Walk downtown in Seattle
and you're likely to come across this.
Oh, sorry. I mean this.
It's technically an Amazon office
but really it's a gaudy show piece.
Look at us. We're Amazon.
We built a rainforest smack dab in the middle of Seattle
and encased it in silver balls because we can.
It's the kind of thing that seems like a good idea
right after you've drained your blood boy
but that you later regret.
Next thing you know, you have to build a stand
right by your giant balls
and give away free fruit all day as an apology.
We're sorry for what we've done,
have as many bananas as you'd like.
Seattle's obscene wealth
has turned the real estate market here
into a brutal free for all.
Just ask these people.
The sprint to find permanent housing here,
whether you're buying or renting is insane.
And to actually buy a place
feels out of the realm of possibility
unless you're a millionaire.
It just seems like it keeps getting worse and worse.
The inventory is pretty tight.
It's hard to find really good stuff.
I think renting was easier.
I was kind of shocked at how expensive everything is
and how competitive the market is.
The Seattle housing scene in one word -- crazy.
I'd say it's a gauntlet.
It's cutthroat.
Mm. Trouble.
To learn about the latest in Seattle real estate
and the art of selling a home here,
I went straight to the top.
Let's roll.
I paid a visit to my old friend, Glenn Kelman,
the CEO of Redfin.
I should warn you that almost no one
is willing to get in the car with me while I'm driving.
It's too late now.
And if at any point you need to grab the wheel
to save us from death, I won't resist.
How do you feel about the yoke?
It's terrible. Yeah.
It's Elon Musk just being opinionated to be opinionated
without actually being better.
I have this theory, by the way,
I think about when people can stand up to CEOs all the time,
'cause I worry that people can't stand up to me.
And for me, the signal version of that is Jar Jar Binks
where clearly, no one can tell George Lucas
what a racist disaster Jar Jar was because he was surrounded
by 100, like 18 layers of sycophants.
I think no one could tell Elon
this is an accident waiting to happen, this steering wheel.
And I can't figure out what mistakes Redfin is making
that no one has the courage to tell me about.
I used Redfin back in the, yeah.
I didn't know that. Really?
Yeah, yeah. I told, you did know it.
No. Once. You did.
I store that shit.
I shouldn't have said the S word, but--
No, you can.
No, you did, 'cause I had gotten to know you
and I was like, oh fine,
I'll give this Redfin thing a try, then.
I feel like you've dated me
when I was a teenager and had braces.
It's so much better now.
So technology is supposed to make industries more efficient.
With real estate, we just found the perfect foil
where you have an agent
who isn't always acting in the customer's best interest
but also charging a high price.
And so we thought that by using technology
we could make the agent more efficient.
We're on our way to see a home
that Redfin bought, refurbished and then sold for a profit.
Buying and flipping homes like this
is a huge risk for the company.
Just ask Zillow.
If housing prices go down,
Redfin might get stuck with money losing inventory.
Glenn's belief is that Redfin can use its technology
and experience to lower the risks.
It analyzes thousands of data points
to monitor quick changing trends
in housing markets across the country.
A mix of machine learning algorithms and computer vision
tell Redfin where to buy homes
and what quick fixes will result in the best returns.
First of all, there's just the fundamental problem
of trying to figure out what a home is worth.
And the reason that you need machine learning algorithms
rather than standard computer science
is because a basement is very valuable in Seattle,
whereas a pool is valuable in Atlanta.
It is constantly reevaluating what factors matter the most.
And so one of them is a pricing algorithm.
And then another one is about renovations in computer vision
and trying to assess the quality of the property
based on photos.
Oh, okay.
The little house here used to look like this,
cozy, but not exactly Seattle's finest.
Unless you're into smoke-tinged yellowing walls.
Redfin has revamped the place
in the hopes of kicking its price higher.
And Heather here is one of Redfin's chief revampers.
This isn't necessarily someone's individual personality.
And you know, we're just trying to position the house
so people can see what the potential is.
So we wanna keep it kind of neutral.
Are there any other just tiny details
that people wouldn't think of, like the kind of faucet or--
I think anything that you touch, right?
So that's why we wanna put in new plumbing fixtures
or we wanna make sure that there's new knobs
because I think that makes it feel
like it's a good experience.
Okay. Yeah, no, that makes sense.
The simplest thing that has the highest ROI
is just update the kitchen without replacing it.
Paint is just transformative,
so paint your whole house and keep it neutral.
Makes sense.
Make sure your flooring is consistent.
This might seem like normal renovation stuff,
but it's all pulled from Redfin's algorithms.
We're doing 5,000 sales a year
and we're capturing data about what works and doesn't
and the simplest lesson is to not overdo it.
When we have lost our shirt,
it's almost always doing too much, not too little.
How many times did you screw it up before you guys,
you know, is this--
You ask as if we stopped screwing it up.
The promise of Redfin has long centered
on lowering commission rates
and trying to modernize real estate
and some of its dubious practices.
Redfin, however, has faced recent criticism
and even been sued for offering better services
to affluent customers.
Glenn says he takes these critiques to heart
and he promises that he's more than some rich guy
capitalizing off a crazed real estate market.
People pay 60 to $80 billion in real estate commissions.
And no one would ever pay that
if you actually had to dig out your wallet
and hand a real estate agent 30 or $40,000.
So technology is supposed to make industries more efficient.
The second part of it is more about social justice
that still lenders who decide that someone who is
Latino or Black is less likely to be able to afford a home
and even if they got the same income.
Why would your agents be less inclined
to do those sorts of things than others historically?
You can't control any human being in every way,
but we can certainly say that when you list a home,
you need to make sure that everybody can see
that it's for sale instead of just posting it on Facebook,
which has become especially popular in Silicon Valley.
You need to give people fair housing training.
So I'm not trying to get on my high horse on this one
and say that we're the end all and be all of fair housing.
But the way that housing has been working
over the past 50 years
can't be the way it works over the next 50.
Okay, so you've been in Seattle now for a while
and I know you don't wanna bad mouth the home team,
but you were-- I love Seattle but--
But you felt like Vancouver's
kind of where the action is or?
Yeah well, it's almost a tale of two cities
because first of all,
Vancouver just has different zoning than Seattle.
So when you go there, you'll see,
it sometimes feels like Hong Kong.
It's very dense and bustling
and Seattle has begun to address that.
But for a long time, what really shaped the Seattle skyline
was this rumor among developers
that Jeff Bezos didn't like buildings
that were taller than eight or 12 stories.
The windows had to open and it had to be tall enough
or low enough that you could take the stairs.
And now the second part is that Canada
is outranking the United States as a destination
for international tech talent.
You have all these foreign students
who believe in the Canadian dream
instead of the American dream
and I think it's really becoming this tech center.
Some of it's urban planning
and some of it's immigration policy.
Yeah. But you're hanging tight in Seattle.
When you actually think
about turning in your American passport
and becoming Canadian and pumping your gas in liters,
it's still a step.
Yeah.
No trip to Seattle is really complete
without some time on the water.
If you're lucky enough, you can find a nerdy sea captain
who will take you out with his crew.
Nathan here used to work with the other Nathan
at Intellectual Ventures.
Then he started a company called Kymeta
that made crazy antennas.
And now he started another company named Rendered.ai.
It makes something called synthetic data.
How are you making the first image of this fake x-ray?
I mean, this--
Literally you can build 3D models,
in Blender or other tools and then simulate them using that.
And this would just either make many, many, many
x-ray images that then get fed
into a machine learning system to see what it can spot?
You go through the airport, right?
They of course scan your baggage
and that's going through an AI.
Do you know how they train that AI?
They literally have people pack bags
and pass them through that
so they can be like, that's a knife, that's a banana.
That is done by hand today. Okay.
So as you can see that has some gaps.
They just have people spending thousands of hours
passing things through?
They do. Okay.
Modern machine learning AI
needs to go through a process called training
where it's fed tons of data
in order to learn how to do a task.
Redfin, for example, feeds its algorithms
data about real estate.
But unlike Redfin, not every company
has tons of information at its disposal
to train its machine learning algorithms.
So what rendered AI does is manufacture data
out of thin air.
It then feeds AI algorithms with this information
to teach them how to perform certain tasks.
These are all synthetically created bags.
This is like add a phone and add a lipstick.
You don't just simulate the x-ray simulation, right?
You can simulate the packing itself,
you can simulate the folding of clothes.
So we have a lot of different simulations on the platform.
So we do satellite imagery, we've done infrared imagery,
we've done security cameras.
We've actually done microscopy
and studied oo sites in human reproduction.
So you're making fake cells?
Well, yeah, like fake embryos, literally.
Sometimes you wanna run tests to see if the AI
behind an expensive piece of technology will even work.
For example, startups are rushing to send satellites
into orbit that photograph the earth in different ways.
They're packed full of expensive,
often experimental sensors.
Rendered AI can help gauge if these sensors will do the job
they're supposed to before you pay
to build and launch the satellites.
Well, you could imagine questions like,
hey, I wanna detect forest fires, right?
Okay. I've got visible cameras in space.
How much sooner can I detect a forest fire
if I was detecting an AI?
So you guys could sort of simulate
what forest fires would look like from space
and do that millions of times
and then maybe we start to see that these patterns
kind of emerge before one breaks out.
Exactly.
What Nathan is talking about is a weird concept.
The AIs need information to become good at their job.
And they're now being fed by other AI systems.
Soon he imagines AI's training the AIs that train the AIs.
What we're doing with synthetic data
is about not just training the AI,
but training the tools that allow us
to do this world building and procedural generation
and it does feed on itself.
And absolutely, that's gonna lead to all sorts
of crazy and unexpected things.
Although I will say,
I'd start by being able to successfully detect cars.
Yeah.
It'll be really good
if we can do that really well.
Everybody ready to tack?
All right. Coming about.
Perhaps there's a divine entity up there
with a giant computer simulating all of this.
If so, well done Supreme Being.
But for the moment, I'm gonna assume this is real
and I'm going to revel in it.
Next up on "Hello World,"
I head to Canada to pound some maple syrup.
It's pure.
And visit a not so paranoid Android.