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July 30, 2024

Harnessing Tech for Economic Transformation: Sani Abdul-Jabbar on AI Innovations, Blockchain, and the Future of Work

Harnessing Tech for Economic Transformation: Sani Abdul-Jabbar on AI Innovations, Blockchain, and the Future of Work

Can emerging technology truly transform traditional industries while creating new economic opportunities? This week's episode features Sani Abdul-Jabbar, the visionary founder of Vestec, who takes us on a fascinating journey from his humble beginnings in Pakistan to becoming a tech entrepreneur. Sani shares his remarkable story of identifying inefficiencies in sales operations, teaching himself to code, and leveraging his skills at major corporations like Toyota and Warner Brothers to streamline processes. His insights underscore the ever-changing landscape of technology, emphasizing the need for adaptability and continuous learning, especially within the realms of artificial intelligence, machine learning, and blockchain.

Curious about how AI will reshape the job market in the next decade? We'll walk you through the International Monetary Fund's predictions about job transformations and the emergence of roles like prompt engineering. Despite the clear competitive edge AI provides, many businesses hesitate to invest due to uncertainties and potential disruptions. By drawing parallels to historical shifts like the move from horses to cars, we discuss how industries evolve rather than disappear. Sani emphasizes the critical role of expert consultation in navigating these transformative changes and preparing for the future.

How can blockchain technology help track carbon footprints and create economic benefits? We'll explore a groundbreaking AI-powered platform designed to monitor the environmental impact of clothing items throughout their lifecycle. This innovation not only promotes sustainability but also introduces new economic opportunities, including the use of cryptocurrency for data contributions. Sani concludes by highlighting the invaluable role of mentors and ethical considerations in AI development, urging leaders to weave human values into technology. Tune in for an episode packed with insights on thriving in the fast-paced tech industry, the importance of mentorship, and the future of AI-driven transformations.

Chapters

00:00 - Emerging Tech and Creating Opportunities

11:17 - Future Job Trends and Emerging Tech

17:09 - Adapting to AI

26:14 - Carbon Footprint Tracking and Economic Opportunities

32:42 - The Power of Mentors and AI

Transcript
WEBVTT

00:00:00.059 --> 00:00:01.122
All right, How's it going?

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Everyone?

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All right, so today we have another special guest, we have Sani Abdul-Jabbar and, yeah, how are you?

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today.

00:00:09.329 --> 00:00:11.313
Excellent, it's a great day.

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How are you?

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Excellent.

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Excellent.

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So to kind of get this started off, can you tell me a bit about who you are, what you're about and kind of what your overall message is?

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Okay, so I'm the founder of.

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I'm hearing a lot of echo.

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Can something be done about it?

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Okay, so, as you fix the sound, as James introduced me, my name is Sani Abdul-Jabbar, the founder of Vestec.

00:00:41.409 --> 00:00:57.671
That's an emerging tech company here in Los Angeles, about 17 years young, and what we do is we provide technology services, advisory and hands-on development in the emerging tech space and, as you can imagine, emerging tech changes.

00:00:57.671 --> 00:01:02.424
The definition of that changes very frequently because of the constantly shifting tech landscape.

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Because of the constantly shifting tech landscape, currently, emerging tech means artificial intelligence, machine learning, blockchain and everything that falls in that sphere.

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On average, the definition of emerging tech changes about these days, about 14 months, every 14 months, which means we are constantly going through this transformation every 14 to 16 months.

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So what motivated you to get into this industry.

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They say and I was advised by one of my mentors a long time ago that when you're looking to do something in your life that you know a profession, for example, that you're going to keep doing for an extended period there are a couple of things that you have to look for.

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One is what's going to you know, what will get you paid, that's, someone will be willing to pay for that service or skill or whatever it is.

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And the second is what skills do you have?

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Something that you know, something that excites you when you're comfortable with it, right.

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And the third is something that's bigger than you and that's your legacy, something that makes change in the world.

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So when I set out to find what I wanted to do after my corporate career many, many years ago, I was looking for something that fit that criteria, something that will pay my bills, something that excites me and something that's bigger than me.

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And technology was the answer.

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I knew technology.

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I had been in that industry in the corporate world.

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It excited me.

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It was not too long after the 2000 dot-com bubble burst in the US and there was still need in the market.

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Money was tight at that time.

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Companies needed tech but didn't have a lot of funding to support that, so that you know there was a space for us to sort of build ourselves in.

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So we started providing services that were lower cost at that time general IT consulting, and something that's bigger than me is that market needed tech, money was tight and so we addressed that need of the market to support the US industry.

00:03:11.569 --> 00:03:14.062
So that's kind of how I ended up in this space.

00:03:14.703 --> 00:03:31.432
So how did you know about this specific need in the market and what sort of gave you this confidence that you needed, that you could be relevant in this market and you could bring the skill sets or the specific skills that were required to do well in that market?

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You know again.

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Maybe later we could ask the question how did you acquire these skills?

00:03:37.280 --> 00:03:43.768
Yeah, no, that's a very good question, especially for someone who might be considering entering this industry.

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Success doesn't have a straight path from point A to point Z.

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It's a very zigzag path.

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You go up, you go down, you get up again.

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I started out my very first job after business school was actually in sales operations, but in a company that sold hardware software to commercial and government clients at that time a billion dollars company.

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So I started with sales ops and very quickly I realized that there was redundancy in the way that business was run, especially in the sales division where I was a part of.

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And what was happening just to give you one example is that there were three individuals, including myself, who were running the same types of reports for different sales channels.

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So good old days, before automation, before there wasn't even a proper ERP system in place, we were using spreadsheets, microsoft Excel, and these three individuals, including me, we would run sales reports daily.

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That was our job all day long, running sales reports for three different channels one for stores, another for catalog sales, another for something else online sales, I guess and a few weeks into that job I started asking myself why do we have three individuals doing the same job all day long.

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I went to my boss at that time, a really smart gentleman.

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I asked him this question.

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He said well, because that's how we do it.

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That's how we've always been doing it and I have no IT background, by the way, my training is all in business.

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So I knew intuitively that automation was the answer.

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I asked my boss to pay for some training in coding simple basic coding, uh.

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Visual basic, uh, so that I could program microsoft excel sheets.

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And he's like, well, I can't send you for training, but I can buy you a book.

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I said, okay, buy me a book.

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You bought me a book.

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I, you know, taught myself visual basic, started automating those reports and once I was done with all that, I could run reports for the three of us, three different channels, every day of the week and then go for late lunch every day, or late breakfast, rather.

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That's how I kind of realized that there's need for automation, there's need for technology and companies aren't willing to spend a lot of money on it.

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Then I was asked, and that notion was reinforced when I was asked, to go from department to department within the same company, do the same thing, essentially automate processes and make things more efficient.

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Then I left that company.

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I was asked to do the same thing at Toyota, at Warner Brothers, at Direct TV, at a bunch of other corporations, and so that's the answer to the question you asked how did I realize there was a need, how did I realize I had the skill and how did I develop the skill?

00:06:34.605 --> 00:06:36.468
So that was the entry into that space.

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And then, of course, over time, I kept learning and kept observing.

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I do want to mention here an unintended byproduct of this activity, a negative consequence what happens to people when things get automated Right?

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They let go, they become redundant.

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That was the question that my grandmother raised at that time, that my grandmother raised at that time.

00:07:04.744 --> 00:07:10.026
I was quite successful in doing that process optimization and automation and taking people out of their jobs.

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Single guy flying around the country making money.

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Life was good.

00:07:15.300 --> 00:07:18.651
And I visited my grandmother during that time.

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She asked me what I do, what did I do for work?

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I explained to her and she said "'Oh, so you take away people's bread and butter, and that was a gut punch.

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Sometimes, in the pursuit of shiny new objects, we forget the human cost, the social cost, the you know how it impacts everybody around it.

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So that was the time when I realized I needed to stop doing that and start creating opportunities, economic opportunities.

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And that's when I started the company.

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That's when I created a policy for the company from the get-go that we're always going to work on projects that create economic opportunities instead of just blind automation and making people redundant.

00:07:59.555 --> 00:08:04.660
So that's like a short version of my story of origin.

00:08:16.369 --> 00:08:20.192
So that's like a short version of my story of origin.

00:08:20.192 --> 00:08:23.574
Now robotics now it makes me wonder.

00:08:23.574 --> 00:08:30.766
Now you know, yes, it does help to automate things, but it does lead to problems, like you suggested.

00:08:30.766 --> 00:08:30.887
To.

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Now what you're saying, I'm assuming it's a bit different.

00:08:34.822 --> 00:08:37.269
But what does Vestek?

00:08:37.932 --> 00:08:39.075
USA, vestek.

00:08:39.075 --> 00:08:41.602
I do want to answer your question, but quickly.

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What does Vestek do?

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Vestek provides advisory and hands-on software development services.

00:08:48.643 --> 00:08:50.748
These are the two things we do.

00:08:51.549 --> 00:09:03.645
But the first part of your question, that my aspiration to create economic opportunities doesn't seem in line with the promise of AI that's, automation, take people out.

00:09:03.645 --> 00:09:12.721
I have struggled with that thought and I've been asked that question many, many times, because I built my career on this idea of creating economic opportunities.

00:09:12.721 --> 00:09:18.254
But you notice, I didn't say creating jobs, I said creating economic opportunities.

00:09:18.254 --> 00:09:19.823
These are slightly different things.

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Recently I was interviewed by a very successful psychologist and he asked me this interesting question Mark Goulstein, dr Mark Goulstein.

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His question was does AI make us more human or less human?

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And my response to that was what takes our humanity away?

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Let's clarify that.

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First Fight over resources.

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Resources means money, time, space.

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Resources means money, time, space.

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Having to do things that we don't want to do, such as being stuck in a cubicle all day long, working on a job that you don't find inspiring, having to do things that we find risky and threatening those are jobs that are perceived unsafe or dirty, things that we don't find inspiring, such as having to do redundant things redundant work.

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I once worked during my school days at an assembly line in a paper factory and my job was to pick up stacks of paper from here, put them here, pick from here, put them here, and that was the most difficult work I've ever done in my entire life.

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Why?

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Because there is no inspiration, there is no joy, it's just blind, mindless, redundant.

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You know, repetitive motion.

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What AI does?

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Ai takes away, takes on, rather, these things which are redundant, which are uninspiring, which are unsafe, and allows you to do things that inspire you, things that bring joy to your life, things that make your life easier, safer, more comfortable.

00:10:58.168 --> 00:11:00.581
So does it make us less human or more human?

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I would argue that it makes us more human because now we are allowed to, or more human?

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I would argue that it makes us more human because now we are allowed to, we are enabled to experience more as human.

00:11:09.871 --> 00:11:15.083
Now the question how is it going to impact our economic opportunities, our job markets?

00:11:15.083 --> 00:11:16.687
That's a valid question.

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A lot of people are thinking about it.

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Imf issued a report, I think, late last year, and they said without going into the numbers, I think they said, majority of the jobs that exist today, they will disappear by the end of the decade, six years from today.

00:11:31.832 --> 00:11:40.780
Then they said a lot of new jobs that don't exist today, that will be created, new job categories, new job types.

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An example of that is prompt engineering, for example.

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Until two years ago.

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New job types.

00:11:45.869 --> 00:11:47.772
An example of that is prompt engineering, for example.

00:11:47.772 --> 00:11:51.957
Until two years ago it wasn't a word that was part of common conversation.

00:11:51.957 --> 00:11:54.903
I mean, we nerds knew it, but it wasn't part of the common conversation.

00:11:54.903 --> 00:11:57.009
Prompt writing, prompt engineering like when you use ChatGP you say do this, write me.

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That that's prompt engineering.

00:11:58.172 --> 00:12:02.701
And new jobs are also being created as we speak.

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You could argue that are the new jobs going to offset the losses of the new jobs at the same magnitude, at the same level, the same level of wages?

00:12:15.364 --> 00:12:16.822
That's yet to be seen.

00:12:16.822 --> 00:12:22.336
But the good news is that a lot of companies, a lot of smart people, are looking into it.

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I just saw a news this morning that Google and Microsoft traditionally competitors they teamed up to study the impact of AI on the job market.

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So when you hear people saying, oh, your jobs are going away, your jobs are going away, yes, jobs are going away it doesn't mean that new jobs aren't being created, new opportunities aren't being created.

00:12:42.825 --> 00:12:46.700
And I'm not going to candy coat it and say some people aren't going to lose.

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In every paradigm shift there are winners and there are losers.

00:12:49.469 --> 00:12:58.158
Some people will lose, especially people who insist on staying in their comfort zone, insist of keep doing what they want to do.

00:12:59.985 --> 00:13:02.712
An interesting tidbit we got a study done.

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So every year we invest a bunch of money in getting market surveys done, market research done to get a sense of what's going on, because change is very rapid in our industry.

00:13:10.668 --> 00:13:20.386
So every about 14 to 16 months you have to reinvent yourself because new technologies are coming down the pike and the definition of emerging tech is changing.

00:13:20.386 --> 00:13:21.889
So we do that every year.

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When we did that last year, we found out that a very high number I think 78% of business leaders who are surveyed.

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They said they understand that AI is a competitive advantage which, if they don't adopt, their businesses will be impacted within this decade.

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Adopt, their businesses will be impacted within this decade and within the next 10 years, if they don't adopt these new emerging tech tools, they will lose.

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They won't be able to actually exist.

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Forget about compete, exist.

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So it's not just a competitive edge, it's a question of survival.

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Then we found out that less than 4% of these leaders are actually investing in those emerging technologies in any significant, tangible manner.

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Not just saying that, yeah, we have a guy who kind of keeps an eye on what's going on in the industry and we'll see sometime in the future that's also a trend just to appease the board or stakeholders board or stakeholders.

00:14:24.566 --> 00:14:27.791
But people who are leaders, who are actually in a tangible manner investing in this technology, are less than 4%.

00:14:27.791 --> 00:14:30.775
So why the discrepancy?

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78% know and understand that this is a competitive edge and a question of survival.

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Less than 4% are investing.

00:14:37.916 --> 00:14:39.427
And the answer to that is a lot of fear.

00:14:39.427 --> 00:14:49.350
There's a lot of fear in the marketplace fear of the new, fear of the unknown, fear of, oh, what's going to happen to my current business processes that have been working for so many years?

00:14:49.350 --> 00:14:53.195
All of a sudden you're going to take them away or change them somehow.

00:14:53.195 --> 00:14:54.157
They're going to get disrupted.

00:14:54.157 --> 00:14:55.370
My business goes down the drain.

00:14:56.905 --> 00:14:59.294
So the fear of the new, fear of the different.

00:14:59.294 --> 00:15:08.001
And to that my advice is talk to people who do this all day long, people who live and breathe emerging technologies.

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There are people who specialize in this stuff, some of the advisors in my company, vestec, they're like top of their game.

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These are the people who've been doing it, not since 2022, when ChatGPT was released, but since many years before that, and people like that in our company, in other companies they are.

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These are the people that can help demystify uh the all the you know complexities, and separate hype hype from reality, which happens every time there's a new uh tech that's in the market.

00:15:38.346 --> 00:15:42.371
So I'll stop stop at that if you have any comment or question.

00:15:42.611 --> 00:15:56.697
I think it's really interesting how you mentioned new jobs coming up and old jobs dying out, because I think a lot of people in the general mainstream media they only talk about the jobs that are lost.

00:15:56.697 --> 00:16:01.917
So could you maybe potentially give an example?

00:16:01.917 --> 00:16:07.217
Like me, personally, when I think about this, it reminds me a lot of the idea of horses.

00:16:07.217 --> 00:16:12.236
You know, horses used to be a means of transportation from point A to point B.

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But when cars came about, what happened to horses?

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Did that industry die out entirely?

00:16:18.034 --> 00:16:24.899
Not exactly, but horses became more of a hobby, a novelty and something a bit different.

00:16:24.899 --> 00:16:42.898
Now this is obviously completely different from what we're discussing here, but if you could give maybe a more in-depth top, more in-depth example that's more attuned to what you were talking about, yeah, so that's a comparison that's often made in these kind of conversations.

00:16:43.225 --> 00:16:45.130
Nothing happened when we started driving cars.

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Horses are still there.

00:16:46.095 --> 00:16:59.099
The horses industry it's actually a higher paying industry now, like if you are in that industry, you make more money than you did when horses were more common, or horses-based transportation, horses-based transportation.

00:16:59.099 --> 00:17:14.631
The difference is that in the analogy of horses, what you replaced more than horses, you replaced the industry around horses Horses breeding horses, racing horses in the wild.

00:17:14.631 --> 00:17:15.872
They all still exist.

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It's the industry around horses who builds the buggies and who are the trainers and everything else, the tools needed to ride a horse or to ride a buggy All those things.

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They mostly disappear because they're not needed anymore.

00:17:36.996 --> 00:17:38.661
In the analogy of AI, who is the horse?

00:17:38.661 --> 00:17:39.763
I think it's you and I.

00:17:39.763 --> 00:17:40.204
Who is the horse?

00:17:40.204 --> 00:17:42.707
I think it's you and I, right?

00:17:42.707 --> 00:17:46.148
So do we want to end up being a?

00:17:46.148 --> 00:17:47.769
What's the word you use?

00:17:47.769 --> 00:17:49.010
Horses became what Novelty?

00:17:49.010 --> 00:17:51.532
Do humans want to become novelty?

00:17:51.532 --> 00:17:53.934
Probably not, right?

00:17:53.934 --> 00:17:55.095
So that's one.

00:17:55.095 --> 00:17:58.617
The other thing is the scale and speed.

00:17:58.617 --> 00:18:10.373
When we moved from horses to buggies, that took some time and in parts of the world, horses are still being used as primary means of transportation till this day.

00:18:10.373 --> 00:18:23.532
I grew up in Pakistan, my family owned horses as means of transportation till I was probably in third or fifth grade, not in the city, but countryside.

00:18:23.532 --> 00:18:26.334
You know, we had some farms that we owned in the countryside.

00:18:26.334 --> 00:18:38.574
So, point being, even though cars were invented early 1900s, right in parts of the world, horses are still being used as primary means of transportation Not widespread, obviously, but some parts.

00:18:38.574 --> 00:18:46.838
The scale and speed that AI brings with it has never been seen before.

00:18:46.838 --> 00:18:52.556
It's not giving us time to adapt to the shifting landscape.

00:18:52.556 --> 00:18:53.478
That's the challenge.

00:18:54.684 --> 00:19:04.115
Until 2022, october and November, the majority of the people in the world they didn't know AI beyond what's being portrayed in Hollywood movies.

00:19:04.115 --> 00:19:11.233
Like you talk to people till this day, there are spaces where I go and I talk, I bring up AI and the very next thing is robotics.

00:19:11.233 --> 00:19:16.088
Tell us about robotics, because in people's minds, ai means Terminator robot.

00:19:16.088 --> 00:19:24.608
Until Chad GPT, every time I brought up AI in my conversations, the very next question was so terminators are coming, they're going to take over the world.

00:19:24.608 --> 00:19:29.445
Right, I actually wrote a whole book about it that you see on my shoulder Makers.

00:19:29.445 --> 00:19:30.450
Can you see it?

00:19:30.450 --> 00:19:31.554
I can see it.

00:19:31.554 --> 00:19:42.278
Yeah, we'll talk about it a little bit later, but people did not separate AI and robotics until late 2022.

00:19:42.278 --> 00:19:47.090
And after that, within months, everyone was talking about chat gpt.

00:19:47.090 --> 00:19:50.307
November late november is when chat gpt was released, so that's, that's.

00:19:50.307 --> 00:19:51.431
That was the turning point.

00:19:51.912 --> 00:19:54.769
And then, all of a sudden, it became, uh, a household name.

00:19:54.769 --> 00:19:58.883
Everyone is talking about it, from, you know, little kids to grown-ups.

00:19:58.883 --> 00:20:00.347
Everyone is worried about it.

00:20:00.347 --> 00:20:03.798
Then next came the fear, the threat jobs are going away.

00:20:03.798 --> 00:20:10.757
These are tools, but now, for near future, near to midterm future, these are tools.

00:20:10.757 --> 00:20:14.034
So the question is not that AI is stealing your job.

00:20:14.125 --> 00:20:18.436
The question is one can you use AI as a tool?

00:20:18.436 --> 00:20:24.088
And, by the way, james, you're using AI right now in our conversation, right, the mic that you're using?

00:20:24.088 --> 00:20:26.134
I think I have the same kind of mic.

00:20:26.134 --> 00:20:28.651
It has AI built into it.

00:20:28.651 --> 00:20:33.256
I'm using a Rodecaster Pro pro, which you might have too, something like that.

00:20:33.256 --> 00:20:34.227
It's a sound mixer.

00:20:34.227 --> 00:20:35.951
Ai is built into it.

00:20:36.732 --> 00:20:40.069
You're probably going to use some sort of ai tool to create clips and whatnot.

00:20:40.069 --> 00:20:45.731
Afterwards sorry, I'm giving away podcasting secrets, right, so you're not going to sit there and manually cut and paste.

00:20:45.731 --> 00:20:51.934
You're probably going to use something like descriptor, opus or something along those lines that can automatically create those clips and whatnot.

00:20:51.934 --> 00:20:52.596
That's AI.

00:20:52.596 --> 00:20:53.617
These are tools.

00:20:53.617 --> 00:21:03.288
Now imagine you are using those tools and within minutes after this conversation ends, you're able to publish this episode with clips cut out and everything.

00:21:03.288 --> 00:21:06.336
And then there's another guy who is not using any of those tools.

00:21:06.336 --> 00:21:08.106
He needs two weeks to get that work done.

00:21:08.106 --> 00:21:08.807
Who is going to win?

00:21:08.807 --> 00:21:12.252
Are you going to blame the AI or me, who is not using the tools?

00:21:12.252 --> 00:21:25.846
So for now, for the foreseeable future, think of these things as tools and if I can leave your audience with one advice, that is, learn the tools, regardless what industry you're in, regardless what you do.

00:21:26.608 --> 00:21:35.409
There was a notion until a few years ago and even I believed in it that the manual labor tasks will be impacted by AI.

00:21:35.409 --> 00:21:38.734
Later, creative tasks will be impacted by AI.

00:21:38.734 --> 00:21:44.175
Later, analytical tasks accounting, finance, data, analytics, that kind of stuff will be impacted first.

00:21:44.175 --> 00:21:47.349
Now guess what AI is creating art.

00:21:47.349 --> 00:21:50.777
Ai is creating full-scale movies.

00:21:50.777 --> 00:21:53.261
Ai is creating all sorts of work.

00:21:53.261 --> 00:21:55.026
Now add robotics to that.

00:21:55.026 --> 00:22:05.075
And, by the way, the next big thing that's coming down the pike is robotics, because now we have the thinking part to a degree taken care of.

00:22:05.075 --> 00:22:10.519
The next thing is doing part, and that is the robotics part where you'll see more and more robotics.

00:22:10.519 --> 00:22:28.371
I live in Los Angeles and down the street like 10 minutes drive from where I live, there is a restaurant completely run by robots Completely what is this restaurant called I don't remember the name, yeah, I can look it up later for you.

00:22:28.612 --> 00:22:32.318
So that's what's happening and you'll see more and more of that.

00:22:32.318 --> 00:22:41.391
So, saying that these technologies aren't going to impact whatever we do, that's or you know, there's still time, or I'm not retired in a few years.

00:22:41.391 --> 00:22:46.708
Anyway, all those things are risky, very high risk, to every profession.

00:22:46.708 --> 00:22:55.340
So, thinking of these things, these tools as tools, adding them to your tool chest, developing skills, that's the way to do it.

00:22:55.340 --> 00:22:59.835
Now, there are going to be some jobs that are not going to be.

00:22:59.835 --> 00:23:07.578
The jobs will probably still exist, but the demand will go down significantly.

00:23:09.066 --> 00:23:19.513
Imagine something simple as copywriters, the speed at which a person who is using AI tools to write copy for anything is much higher now.

00:23:19.513 --> 00:23:26.074
So you need one person to do the job of five people, or 10 people, compared to the manually writing something right.

00:23:26.074 --> 00:23:29.527
So who is going to survive?

00:23:29.527 --> 00:23:32.375
The few jobs that are going to survive?

00:23:32.375 --> 00:23:41.734
They're going to be left for people who develop skills and learn these tools, not for those who are going to say no, no, no, I'm going to stick with my traditional.

00:23:41.734 --> 00:23:44.680
I'm a Puritan, so I'm going to stick with my old ways.

00:23:44.680 --> 00:23:45.585
I'm not going to change anything.

00:23:45.585 --> 00:23:47.010
I hear that quite a bit.

00:23:47.010 --> 00:24:05.679
I hear that and I brought up copywriting example because recently a gentleman argued with me who has built his career on writing copy for marketing and he's like no, no, no human copy written by humans, that machines can never beat that, so I'm always going to write by hand.

00:24:05.679 --> 00:24:07.428
I was like, okay, keep writing.

00:24:07.428 --> 00:24:14.859
You know, um, you can't force these individuals, but they've got to learn and they've got to change.

00:24:15.425 --> 00:24:27.820
You raise a very interesting point because I think, out of most industries, I think the authorship and writing industry that is being assaulted very heavily with the rise of AI.

00:24:27.820 --> 00:24:55.092
The rise of AI, you know, there's a lot of software right now, such as you know.

00:24:55.092 --> 00:24:57.257
I don't want to give any plugins, but there's a lot of high end interesting.

00:24:57.257 --> 00:24:59.804
But now there's new software coming out, such as you know, text cortex, for example.

00:24:59.804 --> 00:25:03.959
It could imitate eight different people and it could even learn how you write.

00:25:03.959 --> 00:25:10.134
So now you could create new stories, now with very unique forms of writing styles now.

00:25:10.134 --> 00:25:25.336
So in a way, you know, I could maybe, if you know who Stephen King is, I could maybe tell an AI piece of software to write like Stephen King and I could write a Stephen King-like story without any of the skills needed.

00:25:25.715 --> 00:25:39.526
So what you raise is you know a very good point and it's going to be dangerous, and you know.

00:25:39.526 --> 00:25:42.490
This is when I'm beginning to ask now, where do you come in?

00:25:42.490 --> 00:25:48.858
How do you begin to now develop systems where I can't quite remember what you said, but it wasn't create new jobs, but economic opportunities.

00:25:48.858 --> 00:25:53.435
So how do you begin to create new economic opportunities?

00:25:53.435 --> 00:25:55.332
Could you give some examples of this please?

00:25:55.792 --> 00:25:59.246
Yeah, no, I have to think which, ok.

00:25:59.246 --> 00:26:09.355
So here's an example, because I'm not I can't talk about projects of our clients like openly, but there's an example from recent past that I can share.

00:26:09.355 --> 00:26:13.655
So there's a pedal company for which we created a platform.

00:26:13.655 --> 00:26:18.957
The idea was carbon footprint tracking in the apparel industry.

00:26:18.957 --> 00:26:24.416
Apparel industry, arguably, is the largest polluter, environmental polluter in the world.

00:26:24.416 --> 00:26:29.164
If we talk about pollution, most people will think about the oil and gas industry, probably.

00:26:29.164 --> 00:26:36.382
So apparel is up there for different reasons it's either the first or the second largest polluter.

00:26:36.382 --> 00:26:42.074
And then the fashion these days has become um disposable and is very short-lived, like.

00:26:42.074 --> 00:26:50.445
So that's that's why, you know, apparel industry has to constantly keep producing this disposable fashion, and that's resulting in pollution.

00:26:50.906 --> 00:26:52.090
So what this company wanted to do?

00:26:52.090 --> 00:27:07.358
They wanted to track their carbon footprint from the cotton fields in Colombia, where they were picking up their raw material, to production in Mexico, to the retail stores in Europe and UK, and then till the end of life of a clothing item.

00:27:07.358 --> 00:27:10.309
What happens after you're not using it anymore?

00:27:10.309 --> 00:27:18.557
So we created a platform that tracks carbon footprint or environmental impact of a piece of clothing.

00:27:18.557 --> 00:27:22.528
The first thing that AI needs is data.

00:27:22.528 --> 00:27:29.372
That's the lifeblood of AI, and this tool that I talked about, or this platform that I talked about, is a blockchain AI power tool.

00:27:29.372 --> 00:27:47.708
Without data, these tools don't do anything but to bring data from cotton fields in Colombia, for example, you need humans to enter that data into the system how the cotton is being produced or picked, or things like that because you don't have a lot of sensors over there or IoT devices installed in cotton fields, for example.

00:27:47.708 --> 00:27:50.057
So you need humans to collect that data now.

00:27:50.460 --> 00:27:54.119
Now you create an economic opportunity for this person, because no one is going to do it for free, right?

00:27:54.119 --> 00:28:11.657
So whoever is entering that data, you are um rewarding them somehow, you're paying them somehow, and in this case, we created a system of uh cryptocurrency within this platform, and this cryptocurrency, then, is transferable across other crypto platforms, so you can actually get paid from the first platform.

00:28:11.657 --> 00:28:20.589
Then take that cryptocurrency, either keep it within the system or take it to Ethereum or Bitcoin, like more mainstream currencies, or USDT, usdc.

00:28:20.589 --> 00:28:24.593
These are tethered cryptos, tethered against the US dollars, right?

00:28:24.593 --> 00:28:28.748
So you are actually making money by providing that data, so that's an economic opportunity for you.

00:28:28.748 --> 00:28:42.160
This job did not exist until recently, so that's an example of how new jobs are being created, new economic opportunities are being created for people who traditionally you don't perceive Like a farmer working in Colombia in a cotton field.

00:28:42.160 --> 00:28:52.625
You don't perceive that person to be an IT expert or a blockchain expert, but that person is providing data and getting paid for it, so that's an example where we're creating opportunities for people.

00:28:53.315 --> 00:28:59.835
Now I'm beginning to think now what is sort of the future of Vestek and your future?

00:28:59.954 --> 00:29:03.701
perhaps as the CEO, future of Vestek and future of me.

00:29:03.701 --> 00:29:07.148
So our work is very much.

00:29:07.148 --> 00:29:15.259
It changes because, as I mentioned earlier, the definition of emerging tech changes every you know about a year.

00:29:15.259 --> 00:29:21.740
So today we are working on AI, yesterday we were working on blockchain, tomorrow we'll be working on something else.

00:29:21.740 --> 00:29:26.065
Technology is the industry that I understand.

00:29:26.065 --> 00:29:31.688
Now what we are doing currently, we are bringing these emerging technologies into different industry verticals.

00:29:32.234 --> 00:29:35.365
One of my primary areas where I'm focused right now is oil and gas.

00:29:35.365 --> 00:29:39.244
Oil and gas is a very traditional industry, especially midstream.

00:29:39.244 --> 00:29:43.320
Midstream means on the top you have the producers, at the bottom you have the users.

00:29:43.320 --> 00:29:58.421
Like yourself, you put fuel in your car, but in the middle there are several entities involved that make fuel going from point A to point Z, and it's a very traditional business model People still communicating via phone calls and WhatsApp, and WhatsApp is advanced.

00:29:58.421 --> 00:30:01.484
That's advanced technology, right, very traditional.

00:30:01.484 --> 00:30:08.387
So what we're trying to do is bringing these emerging technologies into these traditional industries.

00:30:09.397 --> 00:30:11.454
I mentioned apparel traditional industry.

00:30:11.454 --> 00:30:12.881
It's been around for a while.

00:30:12.881 --> 00:30:15.240
Healthcare is a big one.

00:30:15.240 --> 00:30:23.277
Fintech we have done a lot of work in FinTech, banking, finance sector, done a lot of work in healthcare apparel supply chain across different industries.

00:30:23.277 --> 00:30:23.979
That's a big one.

00:30:23.979 --> 00:30:25.544
Currently, oil and gas.

00:30:25.544 --> 00:30:26.246
That's a big one.

00:30:26.246 --> 00:30:31.483
Then services industries legal we have done work for legal.

00:30:31.483 --> 00:30:35.119
Then governments trying to bring emerging tech for the governments.

00:30:35.119 --> 00:30:43.007
We have worked for TSA, we have worked for the Arizona court system.

00:30:43.007 --> 00:30:51.586
So where you see a lot of traditional way of doing things, how can we automate that and bring more smart tech into that?

00:30:51.586 --> 00:30:53.701
So there's a lot of that going on.

00:30:53.701 --> 00:31:02.347
My personal interest big one is finding ways to address the risk of fraud.

00:31:02.347 --> 00:31:11.943
Ai-powered fraud that's huge and it's expanding and getting… yeah, disinformation, deepfakes.

00:31:12.315 --> 00:31:13.616
Yeah, all of that, all of them, yeah, all of that.

00:31:13.876 --> 00:31:25.270
So I'm part of a consortium of companies that is looking into it and trying to find ways on what we can do as industry players in order to address those kind of things.

00:31:25.270 --> 00:31:39.480
Improve digital literacy, you know, yeah, a lot of that now.

00:31:39.480 --> 00:31:41.712
They're actually studying a lot of that now in research and top universities and, yeah, what you're doing is very relevant.

00:31:41.712 --> 00:31:42.295
Yeah, yeah, so we partner with universities as well.

00:31:42.295 --> 00:31:42.742
You mentioned universities.

00:31:42.605 --> 00:31:53.435
So the lot of research that's being done in the academia and we partner up with here Caltech in Los Angeles USC is not too far UCLA, so scholars from there we work with them.

00:31:53.435 --> 00:32:05.131
In the past, when we were working on healthcare, bringing emerging tech in healthcare, we partnered up with UCLA, brought in researchers, phd-level researchers, in that space.

00:32:05.131 --> 00:32:27.047
So we try to bring in most cutting-edge research and technology from whatever we find and then we try to match that with the industry need, because science and technology sitting in those, you know, thesis and papers and books doesn't do a whole lot for the society until it comes and applied in different industry verticals and social verticals.

00:32:27.047 --> 00:32:30.722
So trying to be a bridge there too as well.

00:32:31.505 --> 00:32:31.826
Excellent.

00:32:31.826 --> 00:32:40.704
So this is another question I have for you If you could go back in time and perhaps maybe speak to your younger self?

00:32:42.067 --> 00:32:42.989
what would you say to him?

00:32:42.989 --> 00:32:44.840
That's a very good question.

00:32:44.840 --> 00:32:53.230
I think I would teach my younger self the value of mentors and guides in life.

00:32:53.230 --> 00:32:56.204
I did not see that value until much later in life.

00:32:56.204 --> 00:33:00.536
I grew up in Pakistan.

00:33:00.536 --> 00:33:03.663
It's a very masculine culture where you don't ask for help.

00:33:03.663 --> 00:33:11.886
You have to find answers for yourself, and that's how you learn by your own mistakes, from your own experiences.

00:33:11.886 --> 00:33:15.520
But that's not the most efficient way of doing things.

00:33:16.142 --> 00:33:23.423
If I could go back in time and talk to my younger self, I'd be like my advice would be like go out and find advisors right.

00:33:23.423 --> 00:33:28.703
And even when I started looking for advisors and mentors, I thought that I needed one mentor.

00:33:28.703 --> 00:33:30.761
You never say I have mentors.

00:33:30.761 --> 00:33:32.241
Most people say I have a mentor.

00:33:32.241 --> 00:33:38.163
So I thought my younger self thought back in the day that I just needed one perfect teacher.

00:33:38.163 --> 00:33:39.277
That doesn't exist.

00:33:40.619 --> 00:33:43.847
And over time I learned that we need guides and mentors and teachers.

00:33:43.847 --> 00:33:58.269
We need several of them, some at our level, some few years ahead of us, some many, many years ahead of us, so they can present to us different angles or different perspective to address a situation or to plan your life.

00:33:58.269 --> 00:34:04.144
That's actually one of my regrets in life I didn't see that value till much later.

00:34:04.144 --> 00:34:11.407
So that would be my advice to my younger self and that's what I tell to all young people who come to me for advice Find teachers.

00:34:11.407 --> 00:34:12.835
Don't look for one perfect teacher.

00:34:12.835 --> 00:34:18.447
Find teachers in different areas of your life, whatever you want to achieve.

00:34:18.447 --> 00:34:27.264
And, by the way, anything that I have achieved in my life, anything and everything, I give credit to my guides and mentors and teachers and Sherpas.

00:34:27.264 --> 00:34:29.856
I couldn't have done that on my own.

00:34:29.856 --> 00:34:31.099
Excellent.

00:34:31.679 --> 00:34:36.224
So just to kind of close this off, end this off.

00:34:36.224 --> 00:34:40.411
Are there any other things you would like to let the audience know?

00:34:40.411 --> 00:34:48.588
Any ways we could reach out to you, maybe learn more about you and your business as well, and your other ventures too.

00:34:49.210 --> 00:34:55.068
Yeah, so I would like to mention the book that we touched upon earlier.

00:34:55.068 --> 00:35:00.525
The book that we touched upon earlier.

00:35:00.525 --> 00:35:14.018
So what happened is that several years ago, I mentioned earlier in this conversation that every time I brought up AI, people would start talking about terminators, robots coming to take over the world, and that question was asked so many times that I started asking counter question how can we avoid that?

00:35:14.018 --> 00:35:20.400
So I asked that question to many experts and scholars in different walks of life.

00:35:20.400 --> 00:35:25.496
The question was how can we avoid AI to do dangerous things 20 years from today?

00:35:25.496 --> 00:35:33.266
And the reason behind 20 years is because, based on all the formulas and all the forecasts at that time was that it would take about 20 years for AI to become smart enough.

00:35:33.266 --> 00:35:36.648
By the way, that timeline has shrunk after COVID.

00:35:36.648 --> 00:35:48.286
So when I started asking that question, one of the gentlemen that asked the question, he said what would you do today to prevent your kids from doing stupid things 20 years down the road?

00:35:48.286 --> 00:35:54.266
I said, well, we'll teach them some good human values and then hope that they will behave.

00:35:54.266 --> 00:36:11.043
He said yeah, that's exactly what you need to do with AI, because there is a resemblance between how you raise a child and how you train AI, you expose them to different situations, provide information, let them deal with different situations, come up with their own solutions, all that kind of stuff.

00:36:11.043 --> 00:36:15.824
So there's that resemblance, so I thought that was a great idea.

00:36:15.824 --> 00:36:18.094
Human values, empathy, compassion, kindness you know that kind resemblance, so I thought that was a great idea.

00:36:18.094 --> 00:36:20.103
Human values, empathy, compassion, kindness, that kind of stuff.

00:36:20.103 --> 00:36:28.646
If we can embed that in the evolution of AI, make it intentionally, make it a part of how you evolve AI, I think that would solve the problem.

00:36:28.646 --> 00:36:30.317
So I wrote a book about it.

00:36:30.317 --> 00:36:34.786
You'll have to read the book to see my five-point framework.

00:36:34.786 --> 00:36:40.539
It's a work of fiction, but written around those five human values that I believe.

00:36:40.539 --> 00:36:53.217
If we can bake that into AI, then future more advanced pieces of AI and robotics will be more beneficial to human society than a threat and we can coexist and thrive alongside AI.

00:36:53.217 --> 00:36:54.920
So that's that.

00:36:57.764 --> 00:37:00.108
So one thing that we talked about is data.

00:37:00.108 --> 00:37:04.539
Data is lifeblood of AI.

00:37:04.539 --> 00:37:05.521
Where does data come from?

00:37:05.521 --> 00:37:06.525
Data come from you and me.

00:37:06.525 --> 00:37:18.543
Every decision that we are making today in any organization, any leadership position, that decision, our decisions today, that becomes training data for AI for tomorrow.

00:37:18.543 --> 00:37:22.043
So when we're making that decision now, it puts more responsibility on our shoulders.

00:37:22.043 --> 00:37:26.523
So that would be my advice Be more mindful, learn these tools.

00:37:26.523 --> 00:37:28.722
I can be reached via LinkedIn.

00:37:28.722 --> 00:37:30.000
That's the best way to reach me.

00:37:30.000 --> 00:37:45.777
Just my name Sunny S-A-N-I, and if you are in a leadership position in a company and you're looking to do, if you're wondering if AI's tools or other emerging tech tools are something that your organization can benefit from, but you don't know where to begin, talk to our people.

00:37:45.777 --> 00:37:46.320
Reach out to me.

00:37:46.320 --> 00:37:52.784
I can connect you with people within our organization who can provide some guidance and insights on how to move forward.

00:37:52.784 --> 00:37:54.248
That would be my.

00:37:54.248 --> 00:37:57.617
I would like to leave your audience with Happy to help.

00:37:58.355 --> 00:38:01.744
Okay, well, thank you again for being on the show, sani.

00:38:01.744 --> 00:38:03.822
This really has been a privilege.

00:38:03.822 --> 00:38:07.943
I definitely learned a lot, and I think the audience here will learn a lot too.

00:38:07.943 --> 00:38:14.981
I would also like to thank everyone else here for watching the show, and I will see you all next time.

00:38:14.981 --> 00:38:16.284
Thanks for having me.

00:38:16.284 --> 00:38:16.384
John.