KCAA: Inside Analysis with Eric Kavanagh (Sun, 12 Jan, 2025)

KCAA: Inside Analysis with Eric Kavanagh on Sun, 12 Jan, 2025

Episode Transcript

Speaker 1 (00:00):
People trained and placed in open positions in public service,
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is a new opportunity to advance your career and raise
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(00:22):
dot org.

Speaker 2 (00:24):
Listina KCAA Lomolinda at one O six point five FM
K two ninety three c F Brito Valley.

Speaker 3 (00:31):
The information economy has a rod. The world is teeming
with innovation as new business models reinvent every industry industry.
Inside Analysis is your source of information and insight about
how to make the most of this exciting new era.
Learn more at Inside Analysis dot cosideanalysis dot com. And
now here's your host, through Eric.

Speaker 4 (00:52):
Kavanaugh, and keep all right, ladies and gentlemen, Hello and
welcome back once again to the only nationally syndicated show
all about the information economy. It's called Inside Analysis. Your
host Eric Kavanaugh here very excited to kick off twenty
twenty five with world renowned influencer analysts that all around

(01:14):
cool guy Jim Harris. Look him up on Jim Haarris
dot com. Just like it sounds we're at cees all
week and we're talking to lots of really cool companies
like Weepower and my Trust and a whole bunch of
other folks are to get to handle on what's going
on out there in the world of consumer technology, and Jim,
there is no shortage of cool stuff to talk about,

(01:37):
but there are some caveats, of course. This era of
open data and sharing data, it's great stuff. We can
learn a lot about each other what's going on, but
some things maybe we want to keep private. And there's
a story in the news today about a car company
that had a breach and all kinds of data got out,
and lots of people are very unhappy about that. Connected

(02:00):
cars world, if you can tap into someone's information system,
you can find a way to get their information, and
that is a big problem for many companies. So privacy
is still an issue. Security is always going to be
an issue. Anytime you're connected to the Internet, you're connected
to all the good guys and all the bad guys.
The IoT world, as they call it, Internet of Things.

(02:21):
Of course, there's also the IIoT, the industrial Internet of Things.
We'll talk about that at some point, I'm sure. But
Jim first of all great stuff is happening, but some caveats.
What are your thoughts going into CEES twenty twenty five.

Speaker 5 (02:34):
Well, it is such an exciting show. There'll probably be
one hundred and fifty thousand people there, Eric, There're going
to be thousands of companies exhibiting great keynotes, all sorts
of panel discussions. I'm shairing a panel on AI and
predictive AI. So it is just an incredible conference. It's

(02:59):
every year in January in Las Vegas, and it's the
most influential tech show in the world. So we're going
to see a lot of exciting things, a lot of
really interesting discussions. And last year the number one trending
topic was AI and it is AI again on Twitter

(03:23):
in advance now called X. But this year there's a
slight twist to it. The number one trending topic for
CEOs in advance of the conference is agentic AI. Sure,
so we'll talk about that in the show. So a
little teaser agentic AI.

Speaker 4 (03:44):
Yeah, And just to explain to our audience what Jim
is talking about. Our AI agents and these are little
semi autonomous applications that can do all kinds of different things.
It's not just traditional automation where you will tell a
computer do this set of processes whenever this happens. That's
standard automation. It's been around for decades, quite frankly. But

(04:07):
AI agents are very very interesting little buggers because they
can reconcile, they can make different decisions based on dynamic
and fluid situations. Now, what I've heard, I'd be curious
to know what you've heard, is that by and large,
AI agents are designed to do one thing very well,
whether that's grab data, analyze data, delivered data, process data,

(04:32):
run some algorithm, figure something out. But some people are
suggesting AI agents could be more versatile. And the most
compelling story I've heard out of companies like Variant. For example,
we were talking about a buddy, Tom Augenhaler. He works
with Variant. Their CEO told me that they like to
have these agents that are very purpose built and specific.

(04:53):
But there are other companies now, and one of them
I think of is Mistral, which is one of the
new large language models. They have this mixture of experts
process where they have an orchestrator that kind of sits
on top of the agents. So just like a manager
with a bunch of direct reports. That's how these multi
layered AI agent architectures work, and that is pretty cool stuff.

(05:14):
So the little orchestrator sits there and goes, okay, Bob,
you do this, Sue, you now do that, Fred, you
do this, And that's their job is to orchestrate, which
is basically what Kubernetes does from Google for a system's
use case, which is fascinating stuff. I mean, kubernetesays absolutely amazing.
But I think this orchestration layer is going to be

(05:35):
really important for AI agents. What do you think?

Speaker 5 (05:38):
Absolutely? And we often think about AI as a single entity,
but here you're talking about AI as a team, a
team of skilled agents AI agents. And so let's take
for instance, accounts, receivable, accounts bayable. Every year in a

(05:59):
large company, there are thousands upon thousands of conflicts that exists,
like we invoiced you for this ten thousand dollars and
you only paid US nine thousand, nine hundred and fifty dollars,
and there's a difference in this. Well, you know, historically

(06:20):
a person had to get involved in all this. Well,
imagine agent to agent, account payable to account receivable, discuss
it and say, well we actually when we received the shipment,
there was one broken piece which was worth fifty dollars.
So these agents go back into their ERPs, their respective systems,

(06:46):
and say, oh, the shipping manifest at the shipping dock
shows one broken thing which was worth fifty dollars. That's
why we're paying you fifty dollars less. And it goes oh, yeah, okay,
I'll take I'll accept that, and boom that ARAP dispute
is closed with no human getting involved, and two humans

(07:09):
on either side of this transaction to get involved will
probably cost three hundred dollars of person time. So we've
actually solved a fifty dollars dispute with two agents AI
agents at basically next to nothing in cost. So how

(07:31):
can we take eighty percent of the disputes in ARP
and solve them?

Speaker 4 (07:37):
Yeah? That is an excellent use case for lots of
different reasons. One, it's a task that these AI agents
can do very well. It's a fairly simple thing. It's
fairly easy to understand. There's a discrepancy between this number
and that number. Where did it come from? And of
course these agents and the new IT world in general
operates on what are called declare itative programs, or declarative

(08:02):
functionality where instead of the old way of doing computing
with imperative programming, where you tell the computer line by
line what to do, with declarative you set you declare
an objective that you want accomplished, and you let the
system figure it out on its own. It's really fascinating stuff.
Kubernetes is declarative. A lot of these new models are declarative,

(08:23):
and so it's a good way to just get what
you want done without having to micromanage the computer. That's
really what it falls down to is it's not micromanaging
the computer. So this is great stuff because the agency
go back and forth that oh, okay, no, we got it,
and then they'll they'll give some report on that, and
then a human will go once a day or once
an hour and look at all the different things that

(08:44):
have been resolved and just make sure that they're correct,
and then throw in some curation, throw in some commentary.
And of course they're not always going to be right,
but people aren't always right either. So all we really
want for these things to do is get to where
they're good enough or better at the people at doing
things and much more efficient and Besides, what a dreadful

(09:05):
job for a human to do. I mean, who wants
to do that all day? Nobody does.

Speaker 5 (09:12):
I remember that my accountants, for instance, feel they need
to balance to the penny right, And you know you're
paying your accountant to three hundred bucks an hour to
find three pennies that's not balanced, and it drive me crazy.
So how can we just say, Okay, well we're pretty close.

(09:35):
I guess the principle is underneath it. Well, maybe there's
two transactions that are skewed, that are three cents offen
are really highlighting a problem. But I think what we're
to your point, we're going to end up automating things
that are dull, dirty and dangerous. So anything that's a

(09:55):
really repetitive task will get automated by agentic AI. And
people worry about job loss, But there are two million
job openings right now in the US healthcare system, two
million job openings, and it's estimated there's about three hundred
billion dollars of waste and inefficiency in the US healthcare system.

(10:18):
So agentic AI could really help improve the efficiency of
the healthcare system and address this two million gap of
people that we can't find to fill us healthcare jobs.

Speaker 4 (10:35):
Yeah, and we're going to go through a very tumultuous
and disruptive period of time. But for those who have
their sea legs under them, it should be a bit
of a fun and challenging time. I think the key
piece of advice I give to anyone in the working
world who wants to keep going out there and doing
cool things. Start using these technologies, use GENAI. Understand it's

(10:57):
not perfect, but learn the ins and outs of these systems.
And Jenny, of course, is just one facet of AI,
and it's very interesting. It does cool stuff. There are
many other facets of AI. Traditional or as I call it,
old fashioned AI is still out there doing cool things
where you build models to do predictions. As a company

(11:17):
I interviewed not recently called Safebooks AI, which is doing
really interesting stuff in the accounting space you're talking about,
and they can help companies avoid major problems like at
Macy's where this big chunk of money was not reported
as an expense, causing their accountants lots of trouble and
causing a lot of trouble across the company. That kind

(11:38):
of thing will be found by AI, and I think
we should also spin into the whole world of manufacturing
and how automation and even AI is coming into play there.
And you brought up the stat that I saw Alvin
fuh mentioned the other day, which is that China is
now dominating the automotive industry, not just the EV space,
which they are. They're number one electric via goals. They

(12:00):
are crushing it in terms of being able to export cars.
They're number one in the world. The US stinks compared
to them these days. It's almost unbelievable, but you have
to look at the charts to see right.

Speaker 5 (12:14):
So for forty four years, Japan was the number one
exporter of cars in the world, and then China began
focusing on production capacity in evs, and in twenty twenty
three it became the largest exporter of cars globally, just
blowing past everyone else Japan, Mexico, Germany, South Korea, and

(12:37):
the US. And part of it is the focus on
electric vehicles called evs. Seventy six percent of all EV's
in the world are produced in China. It has just
doubled down on this. And so while Europe and the
US I don't know about ev is, China is all

(13:02):
in on it and This is in part leading to
their domination globally. And what we're seeing is a discussion
of tariffs in response. Tariffs are one of the items
that Trump has been talking about pretty prevalently, putting one
hundred percent tariffs on imported Chinese cars. And so wherever

(13:28):
there's a domestic auto industry, you're seeing governments talk about tariffs.
But for instance, in Australia, there's no domestic auto industries,
so what is the benefit for them? They get inexpensive
cars like cars, right, So there's no protectionism in any
country that doesn't have its own auto industry. So China

(13:51):
is going to end up dominating global trade with every
country that doesn't have a domestic auto industry. Right until finally,
and then you're seeing news like Onto announcing it's going
to merge with Nissan and Mitsubishi.

Speaker 1 (14:13):
So I saw that that's.

Speaker 5 (14:15):
Three Japanese car companies who are being crushed by the
growth of Chinese evs. There have been japan Japanese car
company is very slow to shift to EV's, so they're
getting crushed and their solution.

Speaker 4 (14:34):
To merge, right, and these days, speaking of technology and
data and analytics and ERPs and things, of this nature.
It is a lot easier thanks to AI and machine
learning and automation to pull off mergers and acquisitions, and
that therefore, I predict we will see more of these
coming down the pike because it's much easier now to

(14:55):
get an analysis, a real brass tax look at what
our assets are are, how do they align with the
assets of this company or that company, and you can
get a real clear view because hitherto you were just
kind of guessing. I mean you're guessing on the personnel side,
on the manufacturing side, and all kinds of things, and
hoping it's going to work out, and it could take

(15:17):
years to really make that acquisition or that merger.

Speaker 2 (15:21):
Jeil.

Speaker 4 (15:22):
That's not going to be the case in the future,
as I see many organizations are going to do what
you just commented on. They're going to merge to stay alive.
Like I said, we're going to go through a very
tumultuous period here, But for the agile I think it's
going to be a win win. What do you think
I'd agree?

Speaker 5 (15:37):
I think I made a prediction that we're going to
see half of the traditional car companies, legacy automakers of
gas cars disappear over the next ten years, they're going
to either go bankrupt, they're going to merge. As in
the case of Honda, Nissan and Mitsubishi. There you have

(15:59):
three car companies combining into one. You've lost two car companies.
So we're going to see a shrinking of the legacy
auto industry. And this next stat is shocking to me, Eric,
but Tesla right now today is worth more than the
rest of the auto industry added together.

Speaker 4 (16:21):
I mean, it's amazing.

Speaker 5 (16:22):
That blows me away. If you don't think electrification is
going to change the ten trillion a year transportation and
logistics market. That stats for you half the value of
the industry.

Speaker 4 (16:36):
Yeah, that's amazing. And it goes back to innovation and
to doing things in new ways.

Speaker 5 (16:42):
You know.

Speaker 4 (16:42):
I attended the Reuters Next conference. I guess it was
two novembers ago. I spoke last November and two Novembers
of I tended and a girl from Routers was interviewing
the Alex P. Morgan I think his name is. He's
the CEO of JP Morgan or one of these companies.
I think that was Gorman was his name. Very very
smart guy, and she's hounding him, basically trying to get

(17:05):
him to admit that they made a bad bet on
Twitter because they threw some money in to help him
buy Twitter, and he just he shook his head for
a couple of seconds and then he said, we're not stupid.
I couldn't believe it. I was like, Wow, what an answer.
He goes, anyone who doubts Elon Musk should go visit
a Tesla factory and then you'll understand because these folks

(17:27):
thought through the entire end to end process and they
re envisioned everything and that's why they're able to achieve
these amazing numbers. And that's what innovation takes. It takes
unlearning your biases and then relearning something new, and that
I think is going to be a hallmark of success
in twenty twenty five. Final thoughts from you, Well, I love.

Speaker 5 (17:47):
That that Tesla is vertically integrated. In other words, it
makes the engines, it makes the chassis, it makes the batteries,
it makes the wheels, it makes the seats, and there
forward to your point, it can control the production process
from end to end and drive efficiencies out of it.
Legacy Auto, No, they have thousands of suppliers and so

(18:12):
to actually change is very hard since there isn't that
vertical integration. So I agree with you absolutely. We're going
to see big changes in the auto industry, in basically
every industry with AI and automation.

Speaker 4 (18:27):
Yeah, and retail, we'll see a lot of cool retail stuff. Healthcare,
of course, financial services. The pinch is everywhere. Folks will
send me Neil if you want to be on this
show Inside Analysis dot com. That comes right to me.
We'll be right back. You're listening to Inside Analysis.

Speaker 3 (18:49):
Welcome back to Inside Analysis. Here's your host, Eric Tabanaugh.

Speaker 4 (18:56):
All right, folks, back here on Inside Analysis, and I'm
so excited today is part of our cees preview to
get a newbie, a guy who is not new to media,
he's not new to technology. He's not new to sports
and fitness or interviews or tech or understanding what's going
on in the real world out there. None other than
John Meyer of the podcast bearing his name, and we're

(19:19):
pretty excited. He's a fellow Pennsylvanian and John here in
Pittsburgh they call folks yinzers or like Yin's, Hey, Yin's
the guys, And I was like, yins what on earth
is yeans. What are they talking about. I have a
theory on that which I throw at Pennsylvanians and they
like it because if you're from Pennsylvania, you're a pennsylvani yin, right,
So multiple Pennsylvanians yins. It's at the end of the word.

(19:42):
That's my theory. I don't know if it's true or not,
but hey, you're on the other side of the state.
I don't hold that against you. Eagles fan. Tough team Stullers.
You know we're usually a tough team at a bad
few games lately. But tell me a bit about your
passion for sports and fitness and where that dovetails with technology,
like where and all that kind of fun stuff.

Speaker 6 (20:02):
Eric, thank you for inviting me on to the show.
As you mentioned. John Meyer from Meyer Media also to
John Meyer Podcast. I've got a theory now that you
mentioned for your yins. It could be going along with
yingling beer and brewery, just saying I'm sure you're familiar
with it.

Speaker 4 (20:18):
Someone else said that too, so yins ying's yin's yangs ye.
I could see after a few yings agains, you know,
it starts to slur a little bit.

Speaker 6 (20:26):
That's Okay, after a few yinglings, it will slur just
a little bit. So, Eric, my huge passion is around
media content and creating. As you mentioned, I am a
nube to ces, the first one we've been accepted as
media joining at totally overwhelming right now. I mean, I've
been to Vegas so many times, but coming to this event,
I just realized this is the like the Super Bowl

(20:49):
event of technology for consumers. You mentioned fitness and everything. Obviously,
huge Eagles fan, die hard, don't hold it against you.
On the other side of state, I'm actually hoping for
maybe a PA would be really cool to watch.

Speaker 4 (21:01):
Wouldn't that be great?

Speaker 6 (21:02):
That would be the first time in history. And yeah,
obviously I'm rooting for that, you know, and I'll root
for the Eagles to win, but you know, hey, we'll
have a good time and they're going down Broad Street.
We'll definitely see some of the Steelers fans.

Speaker 7 (21:15):
Uh.

Speaker 6 (21:15):
Talking about fitness, been in fitness all my life, started
out at a very young age, and I just it's
a natural thing to do. Some of the technology that's
out there to track it. I saw some of the
things that are going to be happening. I sees the wearables,
not only the headsets, but the gear, the recovery stuff,
the massade, everything around them. Just looking at how to

(21:37):
improve my game but also recover from injuries or from
workouts much faster.

Speaker 4 (21:42):
Yeah, that's good stuff. And you know, I talk with
someone else just today about the wearables. And here's what
excites me about that stuff is the data that you
can capture for individual health, for population health, to understand
how is the workout affecting you, what is good for you,
to eat, what's not good for you. I mean, I
think hitherto most healthcare has been boiled down to very

(22:06):
generic basics. I mean they take your vitals, your heart rate,
your temperature, stuff like that. Okay, that's useful. But when
you can start absorbing massive amounts of data about how
your body acts, when you sleep, when you run, when
you walk, when you're sitting, all these different things, I
think we're at the beginning of a fascinating age in

(22:28):
which we can get a much better understanding of ourselves,
how we sleep, and how to improve our lives every day,
how to improve our health. What do they say, if
you don't have your health, you don't have anything, right,
So I think that in sports, of course you have
to be very fit, and so in that world, it's
a whole other level of intensity and practice and work,

(22:50):
and you want to know what's working with it's not working.
I think we're at the beginning of a golden age
because of that.

Speaker 6 (22:55):
What do you think, Eric, you actually just touched on
a bunch of things, because that actually crosses over into
healthcare if you think about it. You talked about, you know,
going into a doctor and they just take care of
simple vitals your heart rate to your blood pressure. But
how would you love to walk in there with all
the data and say, hey, listen, here's what I got
from my fitness here's what I got from allmine, and they're.

Speaker 4 (23:17):
Like, wow, I wish we had this.

Speaker 6 (23:20):
Now you can present him problems are easily solved. You
can avoid injury, you can avoid long term illness. There's
so many things that you can understand as a person
to do much better. So you actually avoid the doctor.

Speaker 4 (23:32):
Right, that's right. An apple a day keeps the doctor away. Baby.
I'm all for that. And you know I remember, I'm
origually from Chicago. Saw I was a huge Michael Jordan
fan and the guy who's just a machine I mean,
honest to goodness, he's just easily taught players of all time.
And he would stretch before every game. I think it
was like an hour or so. He would take the

(23:53):
time to stretch. And because of that and maybe because
of his physique, he was rarely injured. You didn't see
that guy get injured very often at all because he
took care of himself. And see, I think again, with wearables,
you're going to have you need software too to analyze
the data understand what it all means. Because telemetry data,
when you look at it, the raw data, it's like
ones and zeros and very incomprehensible stuff. But in a

(24:16):
certain application you can kind of start to understand how
that's interesting and compare yourself to other people, the people
your size, your weight, your height, whatever. The more we
can understand how our body is responding to the world
and to what we eat, the foods we eat, how
much we drink, what we drink, I think it's going
to really change and give a lot more awareness and

(24:38):
power to individual people to live better lives.

Speaker 6 (24:41):
What do you think, Eric, the wearables? I saw one
on Therefore, you're wearing a pair of pants, right, and
it had all the RFID and all the telemetry, all
the data being pulled from. It's almost like the stuff,
like the copper stuff you wear, but here you put
it on and you can actually start to read your
body and the metrics as are happening on your body,

(25:01):
your muscles, where they're tightening, where they're not working, where
you're performing, where you're not. You're at the gym and
you do something, you're actually doing an exercise, and if
you do it incorrectly, you're going to get hurt at
some point, not all the time, right away. This can
tell you how well you're doing immediately while you're doing it.
You can read all this data efficiently right on your

(25:23):
phone while you're at the gym, be like, oh man,
I need to stop running now. Normally you like run
and you do thirty minutes of cardio while this is
already reading immediately what's happening to you, and be like, hey, listen,
you need to you know, shut it down and go
into a soft mode so that you don't injure yourself.

Speaker 4 (25:39):
Right, No, that's right. Feedback I mean everyone loves a
feedback loop, whether that's from your colleagues or friends or
your boss. Say Hey, good job, or Okay, maybe better
next time. Whatever it is, it helps to have feedback.
And now we have digital feedback about what's really happening
in our lives. You know, I came up with this
concept a few years ago about big data, and I

(26:01):
talk about something I call real world data at scale,
and that's where we are these days. You can capture
the data, you can analyze the data, process the data.
I think population helps. You know, in San Antonio they
have one of the highest heart attack rates, Well, why
is that? It's probably because of all the food and
tied fide fat for example. You don't really know that,

(26:21):
but I think, like I say, until now, we've kind
of been guessing for a lot of stuff, and now
we're going to be able to test and validate and
understand from the data itself how this affects us, How
this makes me feel better? What doesn't look when I'm
feeling down? Why is that We're going to have a
lot more information? And to me, that's just supercharging this life.

Speaker 5 (26:41):
Eric.

Speaker 6 (26:41):
When you talk about feedback, think about the feedback that
you receive from colleagues, right, constructive criticism. It's very tough
for a lot of people to take and to receive.
But if you have a device telling you one hundred
percent honest, this is what's going on, and this is
what's happening, you're more at to believe it and just
to it rather than somebody telling you you might take

(27:02):
a while to you adjust or until you experience the injury.
I'm like, I should have listened to them. Here you
listen immediately.

Speaker 4 (27:10):
That's funny. Well, another one of my fun lines is
machines don't lie, right. I mean, machines are just saying
what's on the information that they're giving. They're just giving
it back to you. And even simple things like your
steps or your screen time or whatever it is. It's like,
if you take a minute to look at that, you'll
realize how how your behavior is day to day, and

(27:30):
then you can start to improve things. And people want
to improve. Like let's say you want to lose some weight.
While you can weigh yourself every day and that helps,
but it's just once a day, right, or maybe twice
a day or something. But to have this constant feed
giving you information and give you insights and giving you
a nudge perhaps, I mean you're starting to see some
of that in the tech world too, Like, Hey, starting
to get laid, maybe you should go to BED. I mean, personally,

(27:52):
I don't like the school marm apps on my phone,
but I do understand it's good to get feedback and
to understand what's happening.

Speaker 6 (27:59):
Right Yep, I'm definitely looking forward to not only the sports,
the fitness, the wearables, just the information the things that
I can do to not improve my personal fitness in life.
But see what's out there.

Speaker 4 (28:11):
M m well in ces, I mean it's I've only
been to one last year, and it's just massive. I
mean it's so big that they don't just fill up
the exhibit halls, they fill up the Venetian Lots of
companies will rent hotel rooms, four demos and things of
that nature. So it's just like five convention centers strung together.

(28:31):
You're talking like one hundred and fifty thousand people gathering.
And there's a lot to learn. I mean, I try
to keep an open mind every day and learn about
new technologies. And we are in an era where because
of AI, to a certain extent, we're able to do
things that we were not able to do before. We're
able to optimize things right. We can crunch the numbers
and understand you know, again, like with media, what what

(28:53):
if people want to watch? What do they not want
to watch? Now, I will say I have some pet
peeves with software as a service and some of the
data we get from these engines. In fact, we're gonna
do a show next year called Lies, Damn Lies and
SaaS statistics as it's all about, like, all right, is
this real? What are you talking about? You throw some
money at YouTube or LinkedIn or Google, like, oh well,

(29:14):
look at all these impressions you got, And I like,
who are these people? Are you sure you have new subscribers?

Speaker 8 (29:20):
Do I really?

Speaker 5 (29:21):
Yeah?

Speaker 6 (29:21):
Yeah? Are they real? Let's just put it that way,
or they're a new one. But then they just they're
not there anymore. It's a dummy account.

Speaker 4 (29:28):
You have to wonder. I mean, I'll just give you
a stat The other day I saw because I threw
some money at some of these YouTube videos and there
were two hundred and sixty one views, and they look
at the demographics and every last one of them was
a male over the age of sixty five. Now, when
you have like eleven strata of years, like you know,
eleven to fifteen, I can't remember what they were, and

(29:49):
then the last one is sixty five plus and I
got two hundred and sixty one viewers. You're gonna tell
me every last one of these viewers when I go
viral and old folks home somewhere, what the hell's go
on here? I don't think that's real. So I do
think there is a you know, a bit of a
hedge on the excitement around the data because we need transparency.
That's that's one of my mantras is, you know, the

(30:10):
more transparency we get, the better, because if we can
all see what's really happening, then we can all improve it.
What do you think about that?

Speaker 6 (30:16):
I agree, And you got two hundred and sixty one views,
but you probably got two hundred and eleven likes, and
they're like, okay, is that really possible that these people
all likes my video? Because I'll tell you what, when
I go and watch a video, I try to do that,
but I don't do that all the time.

Speaker 4 (30:33):
So right, Yeah, When I saw one the other day
where it's it gave a keynote and at first it
was like twenty thirty four and then over like two
weeks it was ten thousand, ten thousand views and zero
likes and no comment. Obviously it wasn't zero. There was
zero comments and just like twelve likes or something. I'm like, hmm,
to ten thousand people really watch this and no one

(30:53):
commented it was pretty forward looking stuff. I basically said
that before too long, AI is going to take over
the judicial system, at least for civil cases. I think
you're going to be able to just upload your case
into a folder, the defense uploads their case into the folder,
You do an interview on camera to an AI engine
a chatbot, and then it goes all right, thing guilty,

(31:15):
paying five thousand dollars next, and like no one commented
on that, like.

Speaker 8 (31:20):
Wow, wow.

Speaker 6 (31:21):
I can see a lot of comments on that. It
will definitely clear a backlog, but I think it will
also create some friction.

Speaker 4 (31:28):
My theory is that people will have a harder time
lying to a cold computer camera than to a person.
That's my theory. I think it's going to be hard.
I don't know why I think that, but something tells
me it's like oh, because the other side of AI
is that these models are getting so good they can
tell like your behavior, like is the acting shifty? I mean,
there are little tells you can learn just from experience.

(31:50):
Like you know, when you ask our question, someone looks
down and blinks as they talk, Well, you know, they
probably did something wrong or they're probably not being straight
with you, and these algorithms are going to pick that
stuff up. I mean, that's I guess the last question
I'll throw at you is you as we face this world,
this AI overthrow, as I call it, because it's going
to be everywhere. It's already everywhere. It's going to be
in every major cloud based application that you use. There's

(32:12):
going to be some aspect, whether under the covers or
right there on the surface. What are your thoughts about
this changing dynamic and how we as humans can remain
in charge.

Speaker 6 (32:23):
I think one of the things about remaining in charge
for AI is validating it and always having a governance
around it. Not AI governing AI, because that's like the
government governing the government. It just doesn't work anything. Because
I think for us with AI, let's test a little
bit on the audio and video stuff that are happening

(32:45):
in that CS and AI is a huge part of that. Now,
a lot of the videos that are created today, some
of the stuff is spoofed from video from AI. Generating
on it. How do you tell the difference. I think
there needs to be a governance around it in order
a tag or something within the video, even if it's remade, recaptured,
you know, whatever screenshot. There needs to be a way

(33:08):
to tag that that is AI generated in order for
us to understand what deep fake is and what is
happening out there. But I also believe there's so many
positives for AI and around video and audio because it
has helped us in our business nowadays be more efficient
not only creating the video, but fine tuning, editing and

(33:28):
cleaning up some of the stuff. So, circling back to
your question, I just think there needs to be a
way that we got to put something in place to
monitor what we're creating from AI and to validate it,
whether it is using a third party AI, to validate
that that is happening because not a human. It's suffer
a human to understand that that's AI generated in some cases, right.

Speaker 4 (33:53):
I think you're right, and I'm sure some smart people
are working on this right now. My theory is that
you can do a number of different things. One, you
can use the metadata that is baked into cameras, for example,
when you take a picture with all these new iPhones
and Samsungs, there's metadata layer that captures where you were
at the time, what time you took this thing. All

(34:14):
this information is captured in the video, so to be
able to capture that and say, ah, this is a
clean video. This has not been edited, this has not
been doctored. I think that's the key in probably QR
codes too, like a watermark of some kind of QR code.
But I think you're right, we do need to have
some governance around this because otherwise evidence, even in courts,
is going to be out the window. But folks, look
this gentleman up online, John Meyer. That's m ye er

(34:36):
the John Meyer Podcast. Look forward to seeing you at CES.
We'll be right back. You're listening to Inside Analysis.

Speaker 3 (34:40):
Respect now, welcome back to Inside Analysis. Here's your host,
Eric Tavanavo.

Speaker 4 (34:54):
All right, folks, welcome back to Inside Analysis. In our
CEES preview for twenty twenty five, I've had, folks. I'm
super excited to have a fellow Yinzer, a fellow Pennsylvanian
on the call here today, Doctor Frank Vigiano. What's new, doc,
that's his brand, that's what he talks about He has
been a judge at CEES for a very long time now.
It has been focused on the healthcare industry for years

(35:16):
and years, and as a regular TV and radio personality.
So I got to ask you, Frank, what's new? Doc?

Speaker 8 (35:23):
So much? You know with CS I mean I've been
going for it'll be my believe it or not, my
fifty seventh year attending cs So they started in New
York City. I'll send you a clip. What's interesting is
that CBS in Las Vegas did a special when I
arrived there seven years ago. I had my badge said

(35:44):
fifty years and had a special ribbon, and I saw
this is great. So we started, you know, networking with
a bunch of different people talking about badges, and I
learned that I was only one of two people that
have attended every cs SIN since the origination in New
York City. Yeah, yeah, pretty crazy.

Speaker 4 (36:03):
Well, and as you know here in Pennsylvania, the number
fifty seven has a certain meaning, right, heinds fifty seven.
So it's all coming full circle. Now, what do you
see what excites you about CEES twenty twenty five.

Speaker 8 (36:16):
Well, there's so many new technologies. I think it's branched
out into We talked a little earlier about healthcare, and
that's a real big important category. People are finding, they're
wearing rings, they're wearing watches, they're wearing they're wearables to
give them insight into their body and what's happening. And
there's more and more apps being created. So that's a

(36:38):
big growth area for CES. And you still the standards,
you know, you know, television appliances, I mean, it's all
still there, but these other new categories. For example, in
the automotive section, a lot of these manufacturers are exhibiting
now at CES where they, you know, had never done

(36:58):
so before, and the reason being is that they had Detroit.
So when the pandemic came, everything stopped and nobody went
to the Detroit show because they canceled it. They had to,
they had no choice. So because of that and kind
of the combination of CEES growing and inviting more automobile

(37:19):
manufacturers to exhibit there, they had a whole area in
the North Hole where the majority of it was all automobiles,
different things to light, radar, sensors, all different technology, and
the vehicles themselves.

Speaker 4 (37:34):
You know, you know what really excites me because I'm
a data guy. I focus on data, artificial intelligence, big data, leveraging,
data telemetry. We have all this data these days, and
we now have the compute capacity and the algorithms to
analyze data at scale and really understand what's going on.
So when I think about population health ory, even individual healthcare, yeah,

(37:57):
a few years ago we had a few things. They
take your vitals, they can do blood draws, they can
look at you through different lenses. But still for those
who have paid attention, it's a relatively opaque window. I
mean it's hard. I mean it's translucent a little bit,
but you really have to know what you're doing to
figure out what these scores mean on blood tests and

(38:17):
things of this nature. But now, if you have one
of these wearables and it's keeping track of your pulse,
of your blood pressure, of your steps, of just everything
about you, what you're doing, I have to believe that
in the near future, if not already, we're going to
have tremendously improved capabilities to understand what is my health,

(38:38):
what are my problems, what are the Because once you
understand leading indicators, you can start watching for things like diabetes,
for example, or respiratory problems or whatever. And I think
we're going to enter in age and as long as
we can hack through hippo regulations and security and compliance
and all the concerns about those things, I think we're

(38:59):
going to enter an appbsolutely golden era of personal health
care and population health.

Speaker 8 (39:03):
What do you think, Well, I agree with you totally, absolutely,
and it's meaning welcome to I think initially, for example,
when light arc came out and some of the technologies
for automobiles, the biggest concern from consumers was, oh, it's
recording me while I'm driving. This is recorded, and many
things do not record. The only thing they do is

(39:25):
they process the data. For example, if I'm driving and
I'm sleepy and i start to drowse a little bit,
senses that I'm not awake from, and I'm not driving
the vehicle or at least be paying attention to the
vehicle as it's moving. So therefore that's going to create
all kinds of issues. It's going to slow the car down.

(39:46):
They could even bring it to a stop until I,
you know, wake up and say, oh, no, I'm here,
I've got the steering in my hand. That type of thing.
So I think, what's important is that the fear that
people have of their private see and honestly, Eric, there
is no more privacy.

Speaker 4 (40:04):
Yeah. Well, I hosted a stage at the Data Universe
conference in New York back in April, and they have
me host the privacy stage, and the first thing I
said is privacy is dead, Like forget about it. I
mean not that we shouldn't aspire towards respecting privacy. I
think that's still a very worthwhile goal. Yes, big companies

(40:25):
want to protect your sensitive data. But to think that
your data is not everywhere is just a naive perspective,
it seems to me, right.

Speaker 8 (40:32):
Oh, Relliant, I mean, if you have a cell phone, really,
are you kidding me? They know where you are every
minute of every second in regards to where you go.

Speaker 4 (40:40):
Right, that's right, And sharing data is valuable. I mean,
especially in the healthcare space again with all these devices.
Now you have to normalize the data. You have to
attend to lapses in data. That's one of the issues
with IoT, right, is that you do have lapses of
telemetry to watch out for that and model for that.

(41:02):
But nonetheless, I mean, I think at some significant scale,
and I'm sure universities are working on this, and major
manufacturers are looking into this. There is just an absolute
treasure trove of information that we can now finally access
and analyze to figure out absolutely what are the behavioral
patterns that lead to better health? Right.

Speaker 8 (41:23):
Well, a good example too would be a device, let's
say that would send a message to a physician and
they're monitoring in a certain let's say, a certain part
of the body for a certain reason, and here's an
alert that comes over and so I'm my goodness, this
is like, we got to take care of this immediately.
When it saves someone's life and that information is shared
with others, that's huge. So people don't worry any more

(41:46):
about privacy because guess what, it's superseded what's needed to
save a life. I mean, how could you be upset
with that?

Speaker 4 (41:55):
Well, and you know, I'll make an analogy here to
maintenance of machines like trains on automobiles and things of
this nature. We've had predictive analytics in the industries where
they could afford it thirty years ago, even prossibly forty
years ago, like in aeronautics for example, with airplanes, and
what they've learned is that if you capture all the data,
the censor data, you could tell hey, if this part breaks,

(42:18):
that part's going to break shortly thereafter. So you sense
and wait for this part to reach a certain threshold.
And I was fascinated to learn that sound is a
big part of that whole game, because when they start squeaking,
they make little sounds like a timing delt making a
sound like, hm, we got a problem here, you have
to address it. Well, if you think about how that
changes the attitude of the person monitoring this information. Beforehand,

(42:42):
the guy on the train would just have to go
check every door, look at every wheel, and you're never
ever going to find it, not never, but almost never
going to find anything. But if you're acting on data
from the system that's telling you a problem is coming,
then you're attentive and you're focused and you know where
to focus your attention. So to me, that is a
massive sea change in operational efficiency and engagement with the user,

(43:07):
with the human right. And as the old saying goes,
what gets measured gets managed. So I think it really
changes the game for how people can pay it, and
they don't want to pay too much attention, don't want
to get all worked up about it, but still to
know that you have this problem and have some way
of measuring it. That's going to be huge for improving
healthcare overall. Right, no question, absolutely, Yeah, that's good stuff. Well,

(43:32):
so what are you excited to see at the cees A.

Speaker 8 (43:34):
You're going to be a couple of things that are interesting. Now,
LG has come up with some great technology. I mean
they have for years, but they just launched about a
week ago. They teased it at CEES twenty twenty four,
but now they've launched it and it's the first see
through old LED television. Oh wow, you see through it now?

(43:55):
People say why or what is So the idea is
that many I think you know that from interior design perspective.
Many people say, I don't want that TV in my bedroom.
I don't want it in the living room. I don't
want to see it sitting now, I don't want it
hanging on the wall whatever. And we understand, we get that.
So what LG has done is they've taken an OLA
television and you can see right through it. So you

(44:16):
put it in the picture window of your home, let's say,
in front of you of an ocean view, a mountain view,
it's incredible. And then what happens. There is a black
screen that rolls up when you want to see TV,
and when you do that, it blocks a lighte from
going through and therefore the image is just like it
would be if you were watching a regular television. It's amazing.

Speaker 4 (44:38):
Probably, yeah, it's it's fun to watch all these innovations.
In my goodness, you've seen many of them. You're fifty
seventh CEES.

Speaker 9 (44:47):
Going to.

Speaker 8 (44:50):
When I was on, you know, seven years ago. Of
course this was big because everybody's like CES fifty years.
So they said, doctor Frank, what was the d the
first CES? What was it all about? And I said
color television. It was in New York City. Wow, And
they showed color TV. That was such a breakthrough. I mean,

(45:13):
you know, and I mean I remember all this was
like my father, he's the one that really got me
into electronics and technology. He was a physician, but he
loved tech, loved it. He bought a Hoffman solar radio
from Hoffman Electronics in California. I still have it. It
was AM batteries in the back and I took it.
I said, da, can I take it to the pool?

(45:34):
He said, well, this is not cheap. And you know,
if you take you better be careful. I said, okay,
so mister magician. You know, I get it to the pool.
All my friends are standing around, We're listening to the radio,
and I pulled the battery out. Everybody's like, what you know,
it's still playing and it's not plugged in. That was solar. Yeah,
I was nineteen. Let me think what that would be

(45:57):
about nineteen fifty seven.

Speaker 4 (46:00):
Nineteen fifty seven, Oh my goodness, and solar power you
look at I mean, I just I wrote it on
LinkedIn today about and we'll look for solutions at CES
what just happened in Puerto Rico. Eighty percent of the
power is down now in Puerto Rico. And you know,
we've seen the horrible things happening over in Ukraine where
the Russians target the energy infrastructure, and it just tells

(46:22):
me we got to get off the grid, man. I mean,
the grid is there, it's very powerful, it is serves
society very very well. But nonetheless, I mean, I love
the push for solar, I love the push for alternative
energy forms, and you know, let's let's try to focus
on that and really incentivize people to get off the
grid and just be more more sustainable. I mean, that's

(46:43):
what sustainability is all about, right, I mean, we totally
numbers have to come together and make sense. But nonetheless
CES is the place to find that stuff too, right well.

Speaker 8 (46:52):
Of course, And you know the problem is, you know
what I never understood the iPhone, great phone, love the technologies,
love the software, the people. I see them at airports everywhere,
tethered to a wall to plug it into charge. And
it's like, hey, this makes no sense. I mean, why
can't we just replace a battery? And Kia Sarah, by
the way, is the only company that I'm aware of

(47:13):
currently they have a they are crowded, some models seventy
two hundred, but it is the only phone that I
know that you can replace the battery, so you take
the pack off.

Speaker 4 (47:27):
I remember I remember being very annoyed about that with
the with the iPhone, and you know, you have to
ask yourself yes. And I just had a guy from
Apple on the show moments ago who we were talking about,
Steve Jobs and his commitment to design being a philosophy,
because there's a great quote I read from him where

(47:47):
he said, you know a lot of people view design
as a sort of veneer that you put on at
the end of the of the process of building something.
With us, it's central, it's the beginning, it's everything. Design
is form and function combined. And so I do respect
that and I understand it. But nonetheless, the batteries man
like to be able to get a new battery because
these bones, when they get older, the battery life gets

(48:08):
shorter and shorter and shorter and just gets more annoying,
you know. And so let's let's move in that direction, right.

Speaker 10 (48:15):
Yeah.

Speaker 8 (48:15):
Well, the key is Sarah, which I like about it.
You can, like I say, you can swap the battery.
Here's the best part. Three hundred and fifty dollars. That's
it only only available for Verazon, but when you have
a few young people saw my phone and said wow
because I dropped it, and I said, well, you can
drop this in six feet of water, nothing happens. And

(48:35):
the glass on the front, it's got gorilla glass, so
you can't crack it, you can't scratch it. It's unbelievable.
I mean, it's really yeah, and so and they said
three hundred and fifty dollars. I just paid thirteen fifty
for an iPhone. I said, well, but the market will bear.

Speaker 4 (48:52):
Yeah, that's that's a lot of money. And you know,
the cool thing about cees is that it is a showcase.
And one of the things I learned last year when
I went to my first one. So I don't have
nearly as many in my history.

Speaker 8 (49:02):
As you do.

Speaker 4 (49:03):
But one of the cool things I like. I think
it was LG in fact, who were showing me around
and all their cool little things. And what they do
is they have prototypes that they bring to the conference,
and then they'll have cameras watching who goes by which
object and how long they stay there. So they're using
data about how sticky these technologies are to determine which
ones to push into production, because obviously it's a big

(49:25):
risk pushing some prototype into production. You got to spend
a whole bunch of money, a whole bunch of parts,
hire people, all this stuff. So you want to know
what the winners are and what the losers are or
the ones that probably will win. I thought that was
a brilliant strategy and it just shows a real comprehensive
view of the problem space and the opportunities. Right.

Speaker 8 (49:45):
Well, that's exactly what they did. Last year with they
called ol ed T for transparency, so they headed out.
People were like just blown away. Oh my goodness, this
is incredible technology. So they got feedback and here we
are a year later and now you can buy it.

Speaker 2 (49:59):
Wow.

Speaker 4 (50:00):
I love that. Well, look this gentleman up online, folks,
Doctor Frank Vigiano sounds like a good Italian name who
is from down the road.

Speaker 5 (50:09):
Here.

Speaker 4 (50:09):
I'm up in Gibsonia, Pennsylvania. He's down the road in Indiana, Pennsylvania.
But what's new, doc? That's his whole tagline. He's been
doing this stuff for a long time. We look forward
to seeing you at Cees in Las Vegas. Don't touch
that del folks, will be right back. You're listening to
Inside Analysis.

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eight This message from Trician's staff at Dix Auto Wreckers
in Kingman.

Speaker 10 (57:45):
What does it take to take on Alzheimer's? Awareness that
nearly two thirds of those diagnosed their women, including black women,
dedication to luring your risk by eating healthy and monitoring
blood pressure, and confidence to talk to your healthcare provider
about screening and early detection. You have what it takes
to take on Alzheimer's. Learn about signs and screening at

(58:08):
take on alz dot com. Brought to you by the
California Department of Public Health.

Speaker 1 (58:15):
Located in the heart of San Bernardino, California, the Teamsters
Local nineteen thirty two Training Center is designed to train
workers for high demand, good paying jobs and various industries
throughout the Inland Empire. If you want a pathway to
a high paying job and the respect that comes with
a union contract, visit nineteen thirty two Trainingcenter dot org

(58:38):
to enroll today. That's nineteen thirty two Trainingcenter dot org.

Speaker 7 (58:49):
NBC News Radio. I'm Lisa Carton. President Biden is receiving
a briefing on the deadly California wildfires this afternoon. According
to MSNBC, he may speak about the federal response from
the White House soon. Biden and Vice President Harris have
been monitoring developments Santa Ana. Wins are expected to intensify
today as crews battle the deadly wildfires. At least sixteen

(59:11):
people are dead and more than one hundred thousand residents
are under evacuation orders in the Greater Los Angeles area.
Fire officials are reporting some progress against the two biggest fires,
which have blackened more than forty thousand acres and destroyed
over twelve thousand structures. Governor Gavin Newsom is taking steps
to help speed up the rebuilding process for both homes

(59:31):
and businesses destroyed by the fires. He issued an executive
order today suspending some provisions of the California Quality Act.

Speaker 4 (59:39):
When someone rebuilds that they have their old property tax
assessments and that they're not increased.

Speaker 7 (59:44):
Lisa Carton NBC News Radio.

Speaker 2 (59:48):
NBC News on CACAA Lomolada, sponsored by Teamsters Local nineteen
thirty two, protecting the future of working Families, Teamsters nineteen
thirty two dot org.

Speaker 10 (01:00:00):
Mm hmmmm, Welcome to the Fabulous Lifestyle radio Show.

Speaker 14 (01:00:06):
Tune in for a vibrant mix of fashion, fine