for chat GPT or BART or Bing that would help us think
(06:02):
about, you know, how would you identify a small problem that may become a big one?
And if you identify it, how do you go about it? So I'm sure there may be ways,
but I don't think AI will solve that.
It will give you hints. It will help you think maybe. So AIE,
my impression with what's going on right now is that it's a great assistant. It's a co-pilot.
(06:23):
It's going to help you, you know, get to the roots of problems,
maybe support you with decision-making, but man, humans are still at the wheel now for now. Oh yeah.
So I want to express my gratitude for you and your team putting together that
amazing presentation that Learning Chair Dave Will helped put together for our chapter.
(06:47):
And folks, if you're missing out on these, you're missing out on a huge,
huge value proposition for EO, and that's these learning events.
And Luis put together one for AI. I wanted to show you something real quick.
I brought a prop. Are you ready?
Oh, come on. So after that event, I was blown away by some of the comparisons
(07:10):
and some of the what-ifs and And where are we going with it?
And I was at my in-laws house and look what in there.
That's a great one. Yeah. For those 90% of you who are listening and not,
and not watching, I showed Luis this old fashioned calculator,
(07:30):
the ones where you, you punch in the numbers and you pull down the handle and
you go through that all day long.
And they showed a slide of an entire row of people doing that.
And then they said, and then there's an entire floor of those people.
And now visualize an entire building of people doing that same thing,
(07:51):
punching in the keys, pulling that handle right here.
And now all of that is one CSV spreadsheet. spreadsheet.
So what happens in AI? So we have the fear mongers out there.
Oh my goodness, all of the jobs are going to be eliminated.
What are we going to do? This is going to be the end of it. Let's hear the other side of that.
(08:13):
Well, it's not only not the end of it, but this is just going to take us into
a new age, a new wave of productivity and gains for the economy and for people.
At least I'm a great believer of that.
And just two data points here, right? So believe it or not, 60% of every job
(08:35):
that exists today didn't exist back in 1940.
Wow. Think about that for a minute, right? Right.
So 60 percent of six out of every 10 people working today do something that
didn't even exist, which need wasn't even there like 80 years ago. Right.
And we have what, a billion people now in the planet, something like that.
(08:57):
So why why did this this renovation in employment has come out of technology, of course.
So now we have machines picking up crops instead of people, and we have spreadsheets
doing work instead of people just pulling handles.
So that's basically every person.
We're now way more productive than way before. We live way better now.
(09:20):
So standard of living has raised across the planet and health conditions and the minimum wages.
There's still, of course, big gaps in many countries, but everybody's a little
bit better than it was many, many years ago.
So from that perspective, AI is just another wave in technology.
You can think like, you know, 30 years back when we started talking about the
internet and most of us got in there like, what, 20 years back or something.
(09:42):
The internet just created a whole bunch of new jobs that didn't exist before, right?
Like graphic design and programmers and so many people doing crazy things around the internet.
And then mobile apps, the same thing, right?
So all of a sudden, a new way of using everything is no longer a computer,
which, by the way, only started in 1981, like 50 years ago, right?
(10:05):
Now we have smartphones.
And this created new jobs and probably also cut rid of a few other jobs. So this is just ongoing.
And I believe AI is basically a greater system that gives people superpower.
So each of us can now, again, to our earlier point, right, make better decisions,
be more informed about things, be more productive, be more creative.
(10:27):
And that is just going to expand the value we have to businesses.
Businesses will be able to grow more, make more money, hire more people because they're growing.
So I see this as a virtual circle, not a selfish one.
Yeah, you know, so many people have this two-way path, right?
It's either going to be utopia or it's going to be dystopia.
I see that this is the new revolution, right?
(10:51):
AI revolution, the AI, you know, the industrial revolution, the agriculture
revolution, the tech revolution, AI revolution.
It's simply going to change everything, which scares a lot of people when you say things like that.
It's going to change everything. And that's okay.
Yes. And the other important thing here to keep in mind is, you know,
(11:13):
when they, AI is not going to take away anybody's job, but someone that uses
AI better than you do, me, right?
So it's basically about learning.
AI by itself doesn't have an incentive, doesn't have the ability to come up
with goals or do a number of things.
That's humans. Now, me without AI versus me with AI, me with AI is going to
(11:35):
be X times as more productive, right?
So actually we had in our event, we had Dale Bertrand talking about how the
implementation of AI was just producing 30% gains, productivity gains,
and actually EBITDA gains, like money that he could measure,
right? More coming into the business, right?
And he told us how he was using that 30%, right? So, you know,
10% went for training, 10% went for people experimenting with time.
(11:58):
The other 10% was focusing on growth of the company, right?
So actually everybody's 30% more productive and his business is growing faster,
making more money. So everybody wins, right?
So now you need to make sure that you learn and you play with it the same way
that we did with the internet or with smartphones. You know, it's just another step.
(12:19):
And of course, if you're 20, it's going to be easier than if you're 70.
I get that. But again, technology is easier and easier to work with.
So like my dad, he's 90. He just turned 19 in October last year,
right? Last year was 2023.
This is January 2nd, right? And he has his smartphone, his iPhone for a long
time. He's got his iPod, he's taking pictures.
So, I mean, there's no limits to how easy technology is getting these days.
(12:42):
And I don't think AI is going to be different.
I don't either. And it's definitely moving fast. But I love that quote,
AI is not going to take your job.
Someone who's effectively using AI is going to take your job.
And that's an important distinction.
That's the delegate to elevate conversation we were having before the show is.
(13:05):
Do you need to be doing that task? If not, what purposeful task can you be doing
while, fill in the blank, somebody else is doing it or the technology is doing it?
So I've been having a lot of fun with GPT-4.
What are some of the things that people might not know about with AI right now?
(13:26):
So again, let's timestamp it for those folks listening.
It's January 2nd, 2024. 24.
We simply turned the calendar to another year. I can't believe it's 24, by the way, Luis.
Can you believe that? Yeah. But let's timestamp that. GPT-4 is now here and
we're able to play with it, work with it, utilize it.
(13:48):
What's out there that people may not know about that you want to share with us?
So I think people have gotten used to asking things to chat GPT and to other
bots like BART or Bing or Clot from Anthropic, some others.
I think there's probably two things. One is these apps, these bots,
(14:10):
they are not just like a Q&A agent that you just ask and receive.
You can dialogue with them.
Okay? Okay, so this, you can turn every prompt, every question into a conversation
with it. So you ask for something, you get a response.
And you can, okay, so I didn't quite like that. Change the second sentence to
(14:30):
be more incisive, more friendly, or more highlighter, whatever.
It will change it. Okay, now change the order now.
Or you're asking for a summary of a meeting, right? Dig down into the third point.
What do you think the author thought about this and this and this?
Is you can have a dialogue to
get as deep as you want into whatever conversation you're having with it.
And I think that's something that sometimes people overlook,
(14:51):
but I think that's very helpful.
And help me understand the companies that are propping up and coming out and,
in essence, overlaying ChatGPT, right?
So they're simply creating a service that is, the foundation is ChatGPT, right?
(15:13):
Because it's open. Everyone has access to all of the computer inter-depth things
that I don't really fully understand,
but it is open access to anyone to utilize and, in essence, connect with other
applications, right? Right.
Exactly. So, and it's not too difficult to actually use that power,
(15:37):
even without programming, because you can now build your own assistants,
your own GPTs, as they call them, without any programming at all.
And if you have someone in your business that's a programmer,
Python is a very popular competing program that developers use to work with
chat GPT, but anything that can talk to an API, API, basically,
(16:00):
an application programming interface, you can connect it and build your own
applications very, very easily.
So, you know, something you could do, for instance, is many companies actually
record their customers' calls and you hear that, you know, this call is being
recorded for quality purposes, right?
Well, okay. In many cases, they are actually learning from those calls.
So actually, if, you know, if any of us entrepreneurs, when we talk to our customers,
(16:24):
imagine that you could record every conversation with the customer, right?
I'm sorry. You can ask ChatGPT to transcribe it.
So something I mentioned at the event. And if everything that can be text should
be text. Why? Because now you can use it to train a bot.
You can ask ChatGPT, go through this conversation and identify all the questions
that were asked by the customer and put them here with the answers.
(16:49):
So what did I answer to that objection from my customer, right?
Well, Office, if you do this for like a couple of months, you're going to have,
I don't know, hundreds of conversations. sessions, you're going to very easily
have documented every possible answer to every possible customer question.
So now it becomes very easy to go and train your people so they can actually
clone you, which is one of our key delegation tasks is how do we make our people
(17:10):
as efficient as we are, right?
And vice versa, every time we ask the customer and the customer tells us something,
we can use that to build our sales training for our sales people and say,
hey, when these are are the questions and answers that we can have with customers,
and we can automatically.
Get all that ready just out of recording customer conversations.
(17:31):
So this, you know, two years back, three years back, this was almost impossible
because the computing power wasn't there.
Not to your point, this is open. So the moment you have text,
you have a conversation, you have a book, whatever, you can have all these type
of conversations and extract wonderful value out of it.
Wow. So, you know, I'm seeing these Otter AIs and the Read AIs and the people
(17:54):
are joining in with their notes and the summaries are unbelievable for someone
who's a high DI to see the summarization of the call and be able to walk away with it and be like,
okay, I got this and I can refer back to it.
But taking it to that next step and then teaching the system what we're looking for, right?
(18:19):
The end solution, the prize.
How do we get to the prize? And we can keep feeding the machine until we get
it there. That's fascinating.
So there's a lot of really amazing things going on with AI.
What are some of the things that people want to be careful about?
I'll tell you, one of the things we're sharing with the team as we experiment,
(18:43):
because that's all we're doing right now is really, truly experimenting with it, is no names.
Never, ever put a name into chat, a GPT, and never put any confidential information in there.
Obviously, we're asking very generic questions at this point,
you know, that overlay, that introductory research, if you will.
(19:04):
But one of the things we're saying is no names, no names to start with.
But what else ought people be thinking about?
I think that's critical. No confidential information if you're using the regular chat GPT.
I think that's one thing. The other thing is to carefully check the answers
back to make sure that things kind of align, right?
(19:26):
Because these models, due to the way they are trained, they will never acknowledge
they are making something up.
So, I was just reading two days ago, lawyers keep including wrong information
that they extracted. Yes, still.
I mean, there was this famous Avianca customer that put a suit to the airline
(19:52):
for something that happened.
And the lawyer was using chat GPT to come up with similar cases that,
of course, didn't exist, right?
So, I would say, I think the other key thing is exactly that.
That is just double check on everything that it comes back just to make sure
that it kind of makes sense.
Right. The artificial intern, right?
So, you know, you wouldn't be handing a judge the intern's memo without proofreading
(20:15):
it and shepherdizing it and making sure that the cases actually existed and were relevant.
That's, that's, that's pretty funny. And, and, uh,
And probably something to your question about things that people don't know
is the, so TPT, there's an app for it, for your iPhone, and it includes image recognition on it.
(20:38):
So you can take pictures of things and, you know, you can turn,
you can draw something on a whiteboard and ask it to turn it into HTML content.
It will build a webpage for you that shows. Wow. Or I just used it recently,
so I didn't know whether I could put something on the tumble dryer or not.
So I just took a picture of all those little rounds and circles and triangles
(21:01):
that I don't know what they mean.
And the thing came back, don't put it in the tumble dryer. So I'm a better person
going forward just because of that, right?
That's pretty cool. That's pretty cool. But I want to go back to the hallucinations
that you were referring to, right?
So that's what they're calling them, right? that the system will give you an
answer with confidence, although they've completely made it up.
(21:26):
At what phase do you think that that's going to start to correct itself?
I mean, we're at ChatGPT 4 now. Is it 5? Is it 6? Is it 10?
It's really difficult to get rid of that because of the way the models are created.
So basically what happens in ChatGPT is is it's interestingly,
(21:49):
it's not as intelligent as we think.
Basically what it does, it's an auto-complete on steroids.
You know, when you're typing messages on your iPhone, on your phone,
it will suggest the next word, right, sometimes?
Well, ChatGPT is doing that all the time. And it's so efficient,
so good at it, that it builds a whole complete pages and pages of content that
make perfect sense, that are perfectly organized, etc.
(22:11):
Now, the problem with that is that it is not checking.
It's just looking for patterns. So if the pattern kind of matches,
it doesn't have any knowledge or meaning about what it means.
So it just can't check itself. And there's ways of putting guardrails around
it so it kind of reduces the likelihood that it will come up with weird stuff
(22:31):
by reducing the creativity that you use with a parameter called the temperature.
But even with a very low temperature, results may be better,
but the risk of hallucination is very difficult to get rid of.
And you would maybe chat GPT six or seven will have like automatic self.
(22:52):
Source check or something like that that
will make sure that nothing is false right
but then we would get into what's true what's
false what's fake who is interested in this or
that that's a covid vaccine work or not well depending on what you read so how
is chat gpt going to know whether it works or not i'm just picking on something
random right yeah so it's it's not an easy problem to fix currently and there's
(23:18):
efforts being made by the by the scientific community of course,
to get there because it's becoming so pervasive that people are trusting the
results at face value, right?
But it's one of the challenges that we still have with generative AI.
I do love how it gives you sources though.
So as you get the response and you can click through, and it's a website that
maybe I've never seen before.
(23:40):
And you can go a little bit deeper and And it's almost acknowledging that,
listen, I'm not 100% sure.
Here's where I got that information and do your own research,
right? Again, it's a rough draft.
That's what I keep terming it as. This is a rough draft. It's a good start.
It's going to break the writer's block.
(24:02):
It's certainly going to get the flow going.
I mean, some of the stuff that I've been able to pull out of there,
it's pretty mind-blowing.
When we ask it for something that I
mean it could take two hours to figure out
and it spits it out and it's
it's a great start it's fascinating and actually
(24:23):
you know if if you don't mind I'm going to take a picture of the screen right
now with my phone and we're going to ask it to describe what it's seeing yes
so we can have like a real time so now what platform are you going to put this picture into?
So I'm just taking a picture with chat tpt with the app in my own.
(24:46):
Okay. So this is a picture. Okay.
And then I'm just going to ask, describe this image.
Okay. So that's what I put. I don't know if you can read that.
Yeah, I can. Okay. And it's coming up.
So it's saying the image is a screenshot of a zoom meeting with two participants
on the left side of the screen.
There's a person with a headset in front of a virtual background featuring an
(25:08):
eye and and words like kind, smart, vision, beautiful, and strong.
On the right side, another person is displayed in front of a colorful,
artistic background that appears to be a flip cityscape with a QR code and text.
Pretty good. It didn't recognize that this was the Leadership in Action podcast.
Yeah, it's not that good. That's a step away.
(25:31):
You can see here, right? That's fantastic.
It sees it. It understands it. It's literal.
Exactly. And it's not just, you know, this can become like a toy or a play.
You can play with it and it's fun.
But imagine what it can do for people, right? So it can help people with limited vision to see.
(25:53):
It can help you classify images in your company.
It can be used to compare images and see if something's off.
I mean, the applications are endless, both for personal and for business purposes.
So tell me about B Combinator.
So B Combinator is the leading accelerator in Southern Europe.
(26:15):
So we started, I'm a co-founder there. We started like five years ago,
six years ago, I should say now, because we're 2024.
And we started as a co-working space. So we have our own building.
We own our building, which is like two minutes away from the beat in Barcelona.
We have over a hundred hot desks that startups, entrepreneurs can use to terraces
(26:35):
on top with barbecues and stuff or parties and letting off stress, right?
And then, so we started doing that and we realized how cool it was to work with
entrepreneurs. So we started mentoring entrepreneurs just out of the fun of it, right?
Well, we started bringing in mentors. That mentor community grew up to 150 mentors.
(26:56):
We have way more now. And then...
We developed incubation and acceleration programs to help startups become businesses
and then be able to have a product, sell product, get money from investors,
grow internationally, right? One step at a time.
This is all inspired by the Lean Startup methodology.
(27:18):
And then in addition to years ago, we said, you know what, we should be able
to invest in these startups in addition to mentoring them, right? Right.
So we raised a venture fund that invests in pre-seed stages,
like very, very early stages.
And now we are raising a second fund, a 40 million euro fund that is going to
invest in seed and pre-series stages.
(27:40):
Very cool. So how many of those companies are working in the AI space?
So we currently have around 40 companies in our portfolio and seven are in the
AI space. Wow. What are some of the things that they're working on with AI?
With AI, so they are working on emotion recognition.
So they can take a video of your face and then identify micro-expressions in
(28:01):
your face to see if you're expressing basic emotions, fear, disgust, joy, etc.
And they use that for market research.
So because sometimes you ask people what they think about something and they
say, yeah, I like it, but there's something in their face that is saying that they don't.
So this software can help give you a clear image of what they're doing.
We have another very cool one that is completely changing the landscape for
(28:25):
human resources, all the way from recruiting, making sure the persons that we're
recruiting have a CV and interviews that kind of match the values of the company.
Because I don't know about you, but something that I do consistently wrong is
I hire too fast and fire too slow.
Right. So people spend too much time. There's an AI solve for this?
(28:46):
Well, yes, because AI will help identify if that person fits with the values
of the company, fits with how we do things by analyzing the response that is given to us.
So it's going to give like criteria and say, you know, we'll give you a scorecard
in telling you, you know, there's the 10 partometers that we're measuring.
And this is the results that the AI says. And then you can see whether that
(29:08):
matches with your perception of the person. And then maybe instead of,
you know, spending time looking at 300 CVs, you can focus on 20,
and then you're going to get better scoring.
At least it's an additional viewpoint that is working very, very well.
So basically, what they're trying to do is to identify the Jeff Bezos that every
company is hiring before that person kind of actually goes, right?
(29:32):
We have another one doing that also for financial planning and accounting.
So, yeah, it's very, very interesting. to see how they're being so creative
in applying AI to solve actual problems that companies have.
It's so exciting, this new frontier. I'm so excited about it.
How does someone find, be accommodated?
(29:53):
Like, how do you find these folks and how did you decide which ones to invest in?
Well, after this, we get around 100 leads every month. Okay.
Which means, and we choose between three to six to join the program.
And we end up investing in one or two out of them, right?
So basically one of the key things that we do is, we definitely, we need to talk to them.
(30:18):
We're starting to use some AI to try to filter that because it's a lot of volume.
But in addition to that, we don't only invest after they have completed the
incubation or the acceleration program.
So if I were to ask you, Mark, if the best way to make sure that someone actually,
you want to work with someone.
Probably you would say that one of the best ways would be if you could work
(30:38):
with that person for two or three months without a pay, make sure that they
actually deliver, right?
Well, that's basically what we do with these companies. We work with them for three to six months.
And then once we're convinced that they're the right fit, then we put money into them.
Worst case, they learn something, they become better entrepreneurs, right?
And, you know, that's fine. So it's this learning process and we continue to
(31:03):
scrub, but we also continue to nail it down.
How much of it is the people versus the idea?
It's always the people first. Yeah, absolutely. Because, you know,
an A team with a B idea will eventually figure it out.
But if the team is not proficient, mature, they really know what they are getting
(31:25):
themselves into. to, they're becoming entrepreneurs, right?
Even if their idea is like the next Amazon, they won't be able to execute. Right.
So we try, sometimes we get a B team with an A idea, but then we work with them
very strongly. We have different pillars that we work. One, the critical one is always team.
So we try to get the right people in the bus.
Right people on the bus, in the right seats, which is important.
(31:48):
Yes, that, yes, exactly.
But, you know, initially there's the wrong people that if, if the people is
wrong, doesn't matter whether they are where they're sitting, right?
So at least we try to get the right people in the bus and then say,
okay, you know, this should be the seats where they go.
But again, remember entrepreneurs, they run their business.
You need to go with them. We can influence them. We can't make them do what we think should be done.
(32:11):
And it's, I always tell them, you know, don't pay attention to anything I tell
you as a mentor, just make whatever decision you want to make.
Just, if you go this way, these are the consequences that I'm seeing,
both positive and negative. If you go that way, this is what I'm saying.
But at the end of the day, it's your business.
I need to trust your decision-making.
That's really interesting. How do you find the mentors?
(32:35):
So mentors, so in many cases, they come from the investment community.
So we do demo days once a month. And then we get, so business angels come,
investors come, people in the industry come.
So eventually, you know, it's word of mouth. So initially, many,
many of them actually come from EO.
So that was the seed mentor community was EO members from all over,
(32:59):
many of them from Barcelona, of course, because that was kind of our network, right?
But now it has grown and they come from all places in life.
David Pérez- I love it. I love it. I mean, it must be a very purposeful thing
to do to help mentor others.
Tell me about your experiences at EO. I mean, you're very involved.
How come? Why, why, why are you so involved with EO?
Carlos Bernal de Liga- So I joined EO after my co-founder in Polymeda joined.
(33:24):
So he joined in June and by Christmas time, he was like, you gotta join EO.
I'm having so much fun. I'm learning so much, this and this and this.
And I was like, yeah, whatever. We're growing a business.
I'm too busy. You know, classical, right?
And then he came one day and he was like, we don't have a defined set of values for our company.
We're a very young company, right? And then he gathered everybody in the team
(33:48):
in a room, took out a whiteboard, and just repeated an exercise that he had
gone through in a TLC training.
Got it. And we came, you know, an hour, an hour later, we just had perfectly
defined values that everybody kind of agreed to.
And it was, um, just fascinating.
Right. And I was like, dude, I mean, this is, well, I just learned this in the
(34:12):
all, you can join whatever.
So I joined January 2008 and I joined the board right away, which was kind of,
you know, initially was, was kind of frightening because it's like,
what, what on earth are we doing here?
Right. There was this fresh. So that was, I was finance chair for two years
and then I became president for two years.
And I always think that they picked me because I didn't campaign or anything
(34:33):
just because I was so passionate about it. So I went to GLCs. I had so much fun.
I, I kind of identified so much with EO people, which is like,
you know, learning, growing, no bullshit.
I mean, people you can instantly trust because you know, they,
we share the same kind of values, right?
Yeah. And the other thing is that I used to travel a lot internationally back
(34:56):
in the day because we were opening up new markets and distributorship and everything.
And every time I would travel somewhere, I'm traveling, I mean,
international states, Europe, Asia, everywhere.
I would beforehand find out if there was any old chapter in that city and I
would let them know I'd be around.
And eight out of 10 times, someone would show up, someone from the board,
(35:17):
some random member, whatever. We would have so much fun. We would talk about everything.
So it gave me so much comfort that, you know, something I really,
really encourage people to do is just experience the international aspect of
EO because we're so busy with a business.
We love our country, et cetera, but there's so much out there.
There's universities, there's colleges, there's chapters out there,
(35:38):
even, even in the same, your same country, right?
If you're traveling, you know, you go to Chicago, New York, Tennessee,
LA, whatever, there's a chapter in every major city, right?
So there's no reason why you can't expand that. But yeah, the international
experience is something I absolutely recommend to people.
I love it. I love it. So we're here sitting here on the podcast.
We're talking AI. We're talking EO. Do you listen to podcasts?
(36:01):
I listen to podcasts, yes. What are you listening to these days?
So I listen a lot to the All In podcast.
I love that. Love it. Yeah, 80% of the times it's just great.
The other 20 just fast forward and that's fine too.
What do you fast forward? always so so you
know sometimes they get into like they they
(36:22):
got into something very specific to like
san francisco something that's happening in san francisco town so they were
talking about homeless people in san francisco so for the first five minutes
it was oh i didn't even know they had this problem and then they start talking
about the 17 different ways of fixing it who is to blame if it's the mayor if
it's the governor and it's like i don't even know what the politics in California is.
(36:42):
Well, it's so funny because all of those people, the hosts of that podcast are like you, right?
They're founders of incubators. They're VC people. They're mentors.
They're getting in there and teaching. And I learn a lot from those folks.
When that whole banking crisis happened with Silicon Valley,
(37:04):
they were spot on and totally explained what was happening. And yeah,
I, I give them a lot of credit, anything else that you're listening to.
So I used to listen a lot to, uh, to Tim Ferriss podcast and then he just got this too long for me.
It's like, sometimes it's like two hours, two and a half hours,
(37:24):
which is fascinating conversation.
But I don't know if maybe I've grown to choose like shorter type of,
uh, of podcasts and then I'm, I'm all the time I'm finding, you know, new podcasts.
I listened to one or two chapters. I love listening to Ted Talks as well,
so which is kind of different type of format. And yes, I love that.
(37:45):
I love hearing what other people are listening to, too. I'm a big fan of All
In, and I get my entertainment from SmartList every week, too,
from those gentlemen. It's really funny.
So busy founder running an incubator, traveling back and forth to Barcelona. Yeah.
(38:06):
What do you do for fun when you have time? Yeah. So I enjoy as much time as I can with my family.
They have two kids, 13 and 17. Well, I shouldn't say kids. I have two teenagers.
There's two kids in my mind, of course. Oh, yeah. So, yeah.
And we live in an area very close to like hiking and lakes and stuff.
(38:28):
So we'll try to go out in the outdoors as often as we can. And so we go walking
or, you know, now in wintertime, for instance, something I love doing is trailblaze
the trails right after a big storm, snowstorm. Yeah.
Which is a great exercise. I don't know if you've tried that.
What is it? What is it? Trailblaze?
(38:48):
So trailblaze would mean, so, you know, you got a foot of snow, right?
Then you will put on your snowshoes and we'll just go and step on the trail to make it again.
But trailblazing, you know what I mean? so you're
the one who's helping everybody else out you're setting it
up for everybody's yeah the rest of their hiking
right you could look at it that way too but it's also a great
(39:09):
exercise for your legs because it's deep snow and
you're working yourself got it exactly it's a great workout and then everybody
else will you know save that and just have the trail ready right so yeah i guess
i'm doing something good too yes you are yes you are you get the trimmers out
there and you clip some of those low hangers and you're really,
really helping people out.
(39:30):
But I love it. You're a trailblazer. I love the symbolism to that as well.
Well, I can't wait to see you again, my friends. I really want to say once again,
how much I appreciate you organizing that AI event. I learned a ton.
I've brought it back. We're experimenting, we're instituting some things,
(39:51):
but we're really excited to lean lean into this whole thing called AI.
And I'm hoping to see you soon, folks. If you see this guy, thank him for putting that together.
But I look forward to seeing you. Are you going to go to the Love Languages Learning?
Yes. Yes, you are. Have you done the test?
I have not. I have that pending, but I think I still have time.
(40:13):
And I'm bringing my wife too.
Good. So I think that's going to be very, very exciting. It's going to be,
and this may actually air after it.
I am looking very much forward to it.
It was a great book. I listened to it on Audible, and I did take the test.
So Glenn and I are both the same. I interviewed Glenn and asked him about this too.
(40:35):
It's the He's Physical Touch and Words of Affirmation 1 and 2,
and I'm Words of Affirmation 1 and Physical Touch 2. So I always joke,
okay, we're going to, every time I see you, we're going to big hug and tell
each other how great we're doing. Exactly.
Well, I'm looking forward to seeing you again. I really, really appreciate you
(40:55):
chatting with us today and sharing your knowledge and wisdom around this new
frontier. Really exciting.
Yep. Likewise, Mark. Thanks for setting this up. Thanks for your energy to move this.
Yes, I wanted to remind people two things. One is if they can just scan this
code here and just join the community and see the recordings and everything we do.
(41:16):
Do, and also is I'll be doing a follow-up AI event because there were so many
questions that I just didn't have time to complete it, so we're planning it
for with Day Will at some point in 2024.
So if you're in for more AI content, you and everybody listening in,
we're going to have more, so stay tuned.
So other than hitting the QR code here, how would someone get in touch with
(41:39):
you if they wanted to connect with you, Luis?
Luis Almeida- Yeah. So probably the easiest is writing to my...
So my email is luisatbecombinator.com. We can put that on the show notes.
I'm on Twitter as well, at LICortez.
And, you know, I think most people in the chapter know me. So just hit me up
with anything. You're traveling to Barcelona.
You're a man. You want to know anything about AI? I'll do my best as well.
(42:02):
You want to talk about anything? Hit me up and we'll make it work.
He's the best. And he's on LinkedIn, believe it or not. So you can connect with
him there. So do so because he's an amazing guy.
Amazing guy. I thank you, my friend. I, I really appreciate you so, so much.
I look forward to seeing you in the flesh and, and learning more with you.
(42:24):
Thanks so much, Mark. Thanks everybody for listening. Well, thank you folks.
I learned something I did.
I always do, especially around this guy, Luis, but if you did and you thought
of somebody share this with them, share this with anyone, share this with everyone.
Thank you all for listening, and we will see you next time on Leadership in
(42:45):
Action, your Boston chapter of EO's podcast.
Hey, thanks for joining us today. If you enjoyed the show, be sure to subscribe
on your platform of choice for a new episode each week and share this with everyone and anyone.
If you have any questions or comments or have an idea for another guest,
feel free to shoot me an email at mstiles at styles-law.com.
(43:06):
That's M-S-T-I-L-E-S at styles-law.com.
And if you are a real estate professional, be sure to check us out on our private
exclusive Facebook page, The Real Estate School at 892 for content and Massachusetts
continuing education opportunities.
Be well, folks. This podcast is being provided for informational purposes only.
(43:28):
The podcast is not a comprehensive overview of the subject and is not intended
to provide legal or financial advice or an endorsement of any product or business.
The views expressed by podcast guests are their own, and their appearance on
the podcast does not imply any endorsement of them or any entity they represent.
Please seek legal, financial, or tax advice before taking any action on the
(43:54):
matters or products discussed herein.
Music.
Welcome to Elements of Styles, the business podcast that trades in scarce thinking
for community, conversation, and ideas in abundance.
Each week, I, Mark Stiles, sit with professionals and entrepreneurs,
both local and global, and learn how they each add value to their communities,
their partners, and their teams. Please enjoy.
(00:23):
Hey, folks, we're going to mix it up a little bit today. Recently,
I was asked by the Boston chapter of Entrepreneur's Organization to host their podcast.
That podcast is called Leadership in Action.
Check it out. Here is an episode that I recently hosted.
Hey, folks, welcome back to Leadership in Action, your podcast for your chapter
(00:45):
of EO here in Boston, Massachusetts.
Very excited to have our guest today.
He is a passionate serial entrepreneur and marketing executive.
He's been a member with EO for over 15 years.
He served as president in his native Barcelona chapter, as well as here in our Boston chapter.
(01:10):
He co-founded and grew Palamita Technologies,
as a co-CEO while leading marketing and sales, and turned it into a worldwide
leader in business Business Process Management Software,
which was then acquired by Red Hat, now IBM, in 2012.
(01:30):
Co-founded B Combinator, the leading accelerator and startup investor in Southern
Europe for B2B and B2C SaaS, AI and generative AI startups.
We're going to talk a lot about that. He's also the leader of the artificial intelligence MyEO,
(01:51):
AI group in all of EO, where over 850 entrepreneurs learn and thrive with AI.
Did I mention who this was? This is none other than Luis Cortez.
Welcome to the podcast, Luis.
Thank you. Thank you. Thank you, Mark.
(02:12):
Thank you for that welcoming intro. I hope I did it. I'm so excited to be here
talking about all these with all my brothers and sisters in Yale.
And yeah, you did a great job. That was a lot of research on my LinkedIn profile.
I hope so. I hope I did you the honor because you are a huge contributor here in the Boston chapter.
And I want to honor and respect that.
(02:36):
So as we begin with all of our podcasts, we ask the same question.
What is the most valuable lesson you've learned while running a business?
Oh, wow, that's, that's, that's great. That's a great question.
You know, probably one of my favorites is that big problem is nothing more than
(03:00):
a small problem that wasn't properly handled at the time.
And I see this over and over.
You know, sometimes you have, you know, it can be anything.
Thing could be person that consistently doesn't
have good results even though
they say they are doing what they
(03:21):
love and everything and for some reason at some point they didn't get
the right enablement or they were put in a they're the right person but they're
not sitting in the right seat of the bus right and that should have been fixed
like two years ago instead of everybody trying to make it go for like two years
of misery if you will right so yeah i don't know where i read that or who I
learned it from. I'm grateful for that lesson.
(03:43):
But yeah, that's one of the many things that I think I've learned while building a business.
So how do you teach that lesson? That's so very important lesson.
Well, you know, sometimes we are just, my experience at least,
right? It's so many things happening at the same time.
So many decisions. We entrepreneurs work more in our business instead of on our business, right?
(04:06):
As we say. Okay, so stepping from time to time and taking a look at,
you know, we are dismissing this because it looks like it's not important,
but if this continues like this, where is it going to be like six,
12 months from now, right?
So trying to a little bit to project something like that, that can help identify those problems.
And, you know, the time when someone or a group is like,
(04:29):
I wouldn't say complaining, but definitely making a deal about something that
something needs to be tackled right there, right now.
Right. Otherwise, you know, you're risking letting it grow under until it's
just this big, ugly pink elephant that is in the room. Right.
Little, little problems become big problems. Right. So pulling back, what's the symptom?
(04:50):
What's really, what's really at issue here? pay attention
keep your antenna up for those those signals
and uh address nip it in the
bud as they say yes and
yeah don't don't don't be lazy trying you know hoping that things will kind
of sort out by themselves i'm talking talking by experience i've made i'm guilty
(05:14):
i'm the most guilty entrepreneur in the planet for letting things pester so
it's not that i do any but at At least, you know,
sometimes it's like, is this going to become a big problem?
And should we kind of tackle it right now?
That's what we do. We share experiences, right? That's all we can do.
And no, I'm with you on that. Are there any AI solutions to avoid that?
(05:37):
It's a nice segue for you. Exactly.
Well, you know, you can train bots with all sorts of documents and things out there.
It's very easy to do these days. so you're actually getting a system that will help you with that.
I haven't seen one for that, but I don't think it would be too complicated to
come up with a question for chat GPT or BART or Bing that would help us think
(06:02):
about, you know, how would you identify a small problem that may become a big one?
And if you identify it, how do you go about it? So I'm sure there may be ways,
but I don't think AI will solve that.
It will give you hints. It will help you think maybe. So AIE,
my impression with what's going on right now is that it's a great assistant. It's a co-pilot.
(06:23):
It's going to help you, you know, get to the roots of problems,
maybe support you with decision-making, but man, humans are still at the wheel now for now. Oh yeah.
So I want to express my gratitude for you and your team putting together that
amazing presentation that Learning Chair Dave Will helped put together for our chapter.
(06:47):
And folks, if you're missing out on these, you're missing out on a huge,
huge value proposition for EO, and that's these learning events.
And Luis put together one for AI. I wanted to show you something real quick.
I brought a prop. Are you ready?
Oh, come on. So after that event, I was blown away by some of the comparisons
(07:10):
and some of the what-ifs and And where are we going with it?
And I was at my in-laws house and look what in there.
That's a great one. Yeah. For those 90% of you who are listening and not,
and not watching, I showed Luis this old fashioned calculator,
(07:30):
the ones where you, you punch in the numbers and you pull down the handle and
you go through that all day long.
And they showed a slide of an entire row of people doing that.
And then they said, and then there's an entire floor of those people.
And now visualize an entire building of people doing that same thing,
(07:51):
punching in the keys, pulling that handle right here.
And now all of that is one CSV spreadsheet. spreadsheet.
So what happens in AI? So we have the fear mongers out there.
Oh my goodness, all of the jobs are going to be eliminated.
What are we going to do? This is going to be the end of it. Let's hear the other side of that.
(08:13):
Well, it's not only not the end of it, but this is just going to take us into
a new age, a new wave of productivity and gains for the economy and for people.
At least I'm a great believer of that.
And just two data points here, right? So believe it or not, 60% of every job
(08:35):
that exists today didn't exist back in 1940.
Wow. Think about that for a minute, right? Right.
So 60 percent of six out of every 10 people working today do something that
didn't even exist, which need wasn't even there like 80 years ago. Right.
And we have what, a billion people now in the planet, something like that.
(08:57):
So why why did this this renovation in employment has come out of technology, of course.
So now we have machines picking up crops instead of people, and we have spreadsheets
doing work instead of people just pulling handles.
So that's basically every person.
We're now way more productive than way before. We live way better now.
(09:20):
So standard of living has raised across the planet and health conditions and the minimum wages.
There's still, of course, big gaps in many countries, but everybody's a little
bit better than it was many, many years ago.
So from that perspective, AI is just another wave in technology.
You can think like, you know, 30 years back when we started talking about the
internet and most of us got in there like, what, 20 years back or something.
(09:42):
The internet just created a whole bunch of new jobs that didn't exist before, right?
Like graphic design and programmers and so many people doing crazy things around the internet.
And then mobile apps, the same thing, right?
So all of a sudden, a new way of using everything is no longer a computer,
which, by the way, only started in 1981, like 50 years ago, right?
(10:05):
Now we have smartphones.
And this created new jobs and probably also cut rid of a few other jobs. So this is just ongoing.
And I believe AI is basically a greater system that gives people superpower.
So each of us can now, again, to our earlier point, right, make better decisions,
be more informed about things, be more productive, be more creative.
(10:27):
And that is just going to expand the value we have to businesses.
Businesses will be able to grow more, make more money, hire more people because they're growing.
So I see this as a virtual circle, not a selfish one.
Yeah, you know, so many people have this two-way path, right?
It's either going to be utopia or it's going to be dystopia.
I see that this is the new revolution, right?
(10:51):
AI revolution, the AI, you know, the industrial revolution, the agriculture
revolution, the tech revolution, AI revolution.
It's simply going to change everything, which scares a lot of people when you say things like that.
It's going to change everything. And that's okay.
Yes. And the other important thing here to keep in mind is, you know,
(11:13):
when they, AI is not going to take away anybody's job, but someone that uses
AI better than you do, me, right?
So it's basically about learning.
AI by itself doesn't have an incentive, doesn't have the ability to come up
with goals or do a number of things.
That's humans. Now, me without AI versus me with AI, me with AI is going to
(11:35):
be X times as more productive, right?
So actually we had in our event, we had Dale Bertrand talking about how the
implementation of AI was just producing 30% gains, productivity gains,
and actually EBITDA gains, like money that he could measure,
right? More coming into the business, right?
And he told us how he was using that 30%, right? So, you know,
10% went for training, 10% went for people experimenting with time.
(11:58):
The other 10% was focusing on growth of the company, right?
So actually everybody's 30% more productive and his business is growing faster,
making more money. So everybody wins, right?
So now you need to make sure that you learn and you play with it the same way
that we did with the internet or with smartphones. You know, it's just another step.
(12:19):
And of course, if you're 20, it's going to be easier than if you're 70.
I get that. But again, technology is easier and easier to work with.
So like my dad, he's 90. He just turned 19 in October last year,
right? Last year was 2023.
This is January 2nd, right? And he has his smartphone, his iPhone for a long
time. He's got his iPod, he's taking pictures.
So, I mean, there's no limits to how easy technology is getting these days.
(12:42):
And I don't think AI is going to be different.
I don't either. And it's definitely moving fast. But I love that quote,
AI is not going to take your job.
Someone who's effectively using AI is going to take your job.
And that's an important distinction.
That's the delegate to elevate conversation we were having before the show is.
(13:05):
Do you need to be doing that task? If not, what purposeful task can you be doing
while, fill in the blank, somebody else is doing it or the technology is doing it?
So I've been having a lot of fun with GPT-4.
What are some of the things that people might not know about with AI right now?
(13:26):
So again, let's timestamp it for those folks listening.
It's January 2nd, 2024. 24.
We simply turned the calendar to another year. I can't believe it's 24, by the way, Luis.
Can you believe that? Yeah. But let's timestamp that. GPT-4 is now here and
we're able to play with it, work with it, utilize it.
(13:48):
What's out there that people may not know about that you want to share with us?
So I think people have gotten used to asking things to chat GPT and to other
bots like BART or Bing or Clot from Anthropic, some others.
I think there's probably two things. One is these apps, these bots,
(14:10):
they are not just like a Q&A agent that you just ask and receive.
You can dialogue with them.
Okay? Okay, so this, you can turn every prompt, every question into a conversation
with it. So you ask for something, you get a response.
And you can, okay, so I didn't quite like that. Change the second sentence to
(14:30):
be more incisive, more friendly, or more highlighter, whatever.
It will change it. Okay, now change the order now.
Or you're asking for a summary of a meeting, right? Dig down into the third point.
What do you think the author thought about this and this and this?
Is you can have a dialogue to
get as deep as you want into whatever conversation you're having with it.
And I think that's something that sometimes people overlook,
(14:51):
but I think that's very helpful.
And help me understand the companies that are propping up and coming out and,
in essence, overlaying ChatGPT, right?
So they're simply creating a service that is, the foundation is ChatGPT, right?
(15:13):
Because it's open. Everyone has access to all of the computer inter-depth things
that I don't really fully understand,
but it is open access to anyone to utilize and, in essence, connect with other
applications, right? Right.
Exactly. So, and it's not too difficult to actually use that power,
(15:37):
even without programming, because you can now build your own assistants,
your own GPTs, as they call them, without any programming at all.
And if you have someone in your business that's a programmer,
Python is a very popular competing program that developers use to work with
chat GPT, but anything that can talk to an API, API, basically,
(16:00):
an application programming interface, you can connect it and build your own
applications very, very easily.
So, you know, something you could do, for instance, is many companies actually
record their customers' calls and you hear that, you know, this call is being
recorded for quality purposes, right?
Well, okay. In many cases, they are actually learning from those calls.
So actually, if, you know, if any of us entrepreneurs, when we talk to our customers,
(16:24):
imagine that you could record every conversation with the customer, right?
I'm sorry. You can ask ChatGPT to transcribe it.
So something I mentioned at the event. And if everything that can be text should
be text. Why? Because now you can use it to train a bot.
You can ask ChatGPT, go through this conversation and identify all the questions
that were asked by the customer and put them here with the answers.
(16:49):
So what did I answer to that objection from my customer, right?
Well, Office, if you do this for like a couple of months, you're going to have,
I don't know, hundreds of conversations. sessions, you're going to very easily
have documented every possible answer to every possible customer question.
So now it becomes very easy to go and train your people so they can actually
clone you, which is one of our key delegation tasks is how do we make our people
(17:10):
as efficient as we are, right?
And vice versa, every time we ask the customer and the customer tells us something,
we can use that to build our sales training for our sales people and say,
hey, when these are are the questions and answers that we can have with customers,
and we can automatically.
Get all that ready just out of recording customer conversations.
(17:31):
So this, you know, two years back, three years back, this was almost impossible
because the computing power wasn't there.
Not to your point, this is open. So the moment you have text,
you have a conversation, you have a book, whatever, you can have all these type
of conversations and extract wonderful value out of it.
Wow. So, you know, I'm seeing these Otter AIs and the Read AIs and the people
(17:54):
are joining in with their notes and the summaries are unbelievable for someone
who's a high DI to see the summarization of the call and be able to walk away with it and be like,
okay, I got this and I can refer back to it.
But taking it to that next step and then teaching the system what we're looking for, right?
(18:19):
The end solution, the prize.
How do we get to the prize? And we can keep feeding the machine until we get
it there. That's fascinating.
So there's a lot of really amazing things going on with AI.
What are some of the things that people want to be careful about?
I'll tell you, one of the things we're sharing with the team as we experiment,
(18:43):
because that's all we're doing right now is really, truly experimenting with it, is no names.
Never, ever put a name into chat, a GPT, and never put any confidential information in there.
Obviously, we're asking very generic questions at this point,
you know, that overlay, that introductory research, if you will.
(19:04):
But one of the things we're saying is no names, no names to start with.
But what else ought people be thinking about?
I think that's critical. No confidential information if you're using the regular chat GPT.
I think that's one thing. The other thing is to carefully check the answers
back to make sure that things kind of align, right?
(19:26):
Because these models, due to the way they are trained, they will never acknowledge
they are making something up.
So, I was just reading two days ago, lawyers keep including wrong information
that they extracted. Yes, still.
I mean, there was this famous Avianca customer that put a suit to the airline
(19:52):
for something that happened.
And the lawyer was using chat GPT to come up with similar cases that,
of course, didn't exist, right?
So, I would say, I think the other key thing is exactly that.
That is just double check on everything that it comes back just to make sure
that it kind of makes sense.
Right. The artificial intern, right?
So, you know, you wouldn't be handing a judge the intern's memo without proofreading
(20:15):
it and shepherdizing it and making sure that the cases actually existed and were relevant.
That's, that's, that's pretty funny. And, and, uh,
And probably something to your question about things that people don't know
is the, so TPT, there's an app for it, for your iPhone, and it includes image recognition on it.
(20:38):
So you can take pictures of things and, you know, you can turn,
you can draw something on a whiteboard and ask it to turn it into HTML content.
It will build a webpage for you that shows. Wow. Or I just used it recently,
so I didn't know whether I could put something on the tumble dryer or not.
So I just took a picture of all those little rounds and circles and triangles
(21:01):
that I don't know what they mean.
And the thing came back, don't put it in the tumble dryer. So I'm a better person
going forward just because of that, right?
That's pretty cool. That's pretty cool. But I want to go back to the hallucinations
that you were referring to, right?
So that's what they're calling them, right? that the system will give you an
answer with confidence, although they've completely made it up.
(21:26):
At what phase do you think that that's going to start to correct itself?
I mean, we're at ChatGPT 4 now. Is it 5? Is it 6? Is it 10?
It's really difficult to get rid of that because of the way the models are created.
So basically what happens in ChatGPT is is it's interestingly,
(21:49):
it's not as intelligent as we think.
Basically what it does, it's an auto-complete on steroids.
You know, when you're typing messages on your iPhone, on your phone,
it will suggest the next word, right, sometimes?
Well, ChatGPT is doing that all the time. And it's so efficient,
so good at it, that it builds a whole complete pages and pages of content that
make perfect sense, that are perfectly organized, etc.
(22:11):
Now, the problem with that is that it is not checking.
It's just looking for patterns. So if the pattern kind of matches,
it doesn't have any knowledge or meaning about what it means.
So it just can't check itself. And there's ways of putting guardrails around
it so it kind of reduces the likelihood that it will come up with weird stuff
(22:31):
by reducing the creativity that you use with a parameter called the temperature.
But even with a very low temperature, results may be better,
but the risk of hallucination is very difficult to get rid of.
And you would maybe chat GPT six or seven will have like automatic self.
(22:52):
Source check or something like that that
will make sure that nothing is false right
but then we would get into what's true what's
false what's fake who is interested in this or
that that's a covid vaccine work or not well depending on what you read so how
is chat gpt going to know whether it works or not i'm just picking on something
random right yeah so it's it's not an easy problem to fix currently and there's
(23:18):
efforts being made by the by the scientific community of course,
to get there because it's becoming so pervasive that people are trusting the
results at face value, right?
But it's one of the challenges that we still have with generative AI.
I do love how it gives you sources though.
So as you get the response and you can click through, and it's a website that
maybe I've never seen before.
(23:40):
And you can go a little bit deeper and And it's almost acknowledging that,
listen, I'm not 100% sure.
Here's where I got that information and do your own research,
right? Again, it's a rough draft.
That's what I keep terming it as. This is a rough draft. It's a good start.
It's going to break the writer's block.
(24:02):
It's certainly going to get the flow going.
I mean, some of the stuff that I've been able to pull out of there,
it's pretty mind-blowing.
When we ask it for something that I
mean it could take two hours to figure out
and it spits it out and it's
it's a great start it's fascinating and actually
(24:23):
you know if if you don't mind I'm going to take a picture of the screen right
now with my phone and we're going to ask it to describe what it's seeing yes
so we can have like a real time so now what platform are you going to put this picture into?
So I'm just taking a picture with chat tpt with the app in my own.
(24:46):
Okay. So this is a picture. Okay.
And then I'm just going to ask, describe this image.
Okay. So that's what I put. I don't know if you can read that.
Yeah, I can. Okay. And it's coming up.
So it's saying the image is a screenshot of a zoom meeting with two participants
on the left side of the screen.
There's a person with a headset in front of a virtual background featuring an
(25:08):
eye and and words like kind, smart, vision, beautiful, and strong.
On the right side, another person is displayed in front of a colorful,
artistic background that appears to be a flip cityscape with a QR code and text.
Pretty good. It didn't recognize that this was the Leadership in Action podcast.
Yeah, it's not that good. That's a step away.
(25:31):
You can see here, right? That's fantastic.
It sees it. It understands it. It's literal.
Exactly. And it's not just, you know, this can become like a toy or a play.
You can play with it and it's fun.
But imagine what it can do for people, right? So it can help people with limited vision to see.
(25:53):
It can help you classify images in your company.
It can be used to compare images and see if something's off.
I mean, the applications are endless, both for personal and for business purposes.
So tell me about B Combinator.
So B Combinator is the leading accelerator in Southern Europe.
(26:15):
So we started, I'm a co-founder there. We started like five years ago,
six years ago, I should say now, because we're 2024.
And we started as a co-working space. So we have our own building.
We own our building, which is like two minutes away from the beat in Barcelona.
We have over a hundred hot desks that startups, entrepreneurs can use to terraces
(26:35):
on top with barbecues and stuff or parties and letting off stress, right?
And then, so we started doing that and we realized how cool it was to work with
entrepreneurs. So we started mentoring entrepreneurs just out of the fun of it, right?
Well, we started bringing in mentors. That mentor community grew up to 150 mentors.
(26:56):
We have way more now. And then...
We developed incubation and acceleration programs to help startups become businesses
and then be able to have a product, sell product, get money from investors,
grow internationally, right? One step at a time.
This is all inspired by the Lean Startup methodology.
(27:18):
And then in addition to years ago, we said, you know what, we should be able
to invest in these startups in addition to mentoring them, right? Right.
So we raised a venture fund that invests in pre-seed stages,
like very, very early stages.
And now we are raising a second fund, a 40 million euro fund that is going to
invest in seed and pre-series stages.
(27:40):
Very cool. So how many of those companies are working in the AI space?
So we currently have around 40 companies in our portfolio and seven are in the
AI space. Wow. What are some of the things that they're working on with AI?
With AI, so they are working on emotion recognition.
So they can take a video of your face and then identify micro-expressions in
(28:01):
your face to see if you're expressing basic emotions, fear, disgust, joy, etc.
And they use that for market research.
So because sometimes you ask people what they think about something and they
say, yeah, I like it, but there's something in their face that is saying that they don't.
So this software can help give you a clear image of what they're doing.
We have another very cool one that is completely changing the landscape for
(28:25):
human resources, all the way from recruiting, making sure the persons that we're
recruiting have a CV and interviews that kind of match the values of the company.
Because I don't know about you, but something that I do consistently wrong is
I hire too fast and fire too slow.
Right. So people spend too much time. There's an AI solve for this?
(28:46):
Well, yes, because AI will help identify if that person fits with the values
of the company, fits with how we do things by analyzing the response that is given to us.
So it's going to give like criteria and say, you know, we'll give you a scorecard
in telling you, you know, there's the 10 partometers that we're measuring.
And this is the results that the AI says. And then you can see whether that
(29:08):
matches with your perception of the person. And then maybe instead of,
you know, spending time looking at 300 CVs, you can focus on 20,
and then you're going to get better scoring.
At least it's an additional viewpoint that is working very, very well.
So basically, what they're trying to do is to identify the Jeff Bezos that every
company is hiring before that person kind of actually goes, right?
(29:32):
We have another one doing that also for financial planning and accounting.
So, yeah, it's very, very interesting. to see how they're being so creative
in applying AI to solve actual problems that companies have.
It's so exciting, this new frontier. I'm so excited about it.
How does someone find, be accommodated?
(29:53):
Like, how do you find these folks and how did you decide which ones to invest in?
Well, after this, we get around 100 leads every month. Okay.
Which means, and we choose between three to six to join the program.
And we end up investing in one or two out of them, right?
So basically one of the key things that we do is, we definitely, we need to talk to them.
(30:18):
We're starting to use some AI to try to filter that because it's a lot of volume.
But in addition to that, we don't only invest after they have completed the
incubation or the acceleration program.
So if I were to ask you, Mark, if the best way to make sure that someone actually,
you want to work with someone.
Probably you would say that one of the best ways would be if you could work
(30:38):
with that person for two or three months without a pay, make sure that they
actually deliver, right?
Well, that's basically what we do with these companies. We work with them for three to six months.
And then once we're convinced that they're the right fit, then we put money into them.
Worst case, they learn something, they become better entrepreneurs, right?
And, you know, that's fine. So it's this learning process and we continue to
(31:03):
scrub, but we also continue to nail it down.
How much of it is the people versus the idea?
It's always the people first. Yeah, absolutely. Because, you know,
an A team with a B idea will eventually figure it out.
But if the team is not proficient, mature, they really know what they are getting
(31:25):
themselves into. to, they're becoming entrepreneurs, right?
Even if their idea is like the next Amazon, they won't be able to execute. Right.
So we try, sometimes we get a B team with an A idea, but then we work with them
very strongly. We have different pillars that we work. One, the critical one is always team.
So we try to get the right people in the bus.
Right people on the bus, in the right seats, which is important.
(31:48):
Yes, that, yes, exactly.
But, you know, initially there's the wrong people that if, if the people is
wrong, doesn't matter whether they are where they're sitting, right?
So at least we try to get the right people in the bus and then say,
okay, you know, this should be the seats where they go.
But again, remember entrepreneurs, they run their business.
You need to go with them. We can influence them. We can't make them do what we think should be done.
(32:11):
And it's, I always tell them, you know, don't pay attention to anything I tell
you as a mentor, just make whatever decision you want to make.
Just, if you go this way, these are the consequences that I'm seeing,
both positive and negative. If you go that way, this is what I'm saying.
But at the end of the day, it's your business.
I need to trust your decision-making.
That's really interesting. How do you find the mentors?
(32:35):
So mentors, so in many cases, they come from the investment community.
So we do demo days once a month. And then we get, so business angels come,
investors come, people in the industry come.
So eventually, you know, it's word of mouth. So initially, many,
many of them actually come from EO.
So that was the seed mentor community was EO members from all over,
(32:59):
many of them from Barcelona, of course, because that was kind of our network, right?
But now it has grown and they come from all places in life.
David Pérez- I love it. I love it. I mean, it must be a very purposeful thing
to do to help mentor others.
Tell me about your experiences at EO. I mean, you're very involved.
How come? Why, why, why are you so involved with EO?
Carlos Bernal de Liga- So I joined EO after my co-founder in Polymeda joined.
(33:24):
So he joined in June and by Christmas time, he was like, you gotta join EO.
I'm having so much fun. I'm learning so much, this and this and this.
And I was like, yeah, whatever. We're growing a business.
I'm too busy. You know, classical, right?
And then he came one day and he was like, we don't have a defined set of values for our company.
We're a very young company, right? And then he gathered everybody in the team
(33:48):
in a room, took out a whiteboard, and just repeated an exercise that he had
gone through in a TLC training.
Got it. And we came, you know, an hour, an hour later, we just had perfectly
defined values that everybody kind of agreed to.
And it was, um, just fascinating.
Right. And I was like, dude, I mean, this is, well, I just learned this in the
(34:12):
all, you can join whatever.
So I joined January 2008 and I joined the board right away, which was kind of,
you know, initially was, was kind of frightening because it's like,
what, what on earth are we doing here?
Right. There was this fresh. So that was, I was finance chair for two years
and then I became president for two years.
And I always think that they picked me because I didn't campaign or anything
(34:33):
just because I was so passionate about it. So I went to GLCs. I had so much fun.
I, I kind of identified so much with EO people, which is like,
you know, learning, growing, no bullshit.
I mean, people you can instantly trust because you know, they,
we share the same kind of values, right?
Yeah. And the other thing is that I used to travel a lot internationally back
(34:56):
in the day because we were opening up new markets and distributorship and everything.
And every time I would travel somewhere, I'm traveling, I mean,
international states, Europe, Asia, everywhere.
I would beforehand find out if there was any old chapter in that city and I
would let them know I'd be around.
And eight out of 10 times, someone would show up, someone from the board,
(35:17):
some random member, whatever. We would have so much fun. We would talk about everything.
So it gave me so much comfort that, you know, something I really,
really encourage people to do is just experience the international aspect of
EO because we're so busy with a business.
We love our country, et cetera, but there's so much out there.
There's universities, there's colleges, there's chapters out there,
(35:38):
even, even in the same, your same country, right?
If you're traveling, you know, you go to Chicago, New York, Tennessee,
LA, whatever, there's a chapter in every major city, right?
So there's no reason why you can't expand that. But yeah, the international
experience is something I absolutely recommend to people.
I love it. I love it. So we're here sitting here on the podcast.
We're talking AI. We're talking EO. Do you listen to podcasts?
(36:01):
I listen to podcasts, yes. What are you listening to these days?
So I listen a lot to the All In podcast.
I love that. Love it. Yeah, 80% of the times it's just great.
The other 20 just fast forward and that's fine too.
What do you fast forward? always so so you
know sometimes they get into like they they
(36:22):
got into something very specific to like
san francisco something that's happening in san francisco town so they were
talking about homeless people in san francisco so for the first five minutes
it was oh i didn't even know they had this problem and then they start talking
about the 17 different ways of fixing it who is to blame if it's the mayor if
it's the governor and it's like i don't even know what the politics in California is.
(36:42):
Well, it's so funny because all of those people, the hosts of that podcast are like you, right?
They're founders of incubators. They're VC people. They're mentors.
They're getting in there and teaching. And I learn a lot from those folks.
When that whole banking crisis happened with Silicon Valley,
(37:04):
they were spot on and totally explained what was happening. And yeah,
I, I give them a lot of credit, anything else that you're listening to.
So I used to listen a lot to, uh, to Tim Ferriss podcast and then he just got this too long for me.
It's like, sometimes it's like two hours, two and a half hours,
(37:24):
which is fascinating conversation.
But I don't know if maybe I've grown to choose like shorter type of,
uh, of podcasts and then I'm, I'm all the time I'm finding, you know, new podcasts.
I listened to one or two chapters. I love listening to Ted Talks as well,
so which is kind of different type of format. And yes, I love that.
(37:45):
I love hearing what other people are listening to, too. I'm a big fan of All
In, and I get my entertainment from SmartList every week, too,
from those gentlemen. It's really funny.
So busy founder running an incubator, traveling back and forth to Barcelona. Yeah.
(38:06):
What do you do for fun when you have time? Yeah. So I enjoy as much time as I can with my family.
They have two kids, 13 and 17. Well, I shouldn't say kids. I have two teenagers.
There's two kids in my mind, of course. Oh, yeah. So, yeah.
And we live in an area very close to like hiking and lakes and stuff.
(38:28):
So we'll try to go out in the outdoors as often as we can. And so we go walking
or, you know, now in wintertime, for instance, something I love doing is trailblaze
the trails right after a big storm, snowstorm. Yeah.
Which is a great exercise. I don't know if you've tried that.
What is it? What is it? Trailblaze?
(38:48):
So trailblaze would mean, so, you know, you got a foot of snow, right?
Then you will put on your snowshoes and we'll just go and step on the trail to make it again.
But trailblazing, you know what I mean? so you're
the one who's helping everybody else out you're setting it
up for everybody's yeah the rest of their hiking
right you could look at it that way too but it's also a great
(39:09):
exercise for your legs because it's deep snow and
you're working yourself got it exactly it's a great workout and then everybody
else will you know save that and just have the trail ready right so yeah i guess
i'm doing something good too yes you are yes you are you get the trimmers out
there and you clip some of those low hangers and you're really,
really helping people out.
(39:30):
But I love it. You're a trailblazer. I love the symbolism to that as well.
Well, I can't wait to see you again, my friends. I really want to say once again,
how much I appreciate you organizing that AI event. I learned a ton.
I've brought it back. We're experimenting, we're instituting some things,
(39:51):
but we're really excited to lean lean into this whole thing called AI.
And I'm hoping to see you soon, folks. If you see this guy, thank him for putting that together.
But I look forward to seeing you. Are you going to go to the Love Languages Learning?
Yes. Yes, you are. Have you done the test?
I have not. I have that pending, but I think I still have time.
(40:13):
And I'm bringing my wife too.
Good. So I think that's going to be very, very exciting. It's going to be,
and this may actually air after it.
I am looking very much forward to it.
It was a great book. I listened to it on Audible, and I did take the test.
So Glenn and I are both the same. I interviewed Glenn and asked him about this too.
(40:35):
It's the He's Physical Touch and Words of Affirmation 1 and 2,
and I'm Words of Affirmation 1 and Physical Touch 2. So I always joke,
okay, we're going to, every time I see you, we're going to big hug and tell
each other how great we're doing. Exactly.
Well, I'm looking forward to seeing you again. I really, really appreciate you
(40:55):
chatting with us today and sharing your knowledge and wisdom around this new
frontier. Really exciting.
Yep. Likewise, Mark. Thanks for setting this up. Thanks for your energy to move this.
Yes, I wanted to remind people two things. One is if they can just scan this
code here and just join the community and see the recordings and everything we do.
(41:16):
Do, and also is I'll be doing a follow-up AI event because there were so many
questions that I just didn't have time to complete it, so we're planning it
for with Day Will at some point in 2024.
So if you're in for more AI content, you and everybody listening in,
we're going to have more, so stay tuned.
So other than hitting the QR code here, how would someone get in touch with
(41:39):
you if they wanted to connect with you, Luis?
Luis Almeida- Yeah. So probably the easiest is writing to my...
So my email is luisatbecombinator.com. We can put that on the show notes.
I'm on Twitter as well, at LICortez.
And, you know, I think most people in the chapter know me. So just hit me up
with anything. You're traveling to Barcelona.
You're a man. You want to know anything about AI? I'll do my best as well.
(42:02):
You want to talk about anything? Hit me up and we'll make it work.
He's the best. And he's on LinkedIn, believe it or not. So you can connect with
him there. So do so because he's an amazing guy.
Amazing guy. I thank you, my friend. I, I really appreciate you so, so much.
I look forward to seeing you in the flesh and, and learning more with you.
(42:24):
Thanks so much, Mark. Thanks everybody for listening. Well, thank you folks.
I learned something I did.
I always do, especially around this guy, Luis, but if you did and you thought
of somebody share this with them, share this with anyone, share this with everyone.
Thank you all for listening, and we will see you next time on Leadership in
(42:45):
Action, your Boston chapter of EO's podcast.
Hey, thanks for joining us today. If you enjoyed the show, be sure to subscribe
on your platform of choice for a new episode each week and share this with everyone and anyone.
If you have any questions or comments or have an idea for another guest,
feel free to shoot me an email at mstiles at styles-law.com.
(43:06):
That's M-S-T-I-L-E-S at styles-law.com.
And if you are a real estate professional, be sure to check us out on our private
exclusive Facebook page, The Real Estate School at 892 for content and Massachusetts
continuing education opportunities.
Be well, folks. This podcast is being provided for informational purposes only.
(43:28):
The podcast is not a comprehensive overview of the subject and is not intended
to provide legal or financial advice or an endorsement of any product or business.
The views expressed by podcast guests are their own, and their appearance on
the podcast does not imply any endorsement of them or any entity they represent.
Please seek legal, financial, or tax advice before taking any action on the
(43:54):
matters or products discussed herein.
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