April 28, 2025 • 35 mins
Dr. Avishkar Misra shares his expertise on implementing AI effectively in businesses and explains how his company Berrijam is making AI accessible, explainable, and useful for organizations of all sizes.
• AI is not just one solution but a set of tools, techniques, and frameworks that allows for intelligent decision-making at various scales
• Berrijam offers three main services: AI strategy development, custom AI implementation, and their proprietary BerryJam AI focused on analytical applications
• The Berrijam AI5C framework breaks down AI capabilities into five areas: Find, Make, Connect, Predict, and Optimize
• Organizations need to start with their specific pain points and business requirements before selecting AI tools or implementation strategies
• AI will transform jobs rather than simply eliminate them, creating opportunities for those who learn to work alongside AI
• Leadership plays a critical role in successful AI adoption by fostering the right cultural framework and strategic approach
• The future workplace will see AI handling mundane tasks, allowing professionals to focus on higher-value creative work
• The IPX-hosted AI Readiness Workshops will help participants understand AI fundamentals, build business cases, and develop implementation strategies
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Welcome to the IPX.
Speaker 2 (00:02):
True North podcast, where we connect people,
processes and tools.
Speaker 1 (00:07):
Hello and welcome back to the IPX True North
podcast.
My name is Brandi Taylor andI'm super excited for the guest
we have lined up for you todayinto utilizing AI within your
businesses to make youroperations more efficient and
effective in any discipline ofyour business, including SAM2.
(00:29):
Our guest today is Dr AvishkarMishra, known to most as Avi.
Hello, avi.
Speaker 2 (00:37):
Hey Brandy, how you doing.
Speaker 1 (00:38):
Doing great.
Let me just tell you a littlebit about Avi.
So Avi is an AI scientist,technologist and entrepreneur
for over two decades ofexperience at the forefront of
artificial intelligence.
Avi has led AI initiatives atcompanies like Amazon, oracle,
teradata and TrackPhone, workingon everything from doubling the
(01:02):
accuracy of recommendations tothe tech behind Amazon's Go's
past year less stores.
He holds a PhD in AI applied tomedical image analysis and is
now the founder of VeryJam,where he's focused on making AI
accessible, explainable anduseful for organizations of all
(01:23):
kinds.
Avi, it is a really a greatpleasure to have you on the
podcast.
Thank you so much and welcome.
Speaker 2 (01:29):
My pleasure, lovely to be here Excellent.
Speaker 1 (01:32):
So I know I did a bit of an intro for you.
Are there any other details,before we get started, that
you'd like to provide ourlisteners about yourself or your
background?
Speaker 2 (01:42):
Sure, I mean the main thing I should highlight.
I do have a manageable caffeineaddiction, so you might see me
reaching for my coffee and myespresso time to time.
Other than that, you know Ilook.
I've been in the area of AI andmachine learning for quite a
while and way before.
Ai suddenly was very, veryexciting for everybody because
it met the new threshold ofcapabilities, and so I've seen
(02:04):
the journey along the way fromresearch and inventing things to
actually building products,services that launch and help
operations, and the servicesthat I've built are used by
millions of people every singleday without even realizing that
they exist.
And that's where the beauty ofAI should be.
It should be somewhere hiddenaway as a support mechanism,
(02:26):
without it taking all thelimelight and attention, and
making sure that the people whoare doing their jobs or creating
things or imagining the newfuture can do that effortlessly.
Speaker 1 (02:38):
All right, excellent.
So you know, I know Barry Jamis doing some pretty fun things
in the AI space and we'reinquiring minds really want to
know.
Just tell us a little bit aboutthat spark.
What led you to the creation ofBarry Jam?
Sure?
Speaker 2 (02:53):
So, as I said, I've been in the space for a while,
and one thing I noticed when Iwas working with a lot of the
Fortune 500 companies looking toadopt AI, data science or
better data-drivendecision-making is that there's
a lot of discrepancy between thecompanies who understand it and
can leverage it versuscompanies that don't even know
(03:13):
how to get started right.
So you know, there are alwaysthese new shiny tools that come
into the market, but without acohesive strategy, it really
made it very, very difficult fororganizations to leverage it.
So you'll see massive gapsbetween the companies who are at
the forefront pinnaclescompanies like Amazon and Oracle
and Microsoft and Google versuscompanies who are trying to
(03:35):
compete in the space very, veryrapidly and just trying to catch
up, and so we saw it both as arisk for the broader economy.
You want to make sure youdiversify the concentration of
that technology and the skillsetso there's more competition,
but also an opportunity for usto come in and help.
(03:55):
How do you help organizationfigure out and chart their
course?
By making AI much, much moreaccessible, much, much more easy
to understand and adopt and sothat they can realize its value
in their day-to-day.
Speaker 1 (04:10):
Yes, value is what it's all about, and you talk
about the things that you'redoing to help businesses achieve
that value.
Tell us a little bit more aboutBerryJam and what services that
you offer.
Speaker 2 (04:23):
Yeah.
So BerryJam started about a fewyears ago about two and a half
years now and we started withthe mission of making AI very
simple, accessible and alsoaffordable for a lot of small
and medium-sized businesses,right.
So the mission is very clear.
We very much focus aroundhelping organization understand,
adopt and excel with AI.
(04:44):
So basically we have three mainproduct offerings.
So the first thing we do is wehelp companies figure out your
strategy.
Without a good, cohesivestrategy, you are not going to
be very successful or you'regoing to flounder along the way
and, in some cases, just give upbecause you're not seeing the
results that you should beseeing results.
So that's very important.
(05:05):
We help organizations figureout what's the right strategy
for them, not just hey, I cameacross this use case in some
website or I saw this YouTubevideo and now I can just copy
paste it for my company or myteam.
That's great for inspiration,but often means a disconnect
between what I need versus whata vendor is trying to sell me.
So we really focus first on thestrategy piece.
(05:27):
The second piece we work on iswe do a lot of custom
development work.
So we're working right now witha neurology clinic, helping the
workflow of doctors andstreamline and potentially save
them two to three hours per day,freeing up their time to see
more patients, but also improvethe quality of the care they
deliver to their patients Again,very, very customized,
(05:50):
specialized for them.
And the third pillar of ourservice is our own AI system,
which is focused on analyticalAI.
We call it BerryJam AI, so I'msure people are familiar with
ChatGPT and other large languagemodels where you can ask
questions and we can do stufffor you.
They're really great fortext-based engagement.
They're good for synthesizingarticles and understanding them
(06:12):
and dissecting them.
But when it comes to analyzingdata structured data like tables
it's a very risky propositionto go down using LLMs.
So we built our own AI systemwhich is grounded in much more
statistically sound systems andalgorithms that are defensible.
So you don't want to bet thecompany's decisions and strategy
(06:34):
on what an LLM might havehallucinated, but what you want
to be able to do is ground thatinto statistics and machine
learning methods that haveactually been proven to be
successful over the last 20, 30years, especially at companies
large companies like Amazon'sand Microsoft's and other places
.
This software is very, veryspecialized, focused on helping
(06:55):
people, going from data toactionable insights and doing it
, you know, factor order ofmagnitude faster than
conventional methods.
Speaker 1 (07:04):
I love it.
So there's a few key thingsthere that you said that I
really resonate with, and withthe work that we do at IPX as
well is one.
it's all about making sure yourdata is meaningful, your data is
actionable, you have theinsights to actually make robust
decisions and do what you needto do with your data.
This is key.
(07:24):
So many people, we have so muchdata these days and we're not
using it properly or not evenusing it at all.
So I think it's really key tomake sure that we're thinking
about it from that perspectiveas well, as we know that
organizations and leaderseverywhere they want AI.
They wanna stay on top of thecurve.
This is what people say.
We need to have this.
(07:44):
But it's not just aboutimplementing something that they
think it just exists out herein cyberspace.
It's really about thinkingabout what pain points you have,
what problems are you trying tosolve, and think about it from
a business process perspectiveof how do we make what we do
more efficient, more effective,more accurate.
So I love when you think aboutit like that, because it's
(08:06):
really good project managementprinciples, right of the proper
planning on the front side, soyou have the right expected
outcomes on the backside.
Speaker 2 (08:14):
Indeed.
And look, AI is not a, it's notan answer for every problem,
and also, AI is not just one AI.
You know this last 75 years ofresearch in the field of AI.
So it's very, very complex,very diverse, and what you need
to do is, you know, we've got toget past the initial knee-jerk
reaction of, oh, everyone'sdoing AI, let's bring it in and
(08:35):
let's just copy paste and let'sdo that.
No, you've got to start withwhat does your team need?
What does your organizationneed?
Be very, very specific aboutthe specific capabilities.
And that's one of the placeswhere we focus a lot of effort
on helping organizations, youknow, start from where their
pain point is and then workbackwards towards figuring out
oh, these are the capabilitiesof AI that I need.
(08:58):
And then you have theconversation around okay, what
is the right type of tool,framework, technology, partner
that is relevant?
So it's very important to startwith a strategy.
If you don't have a goodstrategy, you're likely to be
one of the statistics of 80 to90% of projects that are going
to fail in AI are never going tosee the results that we expect.
Speaker 1 (09:18):
Yep, it's requirements, lead tools follow.
Speaker 2 (09:21):
Indeed and having that sort of understanding of
what that organization'scultural framework needs to be
in place, right, how do you needto think about the space?
It's very, very dynamic, veryevolving.
I know it's a lot of attentionin the news, but the
fundamentals of running a goodbusiness have not shifted.
The fundamentals of teamworkand collaboration have not
shifted.
The fundamentals of thecreative processes and
(09:44):
engineering rigor that goes intodeveloping things have not
changed.
So we've always liked to groundit into good, sound foundations
and then use these as tools togo further.
That's why we work with medicalresearchers.
We've done some work withMichigan Medicine where we've
looked at analyzing the clinicaltrial data.
So Dr Tapua had some data thathe'd run through some clinical
(10:06):
trials and we were able to useBerry Jam AI to do that 6,200
times faster because we designedthat specifically for that
particular analytics.
You can't just use ChatGPT togo and say, oh, analyze this
Excel file for me.
So there's different types ofit has different uses.
Speaker 1 (10:24):
Yeah, so you know to your point.
Let's demystify AI just alittle bit for a minute for our
listeners.
And so, Dr Avi, so you have aPhD in artificial intelligence
and you've built some AIproducts, but many of us are not
in AI, right.
We're in engineering or we'rein supporting functions or
manufacturing, et cetera.
So I guess I would like you,for Frida, to break things down
(10:47):
a little bit for us.
So, from your perspective, whatis AI?
Speaker 2 (10:52):
So the way we like to frame AI is AI is a set of
tools, techniques and frameworksor algorithms whatever it is
that allows for intelligentdecision-making and now that
intelligent decision-making canbe very simple or it could be
very complex.
So, for example, you have asensor in the garden that's
(11:15):
monitoring the moisture contentof the soil and they're making a
decision based on weatherforecast to decide whether to
turn on the sprinkles or not.
If you think about it, it's avery narrow, narrow, narrow,
specific domain of thatparticular system, but it is an
artificially intelligentdecision-making system.
It's not a human involved in it.
(11:35):
So that's an example.
Meanwhile, you have morecomplex systems, right, figuring
out, well, what's the nextmovie we should watch, right,
that might look at signals ofall your previous watches,
movies that you've liked, rated,what's in the market, what's
everyone watching.
All of that combined could beconsidering lots of different
signals and it's very narrowlytarget.
So the key element isintelligent decision-making and
(11:59):
the value that AI can bring in.
It can superscale that beyondhuman capabilities.
So AI can enable human-likeintelligence and behaviors or
decision making for very narrow,specific problem sets, but do
it at immense scale and immensespeed.
So you can imagine consideringmillions of decisions and data
(12:22):
points and personalizing theexperience for every single
customer who visits your websiteor every customer who walks
into the door of your store.
Right, those are very concreteexamples of where you can't
assign a human to do that kindof work.
So it's very much about set oftools.
It's not simple program thatyou can download and run.
It's not one single algorithm.
(12:43):
It's not the latest model thatGoogle or Meta or OpenAI put out
.
It's a collection of tools, andso these collections of tools
can be used in different areas,from robotics to automating
manufacturing, to doing qualityassurance tests, and you can
think about doingrecommendations and also
(13:03):
personalization.
But there's so many differentfields that come up, it's very
easy to get lost in there, andthat's why we've actually built
this framework called theBerrygem AI5C framework.
We focus on bringing thatcomplexity down into the core
five capabilities that AI canhelp us with.
We do very detailed workshopson this, but very quickly.
(13:26):
The first capability is findfinding things for us.
So if you do Google search,it's an example of using the
AI's find capabilities, documentsearch capabilities.
Then there's the makecapability.
If you tell Midjourney tocreate an artwork of a
particular style, that's anexample of making.
You can use it to synthesizedocuments or write emails or
(13:48):
prepare or even create newvariations of a mechanical
design that you want.
Then there's also Connect.
Connect allows you to find theconnections between different
measurements and outcomes, andso if you can understand the
relationships within the data,then you can make prediction,
which is the fourth kind ofcapability of AI to predict
(14:08):
about an unknown future orunknown state.
And then, of course, there isthe fifth one, which is to
optimize.
How do you consider all thosesignals and pieces of
information and figure out ifnot the optimal, a good enough
solution for that complex,constrained satisfaction sort of
space?
So if you think about AI inthose five terms, like broadly,
(14:30):
that's a really goodfoundational place to begin when
you want to go down the pathwayof AI, because otherwise you're
going to get lost in the sea of75 years of research.
Speaker 1 (14:40):
Academic of 75 years of research, academic and
commercial work.
So maybe a bit of aphilosophical question for you.
So can AI truly exhibitcreativity, or is it simply
mimicking human ideas at a massscale?
Speaker 2 (14:57):
Very good question, right, by the way, I'm not an
expert who'll be able to answerit definitively, because no one
actually knows the answer tothis right now.
Because the question is are wehumans doing the same thing?
We are products of ourexperiences.
Imagine certain artists who goto certain schools and they
embody a certain style ofcreativity in the art and the
(15:17):
music they create.
It's because it is what wastaught through their experiences
with the teacher.
Of course, there is innovationand creativity that comes
afterwards, right, that they'reembellishing and creating
something new.
So in some ways, if you look atit purely from an output
perspective, they're mimickingthe kind of creativity humans do
, but at a humongous scale,right?
(15:39):
So I know that would scare alot of us, because the question
then becomes more philosophicalwhat is it unique to be human
Right?
What is it about us?
The answer is we don't know yetand we have to find out, and
this is the process.
We are in a cusp of a massiveeconomic, social and cultural
evolution, thanks to AI leaps inthe recent years, and it's
(16:03):
opened some very, very importantquestions about how should
societies operate.
What does it mean to be human?
What does it mean to create?
What does it mean to engage?
How does that reconfigurethings?
Now, don't panic, that's notrequired.
Tomorrow, you know, we're goingto have a little bit of a
journey that we're going to gothrough, but collectively, it's
important for us to be very openand transparent and not close
(16:26):
our eyes to those possibilitiesand questions.
Speaker 1 (16:30):
Yes, agreed, dive in, Don't be left behind.
We need to understand All right.
You know, I know most of ourlisteners are aware or have used
of ChatGPT and you mentionedthat already.
Where does ChatGPT fit, and youmentioned that already.
Where does ChatGPT fit withinBarry Jam's framework?
Speaker 2 (16:48):
Ah, good question.
So ChatGPT, just like any otherAI tool or product, exhibits
multiple capabilities.
So remember the Barry Jam AI 5Cframework is about capabilities
that an AI can demonstrate orgive us that we can leverage.
So chat GPD has two broadcapabilities.
(17:08):
One is the find one.
You know, if you give it adocument and say, hey, go
through, scan through thisdocument, find me places in that
document where this part ismentioned or this phrase is
mentioned or this description isexplained, that's what it can
do.
It can go and find that.
So like imagine, and a practicalexample is you know you've got
documents and documentseverywhere and you want to track
(17:30):
down where a particular partnumber is mentioned in those
documents and then be able to goand understand the context in
which it's described in, andit's not just a simple string
matching, it's to understand thecontext around it.
That's an example of the finecapabilities and that's what,
like large language models likeChatGPT, gemini from Google,
lama from Meta, claude fromAnthropic they all do these
(17:52):
kinds of things the finecapability.
But they also do the makecapability, which makes them
even more powerful.
Right, because what they areable to do is synthesize new
ideas in a particular frame.
You can ask ChatGPT to explainthe complex world of
astrophysics as a little poem ora haiku.
That's an example of generating,but it's not just text that you
(18:16):
can generate.
A lot of companies, by the way,they're using this to generate
documents, proposals, pitches,presentations.
Now the challenge is going tobe how do you get that right?
Right?
So, how do you make sure thatit's generating the right
content, it's accurate, it'sconsistent, it's aligned with
your speaking style, yourwriting style?
(18:38):
So back to your question whatis ChatGPT exhibiting?
It's exhibiting the find andthe make capabilities.
Speaker 1 (18:45):
Understood.
So let's envision, let's talk alittle bit about, maybe, what
the future looks like.
I think we're all thinkingabout this like what does this
mean?
And we know AI is transformingour jobs, businesses across the
globe.
So how do you expect that wemight continue to see this
impact or how it might show upin our individual lives?
(19:05):
What do you expect that wemight continue to see this
impact or how it might show upin our individual lives?
What do you anticipate that wewill see?
Speaker 2 (19:10):
It's already happening, and it has been
happening for the last 20 or 30years.
By the way, If you've beenonline and you've seen an ad for
a product and so I was atAmazon I built their ad
targeting platform where wewould use the data on your
browsing purchasing history topredict what are the kind of
things you would be interestedin so you can show them relevant
(19:31):
ad.
Google does it, Meta does it.
That's AI driven.
Connect the dots and makeprediction capabilities right.
You are doing that, so you'realready living that.
It's been very transparent foryou In terms of what we're
seeing more and more these daysis a new kind of capabilities
that are being unlocked with it.
So, if you think about whatChatGPT is doing, it's
(19:53):
transforming the way people areproducing content, how they're
generating videos, images,artworks, creating websites,
creating documents, synthesizingmultiple pieces of information
into creating a sort ofsummarized text, and so forth.
So there's all sorts of waysthat people are using it and
(20:14):
they're going to need to usemore, and this is going to
transform the way businessesoperate.
If you look at it, healthcaredoctors we're working with a
(20:34):
neurologist who is actuallylooking at ways to improve their
patient outcome by leveragingAI and streamlining their
workflow.
It's a very, very sensitive,secure area.
We've got to protect thepatient data.
It's a place where people feelmost uncertain about can AI play
a role?
But that's where an AI isplaying a role.
It's playing a supportive role.
It's playing an assistant role.
It's not eliminating the doctor.
It's making the doctor morecapable, and that sort of
general trend is going to applyeverywhere.
(20:54):
Everyone's going to find AIcomponents and capabilities to
enhance particular parts oftheir daily workflows that
basically supercharges.
Speaker 1 (21:05):
Yeah, you know, and so I know some of us seem a
little afraid right that it'sgoing to replace our jobs or you
know something of that nature.
People have concern.
It is reshaping the job marketand in ways that you're
discussing.
Should people be worried orshould they be excited?
Speaker 2 (21:23):
It is definitely going to change and have an
impact on a society.
There are going to be some jobsthat are going to be impacted
and people are going to losethem and some jobs are going to
be created as a result of that.
But I want to think a littlebit about the way I look at it.
This way is like we now have acapability to create movies, if
(21:43):
you think about it, using AI.
Right, and AI can help someonewrite a script.
They can then create andgenerate videos out of it.
So you know, one argument wouldbe hey, you don't need artists
anymore to make movies.
But in reality, if you thinkabout the way the current system
of movie making is set up,99.999% of great ideas never
(22:06):
make it to the screen becausethe cost, the effort, the people
, the budgets required to takean idea and make it, get it onto
the screen is a barrier formost of these ideas.
So there's a massive graveyardof ideas that never saw the
light of day and now we mightsee an opportunity for, because
(22:29):
we've lowered the barrier on thecost of getting those ideas to
the screen, more of those ideasmanifest.
So in some ways, there's goingto be a complimentary, sort of a
result of this right.
You're going to see ideas thatwould never have been imagined
because we didn't have the time,we didn't have the budget, we
didn't have the people maketheir way into society.
(22:53):
You might see the work that wedo in terms of research and
development, Like we've beenworking with medical researchers
doing genetic research andapplying AI for that.
There's a fantastic area therewhere they're using alpha falls
from Google to actually imaginenew protein structures and then
test those more deliberately tofigure out are they stable for
(23:15):
clinical healthcare outcomes.
Same thing could be done formanufacturing process designing.
If you think about designingnew frames and structures for
particular vehicles that aremuch lighter but stronger at the
same time, that would havetaken years to do, or some ideas
never get been enhanced, butnow they can be.
(23:36):
So every domain is going to seean opportunity.
Of course, jobs are going toshift.
If you're not going to be usingAI in the next 10 years to
enhance and deliver and makeyour own work more exciting and
fun, then chances are you aregoing to be impacted with
layoffs.
It's not going to be life asusual, as it used to be.
(23:59):
It's going to be lifetransformed with new
capabilities.
Speaker 1 (24:03):
Yeah, I agree.
So what I hear you saying isit's up to the individual to see
this as an opportunity to maketheir own skill set, their
creativity or their expertisemore efficient, more effective.
It opens up the realm ofpossibility to allow people to
shine in their skill set.
(24:23):
So it's just figuring out whatare the right ways to utilize it
for that end result.
Speaker 2 (24:30):
Absolutely.
And look, people are inherentlyvery creative.
They have the skill set tosynthesize different ideas, work
with people across differentgroups, and they use their
imagination to bring andconceive of something and then
get it to over the line, becausean AI can be a fantastic tool
to help them do that right.
(24:52):
It's not just individuals, it'sorganizations as well, by the
way.
So, right, you know you've gotto think about if you're a
leader in an organization, whatkind of organization am I
creating?
Uh, am I cultivating?
Right, because there is a lot ofeconomic pressures in
organization.
From the look at the conditionsthat are happening in the world
around, the pressure on capitaland investment availability and
(25:14):
so forth, you're being asked,as a leader, to do more with
less, less.
And if you want to get to thatworld where you have to compete,
everyone's doing it, by the way, and there's a fantastic BCG
study out there which showedthat there are companies who are
actually leveraging AI to domore with less and they're
seeing 1.5 and 1.6x improvementsin their bottom lines, revenues
(25:38):
, satisfactions, et cetera, etcetera.
So it's individuals, companies,organizations all have to think
about how do they leverage thisnew capability.
Speaker 1 (25:49):
Yes, and to think about it from a quantitative
perspective, like you're saying,is are there ways we can make
measurable improvements, so thatway we can be more and justify
things more?
Speaker 2 (26:00):
And then change the quality of your experience right
Rather than doing the mundaneelements of it.
How do you change it to?
You're enjoying the kind ofwork you do more and more so.
For example, at Berry Jam, weactually use a lot of AI
internally to critique our ownwork.
We use AI to give it feedbackand say, okay, I've written this
code, help me make it better.
You know how do we enhance itit?
Speaker 1 (26:23):
so there's ways to not get caught out in the
mundane and focus more on thecreative engagements for
ourselves improve the output ofthe work we're already doing, as
well as do more of thevalue-added work that we were
hired to do, instead of minutiaeor wasting more time or
(26:44):
spending time on something thatmay not be as value-add.
Speaker 2 (26:48):
Indeed, indeed.
I mean, if you look at justlook at most engineering
companies and manufacturingcompanies.
We hire amazingly talented,experienced engineers and then
most of the time they're chasingaround updating documents.
They're not creating stuff.
Speaker 1 (27:05):
Yes, right.
Speaker 2 (27:06):
They're going from one meeting to the other.
They're figuring out whichdocument has what.
There was a company inAustralia they were looking at.
They're an electrical companyand they get a lot of requests
for connections and so they putout.
You know, it was interesting tosee how much of their engineers
electrical engineers' time isspent just responding to these
(27:27):
requests rather than creatingand doing the high value stuff
that they need done.
And so those are examples everyorganization has.
I'm sure listeners can think ofat least three examples in
their own organization where, ohman, I wish I didn't have to do
this, but we have to do thisand I wish, with NAI, could help
me either do it faster or justcircumvent this.
Speaker 1 (27:51):
Yes, we hear that a lot on the engineering side as
well, with the organizations wework with.
Where engineering's not.
They're spending too much timeon administrative activities and
we need them to be focused moreon design activities.
So, yes, that is a common painpoint.
So you know we're talking a lotabout the skill sets and
thinking about the future.
What advice do you have forindividuals, you know, moving
(28:15):
into an AI driven economy, oreven more of an AI driven
economy, what skills should webe trying to think ahead and
acquire and achieve andimplement in our own jobs to be
better, to adapt?
Speaker 2 (28:28):
Good question, and there is so much that's
happening and things arechanging so much it's very, very
difficult to be confident inpicking one pathway and say, hey
, this is a tool, this is thecapability.
And I think what we want to bevery circumspect about is
knowing what is the rightpathway, what's the right
strategy, even for individuals.
(28:48):
And so step number one isunderstand what AI means.
It doesn't mean you're goingand writing code.
It doesn't mean you're goingand building your own AI model
and stuff.
I would encourage them to thinka little bit about more of the
strategy side of it, like if youthink about the frameworks that
we're doing at Berry Jam withthe AI5C framework, that's
(29:09):
designed specifically to helppeople contextualize and ground
AI in a deeper and clearerunderstanding, so they can be
very more deliberate about wherethey want to focus their
efforts on.
That's number one.
Number two, and a shameless plughere they should do the AI
Readiness Workshop, becausethat's a place where they get to
learn about the fundamentals ofAI and the leadership
(29:30):
challenges of how to bring in AIso that it's successfully
adopted and, within theorganization, resisted and an
elephant in the room that nevergets adopted and used.
So that's very.
And then the other part we dowith the AI readiness workshop
is actually help you with thetools to figure out how to build
(29:51):
the right business value caseswith AI.
Right, how should you thinkabout it?
How do you design theorganization cultural?
How do you design the strategy?
How do you understand what youneed so that you can then be
very deliberate about what toask when you're engaging with
others who might be AI expertsin those fields?
(30:11):
Right, so you want to be in asituation where you're asking
the right questions.
Problem is, most people don'teven know what the right
questions are to begin with.
So those things are very, veryimportant.
Speaker 1 (30:22):
So you mentioned the workshops that you do and, as
you know, this is why we're hereis AI is a big topic in the IPX
community.
So we at IPX we wanted to bringin Barry Jam as a trusted
solution in this space and you,dr Avi, as our trusted expert in
this space, to support ourcommunity.
So we are excited to now behosting a series of these
(30:46):
Kickstart workshops with you soour community can begin to
understand how they can use AIeffectively within their
businesses and their jobs.
What are the next steps?
How do I speak about thisintelligently?
How do I think about how toscope this properly and start to
figure out what are the nextsteps and just educate people
and make them feel comfortableabout how to scope this properly
and start to figure out whatare the next steps and just
educate people and make themfeel comfortable being able to
(31:07):
engage in these kind ofconversations within their
businesses and with theirleadership.
So I would love for you just totell us a little bit more about
the workshop and what canparticipants expect to do and
learn.
Speaker 2 (31:22):
Absolutely and very, very excited to partner with IPX
and bringing AI readiness tothis community, because I think
there's a lot of opportunityhere and it's going to have a
transformational effect in everyaudience.
The key element of theworkshops is well, firstly, it's
over two days.
It's about three and a half tofour hours where we dive deep
(31:45):
into understanding thefundamentals of it.
Don't worry, no math isinvolved.
No code was written.
You will not be asked to writein Python or C.
It's very much aleadership-centered, strategic
thinker sort of a workshop.
So if you are a leader,decision maker or you aspire to
be one in the evolving world ofAI space, making sure
(32:09):
understanding that space is veryimportant.
So this is for you.
We break down some of the mythsaround it.
We go through some use cases.
We talk about the different AIcapabilities.
We also give you a little bitof a homework.
You get to do a little bit ofplanning on figuring out what
are the problems that aresuitable for this within your
day-to-day or the organization,and then we help you build the
(32:33):
right business case how to thinkabout building a right business
case for this and evaluateyourself whether this is a
worthwhile pursuit of your timeand energy or not, because
there's no point going down avery complex AI adoption program
with things that don't matter.
We recently did these workshopswith a large precision
agricultural company out of NewZealand where we got their
(32:56):
executives in the room.
About 20 people were in theroom and this is after the
online training.
We actually did a separatesession where they went in and
they worked out their company'spain points, opportunities,
built the roadmap around it, andthere were 30 items on that
roadmap that they are nowfiguring out what to do with in
terms of getting funding,spinning up teams, bringing
(33:19):
partners to execute all of that.
Now they can't do any of thatstuff without going through
these kind of deeperunderstanding and making sure
everyone aligns on what isvaluable and what's the value of
doing A before C and B before C.
So those are the elements thatthe AI workshop that we're
offering with IPX and throughthe IPX community is around
(33:40):
helping you understand AI, makesure you understand how to frame
the capabilities you need andthen start building the very,
very important business casearound for you to convince your
leadership and your teams toexecute.
Speaker 1 (33:55):
I'm super excited to be doing these workshops with
you, avi, and so, like Avi said,these are offered once a month
here.
They're a two-day workshop.
It's offered May throughSeptember of this year.
At this point, the workshopsare formatted in the two
half-day sessions.
They're scheduled to be asconvenient as possible in the
(34:15):
latter half of your day.
We encourage you to reach outto us at IPX with any questions
that you may have, or Avidirectly as well.
That would be absolutely okay.
So just let us know if there'sanything that we can do to give
you the information you need togo back and discuss this topic
and this training within yourorganizations, and we hope that
(34:37):
we hear from you guys, and wereally appreciate Dr Avishkar
Misra for spending time with ustoday.
Thank you so much for your timeand take care.
We appreciate it.
Thank you so much for your timeand take care.
We appreciate it.
Speaker 2 (34:50):
Thank you very much for having me my pleasure.
Speaker 1 (34:53):
Thank you for tuning in today.
Don't forget to subscribe andreview the show and for more
information on IPX visitIPXHQcom.
Welcome to the IPX.
Speaker 2 (00:02):
True North podcast, where we connect people,
processes and tools.
Speaker 1 (00:07):
Hello and welcome back to the IPX True North
podcast.
My name is Brandi Taylor andI'm super excited for the guest
we have lined up for you todayinto utilizing AI within your
businesses to make youroperations more efficient and
effective in any discipline ofyour business, including SAM2.
(00:29):
Our guest today is Dr AvishkarMishra, known to most as Avi.
Hello, avi.
Speaker 2 (00:37):
Hey Brandy, how you doing.
Speaker 1 (00:38):
Doing great.
Let me just tell you a littlebit about Avi.
So Avi is an AI scientist,technologist and entrepreneur
for over two decades ofexperience at the forefront of
artificial intelligence.
Avi has led AI initiatives atcompanies like Amazon, oracle,
teradata and TrackPhone, workingon everything from doubling the
(01:02):
accuracy of recommendations tothe tech behind Amazon's Go's
past year less stores.
He holds a PhD in AI applied tomedical image analysis and is
now the founder of VeryJam,where he's focused on making AI
accessible, explainable anduseful for organizations of all
(01:23):
kinds.
Avi, it is a really a greatpleasure to have you on the
podcast.
Thank you so much and welcome.
Speaker 2 (01:29):
My pleasure, lovely to be here Excellent.
Speaker 1 (01:32):
So I know I did a bit of an intro for you.
Are there any other details,before we get started, that
you'd like to provide ourlisteners about yourself or your
background?
Speaker 2 (01:42):
Sure, I mean the main thing I should highlight.
I do have a manageable caffeineaddiction, so you might see me
reaching for my coffee and myespresso time to time.
Other than that, you know Ilook.
I've been in the area of AI andmachine learning for quite a
while and way before.
Ai suddenly was very, veryexciting for everybody because
it met the new threshold ofcapabilities, and so I've seen
(02:04):
the journey along the way fromresearch and inventing things to
actually building products,services that launch and help
operations, and the servicesthat I've built are used by
millions of people every singleday without even realizing that
they exist.
And that's where the beauty ofAI should be.
It should be somewhere hiddenaway as a support mechanism,
(02:26):
without it taking all thelimelight and attention, and
making sure that the people whoare doing their jobs or creating
things or imagining the newfuture can do that effortlessly.
Speaker 1 (02:38):
All right, excellent.
So you know, I know Barry Jamis doing some pretty fun things
in the AI space and we'reinquiring minds really want to
know.
Just tell us a little bit aboutthat spark.
What led you to the creation ofBarry Jam?
Sure?
Speaker 2 (02:53):
So, as I said, I've been in the space for a while,
and one thing I noticed when Iwas working with a lot of the
Fortune 500 companies looking toadopt AI, data science or
better data-drivendecision-making is that there's
a lot of discrepancy between thecompanies who understand it and
can leverage it versuscompanies that don't even know
(03:13):
how to get started right.
So you know, there are alwaysthese new shiny tools that come
into the market, but without acohesive strategy, it really
made it very, very difficult fororganizations to leverage it.
So you'll see massive gapsbetween the companies who are at
the forefront pinnaclescompanies like Amazon and Oracle
and Microsoft and Google versuscompanies who are trying to
(03:35):
compete in the space very, veryrapidly and just trying to catch
up, and so we saw it both as arisk for the broader economy.
You want to make sure youdiversify the concentration of
that technology and the skillsetso there's more competition,
but also an opportunity for usto come in and help.
(03:55):
How do you help organizationfigure out and chart their
course?
By making AI much, much moreaccessible, much, much more easy
to understand and adopt and sothat they can realize its value
in their day-to-day.
Speaker 1 (04:10):
Yes, value is what it's all about, and you talk
about the things that you'redoing to help businesses achieve
that value.
Tell us a little bit more aboutBerryJam and what services that
you offer.
Speaker 2 (04:23):
Yeah.
So BerryJam started about a fewyears ago about two and a half
years now and we started withthe mission of making AI very
simple, accessible and alsoaffordable for a lot of small
and medium-sized businesses,right.
So the mission is very clear.
We very much focus aroundhelping organization understand,
adopt and excel with AI.
(04:44):
So basically we have three mainproduct offerings.
So the first thing we do is wehelp companies figure out your
strategy.
Without a good, cohesivestrategy, you are not going to
be very successful or you'regoing to flounder along the way
and, in some cases, just give upbecause you're not seeing the
results that you should beseeing results.
So that's very important.
(05:05):
We help organizations figureout what's the right strategy
for them, not just hey, I cameacross this use case in some
website or I saw this YouTubevideo and now I can just copy
paste it for my company or myteam.
That's great for inspiration,but often means a disconnect
between what I need versus whata vendor is trying to sell me.
So we really focus first on thestrategy piece.
(05:27):
The second piece we work on iswe do a lot of custom
development work.
So we're working right now witha neurology clinic, helping the
workflow of doctors andstreamline and potentially save
them two to three hours per day,freeing up their time to see
more patients, but also improvethe quality of the care they
deliver to their patients Again,very, very customized,
(05:50):
specialized for them.
And the third pillar of ourservice is our own AI system,
which is focused on analyticalAI.
We call it BerryJam AI, so I'msure people are familiar with
ChatGPT and other large languagemodels where you can ask
questions and we can do stufffor you.
They're really great fortext-based engagement.
They're good for synthesizingarticles and understanding them
(06:12):
and dissecting them.
But when it comes to analyzingdata structured data like tables
it's a very risky propositionto go down using LLMs.
So we built our own AI systemwhich is grounded in much more
statistically sound systems andalgorithms that are defensible.
So you don't want to bet thecompany's decisions and strategy
(06:34):
on what an LLM might havehallucinated, but what you want
to be able to do is ground thatinto statistics and machine
learning methods that haveactually been proven to be
successful over the last 20, 30years, especially at companies
large companies like Amazon'sand Microsoft's and other places
.
This software is very, veryspecialized, focused on helping
(06:55):
people, going from data toactionable insights and doing it
, you know, factor order ofmagnitude faster than
conventional methods.
Speaker 1 (07:04):
I love it.
So there's a few key thingsthere that you said that I
really resonate with, and withthe work that we do at IPX as
well is one.
it's all about making sure yourdata is meaningful, your data is
actionable, you have theinsights to actually make robust
decisions and do what you needto do with your data.
This is key.
(07:24):
So many people, we have so muchdata these days and we're not
using it properly or not evenusing it at all.
So I think it's really key tomake sure that we're thinking
about it from that perspectiveas well, as we know that
organizations and leaderseverywhere they want AI.
They wanna stay on top of thecurve.
This is what people say.
We need to have this.
(07:44):
But it's not just aboutimplementing something that they
think it just exists out herein cyberspace.
It's really about thinkingabout what pain points you have,
what problems are you trying tosolve, and think about it from
a business process perspectiveof how do we make what we do
more efficient, more effective,more accurate.
So I love when you think aboutit like that, because it's
(08:06):
really good project managementprinciples, right of the proper
planning on the front side, soyou have the right expected
outcomes on the backside.
Speaker 2 (08:14):
Indeed.
And look, AI is not a, it's notan answer for every problem,
and also, AI is not just one AI.
You know this last 75 years ofresearch in the field of AI.
So it's very, very complex,very diverse, and what you need
to do is, you know, we've got toget past the initial knee-jerk
reaction of, oh, everyone'sdoing AI, let's bring it in and
(08:35):
let's just copy paste and let'sdo that.
No, you've got to start withwhat does your team need?
What does your organizationneed?
Be very, very specific aboutthe specific capabilities.
And that's one of the placeswhere we focus a lot of effort
on helping organizations, youknow, start from where their
pain point is and then workbackwards towards figuring out
oh, these are the capabilitiesof AI that I need.
(08:58):
And then you have theconversation around okay, what
is the right type of tool,framework, technology, partner
that is relevant?
So it's very important to startwith a strategy.
If you don't have a goodstrategy, you're likely to be
one of the statistics of 80 to90% of projects that are going
to fail in AI are never going tosee the results that we expect.
Speaker 1 (09:18):
Yep, it's requirements, lead tools follow.
Speaker 2 (09:21):
Indeed and having that sort of understanding of
what that organization'scultural framework needs to be
in place, right, how do you needto think about the space?
It's very, very dynamic, veryevolving.
I know it's a lot of attentionin the news, but the
fundamentals of running a goodbusiness have not shifted.
The fundamentals of teamworkand collaboration have not
shifted.
The fundamentals of thecreative processes and
(09:44):
engineering rigor that goes intodeveloping things have not
changed.
So we've always liked to groundit into good, sound foundations
and then use these as tools togo further.
That's why we work with medicalresearchers.
We've done some work withMichigan Medicine where we've
looked at analyzing the clinicaltrial data.
So Dr Tapua had some data thathe'd run through some clinical
(10:06):
trials and we were able to useBerry Jam AI to do that 6,200
times faster because we designedthat specifically for that
particular analytics.
You can't just use ChatGPT togo and say, oh, analyze this
Excel file for me.
So there's different types ofit has different uses.
Speaker 1 (10:24):
Yeah, so you know to your point.
Let's demystify AI just alittle bit for a minute for our
listeners.
And so, Dr Avi, so you have aPhD in artificial intelligence
and you've built some AIproducts, but many of us are not
in AI, right.
We're in engineering or we'rein supporting functions or
manufacturing, et cetera.
So I guess I would like you,for Frida, to break things down
(10:47):
a little bit for us.
So, from your perspective, whatis AI?
Speaker 2 (10:52):
So the way we like to frame AI is AI is a set of
tools, techniques and frameworksor algorithms whatever it is
that allows for intelligentdecision-making and now that
intelligent decision-making canbe very simple or it could be
very complex.
So, for example, you have asensor in the garden that's
(11:15):
monitoring the moisture contentof the soil and they're making a
decision based on weatherforecast to decide whether to
turn on the sprinkles or not.
If you think about it, it's avery narrow, narrow, narrow,
specific domain of thatparticular system, but it is an
artificially intelligentdecision-making system.
It's not a human involved in it.
(11:35):
So that's an example.
Meanwhile, you have morecomplex systems, right, figuring
out, well, what's the nextmovie we should watch, right,
that might look at signals ofall your previous watches,
movies that you've liked, rated,what's in the market, what's
everyone watching.
All of that combined could beconsidering lots of different
signals and it's very narrowlytarget.
So the key element isintelligent decision-making and
(11:59):
the value that AI can bring in.
It can superscale that beyondhuman capabilities.
So AI can enable human-likeintelligence and behaviors or
decision making for very narrow,specific problem sets, but do
it at immense scale and immensespeed.
So you can imagine consideringmillions of decisions and data
(12:22):
points and personalizing theexperience for every single
customer who visits your websiteor every customer who walks
into the door of your store.
Right, those are very concreteexamples of where you can't
assign a human to do that kindof work.
So it's very much about set oftools.
It's not simple program thatyou can download and run.
It's not one single algorithm.
(12:43):
It's not the latest model thatGoogle or Meta or OpenAI put out
.
It's a collection of tools, andso these collections of tools
can be used in different areas,from robotics to automating
manufacturing, to doing qualityassurance tests, and you can
think about doingrecommendations and also
(13:03):
personalization.
But there's so many differentfields that come up, it's very
easy to get lost in there, andthat's why we've actually built
this framework called theBerrygem AI5C framework.
We focus on bringing thatcomplexity down into the core
five capabilities that AI canhelp us with.
We do very detailed workshopson this, but very quickly.
(13:26):
The first capability is findfinding things for us.
So if you do Google search,it's an example of using the
AI's find capabilities, documentsearch capabilities.
Then there's the makecapability.
If you tell Midjourney tocreate an artwork of a
particular style, that's anexample of making.
You can use it to synthesizedocuments or write emails or
(13:48):
prepare or even create newvariations of a mechanical
design that you want.
Then there's also Connect.
Connect allows you to find theconnections between different
measurements and outcomes, andso if you can understand the
relationships within the data,then you can make prediction,
which is the fourth kind ofcapability of AI to predict
(14:08):
about an unknown future orunknown state.
And then, of course, there isthe fifth one, which is to
optimize.
How do you consider all thosesignals and pieces of
information and figure out ifnot the optimal, a good enough
solution for that complex,constrained satisfaction sort of
space?
So if you think about AI inthose five terms, like broadly,
(14:30):
that's a really goodfoundational place to begin when
you want to go down the pathwayof AI, because otherwise you're
going to get lost in the sea of75 years of research.
Speaker 1 (14:40):
Academic of 75 years of research, academic and
commercial work.
So maybe a bit of aphilosophical question for you.
So can AI truly exhibitcreativity, or is it simply
mimicking human ideas at a massscale?
Speaker 2 (14:57):
Very good question, right, by the way, I'm not an
expert who'll be able to answerit definitively, because no one
actually knows the answer tothis right now.
Because the question is are wehumans doing the same thing?
We are products of ourexperiences.
Imagine certain artists who goto certain schools and they
embody a certain style ofcreativity in the art and the
(15:17):
music they create.
It's because it is what wastaught through their experiences
with the teacher.
Of course, there is innovationand creativity that comes
afterwards, right, that they'reembellishing and creating
something new.
So in some ways, if you look atit purely from an output
perspective, they're mimickingthe kind of creativity humans do
, but at a humongous scale,right?
(15:39):
So I know that would scare alot of us, because the question
then becomes more philosophicalwhat is it unique to be human
Right?
What is it about us?
The answer is we don't know yetand we have to find out, and
this is the process.
We are in a cusp of a massiveeconomic, social and cultural
evolution, thanks to AI leaps inthe recent years, and it's
(16:03):
opened some very, very importantquestions about how should
societies operate.
What does it mean to be human?
What does it mean to create?
What does it mean to engage?
How does that reconfigurethings?
Now, don't panic, that's notrequired.
Tomorrow, you know, we're goingto have a little bit of a
journey that we're going to gothrough, but collectively, it's
important for us to be very openand transparent and not close
(16:26):
our eyes to those possibilitiesand questions.
Speaker 1 (16:30):
Yes, agreed, dive in, Don't be left behind.
We need to understand All right.
You know, I know most of ourlisteners are aware or have used
of ChatGPT and you mentionedthat already.
Where does ChatGPT fit, and youmentioned that already.
Where does ChatGPT fit withinBarry Jam's framework?
Speaker 2 (16:48):
Ah, good question.
So ChatGPT, just like any otherAI tool or product, exhibits
multiple capabilities.
So remember the Barry Jam AI 5Cframework is about capabilities
that an AI can demonstrate orgive us that we can leverage.
So chat GPD has two broadcapabilities.
(17:08):
One is the find one.
You know, if you give it adocument and say, hey, go
through, scan through thisdocument, find me places in that
document where this part ismentioned or this phrase is
mentioned or this description isexplained, that's what it can
do.
It can go and find that.
So like imagine, and a practicalexample is you know you've got
documents and documentseverywhere and you want to track
(17:30):
down where a particular partnumber is mentioned in those
documents and then be able to goand understand the context in
which it's described in, andit's not just a simple string
matching, it's to understand thecontext around it.
That's an example of the finecapabilities and that's what,
like large language models likeChatGPT, gemini from Google,
lama from Meta, claude fromAnthropic they all do these
(17:52):
kinds of things the finecapability.
But they also do the makecapability, which makes them
even more powerful.
Right, because what they areable to do is synthesize new
ideas in a particular frame.
You can ask ChatGPT to explainthe complex world of
astrophysics as a little poem ora haiku.
That's an example of generating,but it's not just text that you
(18:16):
can generate.
A lot of companies, by the way,they're using this to generate
documents, proposals, pitches,presentations.
Now the challenge is going tobe how do you get that right?
Right?
So, how do you make sure thatit's generating the right
content, it's accurate, it'sconsistent, it's aligned with
your speaking style, yourwriting style?
(18:38):
So back to your question whatis ChatGPT exhibiting?
It's exhibiting the find andthe make capabilities.
Speaker 1 (18:45):
Understood.
So let's envision, let's talk alittle bit about, maybe, what
the future looks like.
I think we're all thinkingabout this like what does this
mean?
And we know AI is transformingour jobs, businesses across the
globe.
So how do you expect that wemight continue to see this
impact or how it might show upin our individual lives?
(19:05):
What do you expect that wemight continue to see this
impact or how it might show upin our individual lives?
What do you anticipate that wewill see?
Speaker 2 (19:10):
It's already happening, and it has been
happening for the last 20 or 30years.
By the way, If you've beenonline and you've seen an ad for
a product and so I was atAmazon I built their ad
targeting platform where wewould use the data on your
browsing purchasing history topredict what are the kind of
things you would be interestedin so you can show them relevant
(19:31):
ad.
Google does it, Meta does it.
That's AI driven.
Connect the dots and makeprediction capabilities right.
You are doing that, so you'realready living that.
It's been very transparent foryou In terms of what we're
seeing more and more these daysis a new kind of capabilities
that are being unlocked with it.
So, if you think about whatChatGPT is doing, it's
(19:53):
transforming the way people areproducing content, how they're
generating videos, images,artworks, creating websites,
creating documents, synthesizingmultiple pieces of information
into creating a sort ofsummarized text, and so forth.
So there's all sorts of waysthat people are using it and
(20:14):
they're going to need to usemore, and this is going to
transform the way businessesoperate.
If you look at it, healthcaredoctors we're working with a
(20:34):
neurologist who is actuallylooking at ways to improve their
patient outcome by leveragingAI and streamlining their
workflow.
It's a very, very sensitive,secure area.
We've got to protect thepatient data.
It's a place where people feelmost uncertain about can AI play
a role?
But that's where an AI isplaying a role.
It's playing a supportive role.
It's playing an assistant role.
It's not eliminating the doctor.
It's making the doctor morecapable, and that sort of
general trend is going to applyeverywhere.
(20:54):
Everyone's going to find AIcomponents and capabilities to
enhance particular parts oftheir daily workflows that
basically supercharges.
Speaker 1 (21:05):
Yeah, you know, and so I know some of us seem a
little afraid right that it'sgoing to replace our jobs or you
know something of that nature.
People have concern.
It is reshaping the job marketand in ways that you're
discussing.
Should people be worried orshould they be excited?
Speaker 2 (21:23):
It is definitely going to change and have an
impact on a society.
There are going to be some jobsthat are going to be impacted
and people are going to losethem and some jobs are going to
be created as a result of that.
But I want to think a littlebit about the way I look at it.
This way is like we now have acapability to create movies, if
(21:43):
you think about it, using AI.
Right, and AI can help someonewrite a script.
They can then create andgenerate videos out of it.
So you know, one argument wouldbe hey, you don't need artists
anymore to make movies.
But in reality, if you thinkabout the way the current system
of movie making is set up,99.999% of great ideas never
(22:06):
make it to the screen becausethe cost, the effort, the people
, the budgets required to takean idea and make it, get it onto
the screen is a barrier formost of these ideas.
So there's a massive graveyardof ideas that never saw the
light of day and now we mightsee an opportunity for, because
(22:29):
we've lowered the barrier on thecost of getting those ideas to
the screen, more of those ideasmanifest.
So in some ways, there's goingto be a complimentary, sort of a
result of this right.
You're going to see ideas thatwould never have been imagined
because we didn't have the time,we didn't have the budget, we
didn't have the people maketheir way into society.
(22:53):
You might see the work that wedo in terms of research and
development, Like we've beenworking with medical researchers
doing genetic research andapplying AI for that.
There's a fantastic area therewhere they're using alpha falls
from Google to actually imaginenew protein structures and then
test those more deliberately tofigure out are they stable for
(23:15):
clinical healthcare outcomes.
Same thing could be done formanufacturing process designing.
If you think about designingnew frames and structures for
particular vehicles that aremuch lighter but stronger at the
same time, that would havetaken years to do, or some ideas
never get been enhanced, butnow they can be.
(23:36):
So every domain is going to seean opportunity.
Of course, jobs are going toshift.
If you're not going to be usingAI in the next 10 years to
enhance and deliver and makeyour own work more exciting and
fun, then chances are you aregoing to be impacted with
layoffs.
It's not going to be life asusual, as it used to be.
(23:59):
It's going to be lifetransformed with new
capabilities.
Speaker 1 (24:03):
Yeah, I agree.
So what I hear you saying isit's up to the individual to see
this as an opportunity to maketheir own skill set, their
creativity or their expertisemore efficient, more effective.
It opens up the realm ofpossibility to allow people to
shine in their skill set.
(24:23):
So it's just figuring out whatare the right ways to utilize it
for that end result.
Speaker 2 (24:30):
Absolutely.
And look, people are inherentlyvery creative.
They have the skill set tosynthesize different ideas, work
with people across differentgroups, and they use their
imagination to bring andconceive of something and then
get it to over the line, becausean AI can be a fantastic tool
to help them do that right.
(24:52):
It's not just individuals, it'sorganizations as well, by the
way.
So, right, you know you've gotto think about if you're a
leader in an organization, whatkind of organization am I
creating?
Uh, am I cultivating?
Right, because there is a lot ofeconomic pressures in
organization.
From the look at the conditionsthat are happening in the world
around, the pressure on capitaland investment availability and
(25:14):
so forth, you're being asked,as a leader, to do more with
less, less.
And if you want to get to thatworld where you have to compete,
everyone's doing it, by the way, and there's a fantastic BCG
study out there which showedthat there are companies who are
actually leveraging AI to domore with less and they're
seeing 1.5 and 1.6x improvementsin their bottom lines, revenues
(25:38):
, satisfactions, et cetera, etcetera.
So it's individuals, companies,organizations all have to think
about how do they leverage thisnew capability.
Speaker 1 (25:49):
Yes, and to think about it from a quantitative
perspective, like you're saying,is are there ways we can make
measurable improvements, so thatway we can be more and justify
things more?
Speaker 2 (26:00):
And then change the quality of your experience right
Rather than doing the mundaneelements of it.
How do you change it to?
You're enjoying the kind ofwork you do more and more so.
For example, at Berry Jam, weactually use a lot of AI
internally to critique our ownwork.
We use AI to give it feedbackand say, okay, I've written this
code, help me make it better.
You know how do we enhance itit?
Speaker 1 (26:23):
so there's ways to not get caught out in the
mundane and focus more on thecreative engagements for
ourselves improve the output ofthe work we're already doing, as
well as do more of thevalue-added work that we were
hired to do, instead of minutiaeor wasting more time or
(26:44):
spending time on something thatmay not be as value-add.
Speaker 2 (26:48):
Indeed, indeed.
I mean, if you look at justlook at most engineering
companies and manufacturingcompanies.
We hire amazingly talented,experienced engineers and then
most of the time they're chasingaround updating documents.
They're not creating stuff.
Speaker 1 (27:05):
Yes, right.
Speaker 2 (27:06):
They're going from one meeting to the other.
They're figuring out whichdocument has what.
There was a company inAustralia they were looking at.
They're an electrical companyand they get a lot of requests
for connections and so they putout.
You know, it was interesting tosee how much of their engineers
electrical engineers' time isspent just responding to these
(27:27):
requests rather than creatingand doing the high value stuff
that they need done.
And so those are examples everyorganization has.
I'm sure listeners can think ofat least three examples in
their own organization where, ohman, I wish I didn't have to do
this, but we have to do thisand I wish, with NAI, could help
me either do it faster or justcircumvent this.
Speaker 1 (27:51):
Yes, we hear that a lot on the engineering side as
well, with the organizations wework with.
Where engineering's not.
They're spending too much timeon administrative activities and
we need them to be focused moreon design activities.
So, yes, that is a common painpoint.
So you know we're talking a lotabout the skill sets and
thinking about the future.
What advice do you have forindividuals, you know, moving
(28:15):
into an AI driven economy, oreven more of an AI driven
economy, what skills should webe trying to think ahead and
acquire and achieve andimplement in our own jobs to be
better, to adapt?
Speaker 2 (28:28):
Good question, and there is so much that's
happening and things arechanging so much it's very, very
difficult to be confident inpicking one pathway and say, hey
, this is a tool, this is thecapability.
And I think what we want to bevery circumspect about is
knowing what is the rightpathway, what's the right
strategy, even for individuals.
(28:48):
And so step number one isunderstand what AI means.
It doesn't mean you're goingand writing code.
It doesn't mean you're goingand building your own AI model
and stuff.
I would encourage them to thinka little bit about more of the
strategy side of it, like if youthink about the frameworks that
we're doing at Berry Jam withthe AI5C framework, that's
(29:09):
designed specifically to helppeople contextualize and ground
AI in a deeper and clearerunderstanding, so they can be
very more deliberate about wherethey want to focus their
efforts on.
That's number one.
Number two, and a shameless plughere they should do the AI
Readiness Workshop, becausethat's a place where they get to
learn about the fundamentals ofAI and the leadership
(29:30):
challenges of how to bring in AIso that it's successfully
adopted and, within theorganization, resisted and an
elephant in the room that nevergets adopted and used.
So that's very.
And then the other part we dowith the AI readiness workshop
is actually help you with thetools to figure out how to build
(29:51):
the right business value caseswith AI.
Right, how should you thinkabout it?
How do you design theorganization cultural?
How do you design the strategy?
How do you understand what youneed so that you can then be
very deliberate about what toask when you're engaging with
others who might be AI expertsin those fields?
(30:11):
Right, so you want to be in asituation where you're asking
the right questions.
Problem is, most people don'teven know what the right
questions are to begin with.
So those things are very, veryimportant.
Speaker 1 (30:22):
So you mentioned the workshops that you do and, as
you know, this is why we're hereis AI is a big topic in the IPX
community.
So we at IPX we wanted to bringin Barry Jam as a trusted
solution in this space and you,dr Avi, as our trusted expert in
this space, to support ourcommunity.
So we are excited to now behosting a series of these
(30:46):
Kickstart workshops with you soour community can begin to
understand how they can use AIeffectively within their
businesses and their jobs.
What are the next steps?
How do I speak about thisintelligently?
How do I think about how toscope this properly and start to
figure out what are the nextsteps and just educate people
and make them feel comfortableabout how to scope this properly
and start to figure out whatare the next steps and just
educate people and make themfeel comfortable being able to
(31:07):
engage in these kind ofconversations within their
businesses and with theirleadership.
So I would love for you just totell us a little bit more about
the workshop and what canparticipants expect to do and
learn.
Speaker 2 (31:22):
Absolutely and very, very excited to partner with IPX
and bringing AI readiness tothis community, because I think
there's a lot of opportunityhere and it's going to have a
transformational effect in everyaudience.
The key element of theworkshops is well, firstly, it's
over two days.
It's about three and a half tofour hours where we dive deep
(31:45):
into understanding thefundamentals of it.
Don't worry, no math isinvolved.
No code was written.
You will not be asked to writein Python or C.
It's very much aleadership-centered, strategic
thinker sort of a workshop.
So if you are a leader,decision maker or you aspire to
be one in the evolving world ofAI space, making sure
(32:09):
understanding that space is veryimportant.
So this is for you.
We break down some of the mythsaround it.
We go through some use cases.
We talk about the different AIcapabilities.
We also give you a little bitof a homework.
You get to do a little bit ofplanning on figuring out what
are the problems that aresuitable for this within your
day-to-day or the organization,and then we help you build the
(32:33):
right business case how to thinkabout building a right business
case for this and evaluateyourself whether this is a
worthwhile pursuit of your timeand energy or not, because
there's no point going down avery complex AI adoption program
with things that don't matter.
We recently did these workshopswith a large precision
agricultural company out of NewZealand where we got their
(32:56):
executives in the room.
About 20 people were in theroom and this is after the
online training.
We actually did a separatesession where they went in and
they worked out their company'spain points, opportunities,
built the roadmap around it, andthere were 30 items on that
roadmap that they are nowfiguring out what to do with in
terms of getting funding,spinning up teams, bringing
(33:19):
partners to execute all of that.
Now they can't do any of thatstuff without going through
these kind of deeperunderstanding and making sure
everyone aligns on what isvaluable and what's the value of
doing A before C and B before C.
So those are the elements thatthe AI workshop that we're
offering with IPX and throughthe IPX community is around
(33:40):
helping you understand AI, makesure you understand how to frame
the capabilities you need andthen start building the very,
very important business casearound for you to convince your
leadership and your teams toexecute.
Speaker 1 (33:55):
I'm super excited to be doing these workshops with
you, avi, and so, like Avi said,these are offered once a month
here.
They're a two-day workshop.
It's offered May throughSeptember of this year.
At this point, the workshopsare formatted in the two
half-day sessions.
They're scheduled to be asconvenient as possible in the
(34:15):
latter half of your day.
We encourage you to reach outto us at IPX with any questions
that you may have, or Avidirectly as well.
That would be absolutely okay.
So just let us know if there'sanything that we can do to give
you the information you need togo back and discuss this topic
and this training within yourorganizations, and we hope that
(34:37):
we hear from you guys, and wereally appreciate Dr Avishkar
Misra for spending time with ustoday.
Thank you so much for your timeand take care.
We appreciate it.
Thank you so much for your timeand take care.
We appreciate it.
Speaker 2 (34:50):
Thank you very much for having me my pleasure.
Speaker 1 (34:53):
Thank you for tuning in today.
Don't forget to subscribe andreview the show and for more
information on IPX visitIPXHQcom.
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