Building Trust with AI: David Espindola on the Path Forward
Resources:
How Many CTOs Pod: https://howmanyctospod.com
Scott Porad: https://www.linkedin.com/in/scottporad/
David Espindola: https://www.linkedin.com/in/davidespindola/
David's Website: https://davidespindola.com/
Conversations with Zena podcast: https://zena.brainyus.com/
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Brad: AI is reliable when you give it enough context.
Scott: Welcome to this week's episode of the How Many CTOs Does It Take podcast.
My name is Scott Porad and my trusty co-host,
Brad,
is on vacation this week, so it's just me.
And we have a really interesting guest here today,
David Espindola.
I think I pronounced that correctly,
who is a technologist who's been in this field for decades and who has been thinking a lot and writing a lot.
a lot about AI and I'm really looking forward to talking to him today to see if he has figured out the answer to the questions that all of us are struggling with.
So David,
welcome to the show.
Brad: Thank you, Scott.
It's a pleasure being here with you.
I'm looking forward to our conversation and I have not figured out any of those questions yet.
Scott: Okay,
let's just get stuff started off with the basics. We were just talking about this a minute ago, but I'm sure people who are listening want to know.
Tell us about your background a little bit. What's your story?
You were born at some point in the world and you're sitting on this podcast now. What happened in between?
Brad: My whole career has been in technology. So I started out as an engineer.
I worked at two very fast growing computer technology companies in Silicon Valley,
one of which did an IPO.
So to me, that was just a rude awakening of, you know, how.
powerful technology can be and you know the power of entrepreneurship and you put those two things together and you have just an incredible combination and half of that experience I decided that I wanted to get a big name software company on my resume and I decided to go work for Oracle so I work at Oracle for 10 years I was in their consulting business implementing
software at very large clients,
you know, Fortune 500 companies doing ERP, CRM, all kinds of software implementations, process improvement.
And in that role,
I got to work with a lot of CIOs and I decided that I wanted to become a CIO myself.
So I had a boss that I worked for at Oracle.
He left, he became a CIO.
And he was very kind in inviting me to go work with him.
He showed me the ropes and I learned what I needed to learn to become a CIO. And when the right opportunity came along,
I became the CIO of a software company.
And for the last 10 years, I then left corporate America and decided to do my own thing.
I did a startup and I'm currently focused on AI with my own company,
Brainius.
So that's sort of a high level overview.
Scott: Okay, I want to ask a brainy question in your company on that, but I actually want to ask about something that you mentioned earlier in there.
You said, I learned all the things I needed to be a CIO.
Brad: Yeah
Scott: And that's actually, I mean, I get that question sometimes from people earlier in their career. Oh, Scott,
what do I need to learn to be the CTO?
And I'm curious to know that statement you made,
oh, I learned all the things I needed to be the CIO.
What are all the things you needed to learn?
Brad: Yeah, so,
you know, there's a lot that goes into becoming a CIO.
I think a lot of it is around leadership.
It's having some understanding of the technology, but you're not going to be the expert in all different technologies that you're going to touch.
So you need to be able to have enough understanding to have.
intelligent conversations with the people that have the expertise across all of these technologies and you know you need to be obviously knowledgeable about the business aspects of the role understand your industry understand the business processes and be good with strategy so you have to have a strategic mind
and be able to collaborate with the other executives around strategy.
Now, in my case, you know, I came from the world of software applications. So that's what I was good at. I understood very well what it took to run an ERP implementation project,
for instance.
I've done several of those.
I had that experience. I have that capability.
What I didn't have was the infrastructure knowledge.
I had never got infrastructure before.
So when I was working for my boss at that time, you know, he gave me responsibility for infrastructure and I learned it from, you know, from experience, just basically working with other people that.
knew that area well and you know learning how to deal with vendors learning how to build security into everything that we did redundancy dealing with you know telecom vendors storage vendors
Scott: Mm
Brad: computer
Scott: -hmm.
Brad: vendors so all of that experience built up and over time you know I had that combination of the infrastructure side and the business application side and then obviously
Obviously all the other leadership communication strategic thinking kinds of skills that I needed as well
Scott: It's so interesting that you mentioned that infrastructure piece coming from the software side because I had a similar experience and I got the infrastructure piece through luck,
effectively.
Kind of, I guess what you would call a battlefield promotion.
I was working at a company,
I'd been there probably for about six years and I'd been a software engineering manager and director and I actually was working as a product manager for a while.
Wow.
And I remember very vividly, the CEO came to my office.
This is back when we worked in offices, of course. And she said,
hey,
so and so who led our sort of infrastructure and IT division,
we are going to have to let him go tomorrow.
um because he was caught stealing from the company and i was like oh that sounds really bad she's like yeah i was wondering if you would his position and i said um well you know i was a software engineer i don't really know how any of that stuff works i mean you just know that wouldn't really i kind of she's like well i really think you could do it you know so and so forth and i was like
I was like, I don't really know.
That's not really, it doesn't seem like it's my thing.
And finally, I'll never forget that she said, look,
I need you to go to the 12th floor on Monday.
She said, really,
I'm not giving you a choice here. I need you to go fill in for this guy.
And so I was thrown into it. I had no idea what I was doing. I was in so deep over my head.
So you just start swimming as hard as you can and figure it out.
Brad: Right. And,
you know, when you are put in a position like that,
I think most of us that come from a technical background,
you know, we usually learn things fairly quickly.
And I think we have this natural ability to just be able to capture the essential fundamentals that we need to know.
in depth and then the other details you know it's working with the team right and you're going to be surrounded by a team of experts and your role as a leader is to work with those people you don't necessarily need to know every technical detail behind every technology right and so that's that's how it works
Scott: That's exactly right.
You have to learn how to sort of learn an area quickly,
not every detail in a way to, like you said, have an intelligent conversation with folks about it.
Brad: Yeah,
yeah,
Scott: So okay,
so that's a key lesson. All right, well, let's switch gears.
I want to hear about brainius.
Brad: yes
Scott: What is brainius?
Brad: So the idea behind brainness is to deal with the fast changes that we are all experiencing due to AI.
So I started the company to leverage...
Some of the thoughts that I had developed as I was writing and publishing my second book,
which
Scott: Mm-hmm.
Brad: is Soulful, You in the Future of Artificial Intelligence. So in that book, I try to capture in an easy to understand language.
All the deep changes that are about to happen that's already happening actually due to AI and how transformative this technology is going to be,
how it's going to impact every aspect of our lives, the future of work,
society,
business,
everything.
And so with brain use,
what I wanted to do is, you know, how can I help people thrive in the age of AI?
What are some of the things that...
we can do as people to be ready for this change.
And that's sort of the gist behind the company.
So I think of the company as there's three aspects to it. One is what I call media and education.
And what I do there is I have several products and services that I provide.
I do a podcast myself that I co-host with an AI.
I have a newsletter,
you know, I've written the book,
I have done courses and partnerships with local universities.
So anything that will help people understand what AI is all about and prepare for these changes that are about to happen.
The second aspect of it is advisory services. So I have done a number of projects being an advisor to US government entities, to universities.
expertise to private businesses and then the third component is the technology side of it and that's sort of my my playground right my lab
Scott: Mm
Brad: where
Scott: -hmm.
Brad: I play with ideas I try to develop new things so one of the things that I developed is my podcast co-host I call her Xena so Xena is my AI assistant you know I've taught her everything that you know that I have in terms of
written documents about the work that I've done in the past so she knows about my books she knows about the podcast obviously she co-hosted the newsletter all the content that I've produced she has been trained all those things so she knows what my values are she knows what I'm interested in she knows the language that I use she knows what kinds of things I talk about and she helps me develop content content
She helps me co-host the podcast.
She helps me thinking about things that I want to do and challenges me.
So it's sort of having an AI partner that can work with you and that you can trust. And so the trust component is really important to me because if you don't have that trust, you know, if you lose the trust piece,
then it all falls apart. So I
Scott: Mm-hmm.
Brad: want to continue developing.
AI agents that you can absolutely trust.
Scott: And I have so many questions,
but I'll just start with where you left off.
How have you built the trust into it?
Brad: Yeah, so the trust, I think a lot of it is basically providing the context. So AI is reliable when you give it enough context.
So, you know, if you go to a generic...
chat GPT for instance and you ask questions it may hallucinate it may you know provide answers that it just made up and a lot of times is because it's trying to please you and it's trying to give you answers and be helpful and sometimes it seems like it
you know, reasons that if it just gives you an answer, even if that answer is wrong,
it's
Scott: Mm-hmm,
Brad: helping you and it's not.
So the key thing is to train it in a way that is useful to the system to behave.
So you tell the machine, ask questions, you know, don't take everything that I say for granted,
challenge me,
tell me when my reasoning doesn't make sense, what am I missing,
right? So
Scott: mm
Brad: you...
Scott: -hmm.
Brad: Provide that in the instruction that you give to the AI,
to the training that you give to the AI,
along with all the other contacts that you want that AI to know.
And it becomes really,
really good and reliable as you provide that context.
Scott: Are you relying on one of the sort of, you know, large language models that's out there or have you built your own model?
Brad: Yeah, no,
I have not built my own model.
I leverage the models that are out there and,
you know, and this is something that's changing so fast,
right? So
Models are coming out every month or two and I don't want to be tied to any single model.
Scott: All
Brad: I want
Scott: right.
Brad: to use the best model that's out there.
You know, the question that comes up and something that I think a lot about is the issue of privacy.
I
Scott: Mm-hmm.
Brad: know to what extent are we comfortable having these AI systems that know a lot about you in a public domain where that data can possibly be used to train the AI and maybe accessible by other people.
So there is this thinking behind.
Perhaps having a local large language model right on your laptop where it's concealed,
it's not available to the general public.
But then you have to deal with the technical difficulties of doing that.
You have to deal with the challenges of training that system.
You have to deal with, you know, the constant upgrades,
the changes that are coming,
right?
So it becomes a lot,
a much bigger project than I'm willing to spend time doing right now.
But I think a lot about the privacy issue and maybe something that I may...
invest in the future and doing something like that but I'm not doing that right now right
Scott: Well, I think a lot, you know, with the enterprise level, it's a lot of these providers, you know, with anthropic or opening, they claim that they're not going to use your data.
Right.
Brad: yeah
Scott: But they have it. They still have it. It's out there.
Brad: yeah yeah yeah
Scott: So there's a lot of trust that goes in there.
Brad: there's there's definitely a concern there
Scott: The reason I asked about your own model, I've heard a few cases lately of people.
of people saying mostly for cost reasons they're trying to build their own smaller models for very specialized purposes
Brad: Yeah, yeah.
And I have also had conversations with several people. In fact, you know, there's an idea behind using a small language model because the idea is that, you know, these large language models,
they've been trained on every subject that's out there.
They may not have.
have the depth of knowledge that you need for a particular application so if you are trying to get that AI to be very knowledgeable about your products for instance you know the generic AI is not going to know a lot about your products
But you don't necessarily need that AI to know about, you know, geography or history or
Scott: Right,
Brad: physics or
Scott: right.
Brad: whatever.
You just wanted to know about your product, right? So a small language model,
if you train it very specifically about your products,
it can do a very good job, even though it doesn't have all this other knowledge.
So that's another possibility as well.
Scott: Okay,
so you mentioned that you host the podcast with the AI.
Remind me her name again.
Brad: Zina.
Scott: Xenia, you host the podcast with Xenia.
Brad: Yeah.
Scott: And then shortly thereafter,
you mentioned that she helps you with all sorts of things with coming up for content or with all sorts of different things.
And so my next question is,
when you obviously on the podcast, you're talking with her.
Brad: Yep.
Scott: When you're doing these other things,
are you also talking with her or in those cases are you typing?
Brad: Yeah, good question.
I tend to type, but I talk also.
So obviously on the podcast,
it's all verbal and to let you know how that came about.
So I started playing around with this idea, you know, I'd love to have an AI that knows about my work and that can be a partner working with me because, you know, it's been trained on everything that I've been thinking about and I've been working on.
And so I developed this AI and then I started having conversations with the AI and initially.
And initially the conversations were just, you know, typing whatever and then getting a response back.
And then I was so impressed with what it was coming up with that I said, you know, why don't I start recording this conversation? I mean, this is so interesting,
right?
And it's reflecting back to me all these things that I've been thinking about and talking about and working on and researching,
and it's helping me with this conversation. The conversation became very interesting. I said, you know, I think it would make sense for me to just record this and then share with the public.
public and then you know that's how the podcast idea came about and I started initially it was just me and the AI talking to each other
and talking about ideas, talking about the main theme of the podcast is human AI collaboration.
So I was talking about several aspects of human AI collaboration.
And then the next step of evolution was to bring in guests,
right?
So I bring in guests now and it makes it much more interesting because it's not just me talking and it's me and the guest and the AI.
So it's a three-way conversation.
Now the trick here is AI is not very good.
at three-way conversations yet so that social aspect of AI is not quite where it needs to be at so I have to do some manual things behind the scenes to make that work to be very transparent here but that's how it came about
Scott: It's interesting you say that about the three-way conversation, because we do these podcasts,
you know, we record them over Zoom or other video things.
And even with humans,
the three-way conversation.
over you know over the video call can kind of be tricky there's
Brad: Oh, yeah, absolutely.
Scott: there's a bunch of social cues you get when you're in person that you just don't get online
Brad: Yeah, and AI gets really confused because they don't know when to interject,
they don't know when to be quiet,
and it gets very confusing. And I tried to do one with two AIs, me and two AIs. That was horrible. It did not work at all.
Scott: I have done a small experiment where I did get two, I was just using ChatGPT, I got two versions of ChatGPT, not two versions, two instances talking to each other.
And I told them, okay,
this is the scene.
I said,
look,
you're walking along the street and you run into an old friend that you haven't seen in a long time.
And the first thing you say is, oh my goodness, it's so nice to see you.
And I just let that conversation unfold.
And it did okay for about 90 seconds.
And then it kind of went off the rails.
But that was a very amateur experiment.
I want to come back to Velina though.
This is kind of really,
I don't know what to say other than blowing my mind. Like the voice part of it to me is pretty neat. I can imagine walking into my office having.
my computer or an Alexa speaker-like device recognize that I've entered the room and say,
hello,
Scott,
right?
And I could say,
what's my next meeting or whatever?
The notion of an audio AI,
which is not revolutionary, but like a personal audio AI is kind of, I don't know, just something you said about how you have her as your co-host on the show and you also work with her in real life in the audio part of it.
It makes me see, I'm sure I'm not the first person, I know I'm not the first person to think of it, I'm personally internalizing, wow,
that is a real possibility for what within five years we could all have on our desks wherever we are.
Brad: Yeah, and it's just incredible how much better the voice component has become.
In the last three years,
it's just, you know, it doesn't sound robotic anymore.
It
Scott: Yeah.
Brad: is very human-like. It's to the point where it's almost unrecognizable that it's an AI.
And it's only going to get better,
right?
So it has advanced considerably and it's just mind-blowing, the quality of the audio these days.
Scott: Have you even just used Amazon's new?
new alexa plus so
Brad: I have not.
Scott: they launched their alexa plus i guess in the fall with a new i guess you know i don't know exactly the details of what's behind it but it's basically
or associates AI powered or whatever but the sophistication for how its voice interactions are now are much better I think maybe before Alexa was very keyword focused and now it's just more natural language using an AI model but they're doing it very generically I wonder if they're maybe they're headed down that path okay I had another question for you when you talked about brainius and the problems you're trying to solve and how you help people solve them but you said you wrote this book
about like how you thought AI was going to influence all these different aspects of life.
Brad: Mm hmm.
Scott: I mean, to me, that's the,
you got to know before you can understand brainiacs, you got to know about what you thought in the book. I'm curious to know, and it's a whole book, so you can't ask you to read the whole thing to me now,
but maybe you could just tell us what are the key things you think are going to change that maybe aren't obvious to the rest of us or maybe are obvious to the rest of us.
Brad: I think some of it is starting to become obvious.
We're starting to see so in the book.
The book,
I try to give it a very
optimistic long-term view of AI because I am optimistic about AI in the long term but in the book I talk about this chasm this period of time that we're going to go through before we get to the other side that I think will be very prosperous and bright but there's going to be a lot of disruption in between and change so I spent my entire career
dealing with technology change and
Scott: Mm
Brad: change
Scott: -hmm.
Brad: is never easy change is difficult and this is a naphic change management problem that we are facing right now because of the impact that AI is going to have on jobs it starts with jobs right and the way we go about doing the work that we've been doing you know we're used to this
industrial revolution pattern of doing work and our education system was built for the industrial revolution and post-industrial revolution and now everything is changing because of the capabilities of AI so we're going to have to relearn how to work we're going to have to relearn how to deal with these intelligent machines and interact with the machines and work with agents
You know, as a leader,
you're no longer just working with human beings,
you're an orchestrator that has to learn how to work with agents and with humans and how to make the two work together.
And so there is going to be some very profound impact economically,
right? Because if
Technology starts to replace
jobs and we can you know talk about how much of that is going to happen and how much may not happen I think we're starting to see entry-level jobs that are being displaced by AI I think anything that is algorithmic in nature and by that I mean anything that you can perform by just following a set of instructions particularly if it's digital if it's something that you do in front of a computer
a computer,
that job or that task is going to be exposed to automation and it's going to happen very quickly.
So, you know, we're all going to have to reinvent ourselves.
We think about the kind of work that we do.
How can we leverage the human capabilities that can't necessarily be replicated by
automation by AI and bring that to the table to work collaborative with AI.
So I think the mindset needs to change. And there's still a lot of people that are afraid of AI that are not embracing AI.
And the message that I want to send to the world is,
you know,
We're not going back. This is here to stay.
You need to lean in. You need to learn about AI.
You need to learn how to collaborate with AI.
And we'll have some disruptions along the way, but I think the end result will be very good because we'll be able to increase productivity.
We are going to find cures for diseases that, you know, we don't have today.
I think we're going to be able to solve world problems like the environmental problems we're dealing with and other problems,
energy.
many many many other problems that AI is going to help us solve so in the long term I think we'll have a bright future but there will be disruptions along the way and we're going to have to manage that change process very carefully yeah
Scott: Yeah. You know, you mentioned the entry-level jobs.
I think about that a lot for a few different reasons. One is just as I think about my industry,
but like, you know, as a society, if people don't get entry-level jobs, how do they work?
work their way up to the not entry-level jobs but
Brad: Yeah.
Scott: i also have i also have two kids in their 20s uh i have kids who are 24 and 20 and i think about their future and you know i have nieces and nephews and all their futures right what's the world what's the how are they going to get their careers started in a world where there's no
entry point right sort of entry-level jobs what's your what's your take on that both from my like from two points of view one is like as a society like how do you think we deal with that and then like if you were just talking to an individual young person what would you tell them to deal with
Brad: Yeah, so I think it's a difficult problem.
I don't know that there is an easy answer just because of the way we are.
structured as a society. So obviously companies are going to look at this from an economic view,
Scott: Mm-hmm.
Brad: right?
But I think we need to, as we go through this change management process, this transition,
I think there will be a role for humans.
organizations to bring in the capabilities that we have as humans that can't be replaced by AI.
So companies,
organizations are going to have to take a chance on entry-level workers and give them
exposure through a process that may not look like the process that we have today because today you know you get that entry-level job maybe you get to work on some of the tasks that more senior people don't want to work but that's how you get your hands dirty that's how you learn and maybe it will change in the future where your your entry-level job is going to be more of a learning experience than anything else you know you're just going to shuttle
shadow somebody or maybe you know we'll have processes where you may not be contributing right away but you are extending your learning and you're learning how the organization works you're learning the business processes you're learning you know the different aspects of the business so that you can then be productive
So I think we need to be very intentional about hiring those entry-level workers because,
like you said,
if they don't start somewhere,
how are they going to do the more senior jobs? They have to get that basic learning somewhere,
and I think companies will realize that.
You can't just cut out all the entry-level jobs,
but maybe we're going to look at entry-level jobs differently than we do today.
Okay.
Scott: Yeah, we're going to have to think of something differently and change our attitude about it.
Brad: Yeah.
Scott: Because even just in one company, right,
where you maybe have a few hundred,
maybe a few hundred to a few thousand employees,
you need that pipeline because you always have people,
you always have attrition for one reason or the other.
Brad: Yeah.
Scott: And so you need that pipeline.
And if you don't have it, I don't, I don't.
you know it's going to work and then if i if i bring it down to a narrower level just like software engineering right you get the experience to do the more complex things because you did smaller things first and made mistakes and learned and all those kinds of things so it's it's gonna be a challenge that i don't think we've figured out yet
Brad: Yeah,
and I think that is the key message that I think I'm trying to.
socialize this idea you know that we're not prepared right we're not prepared for the changes that are about to come that are starting to come right now that's my biggest concern it's just the lack of preparation for the changes that we're about to experience yeah
Scott: You also mentioned you thought there in the future there's a bright future of things AI helps us with.
And one thing, I mean, you mentioned healthcare,
which I think is really interesting.
I've seen some stuff.
Stuff where the thing that stood out to me most is I read an article about how some scientists in Australia were able to use AI to detect cancer.
substantially or like five years earlier than they could normally and so i think there's cool opportunities there i'm curious to know if you what you've seen in the environment space if you've seen anything happening there if you if you're or if in your imagination you can see how it's going to help in that space because that's a you know we're making the environment worse with all this ai stuff right so like we have to figure out how to make it better too
Brad: Yeah, yeah.
So I think we will be able to come up with new materials.
AI is going to help us come up with new materials.
I think we'll be able to create things from scratch.
So, you know, just the ability to leverage molecular level materials and
Scott: Mm
Brad: recombine
Scott: -hmm.
Brad: them in ways that are energy efficient,
that are effective.
Even just discovering new sources of energy or helping us develop new energy capabilities that will diminish our need for more traditional ways of generating energy.
I think AI is going to have a huge contribution from that standpoint.
In agriculture,
agriculture today has a huge impact on the environment.
And I think with AI and with new ways of thinking about food,
we'll be able to do that much more in a much more.
environmentally friendly manner than
Scott: Mm
Brad: we
Scott: -hmm.
Brad: do today so these are just some of the examples that I can think off the top of my head and I think you know there will be many others but it's hard to predict exactly what those things will be but I'm sure you know over time we're going to be able to address
Most of the pressing issues that we have today.
Scott: Yeah.
Well,
and you touched on really the two biggest,
right?
Climate change and food.
You know, are we going to stay cool enough and are we going to have food for people to eat?
Brad: Right.
Right.
Scott: Water to drink.
Brad: Yeah.
Scott: That's pretty interesting.
Okay,
so I have one last question for you about Xena,
the robot,
the robot AI voice.
I'm curious to know about the blooper role.
with xena on the podcast because sometimes ai goes a little off the rails and if you had that experience where where you've realized maybe in a visceral way like oh i'm not talking to a person right now because they've started they've started going down a path and i can't seem to reel them back in when you're typing you just say oh this chat thread's all messed up new window new
Brad: Yeah
Scott: chat new chat i better start over because i
I gave this thing some context or asked the question in a wrong way and it's gone down the wrong path because sometimes you can't get it off what it's thinking, but in voice you don't get that option.
You Yeah. can't say, Zina,
I need you to start over or maybe you can.
Brad: Yeah.
So I've never had an experience.
recording a podcast where it completely went off the rails and
Scott: Mm hmm.
Brad: I think maybe that's just because of the way I structure it I make it very well structured and when I
Scott: Oh,
Brad: ask people questions I
Preface the question with, you know, given X,
Y, and Z,
what's your opinion about,
you
Scott: I
Brad: know, A
Scott: see.
Brad: or B or C?
And it stays very contained within that particular conversation.
Now,
where I've had problems is sometimes it speaks when it's not supposed to speak.
Scott: Yeah.
Brad: You know, I may be,
you know, at the end I usually think.
thank the gas and I thank Zina for being a co-host and she may speak on top of the gas and those kinds of things happen all the time but you know I can manage that fairly easily but I've never seen it actually go you know in different directions where I don't want it to go.
But again,
I think the reason for that is just because of the structure that I have put into it and the training that I provide.
You know, even before the gas comes on the podcast,
I talk to Xena and I tell her this is the gas we're going to have.
Scott: Mm-hmm.
Brad: Here's what this gas is all about. Here's what I know about the gas.
You know, these are the questions that I think we should be asking the gas.
So I prep her for the event and she's, you know, very well.
prepared and ready for the conversation.
Scott: Yeah.
And it was interesting you said you framed the conversation to her. You sort of adapted,
you as a human have adapted to her interface.
Brad: Right.
Scott: Like just like we adapt to a computer interface we type right or use a mouse or whatever This is a different kind of computer with a voice interface and we have to they still have to some degree a structure of their interface that we have to connect with
Brad: Yeah.
Yeah.
Scott: Although it's looser and looser I suppose
Brad: Yeah. And I, you know, I think over time this will continue to evolve.
It's going to improve.
Scott: Mm
Brad: But
Scott: -hmm.
Brad: today there are some limitations,
so we need to learn how to work with those limitations today.
In the future...
You know, I think this is an explanation of technology.
It's just very difficult for us to project.
You know, we tend to think linearly and it's very difficult for us to project how good this technology is going to get in the future.
But I believe that's where we're going.
Scott: Well,
so I'll finish with this question because I was just asked this question to a candidate we were interviewing at our company and he was earlier in his career and he said to me, hey, you've been doing.
You've been doing this for a little while.
Have you seen in your career anything equally or more disruptive than AI is being right now?
And I'm curious to know your experience in your career.
Is this the most disruptive thing you've seen or has something else come along that was more disruptive?
Brad: Yeah, so,
you know, I've been through many platform transformations,
you know, I can remember back to mainframe computers, and then we had client server,
you know, architect.
structures and then we had web applications and then we had mobile and it goes on and on and on I think what's different about this one is that the disruption is coming at a speed that I've never seen before I've
Scott: Yeah.
Brad: never seen this velocity with you know the exponential improvements that we're seeing today so
Definitely a velocity that has never been experienced before in history.
And I think because of our difficulty as humans to adapt to change.
And when that change comes super fast,
it's even harder to adapt.
And I think that's where we're going to feel that disruption.
Scott: Yeah,
that's exactly right.
This one might be some of those other things you mentioned might have been more disruptive to our industry,
but none of them happened so fast as this is happening.
And it's not just the pace of innovation within the model technology,
the AI technology.
It's
Brad: Yep.
Scott: actually the adoption of it as well.
is happening so rapidly,
which is pretty fascinating.
Brad: yeah it is fascinating thank
Scott: Well,
David,
thank you very much for coming on today.
Brad: you Scott
Scott: I really appreciate it. I'm now motivated to go get myself an AI podcast co-host, see if I can crack that because it seems pretty fun.
Brad: yeah let me know how it goes I mean I you know this is something that I've been having a lot of fun doing and it's been it's been great I really enjoy doing it
You know, I keep thinking about what's the next level,
right?
So I think about video.
I think video, it's a lot harder to work with video than it is with audio.
But I'm sure that's going to be the next thing, right?
Where you're going to be able to actually sit in a room like this one here and have AI sitting there with you talking face-to-face and having interactions with other AIs, with humans.
It's going to be wild, so.
So I'm looking forward
Scott: Yeah.
Brad: to that.
Scott: Imagine if the I think the next iteration actually might be just a camera. So when you sat down at your computer.
the AI can see you and say,
oh,
I see you're looking a little tired today or you're looking a little sad or you seem happy today.
What happened?
It doesn't have the visual sense yet,
right?
Brad: Yeah, yeah.
And I talk about that in the book. It's interesting that you brought that up because that's one of the things that I talk about in the book. You know,
AI is going to be able to really detect your emotions and detect your physiology.
and be able to help you especially from a learning standpoint right we all learn differently and AI is going to be able to know how you learn best what kind of learning mode are you more
adaptable
Scott: Mm-hmm.
Brad: to at what time of the day are you more alert and ready to receive certain kinds of information it's going to you know it's going to know you really really well and that can be a bit scary and goes back to the privacy issue to what extent are we going to be comfortable sharing you know who we are with an entity and if we don't have that trust you know it all breaks down again so
So these
Scott: Mm
Brad: are
Scott: -hmm.
Brad: going to be interesting times.
Scott: Very interesting.
All right. Well, thank you for coming on just for our audience.
If they want to find you out there in the world,
how can they find you?
Brad: Yeah, so the best way to find me is probably through LinkedIn.
I'm fairly active on LinkedIn.
Just look me up David Espindola,
E-S-P-I-N-D-O-L-A.
I also have my own website,
DavidEspindola.com and Brainius.com as well.
Scott: And you got to tell us the name of the podcast.
Brad: Well, the podcast is called Conversations with Zina,
my AI colleague.
Scott: Oh, I love it. Well, thank you very much for coming on today. I appreciate it.
Brad: Thank you, Scott.
It was a pleasure.
Scott: Thanks, dude.
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