Cognitive Buildings

What if your building could think? Cognitive buildings are an integrated approach to the Internet of Things concept.

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Episode Transcript

Speaker 1 (00:00):
Brought to you by Toyota. Let's go places. Welcome to
Forward Thinking. Hey there, and welcome to Forward Thinking, the
podcast that looks at the future and says, I'm an
ordinary guy burning down the house. I'm Jonathan Strickland, I'm Lauren,

(00:22):
and I'm Joe McCormick. Hey Jonathan, Hey Joe. Do you
remember the very first episode of Forward Thinking the videos
I'll never forget. That was a long day of filming videos. No. No,
we only did three that day. We wanted to do five.
So before we get into this topic, just so in

(00:42):
case you're curious about what this experience was like. I
had shot plenty of videos in the past, but never
one with a full crew. And we had a full
crew that first day. So we had sound people, camera person,
we had wardrobe and makeup, we had lighting, and we
had um producers who were there for the first time
to to like the executive producer types who were actually

(01:05):
there to watch this happen. There was a lot of
pressure on Uh. No teleprompter. I never used a teleprompter
for any of the Forward Thinking videos. UH might explain
a few of them to you, because I get a
little wacky and a little off script, so, uh intern't
knowet things was one of the three videos we shot
that day. I remember three D printing was one of
the other, but I don't remember what the third one was.

(01:29):
Oh it was it was a car one I think,
um self driving cars. Self driving cars. Yeah, yeah, because
we actually had a a a car in the studio
that we used. It was not an actual self driving car,
but we treated it as such. Uh So, anyway, Internet
of Things has a long, long, long history with The

(01:50):
Forward Thinking Show, and of course we talked about on
the podcast too. All the time, it comes up a
lot smart devices all around you. We've talked about smart
devices in your kitchen, smart devices in your in your
body right, and the whole idea of just having sensors
that are collecting data and devices that can use that

(02:11):
data to change your environment in some way. This is
not something that you know is a new topic, obviously,
but we wanted to talk about a specific implementation of
this where you incorporate directly into architecture. And this is
an area of research that IBM is conducting. They call
it cognitive buildings. Yeah, so I would say this relates

(02:34):
to the Internet of Things in that it's sort of
like the Internet of Things, but a top down, integrated
approach to it, right, right, Yeah, this is an idea
of we have the capability of incorporating all these different
types of sensors and systems into a building piecemeal, but
what if we were to do it from the design
of a building and incorporated, uh directly integrate everything so

(02:59):
it's into a parable And this is a big idea
that could potentially have uh some some interesting benefits down
the road. So it's something I wanted to explore a
bit more. Um, It's a pretty pretty simple idea that
I think a lot of people can grasp early on, right,
Like the idea of a building that has all of
these things integrated in it and then essentially has like

(03:21):
a pretty hefty processor to take in all that data,
crunch it, and then uh respond in whatever way is
most appropriate, right right. And the process that IBM is
is using for this kind of concept is cognitive computing, yes,
which involves lots of different topics We've talked about before,
artificial intelligence, pattern recognition, a natural language processing, data mining,

(03:45):
machine learning, all of that is part of cognitive computing.
Generally speaking, cognitive computing is trying to use computers to
simulate the way we think, not necessarily in a like, uh,
granular way where a processor is behaving the way a
brain is, but so that the output is similar to

(04:06):
what you would have if you asked a very smart
person to do the same sort of stuff. So it's
a problem solving kind of technique, and it's using some
of the data processing that we've talked about in our
episodes about deep learning. Yes, yes, so if you can
imagine the same sort of stuff that produces incredibly trippy
paintings could be running your home in the future, driving

(04:28):
you mad over a series of entertaining days. I just
realized that we we may be able to put together
in the future tutor a tutorial on how to overclock
your house. That's actually it's not too far off from
from the possible reality, right, So uh, ideally, what this
would result in is a system that would learn about

(04:51):
you as you move through it. So whether it's your
office that you work in or the home that you
live in, if it's a cognitive building, it actually learns
about you, your preferences, your needs, and is able to
respond to that in a way that is seamless, so
that you don't have to even think about it. You
don't even necessarily have to voice a command UH if

(05:13):
it's learned enough. This is not that far off from
some systems we have now, Like the Nest thermostat is
an example. It's easy to point to because it's been
around for a few years. So Nest thermostat can detect
when you are home using motion sensors UH. It can
have some pre program temperatures that you could tell it like, well,
at night, I like it to be around this cool.
During the day, you can turn the temperature up a

(05:35):
certain amount. It might even have have other parameters saying, well,
while the person is gone, we can even crank that
up a little bit more so that we're saving energy.
You know, the a C is not blowing when no
one's home, and we also know that typically the person
gets home at around this time, so we can turn
the a C back down UH an hour before they
get home, so that way the house is nice and
cool by the time you walk through the front door.

(05:57):
That's a pretty easy example, and it's one tiny system,
but in a cognitive building, it would be one part
of an overall integrated system, and it would just be
one element of that. Imagine a building able to measure
pretty much everything you're able to do inside that building
and respond in a way that helps you save energy
so you're not wasting it and also makes the experience

(06:20):
pleasant and comfortable for you. That's kind of the basic concept,
but it's way harder than what it south. Yeah. Yeah,
we're not really quite there yet to the point where
in most buildings we are prepared to do that. Like,
like right now, if you if you want to integrate
all of these different Internet of Things type systems you're uh,

(06:43):
your smart lights in your in your nest, and your
eye toaster, you're gonna need to get a third party
thing that's going to connect up with all of them, right,
because otherwise what you're talking about is having a phone
with eighty thousand apps on it. Like I need to
turn off my lights. Okay, let me just scroll through
all right, it's an this folder. Okay, let me scroll
down through here, there's my light folder. Like it's ridiculous. Right.

(07:04):
If you if you go through a single service provider
or product manufacturer that makes lots of different stuff in
that space, then maybe you could get away with two
or three systems all using an integrated app. But I
don't think anyone makes all the different types of home

(07:25):
automation systems that you can run into. So if you
really wanted like the automated home of the future, the
downside is you're going to have all these different interfaces
that you have to work with in order to make
that happen. Uh. The alternative, as Laurence said, is to
get a third party object that is able to be
kind of like a liaison between you and each of

(07:47):
your disparate systems, one app to rule them all. Yeah.
So Amazon's Echo is a great example that has Alexa,
the the voice activated digital personal assistant. And Alexa can
work with lots of different systems, right, It can work
with Nest, it can work with certain like I think
Phillips Hugh light bulbs. So with Alexa, you could tell

(08:10):
Alexa what you want and then Alexa would communicate with
the appropriate system on whatever terms are necessary for it
to get this done, and it would happen. This is
an inelegant way of going about this because you still
have to have that intermediary. This is essentially translating your
commands so that whatever you want to have happen happens.

(08:33):
It would be it would be nicer to have a
fully integrated system that does this all automatically because it
fully understands you not just what temperature you like, but
what light level you like, and what music you like
and uh, you know, even things like what you prefer
to eat, because this could be incorporated all into the
appliances of your house, not just the lighting and the

(08:56):
climate system. And all of these integrat sans can ultimately
result in energy conservation, which is I think, I would
argue is the biggest point of concern for the IBM
research team. Uh So, designing this building not the easiest
thing in the world to do. You have to have
all these different sensors to detect all sorts of stuff,

(09:18):
you know, temperature, lighting, electricity, water flow. Perhaps. Uh it's
a big job. And in fact, the IBM research center
that they have, they've got a lab with more than
three thousand sensors integrated into it. It's about a four
ft by five ft cubicle. No, I don't I don't
know how big the lab is, but it's not it's

(09:39):
not as far as I know. It's in Dublin, Ireland. Um,
it's not as large as like a full building as
far as I'm aware, Um, but still, I mean, and
if you think about that, if you think, well, if
it's not as large as a full building, then a
full building would need probably even more sensors to get
comprehensive data. All right, But I mean think think about
how many different factors you're you're trying to integrate here

(10:00):
and and this is in every single room in the
entire building. So you know, you're you're you're looking to
detect motion, perhaps have facial recognition, uh, detect light levels
like natural light levels to detect temperature, uma, detect water
use to detect everything that's going on, and all of
the pipes to detect what the sewage pipes are doing. Yeah,

(10:24):
there's a lot of sensors for every single room, and
and you think about that. You you ultimately have all
of that data sent to a central processing unit a
a computer of some sophistication to make sense of what
that information means. It may mean that certain choices in
order to conserve energy could at first appear counterintuitive because

(10:47):
it may be that it's taking into consideration a lot
of factors that you, as a human being inside that building,
aren't necessarily aware of at the time. So it's like
in a closed room, the amount of sunlight that the
roof is getting somewhere near you could definitely affect the
temperature that you're experiencing. Yeah, that's a that's a simple example,
and there are so many out there. Everything like if

(11:09):
if the room happens to have a whole bunch of
pipes that water flows through, that might affect things as well.
It's it's really complicated stuff, and so that's why you
need like the really powerful processing ability on the other
end to make sense of that and turn it into
actionable items that the house can can then go through. So,

(11:30):
like I said, saving energy, that's like the primary purpose
for this project, and a cognitive building could keep track
of all the rooms that are in use which ones aren't.
Essentially it's like the very complicated way of telling people, Hey,
turn off the light when you leave the room, except
now the building is doing it for you, and also
maybe adjusting the the air conditioning for that room. If

(11:53):
if there's like different air conditioners for different floors or
different even different sections of the building. It can manage
it on a very grand, a little granular level. Ah,
And it's h it's pretty intense to do all this.
It's is an intense processing and intense data gathering system.
It's really taking that big data approach on a building

(12:15):
by building or collection of building kind of scale, which
is also crazy because IBM research is looking not just
at making one cognitive building, but making groups of them.
Oh sure, yeah, not not just like personal homes, Like
it's kind of easy to think about this on a
single home kind of level. But but of course they're
trying to expand that out. Yeah yeah, So, uh, let's

(12:36):
say that what where can you where can you go
besides energy conservation? I mean, that's obviously a very important element,
but what else could you do with this? One thing
that IBM is proposing is a system that could detect
problems before they become so great that you have to
have like an emergency response to it. So, let's say

(12:59):
that your smart sensors detect that your air conditioner is
working harder than it normally has to in order to
maintain the temperature. It may mean that you need to
change your air filter, right, it may be something as
simple as that, or maybe that uh oh, we're detecting
a decrease in pressure in the tubes and your your
free on or other your coolant is leaking somewhere. It

(13:22):
can then send you an alert. You get alert alert
on your phone saying hey, by the way, I've detected
this drop in efficiency. Um, the diagnosis I have is
such and such. If it's something like switching out of filter,
you could probably do it yourself. If it's something a
little more complicated, might say that you might need to
call someone, and may even bring you give you suggestions

(13:42):
on who to call, depending upon the way you've designed
this building. Same thing could be true with plumbing. It
could say, well, I detected that they're the the waste
pipes aren't flowing as properly as they should. It may
very well be that the vent that allows air to
pass through the the waste pipes has been clogged with something,
so you need to just run some water down the

(14:05):
vent to clear it out. And then you don't have
to bring a plumber in to do an expensive job
when you can just do it yourself. This is something
that I actually had to go through myself recently. I
had to I didn't have a computer tell me. It's
just one of those things where I thought this drains
backing up. I sure hope the venice claude because that's
an easy solution. Turned out it was, But it would

(14:25):
be great to have a system that tells me that
oh sure, yeah, you know it's something that's that's telling
you where you've got a a leak in a pipe
or a leak in electricity flow. Sure a you know
if if if you're if you're in an area where
your pipes might freeze during the winter. Um, something that
can automatically regulate the temperature in problematic sections at the

(14:47):
house to not let your pipes freeze, yeah, or or
an automated tap of some sort that can just let
enough water flow to prevent it from freezing up right right, Yeah,
it is Yeah, that that that would be great because
again it saves you money in the long runs. It
uh ends up also preventing further damage being done two
elements of the home or the building. It would be

(15:10):
a huge benefit sure And speaking of money, hey, in
multi home buildings like condos or apartments or whatever, you
could track who's using the most resources and adjust the rent. Wow,
So you'd have to pay for the number of times
you flush the toilet and your landlord knows Yep. I mean,

(15:30):
I mean a lot of a lot of a lot
of apartments and condos that I know of have there.
You don't have a have a collected waste removal kind
of fee. You know, I think it's only fair starting
to get into brazil territory. And here's my receipt for
your receipt. Uh. Yeah. And beyond this, like I said,

(15:51):
this does actually remind me strangely of Brazilian Yeah that really? Yeah,
will this cognitive building have ducks? Will There'll be lots
of ducks? How man? Yes, require duct repair people, not
side ducks. I've already been yelled at for talking about
Pokemon Go too much. Uh. As I mentioned earlier, it

(16:12):
doesn't have to just be a building and can be
a collection of buildings. The example that they gave was
imagine a college campus that could actually track the movement
of students not just within individual buildings, but across different buildings.
And then it starts getting into a really complicated kind
of approach where if if you're designing it in such
such a way so that uh it's as a seamless

(16:35):
and experience for the people in there, but also one
that conserves the most energy possible, and it's as busy
as like a college campus that gets pretty tough to
do too. Um. I was really impressed when I was
reading about this, and I was curious, like, how could
they even process this information? And then I found out
that the back end, the brains behind this is essentially

(16:58):
IBM Watson, Like, oh, that would do it. I don't
happen to have access to one of those, but I
can understand how that would help. Um. But it's not
just not just convenience or energy conservation in these cases
that could be helped out too. Oh yeah, stuff like
response to a security or emergency situations could be streamlined

(17:20):
because of the way that everything is connected and the
way that it knows who's coming and going, which gets
back into weird Brazil territory. There's some some privacy issues obviously, sure,
but beyond that even you know, like they would never
run out of your favorite soda in the vending machine
or out of toilet paper in a bathroom. Now you're
speaking my language. There's nothing like just taking that casual

(17:44):
glance over and then thinking I have committed to an
action that I regret now. Wow, yeah, thanks for taking
us there with you, hey, you know, I was speaking
in a circumspect kind of way. I was trying to
be as gentlemanly about it as possible. Hey, how about
another example of a cognitive building that they actually talked
the IBM team is talked about hospitals. Yeah, and this

(18:06):
is a this is a really kind of inspiring one.
So not just energy conservation here either, but also trying
to improve the health and safety of the staff and
patients in the hospital. One of the biggest challenges facing
hospitals is managing infection and contagion. I mean you hear
people say this all the time, like I don't want
to go to the hospital sick people are there. Yeah,

(18:28):
and we talked a little bit about this in our
episode about antibiotics. Yes, so yeah, hospital acquired infections are
real things. Yeah, absolutely, And so it's it's you know,
it's a it's a dangerous environment to be and even
when people are very carefully following protocols. So a smart
building version of a hospital might be able to help

(18:49):
in that way by improving the airflow and even uh
controlling air pressure in individual rooms to help maintain some
safe between different patients, to contain areas that might have
contagious uh pathogens in them or uh some other form
of of infectious material, so that you minimize the risk

(19:12):
of this spreading to either staff or other patients. Also,
just knowing which rooms are occupied and which ones aren't,
I mean you can save energy that way too. You know,
one thing that occurred to me when I was thinking
about the example of the hospital is what if your
buildings in a sense could actually do science for you,

(19:33):
like doing data analysis, And by that I mean taking
the kind of data the buildings like this would naturally
be collecting, and then pairing that with some other kind
of data and cross referencing to see if any correlations emerge.
So in a hospital environment, for example, that might mean
you you're pairing this integrated environmental data like you know

(19:56):
room temperature and where the lights are on, all that junk,
you know, the hundreds of variables the buildings collecting just
about the environment and what appliances are being used, and
you pair that with linked data about health outcomes. You know,
we might not find anything interesting. It probably wouldn't surprise
us if environmental data about the building had no real

(20:16):
correlation with health outcomes. But what if in some cases
it did in ways that we wouldn't have even thought
to look for if we had to do all these
analyzes ourselves. Just like what if patients in rooms with
lower air conditioning temperatures had fewer complications during surgery or
something like that. Yeah, and and this could also help
us us out what's going on with a sick building syndrome,

(20:40):
which is which is the phenomenon in which there tend
to be these these just kind of breakouts of long term,
low grade illness among office workers who work in certain environments.
I can imagine that I've worked with people who have
made me feel sick before. It's it's suspected that it's

(21:03):
usually due to like air quality of some kind or another,
either like surrounding pollutants or mold and mildew or etcetera
flickering fluorescent light that gives you a brain cloud, but
it can also be march. Why march another thing that
you have. When you talked about the building itself gathering data,
it occurs to me that you could even incorporate the

(21:26):
actual like you would probably want to scrub this of
any personal information, but you could you could incorporate things
like the actual nature of diseases of patients in actual rooms,
and the building itself could become a data collection point
and perhaps be an early indicator for something like, Hey,
you need to be on the lookout for an epidemic,
because based on the statistics that we're seeing here and

(21:46):
the number of patients who have come in with this
similar or identical condition, there could be a source nearby
that's making people sick. It could give people the information
they need to actually address the source of an issue
before it gets even worse. Yeah, that's kind of I
never even thought about that, but that is really cool. Yeah. Also, um,

(22:10):
what about what about factories? Um? I mean these these
are places where things are already fairly streamlined, but a
cognitive factory could could monitor the waar too. Again to
like every piece of equipment and alert staff if the
if the heat levels or the sound of the moving
parts or whatever it is, um indicates that something is

(22:30):
about to wear out and and get in there and
replace it to to prevent a costly and time time
consuming or or even a hazardous breakage. Right. You know,
factory environment seems susceptible to the same kind of automated
scientific analysis that I was just talking about. With the hospital,
where you could have the building just ambiently collecting all

(22:52):
of these variables. And whereas in the hospital you'd compare
all that data to health outcomes, in the factory, you
could compare it to productivity or you know, other business.
It turns out that oh, what do you know when
we when we have more lights on in the building,
people have a ten more productive day. Yeah, and it

(23:13):
could even limit downtime. I think that's kind of what
Lauren was saying. It could limit downtime, which time is
money for a factory. So just for this kind of application, uh,
it could be invaluable. You know, it means that you're
you're you're constantly producing or you're producing as much as
you know your factories, as opposed to saying, well, an

(23:35):
unanticipated breakage stop production for four days, that's four days
lost productivity. So a system like this could prevent that
from happening and thus increase profit. And and that's true
I think for for other businesses as well. I mean,
we are all really just producers of content, are we not?

(23:56):
So so okay, So, so imagine an office building wherein
you're an exchangeable human cog with a mobile computer and
when you get to work, you could just be shuffled
off to anonymous workstation seventeen s w D eight and
all your coworkers are are organized to save your corporate
overlords from having to to heat or cool half empty floors. Beautiful, right, Okay,

(24:19):
it's a glorious vision and I welcome it. Or or
at least your elevator banks could could know when people
are approaching and thus minimize your wait times. That's a
glorious vision and I highly anticipate that one. Or or
by tracking WiFi connectivity throughout the building, your I T
kids could maximize the placement of your tech resources so

(24:43):
that your computer never runs into the problem that we
run into in our Sometimes this has been inspired by
actual events. Yeah, here's the thing. Now, would would some
of the data collection in the building just be microphones
listening for whether people are cussing about what they can't get?
Why by you know, it's like, if you hear these
combinations of words, we need to do something about the

(25:04):
connectivity situation. I'd be i'd before that kind of privacy breach. Honestly,
if if it would lead to better WiFi, well we're
gonna talk about something kind of similar to that in
just a moment. Actually, But but when we're one more example,
uh shopping, shopping, y'all. Uh, when when you when you
go out to a store, or if you're managing a store,

(25:25):
you know, this is another kind of business and in
which this kind of technology could could be pretty great.
You know, like Okay, so, like you might be saying,
but Lauren, bar codes and QR codes and wireless scanners
and integrated checkout and warehouse systems, like all of that
stuff is already given stores a pretty incredible power to
to harness big data. But a cognitive building could could

(25:48):
help the staffing and the stocking and just tracking how
many people are in a store in any given time,
tracking what those numbers look like over the course of
a day, a week, a year, um. Correlating purchases to
weather trends, hunting down items that customers have infuriatingly put
on a different shell, you know, just all all of
that little stuff to make Yeah, time is money. And

(26:11):
I can just imagine that that you're you're building, you
own a shop, like a like a sporting goods type
thing and or maybe just general goods type of thing,
and that your building says Hey, about two hours, it's
gonna start raining. Put the umbrellas out right, which I
mean that people do that, but you know, take advantage

(26:31):
of that for some reason, also sell all the grind cups.
It's just just it's like, man, every day I opened
up my email message number one. Well, as I mentioned, sorry,
you said sporting goods store. I was confused why. I
was just thinking of like a place that would possibly

(26:51):
have umbrellas to sell like some places do in some
places don't. I wouldn't say. You go into a pet
store and it says put out the umbrellas, fair enough. Oh,
but those are the two things. I guess. I know
that sporting stores umbrellas and basketballs. I suppose I probably
they've got a lot of sports ball stuff in there.
I've seen it. So as we were saying the brains

(27:12):
of this IBM s Watson, Yeah, and we've taught so
much about Watson and other episodes, Watson could also help
them with the cafeteria menu. Can you just see people
walking into work every day saying, man, I dread lunch. First,
grill your lettuce, Yeah, that's for your lettus, free burgers.

(27:34):
Rill you're olive paste, yeah, Watson's chef Watson is still
I still maintain that one day we're going to have
to bring in food that we've we've cooked based off
a Chef Watson recipe, have a taste test, probably not
on microphone because that's gross. We're gonna we're gonna keep
saying this every time Watson comes up until it happens. Yeah, so, hey,

(27:54):
we we have that snack stuff. That's true, that's true.
We do a live stream where we occasionally subject employees
of how stuff works to eating things that are unusual,
sometimes delicious, sometimes not so much, sometimes painful. We've got
a hot pepper one coming up pretty soon. I think, yeah,
I'll be exciting. Oh I wasn't invited for this, the

(28:16):
hot pepper one. You're totally invited if you want, because
there's there was an email change. We're talking about ghost peppers,
and then I said, well I had a Carolina Reaper
the other day, which is the hottest pepper so far,
and uh, that kind of precipitated into this macheesemo thing
about hot peppers that apparently I've been pulled into. So

(28:36):
not I'm not protesting anyway, I've got off track. So
Watson yes, it is the brains behind this, but beyond that,
they've used Watson to do some interesting analysis. They actually
collected about five million tweets about different buildings around the world,
and they were looking for people describing something in those buildings,

(28:56):
either in a positive or negative way. They aggregated all this,
they analyze the data, and they started crunching the information
to find out who has the best and worst features
of various things in various buildings around the world, like
like what what ideas can we steal and what should
be definitely avoid for building the best type of building
we possibly can. So apparently the best elevators in the

(29:18):
world according to people commenting about this on Twitter. And
remember these are just casual tweets. It wasn't like someone solicited, Hey,
who do you think has the best elevators? This was
just based off people tweeting the information on their own.
The best elevators, according to this analysis, would be the
elevators in the Empire State Building in New York City,

(29:38):
which I was in once when I was thirteen and
haven't been in since. So why are they the best?
That's just because they were the most positive comments about
these elevators in all the in all the data that
they crunched. Yeah, it seems like that might be affected
by things like you know, what are the elevators people
are based on the site? Most absolutely, I would argue

(30:01):
this is not that different from something like Rotten Tomatoes,
where you look at the score and some people say, oh,
the score is indicative to the quality of the movie.
But really, what the score just tells you is what
percentage of critics gave it a positive review versus negative review.
It doesn't give you an indication of the overall quality
of whatever that thing is or how much you'll enjoy it. Yeah. So,
at any rate, all three of us like very very

(30:23):
terrible movies. We do not always not always the same
ones though, uh so. Ibms Watson says that according to Twitter,
Empire State Building is the best elevators, and according to Twitter,
the worst air conditioning in any major building in the
world is in the Louver. That makes sense to me.
Pretty stuffy in there and very French. Uh. And if

(30:44):
you need to take a bathroom break, the best place
to do it is in the Sydney Opera House. I
don't know if that just means that the bathrooms are
the nicest, or maybe they pipe in the opera nice
and loud so you can do your business and not
worry about anyone hearing what's going on in there. Yeah,
you've thought this through. Yeah, I mean, I mean it's fine.
I mean, that's that's a great thing to know. But

(31:05):
other than the kind of like kitch factor of all this,
like what what are we really looking at it? It's
sort of like identifying the best practices for various features
and saying, well, if people really like the way this
one thing works in this one building, maybe we should
pay attention to that. Maybe we should try to incorporate

(31:26):
that same style, that same design, whatever it is that
makes that thing the best in its class, so that
we can uh make future buildings awesome And for all
the ones that are identified with negative features, we can
avoid those so that we don't make really awkward, awful
buildings unless we want to do a really weird art
project where everything is terrible. But if they keep going

(31:49):
just by what people tweet the most joyfully about, every
building is going to have an ikea monkey. Well, this
is again, this is just one part. Don't see the downside.
It's just one part of the overall approach. So it's
one of those things where I saw it and I thought, well,
that's kind of interesting that they're not It's not just
cold analytics and and uh, personality free data. It's also

(32:14):
taking into account you know, what are people passionate about, what,
what do they find comfortable or awesome or cool or interesting.
What do they find uncomfortable or inefficient or aggravating, and
and what are the specific elements that go into that,
so that when we designed the buildings of the future,

(32:34):
we can eliminate as much of the negative stuff as
we possibly can, incorporate as much of the positive stuff
as we possibly can do it in a way that's
as energy efficient as we possibly can make it, and
may get responsive to all of our needs so that
it's a fantastic place to be in all the time.
And as soon as my house does all this, I
will never leave it again, so it'll just collect data

(32:59):
on you night and day. Is my my house is up?
My house is buddy, Buddy with the n essay, are
you kidding me? Um? One of the other things I
didn't put it in the notes, but one of the
other things I thought was interesting is they're talking about
incorporating a R and VR into various buildings in a

(33:20):
very uh like uh like into the not literal foundation
of the building, but into the building itself, so that
you're talking about a holidack. You could have something like
that like there there are there are never went well, look,
we only saw the episodes where the holiday didn't work.
We didn't see any of the episodes where the holiday
was perfectly fine. It's like the van is always at

(33:42):
the corner. You only notice that when it's at the corner,
and when it's not at the corner, you don't even
think about it. Um No, really, that holidack was a
terrible idea, But now they I have seen like amusement
uh like an amusement part type thing where there is
the incorporation of augmented reality or virtual reality and physical

(34:03):
objects within the environment that are mapped to the virtual environment,
so that you can pick up things that are appearing
to you in the virtual environment, but because there's a
physical object that's mapped to you're actually holding a thing.
Oh my god, I just had a great idea for
a home augmented reality application. It would be to haunt
my house, app that it's your own house. But this

(34:26):
just puts some ghosts in it. I was about to say, like,
if you could, like I keep saying, imagine wearing something
like Microsoft Hollow Lens and playing something like pt that
playable trailer that came out for the Silent Hills game
that never happened. Imagine walking down your own hallways and
seeing that stuff. Nope, nope, never sleep again. I think

(34:49):
you'd be pretty awesome. I'd do it at once, Like
I'd be like, honey, um, I'm never sleeping in the
bedroom again. Enjoy I'll be I'll be asleep in the
office see later. Certainly not I was. I was just imagining,
because I'm equally terrible, but in a different bent, that
you could you could have like a physical clippy that

(35:11):
could just help you tour around unknown places. Cool. Yeah,
I see that you're totally lost. Would you like to
be for me to direct you to the specific location?
And if it's a physical object, the best part is
that you could literally throw it out a window. I
like the idea of being in your house and they're
just Pokemon everywhere already happened. That's crazy. But oh yeah,

(35:39):
you're just looking around, you see him, and you're like,
I gotta catch that one, and it's like mapp to
your pet. But then you have to wrestle your pet.
My dog is fast. It would be a challenging and
fun experience for the both of us. But I don't
want you to put your dog in a poke ball.
He'd be fine with it, he'd love it. No, Seriously,
be kind to your pets and be kind of mine too.

(36:01):
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(36:49):
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