April 1, 2024 • 44 mins
Discover how the tech world is grappling with the latest AI regulations from Europe as Sani Abdul-Jabbar CEO of VezTek joins the Tech Travels Podcast. We dive into Europe's latest AI regulations, the synergy of AI and blockchain in energy trading, and the digital era's impact on education and the workforce. Sani brings insights from his book 'Makers: A Slender Knowledge,' offering a nuanced view on AI's global impact, ethical innovation, and the transformative potential of blockchain. Join us as we explore how these technologies are reshaping learning, work, and the tech landscape.
Venture with us into a hybrid realm where AI meets blockchain, and the future of energy trading is rewritten. I explore the hesitation within the business community to combine these powerful technologies, despite the clear strategic advantages. Sani and I scrutinize the dichotomy between recognizing AI's potential and the hesitancy to invest in it, discussing the hurdles that both emerging and established companies must overcome to stay competitive in a tech-driven market.
We round off our conversation with a leap into the digital era's impact on education and the workforce, where Sani shares his vast experiences from his global travels. We ponder the metaverse's growing influence on our daily lives, the emergent tech trends poised to transform industries, and the evolving skills required to thrive alongside AI. Tune in to envisage a future where artificial intelligence is not a specter of job loss but a beacon of entrepreneurial opportunity, reshaping the way we learn, work, and create.
About Sani Abdul-Jabbar
https://www.linkedin.com/in/sani?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=ios_app
“Makers A Slender Knowledge” Book
https://amzn.to/3xn9ajG
VezTek
https://www.linkedin.com/company/veztekusa/
“Makers is a visionary exploration of AI’s societal impact. It challenges us to consider the ethical and human dimensions of AI development, making this a must-read story.”
Nolan Bushnell, Founder of Atari and Chuck E. Cheese, author, and a founding father of the video game industry
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:05):
Welcome to Tech Travels hosted by the seasoned
tech enthusiast and industryexpert, steve Woodard.
With over 25 years ofexperience and a track record of
collaborating with thebrightest minds in technology,
steve is your seasoned guidethrough the ever-evolving world
of innovation.
Join us as we embark on aninsightful journey, exploring
(00:27):
the past, present and future oftech under Steve's expert
guidance.
Speaker 2 (00:33):
Welcome back, fellow travelers, to another amazing
episode of Tech Travels.
Today, we have the pleasure ofhosting Sani Abdul-Jabbar, a
visionary CEO at VizTech, acompany that's at the forefront
of emerging tech.
Sani leads a talented teamthat's pushing the boundaries
around blockchain and artificialintelligence.
Also, as an author and athought leader, a voice and
authority in Web3, sani is hereto share his insights as to
(00:55):
what's shaping our digitallandscape today.
So buckle up as we embark onthis journey through technology
with Sani Abdul-Jabbar.
Sani, welcome to Tech Travels.
It's an honor to have you onthe show today.
Speaker 3 (01:05):
Thank you.
Speaker 2 (01:05):
Steve, it's a pleasure to be here.
I want to very glad to have you.
I really want to kind of leadwith this story here.
It just broke yesterday World'sfirst major act to regulate AI,
passed by European lawmakers.
It says the European Union isnow a global standard setter in
artificial intelligence.
So kind of help us walk througha little bit of this late
(01:26):
breaking news and kind of whatthis means for us here in the
United States.
Speaker 3 (01:30):
Yeah, so that certainly is the hot topic today
.
This conversation aboutregulation in EU has been going
on since December, at least Well, since before that, but
December was early December.
They presented the first draftof this bill in their parliament
and it was eventually approvedyesterday.
(01:51):
The gist of this bill is thatit's so.
They divided, or categorized,rather, ai technologies by risk
level of risk.
So the highest extreme levelwould be unacceptable level of
risk, the lowest would beacceptable level of risk, and
then there are three otherlevels in between total five, I
(02:13):
think and so that's what theyhave done Now.
Historically, I have alwayssupported the idea of regulation
, mindful regulation.
That's the point.
Mindful is the key.
In the US, we have this cowboymindset in the tech world.
Right, don't stop me, don'tregulate me, because if you
(02:36):
regulate me, that hinders thedevelopment of technology.
That's what I'm trying to do.
But the problem is that, yes, Ican develop technology, but if
there are no rules of engagementand I come to you, steve, try
to sell the technology, you'regoing to say well, what are the
rules of engagement?
How are we going to play Ifthere's no gameplay?
If there are no rules of thegame, we can't play right.
I can't sell that technology tolarge corporations.
(02:57):
I can't sell that technology togovernment agencies.
They're not going to touch it.
So therefore we need regulation.
The counter argument of that is,if the regulation is put in
place just for the sake ofregulation, then we run into a
situation where regulationbecomes counterproductive.
(03:18):
Right, lawmakers aren'tnecessarily experts in
technology, it's the influencegroups, it's the think tanks,
it's the influence groups, it'sit's the um think tanks, it's
the lobbying groups who and theindustry groups who have a role
to play in that.
But you know, there's always umpriority of interests and all
prioritization of interest andcompetitive interest.
That is uh that we have to dealwith um.
(03:41):
So, having said all that, Ihaven't read the full bill uh of
in the eu that was passed inthe eu parliament yesterday, so
I can't comment on it withspecifics.
But uh, if it's put togethermindfully, if there are experts
involved in it, if they are notputting regulation in place just
for the out of fear not notnecessarily um to put you
(04:05):
guardrails around it then it canbe counterproductive.
It doesn't seem so so far whatI've read about it.
It doesn't look like it looksquite reasonable, but, like I
said, I haven't read the wholething yet.
Speaker 2 (04:16):
Yeah, absolutely, and I think the idea of regulation
just means that it provides acertainty that we really need.
The tech community really doesthrive on innovation, but
without a clear framework, asyou mentioned, we really can't
realize the potential of thesetechnologies.
But your point about themindful regulation really
resonates strongly with mebecause, I mean, I think it's
(04:37):
really about striking a criticalbalance.
I think we need to ensure thattheir experts are at the table
with these regulations whenthey're drafted so they don't
really reflect, you know, fearor misunderstanding around
artificial intelligence.
But also, given that the EU hasrecently taken steps, I think
it really sets the stage thatit's becoming more and more of a
guide, because here in the USwe have this, like I said, this
(05:00):
Wild West type of mentality oftech towards a more structured
frontier.
Now, with the post-pandemicsurge in AI awareness and
application, I think it's reallycrucial that we navigate the
hype cycle thoughtfully.
So could this bill be ablueprint for really just
marrying innovation withresponsibility, or is it
(05:21):
something that all of us in anindustry need to watch closely
and learn as we move forward?
Speaker 3 (05:27):
Every technology, every innovative technology,
goes through a hype cycle.
Now, hype, in my opinion, isnot necessarily a bad thing,
because what hype does?
It attracts resources, attractspeople, attracts funding and we
develop things, so that's agood thing.
The negative of hype is thateveryone and you know their
grandmother starts claiming thatthey are experts in that field.
(05:50):
I attended a an event not lastweek, no, this week, actually on
monday where we reviewedseveral projects nine 900
projects total, uh with a groupalong with other group of
experts in the industry forinvestment.
So we were reviewing theprojects for investment.
At least 70% of them weresomethingai, and once you start
(06:15):
asking questions, you realizethat there is no AI.
A lot of them was oh, I'mbuilding a custom GPT, a custom
GPT plugin.
Well, that's not yourintellectual property, so don't
call it your project.
You're asking for hundreds ofmillions of dollars for
something that you don't own.
Openai can shut you downtomorrow, so that Then there are
(06:38):
a lot of people who are justdoing smart automation of things
and they're calling it AI doingsmart automation of things and
they're calling it AI.
Overall, I think there are lessthan 10% companies who are
actually building somethinginteresting that can be
legitimately called AI.
So that's that.
That's the current state of theindustry, in my opinion, at
least what I am seeing in thespaces where I operate.
(07:00):
Are we in the hype cycle?
Most certainly yes.
My gut feeling is that we needat least till the end of this
year to reasonably come out ofthis hype cycle, because what's
going to happen by the end ofthis year is that you will know
companies that are ai, companieswhich are actually ai or not.
(07:23):
So that's what's going to happenby the end of this year and my
guesstimate is that by the endof the next year, companies who
are claiming to be ai but not aiand who have raised money, they
will run out of money.
So industry consolidation willhappen towards the end of the
next year and that's when we'llstart seeing real players in the
industry.
The winners will become morevisible.
(07:45):
This is not to say that reallyinteresting technologies aren't
evolving and coming up in themarket every day.
Recently I attended a meeting acouple months ago now, at
Microsoft.
It was the kind of meetingwhere you have to sign NDA
before going to the meeting.
They presented some productsfor the entertainment industry,
(08:08):
film industry and it's mindboggling what you can do the
kind of stuff that theseproducts can do.
I can't talk too much about itbecause of the non-disclosure
commitments, but I can tell youthat this is mind boggling.
Speaker 2 (08:25):
If anyone thinks that jobs aren't going to get
impacted, industries aren'tgoing to get impacted, they're
dreaming right, yeah, and I Ithink the distinction you draw
really is powerful, because thedistinction between superficial
AI applications and genuineinnovation is really a wake-up
call, and I mean it's soberingto hear your estimate that under
(08:45):
10% of projects are trulyartificial intelligence.
I also think that yourprediction on on industry
consolidation really aligns withthe critical need to discern
real expertise from the hype.
So, with that in mind, whenconsidering expertise, what is
your top criteria foridentifying true AI specialists
(09:09):
in this crowded field?
And just give me a little bitof idea kind of what goes into
that thought process.
Speaker 3 (09:16):
So, first of all, this technology is not such a
new technology.
Yes, chad GPT made it popularin the end of 2022, but the
first large-scale AI-poweredproject that we did was in 2018
or 2015, somewhere there.
So technology has been around.
So there's a technical side ofit and that's easy to judge if
(09:43):
someone has those technicalskills or not.
You just look at their previouswork and all that.
Gpt, and especially its use inthe industry, that's relatively
new at the level and the scalewhere it's evolving now.
So, at that scale, what'simportant is that and the rapid
evolution of the industry.
So what's very important for meis I don't care if you know
everything today or not, but Ido care if you dedicate time and
(10:05):
resources to learningconstantly.
Constantly, because it's anevolving industry.
Every day something new iscoming out.
So when I interview, or my teaminterviews, people who are
looking to join our teams,beyond their technical skills,
we also judge what they'rereading.
We look at their LinkedInprofiles and we see what they're
(10:26):
posting.
We look at their you know, weask them you know what's the
recent book that you read orwhat's the recent articles that
you read, because that tells methat this person is staying on
top of things.
Are there any interestingthings you have created using
LLMs, gpts, that kind of stuff,even in your personal time, even
for your personal entertainmentreasons, because that shows
(10:49):
your interest in the technology.
A few things that are reallyimportant right now for the
business world, for the industryand the leaders to understand
is, when it comes to projectselection and product
development, rules are still thesame.
The best practices are stillthe same.
You have to think about ROI.
You have to think about who itimpacts.
(11:11):
You have to think about who thedecision makers, decision
influencers are, who thecustomers and consumers are.
These are the basics of anyproduct development.
Have always been.
What's slightly new this timearound is in the past, data used
to be the sideshow.
Now data is the main show.
What that means is, if you askme today and it happens, I mean
(11:33):
Steve, like, if know, put adollar in my saving account.
Uh, every time someone asks me,so you know, give me this blue
pill that will solve all my, allmy problems.
I'd be quite rich people.
It hap.
It happens every time.
We have a new emerging tech andit's happening again now in in
the wake of ai and evenblockchain.
Still where a business leaderwill come to us and say tell me
(11:55):
how I can bring AI into mybusiness today to automate all
my processes so that I canachieve that competitive
advantage right away that I canusing AI, and my response to
them is no, that's not how it'sgoing to work.
It's the same answer that Igave you two years ago when we
were talking about blockchain,and two years before that when
we were talking about otherthings.
(12:18):
This time around, in in thecontext of product development,
what's new is that?
Or project selection, you haveto first think where do you in
your organization's processesyou have the most amount of data
?
That's the low hanging fruit.
That's where you gotta startchat gpt, having access to it or
any other llm or any ai tool.
(12:39):
Just the fact that you and Iboth have access to it doesn't
give us competitive advantage.
You and I both can getsubscription of chat gpt for 20,
for example, or other tools fordifferent levels of you know
investment, but anyone can dothat if they can afford it.
So that's not competitiveadvantage.
Competitive advantages if Stevepicks up a GPT and trains it on
(13:05):
his writings, his speaking, hishistory, his businesses data.
Now that's competitive advantagebecause Sunny does not have
access to that data, so I don'thave that competitive advantage
you do.
That's what I'm trying toadvocate for businesses is that
when you want to bring in AI,leverage AI and other emerging
technologies for competitiveadvantage, think where do you
(13:27):
have data in your organizationTypically finance, accounting,
sales, so that's the first levelwhere you have the most amount
of and most clean data.
When you go below that, thenthe data is not that clean, but
there's still marketingoperations, things like that.
You still find some data.
So then that would be thesecond layer and so on.
(13:49):
So that would be people lookingfor opportunities in the AI
world if they can just learnthese skills and use these
skills where they can analyzeprocesses of a business, see
where automation opportunitiesare, see where the data is and
(14:09):
then figure out what tools, whatAI tools, can be brought in to
automate those processes usingthat internal proprietary data.
That's the low hanging fruit.
Speaker 2 (14:19):
Yeah, sani, I completely agree that the true
competitive advantage lies inutilizing the proprietary data
with AI tools and then tailoringthem to the unique aspects of
one's particular business.
Them to the unique aspects ofone's particular business.
So, just on the topic ofleveraging unique assets, this
(14:40):
really brings to mind thecontrast with blockchain's
philosophy of decentralization.
Now, while AI, especially inthe form of services like
ChatGPT, really tends tocentralize knowledge within the
major tech companies, it looksto me like blockchain really
aims to distribute that control.
But what's interesting toobserve is these different
(15:01):
approaches AI reallycentralizing versus blockchains
decentralizing.
So I'm very curious how do yousee this interplay affecting
businesses that are looking toadopt these technologies for
competitive edge?
Do you start to see thatthere's a synthesis between
these models?
Could they offer the best ofboth worlds?
(15:22):
I mean, I think they tend tofavor more centralization.
Speaker 3 (15:27):
True, although I think we have an answer to that
problem Within the blockchainindustry, blockchain technology.
You have three different typesof blockchains.
One is public, one is private,one is hybrid.
So public is anyone can join,private is only certain people
can join or certain entities canjoin, and hybrid is a group of
(15:50):
the two.
So think an industry where abunch of companies are allowed
to join that chain.
So that would be hybrid, whereit's somewhat public, but not
quite right.
Ai, on the other hand,especially when you look at
machine learning models, theyuse large amounts of data, right
, so you can limit that data to.
You can say that only look atthis one data set, don't look at
(16:14):
global data set.
Openai actually startedoffering this type of a service
for businesses not too long ago,and other companies will do it
as well, because obviously wecan't open up all our data to
everybody, so that doesn't work.
So one of the companies that Ihead up, it's in the energy
sector energy trading, fuelcommodities, primarily jet fuel,
(16:37):
etc.
And it's middle market, and Irealized that in that market
there are lots of players, many,many, many players.
Some are small, some are largeand some work on deals for years
and never get anywhere.
Others, they have more dealsgoing on, but these deals are
large scale deals.
So if you can close one deal,this is like hundreds of
(16:59):
millions of dollars.
However, there is no centralizedsystem in place, because
information is the key.
If I know where to buy theproduct, where to sell the
product, how to price theproduct, I have the power to
price the product.
I have the power.
Right, that's, that's myintellectual property, that's my
um, that's the power, as assoon as it's uh, this
information is available toanybody else, I lose my
(17:21):
competitive edge, can't survive.
So I propose the idea ofcreating a uh hybrid blockchain,
where a hybrid blockchain basedum erp type system where we can
streamline all these verycomplex processes involved in
energy trading.
Put all of that on the system.
(17:42):
It would be a centralizedsystem in which all buyers not
all, but whoever wants to playyou know they would be members
of it buyers and sellers.
And this idea wasn't verypopular in that industry because
the information to your earlierpoint, because you know, on one
side we have public informationversus private information.
The idea didn't fly very wellbecause, like I said, people are
(18:06):
very protective of theirinformation, no matter how much
you try to assure them that thisinformation stays with you.
You own it and when you put iton the chain, it's fully secured
, no problem.
It didn't work.
But if you bring it at acompany level that you can do
that, technologically you can doit.
You can keep all the datawithin a company, but then the
(18:28):
cost of operating it goesthrough the roof.
And, as I mentioned many ofthese, most of these companies
are small companies.
They don't have those kinds ofresources.
So, can, technologically, aiand blockchain work together?
That's actually a match made inheaven, right?
If you just look at blockchain,it's, I believe.
(18:49):
In my opinion, it's one pieceof the puzzle you have to look
at.
Data collection.
Collection comes from sensors,humans, machines, any sources.
Right Data comes in.
Then you secure that datasomewhere.
That's your blockchain in anyof I mentioned three types.
There are others it's.
Think of it as a spectrum ofhow public a chain is.
(19:10):
And then what do you do withthat data?
That's, that's the AI part.
You do something using AI, lookfor pattern detection or
whatever.
You create some actionableinsights out of that data and
then you use that.
So both technologies are verywell suited to work together.
The issue is not that theycan't work together.
(19:31):
The issue is how much justcommunicating this to the
stakeholders, the idea that yourinformation is secure when it's
on the chain and that's goingto be a problem when you're
working across entities as longas it's within one entity a
government, a very largeorganization you're fine, no
problem.
But when you go outside thatand you want to share
(19:52):
information across entities,even if it's fully secure,
that's a hard sell.
Speaker 2 (19:59):
It's interesting.
I mean, your insights into thesynergy between AI and
blockchain really areenlightening and I love this,
especially considering thesecurity and data privacy
concerns I mean really thatyou've outlined.
But, given your expertise withthese technologies, what would
you say the primary hurdles arewhen you encounter or when
you're advising companies.
Specifically, how do youaddress the hesitation of
(20:22):
executives who really may graspthe potential for AI blockchain
but are reluctant to really makethat leap due to perceived
risks or a lack of a strategicvision specifically for
implementation of AI products?
Speaker 3 (20:39):
So we get some industry surveys done every year
to get a sense of the techlandscape.
In the recent survey, we foundout that over 78% business
leaders they completelyunderstand and believe that AI
and emerging technologies arethe competitive edge.
If they don't adopt thesetechnologies within the next 10
(21:02):
years, they will lose theircompetitive edge.
They won't be able to survivewithin one decade, regardless
how stable you are.
Today, complete understanding,less than four percent leaders
are actually investing umsignificant amount of resources
into leveraging thesetechnologies and and bringing
(21:25):
these tech into into theirbusiness operations.
When asked why, the most commonresponse was I, I don't have
information, I don't haveguidance, I don't know who to
trust because everyone isclaiming to be the expert.
I'm concerned that my existingprocesses that are working
perfectly they will break if Iintroduce a new tech into it and
(21:47):
that kind of stuff.
The issue wasn't money.
The issue was fear.
The solution to that is quiteeasy.
As a matter of fact, theeasiest solution is you got to
find experts.
I mean, we have people in ourcompany at Vesek, who this is
their bread and butter.
This is what they, you know,live and breathe.
So just talking to people likethat and saying you know, look
(22:10):
at my processes and tell mewhere the opportunity is, and we
are not always going to tellyou that you have the
opportunity.
If you don't have the data,either your own or access to it,
somehow you can't use thesetools Right.
It's not a competitiveadvantage GPT type tools or
(22:35):
other AI tools.
You have to somehow customizethem to a level where they
become yours, where they becomeyour competitive edge.
Not just, you know, anybody canpay the fee and get
subscription.
Then that's not a competitiveedge.
Now, on lower levels, like youknow, creating some tech,
generating some text ormarketing copy, or GPT to write
your emails or improve your,whatever that can be done, but I
(22:59):
don't see that as a competitiveadvantage.
Yes, it increases yourefficiency.
I think I made a statementsomewhere, got some pushback for
it.
If today you go in any decentsize organization, look at their
processes, introduce publiclyavailable ai tools, you can
increase their efficiency by byabout 15, 15 to 17 percent.
(23:20):
So that's that.
But almost any reason areasonable size organization has
access to that.
If everybody has access tosomething, I don't consider that
competitive advantage.
Competitive advantage is whenyou have access but others don't
.
To get to that level, you haveto make these tools yours by
customizing them based on yourdata.
Speaker 2 (23:42):
Yeah, and customization takes time, it
takes effort, it takes cycleswithin your team to be able to
develop this.
I think in your book youmentioned again that the book is
amazing.
I started reading it.
The maker is a slenderknowledge uh, phenomenal so far.
I think you mentioned in thebook that vestec, you know,
really shines as an innovationhub for emerging technologies
and that, and then in that itsays it redefines them within 12
(24:05):
to 16 months, and I'm reallyinterested here a little bit
around your emerging convergenceframework and kind of what led
you to it.
How did you know, how do youbridge the gap between skills
and infrastructure and how doyou evangelize that when you're
talking with executives andpeople in the tech space?
Speaker 3 (24:20):
So that that emerging emergence convergence framework
, which is a emerging techforecasting framework.
It evolved and was developed asa very painful need that we had
at that point.
Vesdek, I founded it in 2006,and the idea was we're always
(24:42):
going to be emerging techcompany.
That means, whatever technologyis emerging, we're going to
provide consulting, developmentresources in those technologies.
Well, the challenge was that atthat point, technology
landscape was shifting likecomplete paradigm shift within
about three to five years.
(25:02):
At that point, then whathappened is that that that
change, it became the period ofthat change.
It became shorter and shorterand shorter.
Frequency just kept going up.
Currently, in the post-COVID era, we are at 12 to 14 months, 12
to 16 months max, right, andthen that's when change happens.
(25:24):
If you look back to, every lessthan two years we have some new
technology that that becomestalk of the town.
So this is the landscape thatwe've been dealing, dealing with
since 2006.
What many of our peers in theindustry, what they do?
What they do is they wait forthe demand to come in, and when
the demand comes in, then theygo out and look for resources
(25:47):
and and then they try to capturethe demand.
That model wasn't working for us.
So what we did is we createdthis framework which, like I
said, it's a forecastingframework.
It allows us to kind of lookdown the path and see what
technologies are coming down thepike and then invest in those
(26:09):
technologies ahead of time,develop resources, build
infrastructure, retool, retrainour existing teams and see if we
can be prepared in time tocapture that demand when it
comes up in the market.
So we have to be mindful ofhype versus actual demand.
We have to be mindful foractual investments coming in
(26:31):
that space or not.
Are there enough resourcesavailable in the market or not?
Things like that.
So that's the emergenceconvergence framework.
Currently it gives us about 12to 14 months head start.
So that's a good thing to haveto know that we need to be
prepared for technology X in 12months.
Speaker 2 (26:51):
That's incredible because most of the time you
don't see that quick.
You typically see the cyclesanywhere between 24 to 36 months
, on a turnaround for somethinglike very new, innovative.
We don't really know what thisis.
We're looking for experts inthe field to kind of help us
figure out a trajectory, butthat's incredible that you have
that.
I want to dive into the book alittle bit the Maker's Slender
(27:11):
Knowledge.
I started reading it and I'vebeen fascinated with it.
I really want to get through it.
But what I found interestingwas I want to hear your
perspective on kind of what ledyou to really write the book and
how you kind of curatedknowledge from different people
from different walks of life tocreate this amazing book.
Speaker 3 (27:28):
Excellent question.
So what happened is that manyyears?
I mentioned earlier that ourfirst large scale project that
leveraged AI was in 2015,.
I think what was happening isthat every time I would bring up
AI, machine learning, anythinglike that the first, the most
common response was Terminator.
So robots are going to takeover the world right, the doom
(27:51):
and gloom scenario.
As an entrepreneur, I'm ahopeful person, but that's my
default setting.
So I started thinking there hasto be a way to avoid that
scenario, and so I startedasking questions and at that
point, looking at the evolutionof technology and all the
forecasting models that we had,the estimate was it would take
(28:15):
about 20 years for the AItechnology and robotics
technology to get to a pointwhere it becomes AGI artificial
general intelligence.
That's the threat, that's yourterminators, right?
So I started asking thisquestion what would it take to
stop AI from doing stupid things20 years from today?
(28:37):
And I just literally I askedthis question to countless
number of people, anybody whowould listen to me, regardless
of their background, because Ireally believed that magic
happens at the convergence ofdifferent disciplines.
Because I really believed thatmagic happens at the convergence
of different disciplines aslong as you keep it within one
silo or within one area ofknowledge.
(28:57):
You're kind of limited.
So I went across the aisles andI spoke with people in
different fields, includingpolitics and clergy and
sociology I mean, you name itand the response that resonated
with me the most was the personasked me a question in response
to my question, and his questionwas what would you do today to
(29:22):
prevent your kids from doingstupid things, 20 years from
today?
And it's like that's a goodquestion.
What do you do?
Well, you try to teach goodvalues to your children.
You hope that they would learnand you hope that they're
listening and you hope that theywould become better people.
It's like that's exactly whatyou need to do with AI, because
(29:43):
the way you train AI and the wayyou raise children is similar
in certain ways Similar as inwhen we teach our kids values.
The best way that we've beentaught is be the role model.
Kids are looking up to you.
Be the role model.
Do good things in front of them.
They'll learn, instead oflecturing them, exposing them to
(30:03):
good environments and sometimesyou lecture them.
So equivalent of lecturingwould be direct data entry in
the AI world.
Right, uh, sometime you exposethem to different environments.
Um, take them out shopping, forexample, with you and see how
the process of shopping is doneat a grocery store, right.
And sometime you give them thecredit card and have them, uh,
(30:26):
pay to the cashier theequivalent that exposing them to
different environments in theAI world would be, for example,
exposing your AI model toYouTube data, for instance,
right?
So there are lots ofsimilarities.
So that's where the idea camefrom.
If you teach good human valuesto AI today, if you bake that
(30:49):
morality and the values in theway we are developing AI, then
there is a chance that AI woulddevelop into the kind of beings
that we can coexist with andthrive alongside.
So that's where the idea camefrom.
Now, when I started writing thebook, initially I thought of
(31:09):
writing the book in a almostlike a manifesto how to 10 ways
to do X kind of model.
But, uh, I had the good fortuneof uh speaking with Mr Mark
Victor Hanson uh, chicken soupfor the soul author, very
well-known person.
He later became my publisher.
So I had a conversation withhim about it, asking him the
(31:30):
same question.
He's like you got to write abook about it.
I was like, okay, let's write abook and then when he heard
that I wanted to write it as howto, he's like no, no, no one
wants that Write it as a story.
So the book is a work of fiction, but mindfully divided into
chapters.
Each chapter is about a valueand experience of AI in how it
interacts with humans and howhumans respond to it, and my
(31:53):
hope from this is we can raisesome questions.
We can trigger people to thinkwhat can be done in our personal
capacities today, because ourdecisions today is the data for
AI training tomorrow.
So my decision today in myorganization don't just impact
my people today.
It can potentially impact a lotof people in a lot of places
(32:14):
down the road if my decisionsthat I made today is used for
training of the AI.
So that's kind of was mymotivation.
Speaker 2 (32:23):
Yeah, sani, the way that you've woven the
interaction of human andartificial intelligence values
into a narrative.
It's a very powerful approachand I think it brings awareness
and it really is a stimulatingthought.
The storytelling aspect reallyseems to connect deeply, I think
, with our need to understandcomplex issues like artificial
intelligence through a relatableexperience.
(32:45):
Given this impact, do youenvision that the collective
stories and experiences that areshared in society really could
lead to more unified ethicalframework for AI, and how might
we harness the storytelling toreally create AI values that are
widely accepted and implemented?
Speaker 3 (33:08):
In one of my recent interviews, I brought up the
idea of AI, ethics and values,and the person interviewing me,
he said well, all AI is built onvalues.
There is no AI without values.
Now, whose values?
That's another question.
From the history, we do knowthat whenever we try to impose
(33:29):
any one entity's values on otherpeople, it doesn't work.
We have seen that over and over, whether it's in the religious
context or political context orany context.
So I don't think it's going tobe values imposed by any single
entity.
I think what's going to happenand these are just speculations,
right, we don't know yet.
(33:49):
I think what's going to happenis that, over time, hopefully,
as you know, human race, ascitizens of this world, will
come up to some understanding,some agreement over some basic
rules, some basic.
You know, these are the fivebasic values that we can agree
(34:10):
on, for example, and um, perhapsthat would be the starting
point.
I don't think it's going to be awhole set of values coming from
some one entity.
The other possibility is that,um, you end up with one clear
market leader.
You know, google, for example,controls 80 of of the search
(34:30):
market today.
They can set the rules for thebrowser search industry right
Because they own 80% of themarket share.
So something like that couldalso happen.
Where one company or one entityhas that much power that they
can set the rules, that canhappen.
(34:50):
I have also speculated that UNmay have to get involved, some
UN level body where they cancome in and they can say okay,
you know, we need some centralinternational organization to
come up with some principles,some values and goals, some
values and rules of engagementthat we can agree on.
(35:11):
We don't know yet.
So these are all speculations.
Your guess is as good as mine.
Speaker 2 (35:19):
So, sani, so as our conversation as we draw to a
close, I'm really struck by thepoignant dedication in your book
A Slender Knowledge, where youcharge your sons not only to
coexist but also to thrivealongside AI entities.
And the message really resonateswith me profoundly because, as
a father of young twin boys whoare also on the onset of their
(35:42):
journey in a world where therelies that intersection between
humanity and AI and they'rebecoming increasingly blurred, I
think it's fascinating somewhat.
I think it's fascinating, butsomewhat daunting, to really
consider the landscape and howthey will navigate that in the
next five years, I think, theterrain where AI will become
even more present andinfluential.
(36:04):
So, drawing on your hopefulvision as you set forth for your
children, where do you see usstanding with AI in that
timeframe and how can we as asociety also lay the groundwork
for future generations to notjust adapt but also to leverage
(36:24):
AI to their advantage and alsoensuring that they don't just
survive but they indeed thrive?
Speaker 3 (36:32):
that they don't just survive, but they indeed thrive.
So I don't call myself futurist, I call myself nexus.
Futurist would be oh, in 70years X is going to happen.
I'll be dead in 70 years.
So you can't come and sue me,but I'm more interested in
what's likely in the next fewyears so we can plan for it.
Your kids are young, four years, um.
(36:53):
So they are about what?
20 years away from theworkforce, roughly, yeah give or
take, yeah, my kids a littlebit older, uh, 13 and 10.
The way I think is I I think 10years ahead.
So how the world looks like 10years ahead and then work
backwards 10 years ahead, andthis is not just my opinion.
(37:15):
Many, many experts in theindustry they agree on it.
So the life 10 years ahead islikely to be very virtual.
We got a taste of that with thewhole idea of metaverse.
It was too early, too ahead ofits time.
Right now it's justentertainment and we don't have
enough technology, the rightkind of technology, to really
(37:39):
put Metaverse to work.
If you look backwards, the earlydays of Internet, the very
first version of the Internet,the very first generation, was
just post some articles on theserver and then in
Urbana-Champaign, for example,and then in Chicago, researchers
could read those articles.
That was the internet, the veryfirst version.
(38:00):
The second iteration there wassome interaction.
Third iteration well, in thesecond there was also e-commerce
kind of got involved, and nowin the third one, decentralized
data and trust.
That's big.
So you keep going forward 10years forward.
Virtual lives, virtual internet, virtual lifestyle that's
(38:21):
highly likely to happen, inwhich we work, we play, we live
in these virtual environments.
Very early version of that.
Is this what we are doing rightnow.
You know remotely, but we'retalking about like fully
immersed environments in thefuture.
In order to get there, there arecertain technologies that need
(38:41):
to happen.
The e-commerce system needs toevolve.
The internet speed needs toevolve.
The energy sector needs toevolve.
Currently, 3% of global energyis being consumed by emerging
technologies.
By the end of this year, we areexpecting 8% energy to be
consumed by emergingtechnologies.
That's not sustainable.
So that has to change.
(39:04):
Jobs that are currently any jobsthat's data-driven job.
Well, until recently, I used tosay if it's a data-driven job
anything where your informationthink a physician not a surgeon,
but physician who only useslots of information those jobs
are very much at risk of beingsignificantly impacted.
But I think you posted on yourLinkedIn yesterday, or somebody,
(39:26):
a robot that came out withinthis month that can do like
dishes and folding laundry andthat kind of stuff.
It's like wow, okay, so evenphysical jobs are now getting
impacted.
So for the kids especially,knowing that we're moving
towards that virtual world andknowing that in order to get
(39:48):
there, we need certain othertechnologies and industries to
involve, I think that's where weneed to pay attention, because
that's going to then determinethe education of our children
today, the training and theirfuture professional prospects.
Speaker 2 (40:03):
Fascinating.
So you're probably going to saythat this is me probably
thinking kind of double clickingon that a little bit is
thinking around embracingartificial intelligence and
understanding how AI reallyplays a role in learning and
development at a much earlierage.
So you think that probably kidswho are now in elementary
school will probably be moreexposed as we start looking at
(40:24):
AI's role in education as aneducator, as a way for them to
rapidly adopt and learn fasterthan most kids today you
probably start to.
Is that kind of a vision youstart to see within kids in
school today?
Speaker 3 (40:38):
So I have seen a mix of that.
I've seen some kids actuallypushing back on AI, ai-based
tools, the way they see it, andI think that has a lot to do
with their grownups, teachers,parents, for example.
My son he's like I hate ChatGPT.
I said, why would you say that?
That's a very strong statement.
(40:59):
He's like because beforeChatGPT, my teachers would give
me homework.
I would come home, do myhomework, I'd turn it in, I'm
good.
Now my teacher thinks that I'musing ChatGPT to write my essays
.
Now they want me to do myhomework in the classroom,
sitting in front of them.
(41:20):
Now my son he doesn't like whenhe writes or when he's doing his
thing.
He likes full attention,headphones on certain music
playing full quiet, nodisturbance.
When he's sitting in theclassroom.
He doesn't have that luxury.
So he sees it as a threat tohim and he pushes back.
Even when I tried to explain tohim that it can make your life
easier and there are certainthings you can do, he wouldn't
(41:43):
accept it.
So, um, so there's that.
But then there are other kidswho who see, who are interested
in it.
They want to learn it.
They have to get comfortablewith AI because this is their
future Kids who are in middleand high school today, and even
college.
They're going to be kind oflike how our generation, you and
(42:05):
me, how we adopted the internet.
We aren't internet natives, weare internet migrants.
We were analog before, livinganalog lives.
Then we adopted the internetlifestyle.
Our next generation.
They were digital natives, sofor them, everything comes very
natural when it comes to digitalKids today.
(42:28):
They are not AI natives.
I'm talking about middle andhigh school and beyond, right
Elementary school and younger.
They're going to be, to adegree, ai natives, so they will
be very comfortable with thesetechnologies.
My biggest fear in the contextof this conversation is the
(42:49):
skills that we are giving or wewill give to the kids, because
even grownups are not 100%certain what we need to learn,
how we will use thesetechnologies, how we get along
these technologies.
Many of us see it as a threat,Many of us see it as a tool.
Others see it as a beliefsystem, believe it or not?
I've been told I don't believein AI and I'm like it's not
(43:11):
deity that you have to believein.
It's technology.
So even we are uncertain, so Idon't know how we're going to
give clear guidance anddirections to the young ones.
It's an evolving situation,even in the education field.
Speaker 2 (43:26):
I definitely agree with you that the loss of that
personal connection between astudent and an instructor is
definitely a concern.
I've spoken with a couple ofeducators in this field who also
have that same fear of.
You know is that I have a, Ihave a great connection with my
students and there's a lot of,there's a lot of concern that
that might become a huge driftbetween that student instructor
(43:49):
relationship, but kind of in theclassroom setting, and feeling
like there's that personalconnection, that human
connection to another individual.
But I think back to your bookagain is that, you know,
figuring out how, how we canintegrate and how we can kind of
coexist around these entitieswill probably take some time and
it's going to be interesting tosee what's going to happen.
Probably in the next five years, probably the next 10 years I'm
(44:09):
not going to be a futurist butI'll probably say in the next 15
, 20 years we might see acompletely different landscape
when it comes to the educationin the classroom.
Sani, thank you so much forjoining us today on the show.
Where can we follow you?
Where can we get more?
Where can we learn more fromyou and your travels?
Speaker 3 (44:26):
The best way to get in touch with me and follow me
is via LinkedIn.
I'm quite active there and onLinkedIn it's just my last name
Sani S-A-N-I.
Speaker 2 (44:36):
Awesome.
Sani, thank you for thiswonderful conversation today.
Thank you for sharing yourknowledge with us and we hope to
have you back again on TechTravels.
Thank you very much, it's beena pleasure.
Welcome to Tech Travels hosted by the seasoned
tech enthusiast and industryexpert, steve Woodard.
With over 25 years ofexperience and a track record of
collaborating with thebrightest minds in technology,
steve is your seasoned guidethrough the ever-evolving world
of innovation.
Join us as we embark on aninsightful journey, exploring
(00:27):
the past, present and future oftech under Steve's expert
guidance.
Speaker 2 (00:33):
Welcome back, fellow travelers, to another amazing
episode of Tech Travels.
Today, we have the pleasure ofhosting Sani Abdul-Jabbar, a
visionary CEO at VizTech, acompany that's at the forefront
of emerging tech.
Sani leads a talented teamthat's pushing the boundaries
around blockchain and artificialintelligence.
Also, as an author and athought leader, a voice and
authority in Web3, sani is hereto share his insights as to
(00:55):
what's shaping our digitallandscape today.
So buckle up as we embark onthis journey through technology
with Sani Abdul-Jabbar.
Sani, welcome to Tech Travels.
It's an honor to have you onthe show today.
Speaker 3 (01:05):
Thank you.
Speaker 2 (01:05):
Steve, it's a pleasure to be here.
I want to very glad to have you.
I really want to kind of leadwith this story here.
It just broke yesterday World'sfirst major act to regulate AI,
passed by European lawmakers.
It says the European Union isnow a global standard setter in
artificial intelligence.
So kind of help us walk througha little bit of this late
(01:26):
breaking news and kind of whatthis means for us here in the
United States.
Speaker 3 (01:30):
Yeah, so that certainly is the hot topic today
.
This conversation aboutregulation in EU has been going
on since December, at least Well, since before that, but
December was early December.
They presented the first draftof this bill in their parliament
and it was eventually approvedyesterday.
(01:51):
The gist of this bill is thatit's so.
They divided, or categorized,rather, ai technologies by risk
level of risk.
So the highest extreme levelwould be unacceptable level of
risk, the lowest would beacceptable level of risk, and
then there are three otherlevels in between total five, I
(02:13):
think and so that's what theyhave done Now.
Historically, I have alwayssupported the idea of regulation
, mindful regulation.
That's the point.
Mindful is the key.
In the US, we have this cowboymindset in the tech world.
Right, don't stop me, don'tregulate me, because if you
(02:36):
regulate me, that hinders thedevelopment of technology.
That's what I'm trying to do.
But the problem is that, yes, Ican develop technology, but if
there are no rules of engagementand I come to you, steve, try
to sell the technology, you'regoing to say well, what are the
rules of engagement?
How are we going to play Ifthere's no gameplay?
If there are no rules of thegame, we can't play right.
I can't sell that technology tolarge corporations.
(02:57):
I can't sell that technology togovernment agencies.
They're not going to touch it.
So therefore we need regulation.
The counter argument of that is,if the regulation is put in
place just for the sake ofregulation, then we run into a
situation where regulationbecomes counterproductive.
(03:18):
Right, lawmakers aren'tnecessarily experts in
technology, it's the influencegroups, it's the think tanks,
it's the influence groups, it'sit's the um think tanks, it's
the lobbying groups who and theindustry groups who have a role
to play in that.
But you know, there's always umpriority of interests and all
prioritization of interest andcompetitive interest.
That is uh that we have to dealwith um.
(03:41):
So, having said all that, Ihaven't read the full bill uh of
in the eu that was passed inthe eu parliament yesterday, so
I can't comment on it withspecifics.
But uh, if it's put togethermindfully, if there are experts
involved in it, if they are notputting regulation in place just
for the out of fear not notnecessarily um to put you
(04:05):
guardrails around it then it canbe counterproductive.
It doesn't seem so so far whatI've read about it.
It doesn't look like it looksquite reasonable, but, like I
said, I haven't read the wholething yet.
Speaker 2 (04:16):
Yeah, absolutely, and I think the idea of regulation
just means that it provides acertainty that we really need.
The tech community really doesthrive on innovation, but
without a clear framework, asyou mentioned, we really can't
realize the potential of thesetechnologies.
But your point about themindful regulation really
resonates strongly with mebecause, I mean, I think it's
(04:37):
really about striking a criticalbalance.
I think we need to ensure thattheir experts are at the table
with these regulations whenthey're drafted so they don't
really reflect, you know, fearor misunderstanding around
artificial intelligence.
But also, given that the EU hasrecently taken steps, I think
it really sets the stage thatit's becoming more and more of a
guide, because here in the USwe have this, like I said, this
(05:00):
Wild West type of mentality oftech towards a more structured
frontier.
Now, with the post-pandemicsurge in AI awareness and
application, I think it's reallycrucial that we navigate the
hype cycle thoughtfully.
So could this bill be ablueprint for really just
marrying innovation withresponsibility, or is it
(05:21):
something that all of us in anindustry need to watch closely
and learn as we move forward?
Speaker 3 (05:27):
Every technology, every innovative technology,
goes through a hype cycle.
Now, hype, in my opinion, isnot necessarily a bad thing,
because what hype does?
It attracts resources, attractspeople, attracts funding and we
develop things, so that's agood thing.
The negative of hype is thateveryone and you know their
grandmother starts claiming thatthey are experts in that field.
(05:50):
I attended a an event not lastweek, no, this week, actually on
monday where we reviewedseveral projects nine 900
projects total, uh with a groupalong with other group of
experts in the industry forinvestment.
So we were reviewing theprojects for investment.
At least 70% of them weresomethingai, and once you start
(06:15):
asking questions, you realizethat there is no AI.
A lot of them was oh, I'mbuilding a custom GPT, a custom
GPT plugin.
Well, that's not yourintellectual property, so don't
call it your project.
You're asking for hundreds ofmillions of dollars for
something that you don't own.
Openai can shut you downtomorrow, so that Then there are
(06:38):
a lot of people who are justdoing smart automation of things
and they're calling it AI doingsmart automation of things and
they're calling it AI.
Overall, I think there are lessthan 10% companies who are
actually building somethinginteresting that can be
legitimately called AI.
So that's that.
That's the current state of theindustry, in my opinion, at
least what I am seeing in thespaces where I operate.
(07:00):
Are we in the hype cycle?
Most certainly yes.
My gut feeling is that we needat least till the end of this
year to reasonably come out ofthis hype cycle, because what's
going to happen by the end ofthis year is that you will know
companies that are ai, companieswhich are actually ai or not.
(07:23):
So that's what's going to happenby the end of this year and my
guesstimate is that by the endof the next year, companies who
are claiming to be ai but not aiand who have raised money, they
will run out of money.
So industry consolidation willhappen towards the end of the
next year and that's when we'llstart seeing real players in the
industry.
The winners will become morevisible.
(07:45):
This is not to say that reallyinteresting technologies aren't
evolving and coming up in themarket every day.
Recently I attended a meeting acouple months ago now, at
Microsoft.
It was the kind of meetingwhere you have to sign NDA
before going to the meeting.
They presented some productsfor the entertainment industry,
(08:08):
film industry and it's mindboggling what you can do the
kind of stuff that theseproducts can do.
I can't talk too much about itbecause of the non-disclosure
commitments, but I can tell youthat this is mind boggling.
Speaker 2 (08:25):
If anyone thinks that jobs aren't going to get
impacted, industries aren'tgoing to get impacted, they're
dreaming right, yeah, and I Ithink the distinction you draw
really is powerful, because thedistinction between superficial
AI applications and genuineinnovation is really a wake-up
call, and I mean it's soberingto hear your estimate that under
(08:45):
10% of projects are trulyartificial intelligence.
I also think that yourprediction on on industry
consolidation really aligns withthe critical need to discern
real expertise from the hype.
So, with that in mind, whenconsidering expertise, what is
your top criteria foridentifying true AI specialists
(09:09):
in this crowded field?
And just give me a little bitof idea kind of what goes into
that thought process.
Speaker 3 (09:16):
So, first of all, this technology is not such a
new technology.
Yes, chad GPT made it popularin the end of 2022, but the
first large-scale AI-poweredproject that we did was in 2018
or 2015, somewhere there.
So technology has been around.
So there's a technical side ofit and that's easy to judge if
(09:43):
someone has those technicalskills or not.
You just look at their previouswork and all that.
Gpt, and especially its use inthe industry, that's relatively
new at the level and the scalewhere it's evolving now.
So, at that scale, what'simportant is that and the rapid
evolution of the industry.
So what's very important for meis I don't care if you know
everything today or not, but Ido care if you dedicate time and
(10:05):
resources to learningconstantly.
Constantly, because it's anevolving industry.
Every day something new iscoming out.
So when I interview, or my teaminterviews, people who are
looking to join our teams,beyond their technical skills,
we also judge what they'rereading.
We look at their LinkedInprofiles and we see what they're
(10:26):
posting.
We look at their you know, weask them you know what's the
recent book that you read orwhat's the recent articles that
you read, because that tells methat this person is staying on
top of things.
Are there any interestingthings you have created using
LLMs, gpts, that kind of stuff,even in your personal time, even
for your personal entertainmentreasons, because that shows
(10:49):
your interest in the technology.
A few things that are reallyimportant right now for the
business world, for the industryand the leaders to understand
is, when it comes to projectselection and product
development, rules are still thesame.
The best practices are stillthe same.
You have to think about ROI.
You have to think about who itimpacts.
(11:11):
You have to think about who thedecision makers, decision
influencers are, who thecustomers and consumers are.
These are the basics of anyproduct development.
Have always been.
What's slightly new this timearound is in the past, data used
to be the sideshow.
Now data is the main show.
What that means is, if you askme today and it happens, I mean
(11:33):
Steve, like, if know, put adollar in my saving account.
Uh, every time someone asks me,so you know, give me this blue
pill that will solve all my, allmy problems.
I'd be quite rich people.
It hap.
It happens every time.
We have a new emerging tech andit's happening again now in in
the wake of ai and evenblockchain.
Still where a business leaderwill come to us and say tell me
(11:55):
how I can bring AI into mybusiness today to automate all
my processes so that I canachieve that competitive
advantage right away that I canusing AI, and my response to
them is no, that's not how it'sgoing to work.
It's the same answer that Igave you two years ago when we
were talking about blockchain,and two years before that when
we were talking about otherthings.
(12:18):
This time around, in in thecontext of product development,
what's new is that?
Or project selection, you haveto first think where do you in
your organization's processesyou have the most amount of data
?
That's the low hanging fruit.
That's where you gotta startchat gpt, having access to it or
any other llm or any ai tool.
(12:39):
Just the fact that you and Iboth have access to it doesn't
give us competitive advantage.
You and I both can getsubscription of chat gpt for 20,
for example, or other tools fordifferent levels of you know
investment, but anyone can dothat if they can afford it.
So that's not competitiveadvantage.
Competitive advantages if Stevepicks up a GPT and trains it on
(13:05):
his writings, his speaking, hishistory, his businesses data.
Now that's competitive advantagebecause Sunny does not have
access to that data, so I don'thave that competitive advantage
you do.
That's what I'm trying toadvocate for businesses is that
when you want to bring in AI,leverage AI and other emerging
technologies for competitiveadvantage, think where do you
(13:27):
have data in your organizationTypically finance, accounting,
sales, so that's the first levelwhere you have the most amount
of and most clean data.
When you go below that, thenthe data is not that clean, but
there's still marketingoperations, things like that.
You still find some data.
So then that would be thesecond layer and so on.
(13:49):
So that would be people lookingfor opportunities in the AI
world if they can just learnthese skills and use these
skills where they can analyzeprocesses of a business, see
where automation opportunitiesare, see where the data is and
(14:09):
then figure out what tools, whatAI tools, can be brought in to
automate those processes usingthat internal proprietary data.
That's the low hanging fruit.
Speaker 2 (14:19):
Yeah, sani, I completely agree that the true
competitive advantage lies inutilizing the proprietary data
with AI tools and then tailoringthem to the unique aspects of
one's particular business.
Them to the unique aspects ofone's particular business.
So, just on the topic ofleveraging unique assets, this
(14:40):
really brings to mind thecontrast with blockchain's
philosophy of decentralization.
Now, while AI, especially inthe form of services like
ChatGPT, really tends tocentralize knowledge within the
major tech companies, it looksto me like blockchain really
aims to distribute that control.
But what's interesting toobserve is these different
(15:01):
approaches AI reallycentralizing versus blockchains
decentralizing.
So I'm very curious how do yousee this interplay affecting
businesses that are looking toadopt these technologies for
competitive edge?
Do you start to see thatthere's a synthesis between
these models?
Could they offer the best ofboth worlds?
(15:22):
I mean, I think they tend tofavor more centralization.
Speaker 3 (15:27):
True, although I think we have an answer to that
problem Within the blockchainindustry, blockchain technology.
You have three different typesof blockchains.
One is public, one is private,one is hybrid.
So public is anyone can join,private is only certain people
can join or certain entities canjoin, and hybrid is a group of
(15:50):
the two.
So think an industry where abunch of companies are allowed
to join that chain.
So that would be hybrid, whereit's somewhat public, but not
quite right.
Ai, on the other hand,especially when you look at
machine learning models, theyuse large amounts of data, right
, so you can limit that data to.
You can say that only look atthis one data set, don't look at
(16:14):
global data set.
Openai actually startedoffering this type of a service
for businesses not too long ago,and other companies will do it
as well, because obviously wecan't open up all our data to
everybody, so that doesn't work.
So one of the companies that Ihead up, it's in the energy
sector energy trading, fuelcommodities, primarily jet fuel,
(16:37):
etc.
And it's middle market, and Irealized that in that market
there are lots of players, many,many, many players.
Some are small, some are largeand some work on deals for years
and never get anywhere.
Others, they have more dealsgoing on, but these deals are
large scale deals.
So if you can close one deal,this is like hundreds of
(16:59):
millions of dollars.
However, there is no centralizedsystem in place, because
information is the key.
If I know where to buy theproduct, where to sell the
product, how to price theproduct, I have the power to
price the product.
I have the power.
Right, that's, that's myintellectual property, that's my
um, that's the power, as assoon as it's uh, this
information is available toanybody else, I lose my
(17:21):
competitive edge, can't survive.
So I propose the idea ofcreating a uh hybrid blockchain,
where a hybrid blockchain basedum erp type system where we can
streamline all these verycomplex processes involved in
energy trading.
Put all of that on the system.
(17:42):
It would be a centralizedsystem in which all buyers not
all, but whoever wants to playyou know they would be members
of it buyers and sellers.
And this idea wasn't verypopular in that industry because
the information to your earlierpoint, because you know, on one
side we have public informationversus private information.
The idea didn't fly very wellbecause, like I said, people are
(18:06):
very protective of theirinformation, no matter how much
you try to assure them that thisinformation stays with you.
You own it and when you put iton the chain, it's fully secured
, no problem.
It didn't work.
But if you bring it at acompany level that you can do
that, technologically you can doit.
You can keep all the datawithin a company, but then the
(18:28):
cost of operating it goesthrough the roof.
And, as I mentioned many ofthese, most of these companies
are small companies.
They don't have those kinds ofresources.
So, can, technologically, aiand blockchain work together?
That's actually a match made inheaven, right?
If you just look at blockchain,it's, I believe.
(18:49):
In my opinion, it's one pieceof the puzzle you have to look
at.
Data collection.
Collection comes from sensors,humans, machines, any sources.
Right Data comes in.
Then you secure that datasomewhere.
That's your blockchain in anyof I mentioned three types.
There are others it's.
Think of it as a spectrum ofhow public a chain is.
(19:10):
And then what do you do withthat data?
That's, that's the AI part.
You do something using AI, lookfor pattern detection or
whatever.
You create some actionableinsights out of that data and
then you use that.
So both technologies are verywell suited to work together.
The issue is not that theycan't work together.
(19:31):
The issue is how much justcommunicating this to the
stakeholders, the idea that yourinformation is secure when it's
on the chain and that's goingto be a problem when you're
working across entities as longas it's within one entity a
government, a very largeorganization you're fine, no
problem.
But when you go outside thatand you want to share
(19:52):
information across entities,even if it's fully secure,
that's a hard sell.
Speaker 2 (19:59):
It's interesting.
I mean, your insights into thesynergy between AI and
blockchain really areenlightening and I love this,
especially considering thesecurity and data privacy
concerns I mean really thatyou've outlined.
But, given your expertise withthese technologies, what would
you say the primary hurdles arewhen you encounter or when
you're advising companies.
Specifically, how do youaddress the hesitation of
(20:22):
executives who really may graspthe potential for AI blockchain
but are reluctant to really makethat leap due to perceived
risks or a lack of a strategicvision specifically for
implementation of AI products?
Speaker 3 (20:39):
So we get some industry surveys done every year
to get a sense of the techlandscape.
In the recent survey, we foundout that over 78% business
leaders they completelyunderstand and believe that AI
and emerging technologies arethe competitive edge.
If they don't adopt thesetechnologies within the next 10
(21:02):
years, they will lose theircompetitive edge.
They won't be able to survivewithin one decade, regardless
how stable you are.
Today, complete understanding,less than four percent leaders
are actually investing umsignificant amount of resources
into leveraging thesetechnologies and and bringing
(21:25):
these tech into into theirbusiness operations.
When asked why, the most commonresponse was I, I don't have
information, I don't haveguidance, I don't know who to
trust because everyone isclaiming to be the expert.
I'm concerned that my existingprocesses that are working
perfectly they will break if Iintroduce a new tech into it and
(21:47):
that kind of stuff.
The issue wasn't money.
The issue was fear.
The solution to that is quiteeasy.
As a matter of fact, theeasiest solution is you got to
find experts.
I mean, we have people in ourcompany at Vesek, who this is
their bread and butter.
This is what they, you know,live and breathe.
So just talking to people likethat and saying you know, look
(22:10):
at my processes and tell mewhere the opportunity is, and we
are not always going to tellyou that you have the
opportunity.
If you don't have the data,either your own or access to it,
somehow you can't use thesetools Right.
It's not a competitiveadvantage GPT type tools or
(22:35):
other AI tools.
You have to somehow customizethem to a level where they
become yours, where they becomeyour competitive edge.
Not just, you know, anybody canpay the fee and get
subscription.
Then that's not a competitiveedge.
Now, on lower levels, like youknow, creating some tech,
generating some text ormarketing copy, or GPT to write
your emails or improve your,whatever that can be done, but I
(22:59):
don't see that as a competitiveadvantage.
Yes, it increases yourefficiency.
I think I made a statementsomewhere, got some pushback for
it.
If today you go in any decentsize organization, look at their
processes, introduce publiclyavailable ai tools, you can
increase their efficiency by byabout 15, 15 to 17 percent.
(23:20):
So that's that.
But almost any reason areasonable size organization has
access to that.
If everybody has access tosomething, I don't consider that
competitive advantage.
Competitive advantage is whenyou have access but others don't
.
To get to that level, you haveto make these tools yours by
customizing them based on yourdata.
Speaker 2 (23:42):
Yeah, and customization takes time, it
takes effort, it takes cycleswithin your team to be able to
develop this.
I think in your book youmentioned again that the book is
amazing.
I started reading it.
The maker is a slenderknowledge uh, phenomenal so far.
I think you mentioned in thebook that vestec, you know,
really shines as an innovationhub for emerging technologies
and that, and then in that itsays it redefines them within 12
(24:05):
to 16 months, and I'm reallyinterested here a little bit
around your emerging convergenceframework and kind of what led
you to it.
How did you know, how do youbridge the gap between skills
and infrastructure and how doyou evangelize that when you're
talking with executives andpeople in the tech space?
Speaker 3 (24:20):
So that that emerging emergence convergence framework
, which is a emerging techforecasting framework.
It evolved and was developed asa very painful need that we had
at that point.
Vesdek, I founded it in 2006,and the idea was we're always
(24:42):
going to be emerging techcompany.
That means, whatever technologyis emerging, we're going to
provide consulting, developmentresources in those technologies.
Well, the challenge was that atthat point, technology
landscape was shifting likecomplete paradigm shift within
about three to five years.
(25:02):
At that point, then whathappened is that that that
change, it became the period ofthat change.
It became shorter and shorterand shorter.
Frequency just kept going up.
Currently, in the post-COVID era, we are at 12 to 14 months, 12
to 16 months max, right, andthen that's when change happens.
(25:24):
If you look back to, every lessthan two years we have some new
technology that that becomestalk of the town.
So this is the landscape thatwe've been dealing, dealing with
since 2006.
What many of our peers in theindustry, what they do?
What they do is they wait forthe demand to come in, and when
the demand comes in, then theygo out and look for resources
(25:47):
and and then they try to capturethe demand.
That model wasn't working for us.
So what we did is we createdthis framework which, like I
said, it's a forecastingframework.
It allows us to kind of lookdown the path and see what
technologies are coming down thepike and then invest in those
(26:09):
technologies ahead of time,develop resources, build
infrastructure, retool, retrainour existing teams and see if we
can be prepared in time tocapture that demand when it
comes up in the market.
So we have to be mindful ofhype versus actual demand.
We have to be mindful foractual investments coming in
(26:31):
that space or not.
Are there enough resourcesavailable in the market or not?
Things like that.
So that's the emergenceconvergence framework.
Currently it gives us about 12to 14 months head start.
So that's a good thing to haveto know that we need to be
prepared for technology X in 12months.
Speaker 2 (26:51):
That's incredible because most of the time you
don't see that quick.
You typically see the cyclesanywhere between 24 to 36 months
, on a turnaround for somethinglike very new, innovative.
We don't really know what thisis.
We're looking for experts inthe field to kind of help us
figure out a trajectory, butthat's incredible that you have
that.
I want to dive into the book alittle bit the Maker's Slender
(27:11):
Knowledge.
I started reading it and I'vebeen fascinated with it.
I really want to get through it.
But what I found interestingwas I want to hear your
perspective on kind of what ledyou to really write the book and
how you kind of curatedknowledge from different people
from different walks of life tocreate this amazing book.
Speaker 3 (27:28):
Excellent question.
So what happened is that manyyears?
I mentioned earlier that ourfirst large scale project that
leveraged AI was in 2015,.
I think what was happening isthat every time I would bring up
AI, machine learning, anythinglike that the first, the most
common response was Terminator.
So robots are going to takeover the world right, the doom
(27:51):
and gloom scenario.
As an entrepreneur, I'm ahopeful person, but that's my
default setting.
So I started thinking there hasto be a way to avoid that
scenario, and so I startedasking questions and at that
point, looking at the evolutionof technology and all the
forecasting models that we had,the estimate was it would take
(28:15):
about 20 years for the AItechnology and robotics
technology to get to a pointwhere it becomes AGI artificial
general intelligence.
That's the threat, that's yourterminators, right?
So I started asking thisquestion what would it take to
stop AI from doing stupid things20 years from today?
(28:37):
And I just literally I askedthis question to countless
number of people, anybody whowould listen to me, regardless
of their background, because Ireally believed that magic
happens at the convergence ofdifferent disciplines.
Because I really believed thatmagic happens at the convergence
of different disciplines aslong as you keep it within one
silo or within one area ofknowledge.
(28:57):
You're kind of limited.
So I went across the aisles andI spoke with people in
different fields, includingpolitics and clergy and
sociology I mean, you name itand the response that resonated
with me the most was the personasked me a question in response
to my question, and his questionwas what would you do today to
(29:22):
prevent your kids from doingstupid things, 20 years from
today?
And it's like that's a goodquestion.
What do you do?
Well, you try to teach goodvalues to your children.
You hope that they would learnand you hope that they're
listening and you hope that theywould become better people.
It's like that's exactly whatyou need to do with AI, because
(29:43):
the way you train AI and the wayyou raise children is similar
in certain ways Similar as inwhen we teach our kids values.
The best way that we've beentaught is be the role model.
Kids are looking up to you.
Be the role model.
Do good things in front of them.
They'll learn, instead oflecturing them, exposing them to
(30:03):
good environments and sometimesyou lecture them.
So equivalent of lecturingwould be direct data entry in
the AI world.
Right, uh, sometime you exposethem to different environments.
Um, take them out shopping, forexample, with you and see how
the process of shopping is doneat a grocery store, right.
And sometime you give them thecredit card and have them, uh,
(30:26):
pay to the cashier theequivalent that exposing them to
different environments in theAI world would be, for example,
exposing your AI model toYouTube data, for instance,
right?
So there are lots ofsimilarities.
So that's where the idea camefrom.
If you teach good human valuesto AI today, if you bake that
(30:49):
morality and the values in theway we are developing AI, then
there is a chance that AI woulddevelop into the kind of beings
that we can coexist with andthrive alongside.
So that's where the idea camefrom.
Now, when I started writing thebook, initially I thought of
(31:09):
writing the book in a almostlike a manifesto how to 10 ways
to do X kind of model.
But, uh, I had the good fortuneof uh speaking with Mr Mark
Victor Hanson uh, chicken soupfor the soul author, very
well-known person.
He later became my publisher.
So I had a conversation withhim about it, asking him the
(31:30):
same question.
He's like you got to write abook about it.
I was like, okay, let's write abook and then when he heard
that I wanted to write it as howto, he's like no, no, no one
wants that Write it as a story.
So the book is a work of fiction, but mindfully divided into
chapters.
Each chapter is about a valueand experience of AI in how it
interacts with humans and howhumans respond to it, and my
(31:53):
hope from this is we can raisesome questions.
We can trigger people to thinkwhat can be done in our personal
capacities today, because ourdecisions today is the data for
AI training tomorrow.
So my decision today in myorganization don't just impact
my people today.
It can potentially impact a lotof people in a lot of places
(32:14):
down the road if my decisionsthat I made today is used for
training of the AI.
So that's kind of was mymotivation.
Speaker 2 (32:23):
Yeah, sani, the way that you've woven the
interaction of human andartificial intelligence values
into a narrative.
It's a very powerful approachand I think it brings awareness
and it really is a stimulatingthought.
The storytelling aspect reallyseems to connect deeply, I think
, with our need to understandcomplex issues like artificial
intelligence through a relatableexperience.
(32:45):
Given this impact, do youenvision that the collective
stories and experiences that areshared in society really could
lead to more unified ethicalframework for AI, and how might
we harness the storytelling toreally create AI values that are
widely accepted and implemented?
Speaker 3 (33:08):
In one of my recent interviews, I brought up the
idea of AI, ethics and values,and the person interviewing me,
he said well, all AI is built onvalues.
There is no AI without values.
Now, whose values?
That's another question.
From the history, we do knowthat whenever we try to impose
(33:29):
any one entity's values on otherpeople, it doesn't work.
We have seen that over and over, whether it's in the religious
context or political context orany context.
So I don't think it's going tobe values imposed by any single
entity.
I think what's going to happenand these are just speculations,
right, we don't know yet.
(33:49):
I think what's going to happenis that, over time, hopefully,
as you know, human race, ascitizens of this world, will
come up to some understanding,some agreement over some basic
rules, some basic.
You know, these are the fivebasic values that we can agree
(34:10):
on, for example, and um, perhapsthat would be the starting
point.
I don't think it's going to be awhole set of values coming from
some one entity.
The other possibility is that,um, you end up with one clear
market leader.
You know, google, for example,controls 80 of of the search
(34:30):
market today.
They can set the rules for thebrowser search industry right
Because they own 80% of themarket share.
So something like that couldalso happen.
Where one company or one entityhas that much power that they
can set the rules, that canhappen.
(34:50):
I have also speculated that UNmay have to get involved, some
UN level body where they cancome in and they can say okay,
you know, we need some centralinternational organization to
come up with some principles,some values and goals, some
values and rules of engagementthat we can agree on.
(35:11):
We don't know yet.
So these are all speculations.
Your guess is as good as mine.
Speaker 2 (35:19):
So, sani, so as our conversation as we draw to a
close, I'm really struck by thepoignant dedication in your book
A Slender Knowledge, where youcharge your sons not only to
coexist but also to thrivealongside AI entities.
And the message really resonateswith me profoundly because, as
a father of young twin boys whoare also on the onset of their
(35:42):
journey in a world where therelies that intersection between
humanity and AI and they'rebecoming increasingly blurred, I
think it's fascinating somewhat.
I think it's fascinating, butsomewhat daunting, to really
consider the landscape and howthey will navigate that in the
next five years, I think, theterrain where AI will become
even more present andinfluential.
(36:04):
So, drawing on your hopefulvision as you set forth for your
children, where do you see usstanding with AI in that
timeframe and how can we as asociety also lay the groundwork
for future generations to notjust adapt but also to leverage
(36:24):
AI to their advantage and alsoensuring that they don't just
survive but they indeed thrive?
Speaker 3 (36:32):
that they don't just survive, but they indeed thrive.
So I don't call myself futurist, I call myself nexus.
Futurist would be oh, in 70years X is going to happen.
I'll be dead in 70 years.
So you can't come and sue me,but I'm more interested in
what's likely in the next fewyears so we can plan for it.
Your kids are young, four years, um.
(36:53):
So they are about what?
20 years away from theworkforce, roughly, yeah give or
take, yeah, my kids a littlebit older, uh, 13 and 10.
The way I think is I I think 10years ahead.
So how the world looks like 10years ahead and then work
backwards 10 years ahead, andthis is not just my opinion.
(37:15):
Many, many experts in theindustry they agree on it.
So the life 10 years ahead islikely to be very virtual.
We got a taste of that with thewhole idea of metaverse.
It was too early, too ahead ofits time.
Right now it's justentertainment and we don't have
enough technology, the rightkind of technology, to really
(37:39):
put Metaverse to work.
If you look backwards, the earlydays of Internet, the very
first version of the Internet,the very first generation, was
just post some articles on theserver and then in
Urbana-Champaign, for example,and then in Chicago, researchers
could read those articles.
That was the internet, the veryfirst version.
(38:00):
The second iteration there wassome interaction.
Third iteration well, in thesecond there was also e-commerce
kind of got involved, and nowin the third one, decentralized
data and trust.
That's big.
So you keep going forward 10years forward.
Virtual lives, virtual internet, virtual lifestyle that's
(38:21):
highly likely to happen, inwhich we work, we play, we live
in these virtual environments.
Very early version of that.
Is this what we are doing rightnow.
You know remotely, but we'retalking about like fully
immersed environments in thefuture.
In order to get there, there arecertain technologies that need
(38:41):
to happen.
The e-commerce system needs toevolve.
The internet speed needs toevolve.
The energy sector needs toevolve.
Currently, 3% of global energyis being consumed by emerging
technologies.
By the end of this year, we areexpecting 8% energy to be
consumed by emergingtechnologies.
That's not sustainable.
So that has to change.
(39:04):
Jobs that are currently any jobsthat's data-driven job.
Well, until recently, I used tosay if it's a data-driven job
anything where your informationthink a physician not a surgeon,
but physician who only useslots of information those jobs
are very much at risk of beingsignificantly impacted.
But I think you posted on yourLinkedIn yesterday, or somebody,
(39:26):
a robot that came out withinthis month that can do like
dishes and folding laundry andthat kind of stuff.
It's like wow, okay, so evenphysical jobs are now getting
impacted.
So for the kids especially,knowing that we're moving
towards that virtual world andknowing that in order to get
(39:48):
there, we need certain othertechnologies and industries to
involve, I think that's where weneed to pay attention, because
that's going to then determinethe education of our children
today, the training and theirfuture professional prospects.
Speaker 2 (40:03):
Fascinating.
So you're probably going to saythat this is me probably
thinking kind of double clickingon that a little bit is
thinking around embracingartificial intelligence and
understanding how AI reallyplays a role in learning and
development at a much earlierage.
So you think that probably kidswho are now in elementary
school will probably be moreexposed as we start looking at
(40:24):
AI's role in education as aneducator, as a way for them to
rapidly adopt and learn fasterthan most kids today you
probably start to.
Is that kind of a vision youstart to see within kids in
school today?
Speaker 3 (40:38):
So I have seen a mix of that.
I've seen some kids actuallypushing back on AI, ai-based
tools, the way they see it, andI think that has a lot to do
with their grownups, teachers,parents, for example.
My son he's like I hate ChatGPT.
I said, why would you say that?
That's a very strong statement.
(40:59):
He's like because beforeChatGPT, my teachers would give
me homework.
I would come home, do myhomework, I'd turn it in, I'm
good.
Now my teacher thinks that I'musing ChatGPT to write my essays
.
Now they want me to do myhomework in the classroom,
sitting in front of them.
(41:20):
Now my son he doesn't like whenhe writes or when he's doing his
thing.
He likes full attention,headphones on certain music
playing full quiet, nodisturbance.
When he's sitting in theclassroom.
He doesn't have that luxury.
So he sees it as a threat tohim and he pushes back.
Even when I tried to explain tohim that it can make your life
easier and there are certainthings you can do, he wouldn't
(41:43):
accept it.
So, um, so there's that.
But then there are other kidswho who see, who are interested
in it.
They want to learn it.
They have to get comfortablewith AI because this is their
future Kids who are in middleand high school today, and even
college.
They're going to be kind oflike how our generation, you and
(42:05):
me, how we adopted the internet.
We aren't internet natives, weare internet migrants.
We were analog before, livinganalog lives.
Then we adopted the internetlifestyle.
Our next generation.
They were digital natives, sofor them, everything comes very
natural when it comes to digitalKids today.
(42:28):
They are not AI natives.
I'm talking about middle andhigh school and beyond, right
Elementary school and younger.
They're going to be, to adegree, ai natives, so they will
be very comfortable with thesetechnologies.
My biggest fear in the contextof this conversation is the
(42:49):
skills that we are giving or wewill give to the kids, because
even grownups are not 100%certain what we need to learn,
how we will use thesetechnologies, how we get along
these technologies.
Many of us see it as a threat,Many of us see it as a tool.
Others see it as a beliefsystem, believe it or not?
I've been told I don't believein AI and I'm like it's not
(43:11):
deity that you have to believein.
It's technology.
So even we are uncertain, so Idon't know how we're going to
give clear guidance anddirections to the young ones.
It's an evolving situation,even in the education field.
Speaker 2 (43:26):
I definitely agree with you that the loss of that
personal connection between astudent and an instructor is
definitely a concern.
I've spoken with a couple ofeducators in this field who also
have that same fear of.
You know is that I have a, Ihave a great connection with my
students and there's a lot of,there's a lot of concern that
that might become a huge driftbetween that student instructor
(43:49):
relationship, but kind of in theclassroom setting, and feeling
like there's that personalconnection, that human
connection to another individual.
But I think back to your bookagain is that, you know,
figuring out how, how we canintegrate and how we can kind of
coexist around these entitieswill probably take some time and
it's going to be interesting tosee what's going to happen.
Probably in the next five years, probably the next 10 years I'm
(44:09):
not going to be a futurist butI'll probably say in the next 15
, 20 years we might see acompletely different landscape
when it comes to the educationin the classroom.
Sani, thank you so much forjoining us today on the show.
Where can we follow you?
Where can we get more?
Where can we learn more fromyou and your travels?
Speaker 3 (44:26):
The best way to get in touch with me and follow me
is via LinkedIn.
I'm quite active there and onLinkedIn it's just my last name
Sani S-A-N-I.
Speaker 2 (44:36):
Awesome.
Sani, thank you for thiswonderful conversation today.
Thank you for sharing yourknowledge with us and we hope to
have you back again on TechTravels.
Thank you very much, it's beena pleasure.
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In 1997, actress Kristin Davis’ life was forever changed when she took on the role of Charlotte York in Sex and the City. As we watched Carrie, Samantha, Miranda and Charlotte navigate relationships in NYC, the show helped push once unacceptable conversation topics out of the shadows and altered the narrative around women and sex. We all saw ourselves in them as they searched for fulfillment in life, sex and friendships. Now, Kristin Davis wants to connect with you, the fans, and share untold stories and all the behind the scenes. Together, with Kristin and special guests, what will begin with Sex and the City will evolve into talks about themes that are still so relevant today. "Are you a Charlotte?" is much more than just rewatching this beloved show, it brings the past and the present together as we talk with heart, humor and of course some optimism.
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com