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And now here's your host, Eric Kavanaugh. Oh yes, indeed,
folks, welcome to the future and yours truly. Eric Kavanaugh is here for
the only coast to coast radio show all about the information economy Inside Analysis,
and we're gonna be talking with an expert about one of the most important things
in business today. The network, Yes, the network. We all know
when the network is slow. Everyone knows when that happens, and that's no
fun at all. I saw a great meme a while ago that said something
like, if you want to find out who you're dealing with, put them
on a really slow Internet connection for an hour and just see how they respond.
That's gonna tell just how patient a person you are. You never go
back right. Once you get things faster, you can't go back to having
them slower. You know. I remember the old days with AOL friend of
mine set oh, get on AOL. I really didn't want to do it.
I did it anyway, and downloading images downloading image is and when I
tried to get off of it, like six months later, they're like,
what credit card did you use to log onto? I'm like, I don't
remember, dude. I just want to get off that service. But that's
the old days. Things are better now. And since we're gonna be talking
about networking with Rob Tiffany from a very cool company called Red Bison, I
figured I throw out my one bad, terrible networking story from the early days
in Seattle at TDWY. They went out and they bought that VoIP stuff and
it was just awful. And I noticed it would get worse throughout the call.
So if you're on a call for like thirty minutes or forty minutes,
like forty minutes in man, it's like, I mean, I like all
that kind of stuff. You're just like I remember talking to management saying,
guys, don't you think it's important that we be able to communicate to people
outside the company kind of a critical component of information sharing. But anyway,
things are so much better these days. And Rob Tiffany, you know a
few things about networking, and you guys have a really interesting business model where
you will build out the network for commercial office buildings and then you do all
kinds of other things for them as well. So, first of all,
tell us a bit about yourself and read Bison and why modern networking is so
much better than it used to be. Sure, absolutely, thanks for having
me. Yeah, so Red Bison. The bison is related to buffaloes and
bisons in North Dakota, where our founder was originally from. Nice. But
yeah, it's the company, you know, it's kind of a network as
a service company. Is kind of the primary you know, backstory to the
company. I'd say it's the intersection of high speed networks to commercial real estate,
if that makes sense. And so whether it's skyscraper's, office buildings,
office parks, multifamily, you know, it could be condos or apartments anyway.
You know, bringing in high speed you know, dual fiber you know,
like ten gigabit fiber into into buildings, then you kind of wire up
the buildings. If anybody has walked into building, they saw those weird telecom
closets or here weird strange terms like MDF or IDF or whatever. Anyway,
there's some strange stuff in those closets. It's all about networking and building management,
you know. You know, so you'll see stuff like from Honeywell and
Johnson Controls or Siemens and all that kind of stuff that make these big buildings
work. And so so yeah, we bring in the high speed networks in
there, then fiber and Ethernet going up through all the way up through the
building and out through you know, all the stuff you don't see that you
take for granted that's in the walls, you know, like old stuff like
ethernet right and Cat six cabling, you know, and then and then Wi
Fi access points on the end of that. Everybody thinks we're all wireless,
but it's actually wireless is made of wires. Yeah. My background, it's
mostly software. Uh. You know, I spent most of my career at
Microsoft. First half was doing Windows Mobile, Windows Phone, so I had
to have really thick skin. You know. Things were okay when it was
just us in BlackBerry battling it out, and then the iPhone came along and
it started to get ugly and so and then the second half was building Azure
and that was a lot of fun, building this global cloud thing and how
you design that for availability, and then building Azure IoT. Most might have
just so much background in the Internet of Things, industrial IoT and stuff like
that, and so we built Azure IoT and that was a great building.
You know, Global IoT platform got recruited out of there by Hitachi because they
wanted to build an industrial IoT platform, and so I went and did that
and got to design and build the whole thing from scratch. That was a
great experience. I was living in Japanese factories and wow, you know,
making it real. I think that's probably where I first got into that whole
weird digital twin world. You know, modeling machines or bullet trains or all
kinds of crazy stuff like that, And so you've got IoT and digital twins
kind of together, and then of course you're playing analytics or machine learning AI,
and then back to networks. More recently, I was a VP over
at Erickson, which is one of the companies that makes all the cellular gear,
the five gief stuff you always hear about in Sweden. So it's flying
from Seattle to Sweden every month until COVID of course, and then I'm on
phone calls and weird hours of the night, you know, the rest in
Stockholm. But yeah, so we're pulling it all together here at Red Bison.
So yeah, it's pretty interesting stuff for sure. Yeah, that is
cool. And I totally see the alignment between IoT and building out the infrastructure
for office towers because you have so many objects. You got all these different
routers, you got all these lights, and of course smart cities and sustainability
these are all big issues these days. Knowing what it really costs to have
all these lights on, Knowing what it costs to have all this stuff running,
Knowing how to be able to preen things or prune it down when you
need to, and you know, knowing what the impact of all that is
and you know that gets into these digital twins. And I'm a huge fan
of the robust digital twin because you can really play around with ideas and you
can say, well, what if we did this and what if we did
that, and you do that in your digital twin environment and you get results
and it says, Okay, this is how the costs will go up,
this is how the usage will go You know. Those kinds of things are
really important for planning, right absolutely, and lets you bring the whole thing
to life, you know, makes it a living building. You know,
you think, you know, because you're right, there's the whole bigger smart
city thing. But mostly cities are made of buildings, is the primary thing.
And so if you think of digital twins and kind of zooming in,
it's the it's kind of the overall property. Maybe it's a corporate campus and
then one or more buildings, and then each building has one or more floors,
and each floor has one or more A lot of people are just calling
them spaces. Now there's you know, there was this smart city, a
smart building. I'm hearing a lot of people kind of tver to smart spaces
or sustainable spaces, maybe because they needed to genericize is it office, is
a conference room, is it the lobby, is it whatever? So you
kind of have these spaces, but they're all they're digital twins, and so
each one of these spaces you can, you know, in the software you
of digital twins, you set properties for them and bring them to life.
And so you mentioned you know, just uh throttling things back based on you
know, we can have occupancy sensors. You know, what did everybody discover
during COVID. You had all these office buildings going full speed ahead with lighting
and HVAC and just burning energy like there was no tomorrow, and there was
nobody in them, right, you know, the buildings were empty, half
empty, you know. Even well in today, you know, we've kind
of this kind of in between hybrid back to work and so a lot of
times most of the people you're seeing are kind of like Tuesday, Wednesday,
Thursday ish, you know, right, And so you know, powering those
buildings buildings are one of the biggest emitters you know of you know, greenhouse
gas emissions, and so if there's nobody in there, even if there is,
there's ways to be smart about it. And so that network software IoT
digital twins analytics AI building altogether to make smarter buildings, but probably make sustainable
buildings, you know. Well, yeah, and like the hidden challenge of
IoT is that you have so many objects sometimes and so it's hard to even
represent visually what's happening there. And of course, you know, you get
devices that there are so many cool things happening in the IoT space. I
mean, I can't remember the name, but I had a company on here
that was working in low frequency IoT and basically it's I think it's blockchain underpin.
You probably know who these guys are. I think they're based out of
often somewhere, But basically it's like a low frequency network that can connect IoT
devices with very little power to the home base. And so they're really interesting
things that you can do for just kind of staying on top of things,
where is the money going? Like what does it cost to air condition this
building? And what if we play around with different options on different floors and
things of this nature. Even the elevators, I mean, I have to
think that for some buildings, strategic intelligent elevator management is a pretty good deal,
right absolutely, Because you're right, most buildings it's still kind of mindless
elevators are just doing like what they've done for the last fifty years. Right,
of course that's an even bigger thing. The reality is most buildings are
just old. You know. There's the world that we want, and we
talk about futuristic cities and stuff like that, and we kind of joke about
it. Let's say fifty years from now, when you think you're gonna have
these futuristic logans run looking cities. But the reality is is all that old
stuff that's one hundred and fifty years old will also still be there amongst it.
And you know, unless they're going to demolish all the old buildings and
we go to New York City, go anywhere, they're all still there.
Right. People still use old buildings, and so how can you make them
more efficient? Right? You know? And so it's just like my time
in industrial IoT. You know, it's you're going to be retrofitting old stuff
for a long time to get value. Lots of people dove into that IoT
space thinking it was going to rip out all the old stuff and put in
new, shiny, high tech things. And that's when the guy you're talking
to is like, get out of my office. You know, tens of
millions of dollars for all this stuff, and we're not throwing it out.
You know, it's just not going to happen, you know. But yeah,
it's a good point, you know. And so those sensors, those
things, those objects, they're inside those spaces, and the space is kind
of the twin and you know, you might be saying, well, gosh,
this this conference room. When there's this X number of people in here,
and you know, it gets too hot or there's too much CO two
in the air or whatever it is you're looking for. You can start you
know, there's that kind of real time streaming data where it's telling you what's
happening now, and you've got occupancy sensors and temperature and emissions and stuff like
that. And then so then you can take that same data and train models,
you know, AI models or what we used to call last week mL,
but machine learning's not cool enough, I guess anymore. And so to
tell you what's going to happen down the road, you know, predict Oh
gosh, I noticed every Thursday afternoon this conference room is packed full of people
and they always complain about it being too hot or whatever, you know,
And so you can start using those kind of analytics to predict the future and
make things better for folks. But yeah, space for sure. Well,
and you can learn all sorts of things about yourself, about your business,
about the marketplace, and just by analyzing the data. By looking at the
data and understanding the usage to your point, you can figure out, hey,
for some reason, no one's ever here or very few people here Wednesday
mornings, so we don't have to turn things on as much. You don't
have to get the AC cranking as much. I mean, we really are
an AC overkill kind of society here in America. Right, But my wife
gets called all the time and walk into any corporate headquarters, it's like,
oh my god, it's like sixty four degrees in here. Yeah, I
mean I get the story about they're trying to kill the mold. Okay,
I got that, we don't want mold everywhere, But still, does it
have to be sixty four or going to be like seventy one seventy two?
You know, it's a lot of money to get spent on that stuff.
There is a lot. And it's funny you talk about being over chilled and
stuff like that. When I was with Hitachi and so I was a lot
in Japan, a lot. I remember going all these office buildings skyscrapers in
Tokyo and in the summertime, it's a little warm in there actually, and
I'm like, what's that all about. It's that way everywhere. And it
turns out they think of it in Japan as a shared sacrifice to reduce energy
usage and therefore costs, right, and so it's the first thing you notice
when you go into these beautiful skyscrapers in Tokyo in August and you're like wow,
and it's like they're all on board. You know, the whole society's
on board shared sacrifice to cut costs and energy usage. I was like,
well, that's really interesting. I don't know if our country could get together
here in the US just get on board with that or not. Well,
you know, here's the interesting thing, right, I'm a data guy,
and our show is focused heavily on the data side, because you want to
see the data. What is the data tell you? You have your own
opinions about things, but when you can see the data, then you really
understand, oh, okay, that's what it's really costing. And with a
situation like you're providing with a solution like this, you can see the data
and review the data and talk to people about it and see, hey,
let's just test this for five days. Let's change the temperature from you know,
sixty nine to seventy two, and then watch the usage. I mean,
what's cool is you're starting to see even power companies and end user facing
companies embracing this. So you get your little email, here's your power usage
from the last week. Here, saw compares to last year or last week
or whatever, And so you kind of start to get a field for things.
And the bottom line is what gets measured gets managed. And so when
you can show the board and your team, hey guys, we would actually
save twenty thousand dollars a month if we would just raise the temperature up three
degrees. And then you know, we're going to give each of you a
five hundred dollars bonus at the end of the year. How's that alright?
Like, Okay, I love your comment, though. What gets measured gets
managed, what gets managed gets measured or improved. I am so on that.
And I always always when I talk about IoT, you know, without
it, you're just guessing. You might be making educated guess, right,
but with IoT, you're knowing you've got that realtime data feed and it's letting
you know this is really what's going on. You're not imagining it or using
a gut that's right, and it's so and so often I've noticed with these
kinds of things, you will you will see things that surprise you. I
mean, even though it's your office, it's your environment, you wouldn't think
you should be surprised. But every time you look at some significant data set,
I've found you're always surprised by something. Yeah, so you're going to
see that outlier. It's like, well, what is that thing? Let's
dig into that a bit more and understand what's going on there. And you
know, to your point, you can save a lot of money, a
lot of time, a lot of maintenance. You know. That's the other
interesting thing about IoT is is predictive maintenance stuff. Absolutely. I've been a
huge fan of this for years. As soon as I learned about I was
like, oh, wow, that's cool, because the engineer who has to
go around and check all the doors and check all the windows and all that
stuff, that's a really boring job unless you've got some IoT solution where it's
predicting, Hey, this heater is going to fail. We know because we
recognize the pattern and usage. It goes up and it starts making a noise,
And noises are a big part of that stuff too, right, like
hearing the sound, noise, vibration. And it's like any industry with any
kind of machines, whether you're in a skyscraper or a factory or a car,
you know, and you always hear the deal that the folks have been
working on those for years. When I put my hand on this machine,
it vibrates a certain way. It's about to die next Thursday, right now.
And the reality is is we can't rely on that forever. Those folks
are going to retire. I mean, I'm up here in Seattle on it.
Every year there's some deal in the news. We're like, wow,
you know, all those aircraft engineers at Boeing they're about to retire. And
no one knows how to build airplanes anymore, and we don't know how to
monitor. And it's like you got to let the data tell you. You've
got to start instrumenting everything and let the data be your guide, you know.
In a way, that's it. It's the instrumentation and then it's the
collection of all that data. And that's where maybe in the next segment we'll
get more into the the the unwielding nature of IoT because you know, what
you're typically measuring are simple things like temperature or amount of light or CO two
levels or whatever it is. It's it's some particular thing that the sensor is
designed to watch for. But then again, trying to aggregate all that stuff
and manage and it requires some some sophisticated knowledge about how to look for things
like what is the pattern I'm trying to find in here? Is it when
it goes down? Is it when it goes up? Is it like a
variety of different things. That's what experience will tell you, with the aid
of course of machine learning in the background, because the machine learning algorithms don't
tend to sleep. They just work all night long and they do their little
thing, and you wake up in the morning and they go, oh,
why don't you look at this? Why don't look at that? And I
for one thing, that's how most AI solutions are going to provide value in
the future is by suggesting things to you based upon the baseline and the pattern
they're seeing right now at this moment, folks, don't touch that. Del'll
be right back. You're listening to Inside Analysis. Welcome back to Inside Analysis.
Here's your host, Eric Tavanaugh. All right, folks back here on
Inside Analysis. You're truly Eric Kavanaugh with Rob Tiffany of Red Bison. He's
been all around work for a bunch of big companies. Ericson. I think
ATACI was talking about earlier, and of course Microsoft building Azure. That's not
a small job building out this what is basically a cloud platform. And I
often joke the irony strikes me that Microsoft saved us from the monopoly of Amazon
Web Services, since Microsoft had the monopoly for years of operating systems and that
caused a lot of trouble. I had a theory that Linux was born out
of a desire to escape from that, and someone told me, no,
not really, But it did serendipitously work out that way, that Linux thanks
to IBM dropping a billion dollars into it to harden it to make it an
operating system for enterprise solutions, and it won, and now Linux is the
de facto standard, and open sources teetering a little bit these days, but
we wanted to get a bit more into the IoT stuff, because I think
you have to appreciate how on wieldy it is to have, like even in
a large office tower, like how many phone systems are plugged into this thing,
how many HVAC systems, All these different systems are plugged in. They're
all pulling on the power. And that you want to talk about black magic
man, like really getting into power. Like in these older homes, you
can tell, like when the heater turns on, the lights dim, you
know, it's because it's like pulling on that flow of energy. And to
really understand that, and I'm guessing you guys got some great data and analytics
on that kind of stuff can be very compelling in terms of knowing how to
save money, knowing how to provision services more effectively. And that's all really
important because when the network doesn't work, ain't nobody happy, right, right?
You know, the network is totally a trojan horse for us to get
to do all those other great things. It really is like that, you're
honest about that's fun it is, you know, you know, because I've
seen other IoT players try to go after building management and do building IoT stuff
because there's a lot of great use cases there and most of them just failed.
They couldn't get into the building. They didn't know the right people,
they didn't have the right you know. In the end, it's still about
people and connections and what you're already doing there. And so since we go
in, we're giving the building something they really really really want. People want
fast internet and they want to be able to connect, and they needed to
be reliable. And so because we do that, that gets us in there.
And you can imagine if you own the network throughout the whole building,
IoT needs a network to ride on, right, you know, and so
like you mentioned earlier, you know the low low power, you know,
low frequency stuff like Laura Wan and things like that. You know, people
use outside where you have your IoT devices need to live for five or ten
years on a battery. Luckily, in a building, we've got electricity to
plug into, so we don't have to worry about that as much. But
since we own the network, we've got the fastest, lowest latency network.
You can imagine right there, all those IoT devices now it's easy for them
to piggyback on that and for us to get to all that data. If
you look think about like a pied chart of where the energy is being used
in a building. You know, it's lighting an HVAC or your two biggest
culprits. And then apparently then just everything that gets plugged in, all the
extra stuff, whether it's a printer or your PC or whatever, a million
things getting plugged in turns on, that turns out, that uses a huge
chunk. And then of course there's that relationship between energy usage and emissions,
right. It kind of goes hand in hand. And so you can monitor
energy usage at a building level, you know, voltage, all that kind
of stuff. But there's some great IoT sensors they have today where you can
kind of do segmented monitoring of power usage in just certain parts of the building.
They've got these little devices that you literally hook onto the cabling of the
electricity. The power and the ambient energy coming off that cable is enough to
power the IoT device. Wow. And then the IoT device a lot of
times is using like that low low power, low uh frequency stuff like Laura
to send because it's sending just little tiny bits and bites of data, nothing
major, so you and it'll tell you how much. And so you can
do something called sub metering where you can say, wow, this port,
you know, this many floors or this part of the building is is really
a culprit. It's using way more energy than all the other guys and stuff
like that, And so you get a better granular view, you know,
back to what we were talking about. You know, the data is going
to tell you what's really happening. And so instead of saying, I know
the power usage for this whole skyscraper, now I have a granular view of
who's using what, and you can then make better decisions, and you can
do management and you can improve the situation or anything that not just electrons but
water, right you water and pipes and pumps all over the building to you
know, people are like, how is it that you have a bathroom on
the eightieth floor of the building. How does that work? You know,
how's water coming out of the closet. There's this world of pumps that's pushing
water and stuff up there to make that work. You know, I've done
a lot of stuff kind of in the you know, reducing emissions that I
don't know if you've ever heard of the United Nations Sustainable Development goals. Sure,
so so I've built technology to you know, a lot of IoT to
help that. Well, one of the big ones is water. It turns
out where I forgot how many millions of gallons of water gets leaked and lost
fresh water every day in our cities, in our buildings and so and then
you know, at some point you start to realize that fresh water turns out
to be one of the most important resources we have, and so being able
to monitor and find leaked where there it's happening, and that whole matrix of
plumbing going out throughout a building is kind of a thing. Oh yeah,
yeah. I mean I spent the number of years living in New Orleans,
and the data on the amount of water that is lost from the facility to
the homes it's like, I want to say, it's like two thirds.
It's it's a gobsmacking number which shows you how many holes there are in the
system. I mean, my first job as a newspaper reporter, I interviewed
a guy from in situ Form I think is the name of the company,
and they would go in and use really which at the time was for cutting
edge technology to go through pipes and like sense where the holes are, and
they would actually line the pipes with like a synthetic material to prevent it from
leaking and doing things like that. But you know, just ask anyone who
had plumbing problems, man, Like, getting to the bottom of that is
a huge issue, and that's something that IoT can help you do if you
have the sensors in place, because you can sense the vibration and how much
water is moving through here versus here, and you can use that to identify,
Okay, well the problem must be here, So that's where we're going
to drill through your wall. Like it's brutal. You made the comment earlier,
just creating a baseline m h without even doing any crazy AI stuff.
Just simple KPIs right, you say, I expect this, like you know,
like KPI is green, yellow, red. Right, if you're in
the green zone, I don't need to do anything. If I'm starting to
lose water or electricity is going off or or whatever it is you're monitoring,
you know, you get going to the yellow and you head towards the red
zone. You can you do pattern matching on the data the packets that are
coming in telling you what's going on right in those pipes in the electricity.
You know, how many people are in the building all that kind of stuff,
you know, and you say, I expect kind of like in New
Orleans, I expect this much water to make it from here to here,
right, And the reality is, well I lost two thirds of it.
Maybe there's a problem, you know, and so you've got to, like
you said, you've got to measure it or you can't absolutely can't manage these
systems. And so IoT. You know, I often talk to folks they
think they need the most advanced technology to do IoT to compete in factories or
whatever. And I'm like, just remember, you're competing with a guy with
a clipboard. That's really what it is. That's who your competition is.
Some guy taking logs, monitor looking at gauges, you know, things like
that to find out what's really going on. And so IoT is that person.
It's that person taking logs except continuous monitoring. Right, that's brilliant.
I'm going to quote that and post it here shortly, Like you're competing with
a guy with the clipboard. That's right, Well, as you suggest,
until you take those baselines and let's think about it. Flow applies to water,
Flow applies to electricity, flow applies to data, to information packets going
around on your network right and getting that baseline you talk about security, getting
a baseline of network traffic and what happens every day. There's a company and
a dot I think they're based in Israel and they can't remember how they started,
but they're all about anomalies. Basically, they're looking for strange things like
what is different from yesterday? Well, you don't know until you have a
baseline. Once you get a baseline, then you can start analyzing and understanding
all right, now, why why did things slow down for this period of
time? And you know, there's a guy I interviewed gosh fifty fourteen years
ago in the show I Love this name, Zohargi Lot. He was with
a company called Precise. They got bought by who were they? They got
bought by Idea I think. And it's basically it's it's troubleshooting for systems,
and you know, these days it's even more complex than that, with Kubernetes
and containers and all this stuff. It's like, oh my god, yeah,
once might have all this observability stuff these days, right, but now
you have to like collate all that observability data and figure that out. So
it's like, you know, this stuff comes just but again the point is
understanding what's normal and then what's not normal, and so hard. We were
joking about stuff because I was saying, even if you have all this great
technology, you're still looking at histograms. You know, CPU usage went up,
network went down. Well, how do we correlate these things? And
of course that's where time series comes into play. It's like, well,
let's look at the time series and see what was leading up. There's a
slow rise here and then a big fall there. It's probably related, you
know, absolutely absolutely, and then go ahead. Another thing I thought of
that flows through a building and underneath everybuilding in a city is natural gas,
right right, And so that continuous monitoring is so critical, so you know
in real time and you can react to it even if you're not doing predictive
maintenance. Right, you can nip it in the bud super fast because you
don't want to find out too late that there's a natural gas leak, right
right, right? I saw some and it was a house just exploded in
something. Right, Oh, it's so bad. Well, and there there
are sensors for everything. I mean, that's the thing about IoT, right,
is you get all these new kinds of sensors coming out, and they're
getting better and better and cheaper and cheaper, right, because a lot of
these things are very inexpensive and their whole job is just to go hello when
something changes. Right. But then once you get that all in line,
then if you have a good IoT solution, you can save I mean,
you know, the cost of being able to troubleshoot quickly versus over a long
period of time is massive in terms of disparity, like and the you know,
the reputational harm, the damage to human beings and the buildings. I
mean, good god, water in particular, I'm sure you know being in
the industry, like you get water leaks that go for a while. Man,
oh no, exactly exactly. So you're right, you know, make
sure you've got these little slow cost leak detection sensors in the bathrooms, right
in the room. If there's a restaurant, there's a kitchen, there's a
you know whatever, so many simple things. Temperature, you know, worked
with restaurants that are in buildings and just having temperature sensors in the walk in
cooler and the freezer. You know. I remember having a guy said,
yeah, you know, one of the you know, and we're not talking
rocket science here, but one of the employees left opened the door for the
freezer as he left for the weekend, and it was going to be this
closed down three day weekend. But luckily that sensor told them. And we're
not even talking about some cool dashboards. It was just a text message.
And the guys like, yeah, it saved us, Like we would have
lost thirteen thousand dollars worth of food that would have gone bad just because of
that. Wow. And then and then the leak stuff. You're right,
is just horrible. In fact, you know that's one of the biggest insurance
companies When they have to do payouts. You assume it's a fire is the
number one, but turns out flooding is number one. I'm sure it's neck
deck with fire. I knew some guys at an IoT company and their way
to instead of charging customers to put in sensors for leak detection in their homes
or buildings. It turns out when the insurance companies looked at their actuarial tables,
they came to the conclusion that they the insurance company would pay for the
sensors for free and everything because the loss when it happens is so horrific.
Wow. So that's cool. Yeah, it is cool. And so a
lot of times it comes back to money and insurance and figuring stuff out like
that. Well, but it makes a lot of sense. And that's why
you want actuaries there, right. It's because they're saying, all right,
well, if we just go ahead and incentivize people to get these sensors in
place, we're going to save on the back end millions of dollars, which
is probably true because all it takes is one bad apple to just screw the
whole bunch, right, absolutely, absolutely, Yeah, So yeah, it's
great having that network in there. I was surprised to find out that a
lot of theseuildings, you know, you put in different systems, like you
mentioned elevators or HVAC or lighting. There's all kinds of systems put in by
different companies. And what we've discovered over time is each one of those has
the building owner install a completely separate high speed network circuit interesting for each individual
thing. So you might come to a building and find out that this building's
got five or six separate networks all to cater to these different vendors and stuff
like that, and so a lot of times we help save money for buildings
by consolidating those down too, you know, lower cost but faster, bigger
pipes that way, which is kind of interesting. Yeah, and I'll bet
that. And granted just takes some analysis, and this takes some time to
kind of dig into. But because you do host command and control for all
these different systems, you can do time series analysis across different scenarios. So
when something happens or when a bill comes into high or whatever. It's very
frustrating if you have to look at five or six different systems. But if
you can go to one master's system that has control over all of them,
that's where you get that single source of truth and can really kind of dig
into it. And I you know, again, I have to believe that
there's a lot of money to be saved by not freezing all of your denizens
every day it's sixty four degrees fahrenheit. You know, it's like, okay,
I know we want to be cool, but does it have to be
that cool? Like can we just maybe ease off a little bit and just
and see what it is? When you see the numbers, you'll find out
what the deal is. But folks, don't touch that. That will be
right back talking to Rob Tiffany of Red Bison, all about IoT and fun
stuff. We'll be right back to Welcome back to Inside Analysis. Here's your
host, Eric Tavanaugh. All right, folks back here on Inside Analysis.
A fascinating conversation about networks and electricity and gas and things that flow. Right.
You want things that flow like cash flow right, You got to watch
out and you get a big pool of cash like that's when trouble starts.
You want it to be flowing. You want everything to flow through your organization,
energy, food, fuel, all that kind of fun stuff. And
we've been talking about the networking side of that, which is a foundation of
the information economy. You could argue is networking right. It's the ability to
move information from one place to another, to enable functionality, to enable people
to do cool things. And Rob Tiffany of Red Bison knows a lot about
all that. We wanted to get in a bit more to the I guess
to the edge stuff, and just to people understand edge basically, your cell
phone is at the edge. A computer can be at the edge. It's
an edge device basically. And we went through this interesting period of time client
server, because we started a mainframe, you do client server, and then
the cloud came along, and then you get hybrid cloud and multi cloud and
all that stuff, and then the edge comes along. The edge is very
very interesting because it's it's not the data center per se. It's not like
the big corporate data center. It's not the cloud. It's not just one
device. It's all these devices that are out on the periphery basically, but
you could do interesting things there. And you were talking about this earlier,
rob where you know, you come in, you build a network for the
office tower. And by the way, we now have servers on every other
floor, so we can do a little mini cloud for you. We don't
have to send stuff up to the cloud, because what happens when you're sending
everything up to the cloud. You got to go through the network. Right.
I was in the had Dupe space, which was a big deal.
You may remember had Dupe, But the network was the achilles heel because you
had to move all this stuff around the network, and so all of a
sudden that becomes the bottleneck. And anyone knows in business as in life,
bottlenecks are where you have to figure out what to do, and you guys
have done some interesting things on that, So tell us about how you're able
to enable all sorts of interesting service for your clients. Yeah. Well,
since we don't just install the network and walk away, we kind of do
this network as a service, so we're actively managing it. We have hardcore
firewalls all over the place, We've got AI built in our networking gear,
and so we actively manage and so that's an ongoing thing that we do to
make sure performance is always there to nip things in the bud. Like we
talked about with other things. Security is the huge deal, but just make
sure you know a customer's paying for this much bandwidth, we have to make
sure that they're getting it. And so actively doing a network as service then
gives us the ability to go in and provide other services and have that confidence
because you're right, you talked about hadoop and the network bottleneck being an achilles
heel for a lot of that stuff. So, since we have this crazy
network that we're managing actively. So you walk into a skyscraper and every floor
there's this weird door that's like a closets. Do you remember the good old
days when companies used to put their IT stuff in a closet kind of yeah,
servers literally in the closet. Yeah, and the closet, you know,
before data centers got big or anything like that, there's the IT closet
or whatever. Okay, that still is kind of here today, believe it
or not. And so the bottom floor, don't remember what the acronyms stand
for. The bottom floor is called an MDF and that's where the fiber optics
comes in, and that's where all the building management stuff is. And then
on the subsequent floors you have, they're called IDFs and they're smaller. So
since we get space, since we own the network, we get space rack
server space on every other one of those floors to put compute in there.
And so you kind of asked the questions, well, gosh, you know,
so we have cooling, we've got electricity, we've got compute. It's
right there. It's inside the security envelope that we've created. Like you're inside
the building and you're protected by our firewall and we're actively managing it with AI
systems. And so you've got an interesting scenario where into your point there's all
kinds of edges. I used to think I knew what edge computing was in
the early days of IoT used to be like a rugged PC talking to machines
in a factory. And then the sensors and devices themselves got powerful enough that
we did compute there right at the very very end, right at the endpoint
almost, and so what we're able to do and then gosh, there's companies
that are doing edge computing like literally taking shipping containers like cargo shipping containers and
packing them full of servers and dropping them in someplace in a city and hooking
them up. And so the edge thing is super disruptive to the cloud.
It's also probably collaborative as well, and so lower latency because it's closer to
the source of the data or the people who need to use that stuff.
So since we put this edge compute, we are users of it, and
then tenants in the building or the building owners are also can use that.
And so I'd say our first product offering around that, that was a real
no brainer. With security cameras, turns out, lots of buildings, lots
of people are into having you know, different security cameras around their thing.
It's kind of a thing these days, especially actually it's booming these days.
I hate to say it, right, it's good for business, but it's
it's bad for society that we need more security cameras. And so normally you'd
have all these you know that the rise years ago is of IP cameras,
you know, and all these standards to stream HD video and record it and
do playback. And so a lot of folks are just streaming it off to
AWS or Azure or GC, you know, some cloud and they're paying whatever
for storage up there. So since we have this edge compute, we're like,
well, you're in the building, you could just stream all those HD
streams to us. And we have massive, you know, hundreds of terabytes
of storage locally on site with our edge compute, and so it's a low
latency, high speed way to get that stuff saved and recorded and then playback
really quickly. And then if you want to tie in all this crazy AI
stuff to it. You know, you're seeing more and more computer vision where
it can actually recognize what's going on or is this a person or if that's
a cat, or this person went from this place to this place or whatever,
you know, and so folks are interested in that. So that's a
good use case the same kind of business workloads you might run in the cloud,
you know, like there's the standard I need to spin up a VM
and I need much storage business workload. Sure, we do that at the
edge, as it turns out without having to buy the edge versions of Azure
or AWS. They'll have special fund names for those kind of things and having
to pay them for that. Turns out there's lots of great open source solutions.
Back to you were talking about Linux based on Linux, you know,
me being spending so much time in the time world. You know, all
the telcos, a lot of them are using what is it open shift,
which is red hat the open stack, you know, Canonical, Ubutu,
those guys. Yeah, they even have a smaller version that we've utilized.
It's literally, i think it's just called micro cloud. And so you can
imagine having being able to take a few nodes. It works with as few
as three nodes three servers basically, and it'll create a cloud instance and it
will cluster together storage and everything dynamic. It's so much easier than it used
to be when we had to really do this by hand. Yeah, and
then providing kind of that web interface and now we're providing it just to people
in the local, you know, building, and then they can click and
say, yeah, I want to spin up a VM that's using two virtual
CPUs and this much RAM, and I'm going to run my workload right here
in the building and it's going to be cheaper, it's going to be lower
latency, it'll be more responsive that kind of thing, uh, or just
or I just want to do storing data back data like you might do the
cloud or obviously there's no shortage of cloud based backup data services out there,
right, they can do stuff like that as well, and so they can
run workloads we'll run our IoT stuff is running at the edge in the building
and talking to all those sensors and all those building systems at high speed and
load latency, and so it's kind of a win win for both of us.
And yeah, customers are als, you know, a lot of I'm
surprised there's still people doing it closets today and they're like, can you be
yourn right? Well, And I mean I'm guessing that you have enough analytics
from some of the instances that you have to be able to do some consulting
on this stuff to be able to say, hey, you should put this
here, put that there. I mean data centers, you know, for
example, knowing where to put stuff in the room is pretty important, and
being able to track where the airflow goes you have your hottest machine means right
underneath this particular area, doctor, I mean, there are specific things that
you can do that take a lot of attention and take a lot of effort
to focus on. And it's so important because it's very expensive to run these
big buildings, and it really helps to be able to know what is this
cost, what are our options for being able to achieve this in some different
way, And just having another competitor to the existing cloud service providers is also
good stuff, like just because you'll see there's certain use cases where you really
want that very very low latency, you know, if you're doing a data
science project for example, or experimentation PII. They are all these different use
cases where it makes sense to not go up into the cloud, and you
guys are giving an option for doing all that, right, it's just another
option, you know. There was that notion. I think a lot of
us felt like with the growth of the hyperscale clouds that the data center business
was going to go away, and it turns out the inverse has been true.
They're building those centers like there's no tomorrow, and as soon as they
open they're being sold out, packed full of servers. Five years ago they
were doing bitcoin mining. Now they're all AI training factories. Wow. And
by the way, Helium was the company I was feeling of the guys from
Helium. They're the ones that do the low frequency I mean, that's just
so fascinating to me, using low radio frequency to communicate an IoT devices.
Well, folks, look this gentleman up online, Rob Tiffany from Red Bison.
If you're in the commercial property space, you want to be talking to
these guys. Folks, you've been listening to Inside Analysis. Okay, folks,
time for the podcast bonus segment here on Inside Analysis. A great show
with Rob Tiffany from Red Bison, and you threw out that great segue at
the end of the segment talking about training AI. And there's a company called
Hammer Space. I was on The Girl's Show a few weeks ago. They're
actually training Lama too right now, so that's pretty interesting. And she was
talking about how there are shortages of like you can't even get the processors because
everyone wants them, because all these companies are trying to train AI. And
you know, frankly, I know for sure that these AI models are going
to fundamentally change computing. You know, it's I look at you know,
like for example, when chat GBT was unveiled like in April or something or
May, I started playing around it. Within five minutes, I was like,
Oh, if it can do all these languages, I bet it can
do code too. Yes it can, Yes it can, right, And
it's like they all we had to show last week on this and they're just
talking about Usama Fayad, who is the chief data officer for Yahoo, was
saying, Yeah, really, scientifically, it's not that much that interesting about
these They're just weights. They're just weights, and it's a predictive engine,
but it has so much information that it is absorbed. And yes they do
hallucinate. Yes there are these issues, but I think they're going to figure
out a way around all that. And I think what you're going to see
is a whole new generation of software applications built on top of these things.
And guess what a company like red Bison, because you are running the network
as a service you're very well positioned to do these sorts of add ons and
to basically come in and say, hey, guess what, we have this
new service where we can help you train your own private instance by using all
this data of your usage of what you've done over the years. I mean,
there's all these things you can do if you have the data right.
Absolutely absolutely, you know you're right. Nobody can find those in video GPUs
that everybody wants. I mean, I guess in video was the biggest number
one stock performer in twenty twenty three. Yeah, because everybody wants what They've
got to train AI models and it's going crazy, and so you know,
being able to but I think you're also seeing AMD is starting to get some
love. Intel had to recognize that they need to get in that game.
And there's been a lot of talk in the last few weeks about aipcs and
neural processing units in just kind of desktop or laptop class devices, and so
so we'll be we take advantage of GPUs, you know, in our edge
compute, so that we can we're training models ourselves. And you know,
and actually to your point about writing code, as I've been building a lot
of technology, I've been using it as an assistant. You know, I've
used chat GBT and I've used a Microsoft's Copilot and they've integrated Copilot in with
GitHub and so you know, when I have to if there's some tough problem
you're trying to solve, you'd be amazed of how good it is at figuring
out you know, complicated scenarios or algorithms and stuff like that. And so
it's helped me to build software that does AI. Your ability to not just
have to use AI training software that's in the hyperscale clouds. There's a lot
of stuff you can do locally. You know, you can use Python.
I've been using a technology for Microsoft called mL dot net, the dot Net
framework and c sharp and all that stuff. In that world. They've they've
built a AI training system that's like Microsoft Times to make things easy, which
is great helpful to train models using a dot Net and c sharp versus Python
or R or something else. So and you can do it locally. And
so we can have that technology to train models right there locally at the edge
for folks. We can do it for ourselves. We can do it for
tenants, but you can imagine doing it for third parties who aren't even in
the building. Right, Like, when I think about how I'm designing our
edge cloud, basically is taking a lot of the ideas we had at Azure
and at AWS head this notion of availability zones. You know, you always
want to have uptime and availability. So you can imagine now that MDF on
the first floor might be the main place, but those other closets above there,
those are availability, these zones where we replicate data right across so that
different things can go down because the cloud's designed for failure. You know,
servers are failing continuously, but the software keeps it going. Yeah, so
we start there with availabilities one that way, the next step for us will
then be in the same city where we have other buildings replicating across that and
then so just like you know, just like you so yes, I'm sure
you'll say, yeah. I remember when I talked to some guy at read
Bison and they ended up taking down all the hyper scale clouds just quietly as
the thing just came to life, and it was in every building on every
city in every country. That's wild. It is wild, but there's a
demand. There's a demand to train AI models by people and people are looking
for compute wherever they can get it, and so data centers are being built
as fasts they can and so uh, that's kind of how I think of
our our edge cloud. You know, it'll do that edge IoT stuff,
but it'll will use it for other things as well well. And you hit
the nail on the head when you mentioned how they're just filling up immediately,
so you know, I remember just I'll close on this, but I remember
interviewing a guy from the Illinois Department of Transportation like thirty odd years ago in
my first job, and he made a really interesting point. He said,
the law does not allow you to plan the size of a highway based on
projections of future traffic. You have to look at existing traffic as your baseline
and then build the highways. And he said it's a bit of an issue
for us because as soon as we build these big three four lane interstates,
boom, they're filled. And they did that in Illinois with I three fifty
five, because you've got fifty five, which is a major highway and just
gets clogged as heck getting into Chicago. But they built three fifty five,
and I mean within days, it was just packed with cars, because now
you can go all the way up to the North Suburbs in like thirty two
minutes when he used to take you an hour and a half. So you
go see your friend up in the North Suburbs. You go shopping to different
malls and things like that. So people use stuff when you make it available.
Then you got to And the other thing with the data center is that
you reach the end of the data center, you cannot get one more box
in that data center. That's where the edge comes into play. Because if
you've got a bunch of these little edge nodes, then guess what, you
can very quickly absorb the demand and take their money and make good things happen.
Right, that's the plan. That's the I love it. Well,
look these guys up online. What a fun conversation with Rob Tiffany of Red
Bison. Send me email if you want to be in the show. Info
at inside analysis dot com. We'll talk to you next time you've been listening
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