Latest / The DEX Show: A Show for IT Change Makers / OFFICIAL DEX SHOW END OF YEAR SPECIAL W/ GEOFF WRIGHT

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OFFICIAL DEX SHOW END OF YEAR SPECIAL W/ GEOFF WRIGHT · The DEX Show: A Show for IT Change Makers

0:01
Welcome it, change Makers to the Deck Show with Tim Flower and Tom McGraw.
0:07
Let's get into it. Hello, change Makers. It's the end of
0:12
the year and that has come on the Deck Show to only mean one thing,
0:17
which is for return once again of our favorite guests. But numbers don't
0:21
lie. Jeffrey right from Monday's Jeff, it's lovely to see how you're doing
0:27
living the dream. I want to retire, just like the health band for
0:32
the show. Yeah, he's a house band, you know. I think
0:35
that's you know, we sometimes sometimes people are skeptical with us, jeff when
0:38
we say we like having them show, we like having them back. They're
0:41
one of our favorite guests. They say, I bet you say that to
0:44
everybody, And you know, maybe that's the truth from that. We're obviously
0:47
grateful and love all of our guests, but don't you know, we don't
0:51
say that four or five times, you know, I don't know how many
0:54
times, you know. Never mind, I replaced on us all. I
0:57
think Jeffrey Wright's going to replace me. I I hope. So. I
1:00
want you. I want you to retire. I want you, I want
1:02
everybody to just I'll retire before you. I'm gonna try. This is our
1:07
third end of year wrap up together. Jeff, isn't isn't that nice?
1:11
It doesn't. It's not it really feel like Christmas. It doesn't feel like
1:15
the end of the year unless we do this. To me. Now,
1:17
this is part of my own personal, personal end of view ritual. I
1:19
don't know about you guys. We need to go back and see how accurate
1:23
you were in the other two years. It's about the kind of the forecast
1:26
that never will never turn around. We we we we usual just to review
1:30
the preceding year, so we don't take that predictions with Jeff. We find
1:34
out what just happened and what it meant that I saw some of the I
1:40
saw some of the comments from I think it was a year ago or two
1:42
years. They were like Jeff Odamas, Jeffreydomas. They were like, no,
1:46
no, he knew. He knew about the robots, like the Simpsons
1:51
predicting that that's right. He knew about Trump, he knew about Biden,
1:55
he knew about everybody. Indeed, well, let's find out then what next.
2:00
No, we won't. We'll find out what the year just went by
2:02
was like, what it meant, what it was like, for you,
2:05
Jeff, what are thoughts and reflections on it? Are? What Tim's reflections
2:08
on it? It's going to be a great conversation. But let's just say,
2:12
first of all, Jeff, let's just find out, first of all,
2:15
how are you, how's the year being? How would you put it?
2:16
In a nutshell? On a personal professional level? What would you give
2:21
it out of ten? Give us a quick it's a ten. My life
2:25
is My life is great. The people around me are great. I think
2:30
that's more of a I try my best to keep the people that I truly
2:34
appreciate around me and the people that I don't away from me, Like you,
2:38
guys, I don't mind being around you. I appreciate people that you
2:43
know, I appreciate good human beings that I believe genuinely try to produce something
2:51
positive on planet Earth. You know, I'm asked often what do I consider
2:57
a good friend? And I had a great conversation with a good friend of
3:01
mine from the Air Force, and I said, you know, the best
3:04
of friends, right, the best of friends, Your best best friend,
3:07
if you were stranded on an island, right would not eat you. That's
3:13
how that is how it boils down for me. But also that same person
3:17
would help you and you'd help each other make the best of it. And
3:23
I often find that my tour of duty with every company, with the people
3:27
that I know, that's what it is. You're there and you want to
3:29
do that tour of duty to say we're going to do something good together.
3:32
And unfortunately there are some people that don't have that mindset. Yeah, yeah,
3:38
it's true enough, true enough. And what about you, Tim,
3:42
how would you? Nutshell? Twenty twenty three opinting on I Think twenty three
3:46
was I'll use one word, transition twenty three felt like we're kind of out
3:53
of the pandemic and everybody's getting back to real world stuff, right travel,
3:58
meeting in the office, getting out to dinner. I transitioned professionally from a
4:02
really great role at Next Think but it wasn't my sweet spot. And transition
4:05
now into doing this full time, the podcast, the books, the evangelism
4:11
stuff, so great transition. I moved into my house in June, into
4:15
a different different state, so transition there, new granddaughter in January, transition
4:19
there. It was. It was a year of lots of changes for me.
4:24
Sounds awesome, very cool, Yeah, you man, Yeah, for
4:27
sure. For sure, it's quite funny, Jeff. We were so I
4:30
opened my laptop this morning and I get like a teams from Tim and it's
4:33
like, where are you? What's going on today? And I was like,
4:36
what the hell is Tim doing? Like morning or whatever? Teams?
4:43
I mean? Then I realized he's in London. He'd mentioned it in passing,
4:46
as it were, and he's actually and I totally forgot about it.
4:49
We're gonna, We're gonna, but we are both recording from London. We're
4:54
live in London, but in different now we're on the same side of the
4:57
ocean, right, but we're gonna. We're gonna. We're gonna later this
5:00
week in person, maybe do some recording there, but we are. We
5:03
are both in London, a very very kind of wintry and gray London,
5:08
as it should be. I think it was. How nice did you guys
5:10
were in the same time? Though? Now, now, Tim did you
5:13
what did you do? You took a cruise ship from p A What did
5:15
you? I needed the need the exercise, but I used the robot and
5:20
made it over here in about a week. Excellent. That's that's and you
5:25
got the place in PA right here? Is that? Where where you were.
5:28
That's awesome. Yeah, out in the woods. You know, you
5:30
get a busy travel week like this, you get into the city, it's
5:32
you know, you get into lots of chaos and excitement, and then I
5:36
can fly home and listen to the birds and the crickets. Yeah, there's
5:41
something about being in the middle of nowhere. It's nice. Yeah, very
5:45
nice, very nice. Right right, Jeffrey, we we You and I
5:47
last spoke. We did a show Tim couldn't make it about the middle of
5:51
the year. I think we kind of expressly focused on AI, which unsurprisingly
5:57
has been a focus for show in of many industries this year, and very
6:01
legitimately so even both him gets a little upset whenever we mentioned it. It
6:04
feels a little bit of a future. But we can't deny it. It's
6:09
been the AI year, the year of AI. And you know, back
6:13
then, jeff you were, you were kind of getting your hands dirty with
6:15
it. You were, you'd rolled up your sleeves, you you jumped in
6:19
with both feet and and I you know, in terms of from that point
6:25
middle of the year to this point now, what have been the main developments
6:30
in your utilization of it or in your thoughts or reflections upon it as a
6:34
as a space. It's a great question. I mean, December was chat
6:41
GPT. I can't believe it was just a year ago that CHATCHYPT was,
6:44
Like I mean, I remember around the holiday. I remember it was right
6:47
around Christmas because we're all in that tech space. Yeah, so we all
6:53
heard the buzz about chat chept most you know, you know ordinary Joe,
6:58
you know ordinary sam By, you know Samantha whoever that was that they didn't
7:02
they had no idea. It was like, oh here there's like, you
7:05
know, a couple, you know, some kind of robot thing on the
7:08
internet. It wasn't until about you know, probably March or April this past
7:15
year that I had like my mother in law, my father, like you
7:19
know, people that were like, what's this whole? Like you know like
7:23
cyborg, you know, terminator matrix then on the on the internet. That's
7:26
happened in Jeff, Like, aren't you again every it professional knows this,
7:30
Like if you're in it at all, you know everything about it. You
7:32
know how to like configure a printer, and you know about like you know
7:35
terminators, right, you know what the matrix. But people were like,
7:39
oh what is this? And I was like, well, it's a large
7:42
language model, and you know, I'm because I own the chap out here,
7:45
I kind of understand. I was kind of in the mix. I'm
7:46
like, this is kind of cool. It's like a supercharging it. You're
7:48
plugging in you know, data that will you know, predict things to give
7:56
you back. And you know, there was a little bit of an unease.
7:59
I think around the beginning of the summer, right around Moral Day,
8:01
I had a lot of people that were like, oh, yas chat GPT,
8:05
like what color I should paint my room? And it guessed it was
8:07
right. It was green or whatever. It was right, and you're like,
8:11
well, you're probably a high percentile color person that matches up with the
8:16
you know, like I kind of like try to like it doesn't guess it
8:20
uses data to kind of figure it out. But then around the end of
8:24
the summer, there was a lot of you know, my brother's at Microsoft
8:28
and he was like, you know, it's like it's gonna be this could
8:30
be clippy two point zero. You know, you know, everybody's you know,
8:33
change the soul of the workplace. Supercharge this supercharge your excel super It's
8:39
like everyone's supercharging stuff with chat GPT, and I think there was a lot
8:45
of conversations around well, okay, so open AI did chat GPT, Google's
8:50
doing barred. Amazon's a little behind Apples, you know, and and Amazon's
8:54
a little behind Apples a little bit up behind. But I think the race
8:56
is going to be at least from our standpoint for an enterprise was how do
9:01
we find out that everything that we feed into the machine stays in our silo?
9:05
Yep. Now Bard is doing a great job on making every now and
9:15
then the program we're using to record doesn't like a dozen virtual around him.
9:24
I want to start singing. Happened twice. Now we're very confused, but
9:28
we'll just welcome it. I think it's when the AI kind of hive mind
9:33
agrees with you, Jeff, That's what it seems. That are Catherine's behind
9:37
the scenes pressing on a button somewhere the show. Yeah. So, so
9:43
Bard does a good job at or it's it's they're approaching it more pragmatically.
9:50
And we have some we have good relationships with with Amazon here and with Google,
9:56
and so we have good relationships with all of the big companies. But
9:58
the Google folks are really trying their best to make sure that we could say,
10:03
okay, if you're going to feed the machine this, we can give
10:05
you an instance of GCP, which is the Google Cloud Platform, silo ed
10:11
and kind of have your own you know, chat, GPT bard you know,
10:16
Large Language Model prompting silo And I have to tell you, I believe
10:22
that if we can get to that point, that's smart. Right if you
10:26
can say, I'm a company and I want to have your awesomeness around prompting
10:31
and lll ms, but I don't want to make I want to make sure
10:33
that you know, if my head of finance says, you know, how
10:35
do I how do I make things you know better in finance? Right?
10:41
You want to make sure that stays. Yeah. So there's there's another there's
10:46
another company called like Sarah who's partnered with the Microsoft doing some really similar stuff
10:50
where you can actually change out train that large language model based on all your
10:54
internal inside company proprietary data and train it on how you do business and it's
11:00
all your data and it stays siloed, so you can start building not only
11:03
queries like that, but start building applications too. Departments who have apps that
11:09
don't talk to each other, in separate databases. This is a way to
11:13
start leveraging the data in there and start using it. The other thing I
11:16
saw was I think it was an open AI keynote where in a matter of
11:22
about sixty to one hundred and twenty seconds a minute or two, he had
11:26
created a GPT and trained it based on telling it where to go look for
11:33
data. Here's a book I wrote, here's an article I wrote. Use
11:37
this because I want to now create my separate GPT that will allow me to
11:43
will allow entrepreneurs and business startups give them advice on how to run their startup.
11:50
So now it's almost like it's a new app, right the app craze
11:52
of two thousand and seven, when the iPhone came out. You're now going
11:56
to create GPTs with a specific function to provide a serve us to a consumer
12:01
and start to charge for It's I don't. I'm really what I struggle with
12:05
is every day I there's some new concept and I where does it go next?
12:11
It's just it's it's almost like the universe. It's it's never ending.
12:16
The So again, shout out to Harvard Business School. I'm doing the HBS.
12:20
Uh surviving in the Age of AI. Course it actually finishes up next
12:26
week. Uh. The professor and the dean are I mean, they are
12:31
some incredibly smart people. They're invested in some of these like I mean,
12:35
you say they're angel investors in some of these crazy companies. I say crazy,
12:39
But it's just these incredible companies. I talked about how they have the
12:46
CIO and chief Scientific officer from Maderna, and you know, you would think,
12:54
okay, it's a pharmacy, it's a it's a you know, or
12:56
it's a it's a medical company's vaccine company. But the whole foundational idea around
13:03
a you know, building apps, you know, letting it kind of like
13:05
you know, building that concrete foundation and then building on top of it.
13:11
It's that's that's what new companies or that's what companies need to do. Build
13:16
a new concrete foundation, right, Like the layer at the bottom of whatever
13:22
you're going to do needs to be bulletproof. It needs to be concrete.
13:26
It needs to have a problem statement, right, what are we trying to
13:30
do with this company? And the guy at Moderna talked about how, you
13:35
know, the the technology behind like all the new vaccines and therapeutics. So
13:41
they're trying to do like these treatments where you can you know, vaccine is
13:45
addressing like a potential virus. Therapeutics are you know, kind of like hey,
13:50
my hip kind of hurts a little bit, how do we make it
13:52
better? Type of thing. But he talked about how so many different companies
13:56
were trying to make a new model for something, right uh. And he
14:01
uses the example of Nokia, and you know all the old phone companies that
14:05
would have you know, BlackBerry would have seven models of phones. Nokia had
14:11
eight models of phones, and each one of those models of phones required you
14:16
to have the app. The the app developer would have to do seven versions,
14:20
different screen sizes, different buttons, different this, different that. And
14:24
he you know, of course everyone talks about Apple. What did Apple do?
14:28
One phone? That's it? And then they give everybody the open source
14:33
Here you go, this is it. This is your model, and this
14:35
is how you have to work on it. This is how you build on
14:37
top of it. And I think that's what's what's what's going to change is
14:41
we're going to start finding every company mobiles. I think it's like there's like
14:50
handshoners. So every company we've been hearing this for a long time, way
14:58
before chat GPT already this AI stuff. Every company is going to be if
15:03
they're not already a software company or a technology company. And I've been hearing
15:07
this for a long time and they're like, oh, you know, yo,
15:09
you think you make toilets, you think you make shower heads, You're
15:13
going to be a technology company. And a lot of those leaders were like,
15:18
you know, I make plumbing stuff, why would I be an IT
15:20
company? But those companies that embrace and say no, no, no,
15:26
I get it. We need to have a website, we need to have
15:28
an app, We need to have all of these things to make sure we
15:31
have customer engagement. The people that buy are plumbing stuff, they need to
15:37
understand that we're here to support them at every touch point we can. So,
15:41
are you advocating for a toilet paper subscription service? On an I would
15:46
you imagine? I'll tell you what during the pandemic, do you remember how
15:50
hard it was to get to you? Joked him. If you had had
15:54
that idea, right, I still have a stockpile. I don't need the
15:56
app. I still stockpiled in my closset. The idea is, can you
16:00
forecast that if you were a guy right as the pandemic hit and said,
16:03
you know what, if I'm monitoring my toilet, why can't I forecast?
16:07
Right? You know, let's let's bring us back out of the yes.
16:15
But the idea is, how do you how do you change some of those
16:18
thought leaders? Right, and say that are like, you know, the
16:22
the super creative people that are trying to do what they do best, right,
16:26
make a new thing, or bring about a change in a product,
16:30
or you know, we talk like we talk about at least at mondolies.
16:33
We talk about all, you know, all the changing behaviors and diets.
16:38
Right, people like cookies, people like healthy stuff. Right. I read
16:42
that, Uh, the this was from the HBS school, the we go
16:48
V and ozembic, all of these these GLP one antagonist drugs right that are
16:53
helping people lose tremendous amounts of weight. Right, Their weight loss could have
16:59
a one point seven trillion dollar impact on the on the overall GDP. And
17:04
you go, well, how is that even possible? Well, people start
17:10
losing weight, they're not eating as much, their habits changed, all of
17:14
it's it's a butterfly effect into a completely different realm. And the people that
17:18
are on the other end of that, to capture that and to capture that
17:21
behavior, and to capture that it's going to be here again. If if
17:23
we decided to get rid of toilet paper tomorrow, Tim, you'd be on,
17:27
You'd be you'd be nailing it on the on your on your TP app.
17:30
I'd be okay for a while. But it goes to the question of
17:34
just in general. I get kind of to back to and I know we
17:37
want to talk about the retrospective about this year, but I think people are
17:41
grappling with this. So I think you still think it's relevant to talk about
17:42
the transition in this year to to considering the impacts of AI. So you
17:48
get on the bandwagon, you get on the technology craze, you you you
17:52
internalize it and you make it part of your career or you don't. What's
17:56
the implication to a traditional IT work? Right somebody in an end user compute,
18:02
the listeners of this particular program are usually the techies. What does it
18:07
mean for them? Do they need to start getting educated and get on kind
18:11
of what's your thoughts about career progression for an IT guy right now? Is
18:19
it a curse or is it a Is it a benefit. I mean those
18:25
that embrace it and try I mean start now if you don't pay the five
18:30
dollars a month or ten dollars a month for GPT four and the like the
18:34
better versions on open ai if you're not using barred. There's also one con
18:41
there's a institutional or there's a there's an educational version of a chat GPT by
18:48
some famous person that my doctor actually told me about it and I was like,
18:52
oh, really try it, do it? Understand it? You know
18:57
how many people I know that are L one or L two technicians, People
19:00
that are probably you know, maybe in their twenties, you know, just
19:03
starting out, that haven't even tried it. They like, you know,
19:06
I'm like, have you not gone to like, you know, chech Oh,
19:07
Yeah, I heard about it. I have like them something on my
19:10
phone. I'm like, really, have you like try it? What would
19:15
I try it for? I've had to be like, what would I try
19:18
for anything? Try it for anything? Ask it for recipes, right you're
19:23
broke, ask it for uh the you know, top ten blue chip stocks
19:29
that have earned more than ten percent over the past three years. Put a
19:32
dollar in those. There's a whole there's there are people generating an entire business
19:37
plan for their particular niche and help it helps them just bring it to market.
19:41
There are so many things I know. Just like I said, it's
19:44
it's endless. I mean, the SEC is talking about a lot of different
19:47
things around these llms. I mean, that's that's one of the reasons why
19:52
I tell people. I'm like, have you looked I have you asked a
19:53
chechip about finance stuff? Or like, how do you like plan a financers
19:56
three year or five year or whatever? If you have five dollars ten dollars,
20:00
Because that's the that's the joke. I told my son. He's he's
20:04
fourteen. I said, you know, he's like Dad, I'm like,
20:07
you know, I have like a dollar. I'm like, okay, what
20:10
do you like? We give you this much? Twenty dollars? So I
20:11
give you twenty dollars a month. I said, I'm not going to tell
20:14
you. I want you to use barred and again I want to use them
20:18
all. I said, don't just try Bard, try you know, try
20:22
chet GPT. Ask it for what you could do to invest twenty dollars a
20:26
month? Right, I said, I'll open up the form four and I
20:29
said I want you to do this. So already this we did this in
20:33
like I don't know, we did this in July. He's already made like
20:37
thirty plus percent. I mean, as we know, the market's been a
20:40
little nutty, but you know, he's he's made a couple hundred bucks.
20:44
But of course he's like, well, can I cash it out now?
20:45
And I'm like no, I said, because these these three are these are
20:49
the ones that were selected. They had dividends. And he'said, yeah,
20:53
but it's only like ten cents. Okay, Well imagine I said, ask,
21:00
I said, aschat gpt or Bard, how much that would equate to
21:03
when you're fifty five years old if it goes on that route? And he
21:07
was like, Dad, oh my god, it could be like, you
21:08
know, one hundred thousand dollars. And I'm like, yeah, yeah,
21:12
yeah, I wish I started when I was nine, right right, if
21:18
you could? And I think that, you know. So he says,
21:21
well, what's what you know? What problem I'm trying to solve? Dad?
21:22
I'm like, nice, try you canna pull that one on me.
21:25
You can ask me what problem you try? I said, you're broke.
21:27
You're broke, that's the problem. You're trying to solve. I said,
21:30
you're broke. And here's the great part, I said, some people that
21:33
have invested in their teens and like, you'll have a little bit of confidence
21:37
around if you want to try something exciting and new that has you'll reduce that
21:41
risk. Because he's my son's really big into you know, marine biology.
21:47
Is going to like high school for some you know, for biotech, and
21:49
he really loves that stuff. And I said, look, you may not
21:52
be a millionaire in that space, but if you're happy and you love what
21:56
you do, you also want to be able to say, like, you
21:57
know, hey, next Friday, I'd like to have a steak or if
22:02
you're a vegan, I don't know whatever the vegan equivalent is. I gotta
22:04
be like, you know, I want a vegan steak, a vake,
22:08
that's what they call it, a vegan steak. Yeah, they even want
22:12
to My brother is a full blown you know, like fully fully voted for
22:18
vegan and he he Thanksgivings coming up and we have some interesting things at the
22:25
Thanksgiving table, like a tofurkey and some other stuff which is just all types
22:30
of I mean, it's okay, and I understand it. I understand it,
22:34
and I respect it, and it's it's but like, you know,
22:38
my son last Thanksgiving, we got him a rotisserie chicken. He was and
22:41
he was eating it, and my brother's kids were like eyeball and my son
22:45
like, oh my god, it looks so good. I'm like, guys,
22:51
have some more tofurky, you know the crambers. My nephew must have
22:55
ate like four gallons of cranberry sauce. Man. But coming back to it,
23:03
I tell people in the L one and L two space that are coming
23:07
into it, try it. If you haven't tried it, try it.
23:11
If you're not sure what to do with it, and you know it's funny,
23:15
ask it, ask it, ask GP, ask bart. What would
23:18
you be? What can you help me with? And I guarantee I'm a
23:21
level two desktop support technician. How can you help me? Yeah? What
23:23
should I be focusing on? How can I or what should I do in
23:27
my career to make sure that I don't become irrelevant? You know, there's
23:30
just yes, it's so much more than than I mean, Google change the
23:33
world obviously back in the the browser search days, but this is, uh,
23:38
this is a revolutionary. That's what I'm That's what I'm excited and worried
23:44
about. Because when Google Google has again, we all search in Google.
23:49
Let's you know, you know, there's always those couple people that are like,
23:52
you know, the one percenters, you know, I use it's still
23:56
overund Yahoo and I used Duck duck go right, like, Okay, I
24:03
bing it. I love people that are like, I'm a big man,
24:04
I bing it, And I'm like, you don't. But if Google,
24:11
the only reason being comes up on my computer is because I haven't figured out
24:14
how to change the default they do. They got in trouble for that,
24:17
right, They're like constantly trying to ram jam bing into things, you know.
24:22
But when when Google, yeah, when Google search and barred can find
24:29
a way to sanitize what you're doing, and I'm sure they're there, the
24:34
burden of of of truth is on them to prove that they're not. But
24:38
if Google can now take the entire planet search history right, run it through
24:45
the washing machine, sanitize it, and then feed that into the LLLMS,
24:51
man, it's it's just imagine if you could understand what everyone around the world
24:55
was thinking at the same time, and they are getting closer and closer to
24:57
real time. When it first came out, the history went up to like
25:02
you know, three or four five years back, and they're getting closer and
25:06
closer to real time. But that kind of computing horsepower takes a ton of
25:11
money too, so they really got to figure out how to monetize it.
25:12
I think that the GPT apps are are going to really be the place where
25:18
that comes in. Well, let's talk about next thing, and then you're
25:21
going to get a segue ten. That's a good segue cpu power. How
25:25
much carbon dioxide and greenhouse gases are we going to pump into this planet by
25:30
using all of that compute? It's a It's funny. My boss and some
25:36
other folks are in London. They're going to be hanging out there for a
25:38
little while talking about like the you know, the state of the state of
25:41
the Union here, and they are they talked about next thing, and they
25:45
talked about how we're going to use it, and you know what are the
25:48
big you know, Oh, we're using engagement And I actually said I think
25:52
the most. Again, I know, we're a larger company, so we
25:56
have probably that luxury maybe, but I talk about the greenhouse gases. The
26:02
CO two for compute. You know, there is going to be I'm not
26:07
gonna say no one's watching. Nobody's watching this, but the amount of CPU
26:12
power that it takes for these lllms to run is you can't even imagine.
26:19
And all the times like that they're trying to pull and change the way that
26:26
they're utilizing this. There's like the deep reast state. I have a friend
26:30
of mine that works for AWS, and he's like, why don't you use
26:32
our green We already have green packages that like you know, spins up and
26:36
spins down all this other stuff. I believe we're gonna really be revving up,
26:42
uh with how we use CPUs and how how much greenhouse gas really it's
26:49
gonna be up. I believe it's gonna be a point sooner if not later,
26:53
on how sustainable and how mature the model is for companies to go,
27:00
wait a second, we need to figure out you know, I don't know,
27:03
put them in, put them at the bottom of the ocean. Right.
27:07
Cooling these things is insane in video IBM. IBM has their quantum foam
27:15
like servers now and all this other stuff. They're cool, but boy do
27:18
they they require like a nuclear reactor to run these things. So yeah,
27:26
I think the oceans are probably already getting too warm. I don't know if
27:29
if we want to say Jeffrey Wright said to put all our computers at the
27:32
bottom of the ocean, Well, multipolar ice caps we have, we have
27:34
GBT. Why do we need polar ice clubs? If I say put PCs
27:38
at the bottom of the ocean, it's not for the reason you think.
27:41
It's because I want everything problem solved. We fixed it, We fixed it.
27:48
But answer so, you know, this particular show is kind of like
27:53
fight Club. The first rule of fight club is to not talk about fight
27:56
club. But next thing has already has the ability to you know, our
28:00
first our first entry into kind of the social responsibility and the economic impact was
28:06
to calculate the cost of power when machines are turned on, and we can
28:10
we can do that, But the bigger one is calculating that carbon footprint across
28:15
your entire estate. And then I would argue the even bigger one now is
28:19
with ten to fifteen million devices in our cloud, calculate that across all our
28:25
customers and where is end user compute really consuming the most? How to you,
28:30
as an individual customer stack up against other industries in terms of what carbon
28:34
footprint you are either positively or negatively impacting. There's a ton of data that
28:40
can be pulled. Do you guys do that in infinity? Do you calculate
28:42
across You can calculate across all the endpoints? How you can? So tell
28:51
me a little about because I'm in that console pretty often. So Pie,
28:56
it's in my mind right now. It's kind of the Pie and this guy.
29:00
The first thing we're doing is we're doing it on an executable basis,
29:03
so you can look across fifteen million end points and see, you know,
29:07
is this version of the next app I'm going to roll out? Are people
29:10
doing better with it? Or is it crashing less? Is it crashing more?
29:12
Is it consuming more memory? What are my you know, what are
29:15
my risks? And rolling out the sexecutable based on what fifteen million other endpoints
29:19
have already done. So I almost have a virtual lab where I can start
29:23
to assess impact of either what will be or I just rolled out this version
29:27
and I'm having a problem. Are others having a problem as well? So
29:30
it leverages the community to help you manage. So the concept here is and
29:37
our product team may have already thought of it is to look across all those
29:41
endpoints and start to do it on a carbon footprint basis. Yeah, I've
29:45
been asked the question of like, well, Jeff, okay, so we
29:47
have PCs in a place of the world that uses like coal and peat.
29:52
Right, you guys in the UK you use ped a lot, right.
29:55
I think you guys an pete fireflace. But the idea is obviously that's more
30:06
impactful to the environment than some place in the world that uses cold fusion or
30:11
like you know, has a nuclear reactor or whatever it is. So I've
30:15
been asked like, hey, Jeff, can we target places around the world
30:19
that may have a bigger impact? And I've told them as of now,
30:25
I'm like, we can. But the calculation that we see for at least
30:30
the next thing, right, So the calculation if I say, okay,
30:33
you know in this part of the world, how does it calculate the total
30:37
cost of energy, you know, total cost of energy from a from an
30:42
environmental standpoint, right? And I didn't know we could do that. If
30:48
you're saying we can, I've spoke to some some some of your next thing
30:53
folks, and I haven't heard back. I mean I understand. So it
31:04
was building on the concept of that executable assessment across all ten million end points.
31:10
So I'm not going to tell you that we can do that today.
31:12
It's more of a hey, the data is there. You said, what's
31:15
what's kind of next for Next Thing? What could we potentially do with this
31:19
kind of of intelligence down the road? And that's one thing I would think
31:23
we could investigate is how do we how do we do that? Seriously?
31:26
Jeff, Like you know, Next Thing's had a quite innovative twenty twenty three
31:30
loads of new products. I know you're you're always very hands on with innovation,
31:37
whether it's flow or assist or just the continuing development of infinity. Where
31:41
have you found value? Have you found value? Have you found anything dramatic?
31:45
Amplify this year, so Amplify, But I think Amplify was Amplify.
31:53
Yeah, for sure, I met with you. So yeah, that's were
31:59
we were just we we're piloting as we speak, the l one checklist that's
32:02
in service now. It's look, it's it's great to have a little bit
32:07
of a genie in there in the pocket of the l One desk when somebody
32:13
calls in or chats and says, hey, I'm having this issue. I
32:16
mean, the l one checklist was good, but now we have the ability
32:20
to run some remote actions that you know, if the hard drive is like
32:23
some some basic stuff. But again that's you know, you're deflecting. It's
32:29
I have a problem. Call the desk. It's great, great, right,
32:34
as soon as you go up that pyramid it costs more money, pure
32:36
and and you know everyone's so focused on money, right, Oh, we're
32:39
going up the pyramid. It's more money. Oh we're going to do a
32:42
level two, level three, level ten. I again, thank thanks the
32:46
next thing, right, really, I do owe my at least the epiphany
32:51
I had many years ago. The problem is not the cost, although it
32:57
is ultimately, it's the cost of your employee being miserable. And I think
33:01
that was you want to talk about. You want to talk about what things
33:05
happened during COVID, And now so many younger folks, you know, in
33:12
their you know, teens, twenties, maybe even thirties, I think there
33:15
was a rebaseline for many of what's really important and what it means to work
33:22
for a company that truly respects and appreciate what you do. We're a large
33:27
company, so it's hard to get to everyone. But I do believe a
33:32
happy workforce and ultimate happiness is independent to the person and the individual. I
33:37
get that. But when you come to work. You know, we had
33:42
this joke, I think a couple of years ago, maybe when we were
33:44
doing this, when you have somebody come to work and they go, oh,
33:46
no, I don't mind if my laptop takes three minutes to boot up,
33:50
because that's my routine, you know. I wake up, I turn
33:52
my laptop on, I get a cup of coffee, I take the dog
33:54
out, I get a newspaper if you guys know what a newspaper is anyway,
34:00
But like you know, you get that. Like that shouldn't be part
34:04
of your routine. Your routine should not bend to the will of your of
34:08
your electronics and your technology. It should be I log in, I have
34:15
my stuff, and I should be able to do my job to the best
34:19
of my ability, with the support of the company that I'm working for,
34:22
so that I can get done. We just got there's something going on on
34:31
your machine. This is inspiring me, but it is it's we have so
34:42
many people that have again, the silence sufferers I know that's kind of an
34:45
old term, but it's still true to me that there's so many people that
34:51
just drag themselves through the day, and you know, you I, I,
34:57
I do it all the time. Hey, why are you? You
34:58
know, why are you like so bummed out? Like, dude, my
35:01
laptop man, the you know, the d key has been sticking on it
35:05
now for like, you know, three months. You know, every time
35:07
I open up Outlook, it takes like seven minutes to load. I go
35:14
to open up Excel. Excel works for me like most of the time,
35:16
but then it just crashes and then so, Jeff, if you tried have
35:21
you tried assist yet? No? That's the Is that the chatbot? Yeah?
35:25
Well yeah, you could call it a chop pop, but it's more
35:28
of that large language model, the natural language query model, where you can
35:31
say, show me everyone that has a sentiment level below seven and tell me
35:36
what's happening on their machine that would impact This is the bit. It's the
35:40
chat GPT for Deck. This is the beta, though I don't. I
35:43
don't have that yet. We got to get you connected then, yeah,
35:46
I would. I cannot wait because for me to be again I again,
35:52
the infinity platform still by the way, anyway, this it's still really cool.
35:54
Like it kind of like, you know, I'm not gonna say for
35:57
dummies, but like it does have like that when you do this sequel or
36:00
NQL, like, I mean, you can you can fudge your way into
36:04
trying to figure out what you need to do. It's yeah, but this
36:07
takes all that gets work out. It'll yeah, it'll write whatever you want
36:10
for Give me a recipe for chicken parm And how many people have slow boots?
36:15
How many people are making chicken farm because they're boot there, They're PC
36:19
doesn't boot for eleven months. Great, who's walking their dog and getting a
36:22
couple of coffee because they have a five minute boot to? Yeah, I
36:24
mean that's that's what I feel my ultimate responsibility is. It's yes, we're
36:29
we're saving money and we're helping you know, the the company scale and be
36:35
healthier. But you know, I I I get sad old, I really
36:38
do. I've become again. I'm I'm my old age, I say.
36:43
But just COVID in general kind of had that quickening. I get sad when
36:46
I see employees in my office. I still go to the office and I
36:52
chat with so many people around the world, New Zealand, Australia South.
36:55
I'm like, I'm like on with everybody at this company, and I hear
37:00
the stories all the time. It's the yeah, you know, I tried
37:04
doing this and it just you know, my laptop explodes. I mean,
37:06
how many times we have hard resets. I'm like, are you powering down
37:09
your machine? Yeah? Did you call the support desk? No? Why
37:15
because it's quicker for me to just do that, because they can't help.
37:19
Yeah, because they can't help. What are they gonna do. They're gonna
37:21
break three things while they try to figure this out. Yeah, and it
37:23
you know, I try it. First of all, I try to cheer
37:27
them up as quickly as possible. I'm like, you're not alone. I'm
37:30
here to help. I think maybe you know, like I I quite often
37:36
tell people that even if I can't solve your problem, I'm sure as hell
37:39
gonna try to make your smile for a second and or a minute or an
37:45
hour. And I think, you know, I don't know how many employees
37:47
I might have saved at this company and maybe not had them leave the company
37:52
because of it, But I sure as heck try to get people to at
37:55
least smile when I'm trying to help them. You're the last clown. Thanks
38:00
damn. I appreciate that. Yeah, I mean the look the class.
38:06
I've always been the class clown. And I'll tell you what it's. It's
38:08
it's a good place to be if you're if you're genuinely trying to just get
38:13
people to feel better about a crappy day. And yeah, I was going
38:22
to jump in Tom and just kind of Jeff, we talked about there's almost
38:25
another AI episode, But what what changed in twenty twenty three or what happened
38:31
in twenty twenty three that was not related to AI in your mind? I
38:37
mean, we talk about it. No, it's it's actually no, it's
38:44
the it's it's the human side of it. It was the ocean of mediocrity
38:50
rules. Uh. I have found it unbelievably difficult for for for most people
39:00
just to get things done. It's AI is supercharging everything, but at the
39:07
same time, humanity is taking a nap. Right. It's like, it's
39:10
it's a two sided thing, and it's it's I'm sure you guys have the
39:15
same conversations. It's not my company, it's not someone else's company. It's
39:20
every company. Now, there's you know, we have a lot of people
39:24
retiring, right there's a lot of people retiring. And I have to tell
39:29
you that there's people I know that I love dearly at this company and some
39:31
other companies that are about to retire. And I joke with them. I'm
39:36
like, you can't do it, Like you can't do it, and they're
39:38
like, they're like, Jeff, I'm done. You know, I'm sixty
39:40
I'm sixty five, I'm done. And I'm like, I'm like, i'll
39:45
call hr right now. I'll tell I'll lie and tell them you can't right
39:47
And they're like they're like, I'm done. And it's it's almost like a
39:51
Star Wars kind of thing where they're like, now, like Jeff, you
39:54
know here, you know, I'm passing them tasking. Here's the lights.
39:59
Say you have to do it now and I'm like, no, I don't
40:01
watch, No, I can't. And they're like you gotta get people to
40:05
do this, and I'm like I can't. Like there's a old guard right
40:09
now that's retiring or has retired, and it's left a very big gap.
40:15
You know, people talk about, you know, the old boomers, the
40:20
boomers are getting things done. They're not glued to their phones. They have
40:25
a task at hand that they're focused on and they know how to get it
40:30
over the finish line. I myself am guilty sometimes. I you know,
40:34
I'm looking in a million different directions. But it's nothing compared to some of
40:39
the younger generations. And again I'm not I'm not pointing fingers. I'm not
40:45
generalizing either. This is there's plenty of people I know in their twenties and
40:47
thirty is that they're awesome, But there is there there There was like a
40:52
like steam somebody took the coals out of the steam engine, you know,
40:57
and they're cooling and it's just kind of like coasting in and it could be
41:01
the influx from you know, we have the great resignation now we have I
41:06
read an article we can't get people to leave right. It's such a weird
41:09
thing. You know, people are staying too long now, you know,
41:13
companies are keeping employees for too long. They're not leaving. We hired them.
41:16
It's such an odd organism that's just not figuring out where with the what
41:22
this this the the rest States should be in And uh, I've struggled with
41:29
I've struggled with people early early twenties asking me for chromebooks we have, we
41:35
have MacBooks, we have Windows machines, and they go, eh, Windows
41:38
ugh, like it's got to reboot nine hundred times an update. And I've
41:43
like, oh, you want a MacBook? Not really. I couldn't believe
41:46
people in their early twenties say like, now I don't want a MacBook.
41:50
What do I want to Mac? I can't run like what I want?
41:51
Just give me my Chrome browser, give me my Chrome Book, and I'm
41:55
and an Internet connection and I'm good. We have DAT we have DNA.
42:00
People like all the data guys chromebooks. It's it blows me away, except
42:07
when you really think about it. All of our kids, Tom, I
42:09
know you have like ten of them, but like I know, like I
42:14
know, like all of our young kids. It was grade school chromebook,
42:17
high school, Chromebook, colleges, g suite. It doesn't like anybody that's
42:22
like shocked that these kids graduate college and go like, why are we where's
42:29
my chromebook I've been using? No, they're always on, always on Internet.
42:32
There's no more, no more dial up and hoping you get connected right
42:37
or being able to work offline yeah, it's it's, it's, it's it's
42:42
it's such a weird thing for me to take in because, again, as
42:45
my responsibility, I tell them like, Okay, I'm like, can we
42:50
offer them chromebooks? They're cheaper. They're like, I'm like checking all the
42:53
boxes. They're cheaper, they're easier. And it's like, well, no,
42:58
I don't know if we could do that. We've got to give them
42:59
a you know, give him an HP workhorse, you know the word,
43:02
give them the give them that five hundred pound and you know, look,
43:10
you know, if anyone wants to hear more generalization, generational generalizations, they
43:17
should check out one of our episodes, a few, which was a great
43:21
Jacob Morgan joining the show to say, just as Jeff was there, exactly
43:24
what is wrong with young people today? We like to think we've got that.
43:28
I don't say anything was wrong with young people. I had that you
43:30
to your paraphrasing, wrong with your words, your words. Well, look,
43:36
look you live up as ever to your promise, Jeff of always always
43:40
bringing a smile, not just for for a minute, not just for an
43:44
hour, but many many hours of your appearance from the Deck show. And
43:47
I particularly loved having you back from it's wonderful, I think, wonderful.
43:52
End of the year, end of twenty twenty three, wrap up, absolute
43:54
pleasure to have you back on the show, and let's all hope AI hasn't
43:58
replaced us all and we can all gather together again to discuss it's nearly on
44:02
the verge of replacing us in twelve months time. Guys, it's been an
44:07
absolute, absolute pleasure and enjoy good stuff. Jeff Yeah. Happy New Year,
44:09
guys, Happy holidays you too, Matthew too. To make sure that
44:15
you never miss an episode, subscribe to the show in Apple Podcasts, Spotify,
44:20
or your favorite podcast player, And if you're listening on Apple podcasts,
44:23
make sure to leave a rating of the show. Just tap the number of
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stars you think the podcast deserves. If you'd like to learn more about how
44:30
Next Thing can help you improve your digital employee experience, head over to nextthink
44:35
dot com. Thank you so much for listening. Until next time,