July 13, 2022 • 29 mins
A special preview of the podcast, Unsung Science with David Pogue from CBS News. Journalist and author David Pogue finds the untold creation stories behind the most mind-blowing advances in science and tech—and hears from the characters involved—from their first inspiration to the times they almost gave up. This episode looks at the bad guys who used software bots to sign up for millions of fake email accounts—for sending out spam. Then, PhD student Luis Von Ahn stopped them. He invented the CAPTCHA, that website login test where you have to decipher the distorted image of a word. Or you have to find the traffic lights or fire hydrants in a grid of nine blurry photos. Those tests help to keep down the volume of spam, spyware, and misinformation; they advance the clarity of digitized books and the intelligence of self-driving cars; and, by the way, they made a handsome profit. The only problem: We HATE those tests! Guest: Luis Von Ahn, co-inventor of CAPTCHA, co-inventor and CEO of Duolingo. Hear more episodes of Unsung Science at https://unsungscience.com/.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:15):
Pushkin. Hi, It's Jacob Goldstein and I'm here today with
another podcast I think you might like. The show is
called Unsung Science and it's hosted by David Pogue. You
might know David from CBS Sunday Morning, where he's a
correspondent covering topics like science, tech, and innovation, topics like
the ones we talk about here on What's Your Problem.
(00:37):
In the episode You're about to hear, David chats with
Luis Vonon, the founder and CEO of the popular language
app Duolingo. You might recall I talked with Louise earlier
this year about Duolingo and language and the current limits
of artificial intelligence. But the show you're about to hear
is about what Louise did before he started Duolingo. He
invented this thing called Capsha. Capsha is that test that
(01:00):
you have to take all the time on the Internet
to prove that you're not a robot. And yes, Louise
knows that the test is super annoying. But the story
of capsha and what happened with it is really interesting.
It's got some great twists. By the year two thousand,
the Internet was already becoming a cesspool software bots were
(01:22):
signing up for millions of fake email accounts for sending
out spam. Luis Vaughan stopped them. He invented the CAPTA,
the website login test where you have to decipher the
distorted image of a word, where you have to find
the traffic lights in a grid of nine blurry photos.
The only problem we hate that test. I would be
(01:45):
at a party and you know, people would ask me
what I did, and I would tell them that I
helped invent that thing, and people would tell me, oh,
I hate you. I'm David Pogue And this is Unsung Science,
Season one, episode fourteen, The man who stopped the spammers.
(02:08):
In his forty three years on this earth, so far,
Luis vonn has had three ingenious innovative world changing ideas.
I guarantee that you've encountered his second one, probably hundreds
of times. Actually, most of us have zero world changing ideas.
Occasionally somebody has won, but three times. His first idea
(02:34):
came to him in Guatemala, where he grew up. They
wanted to start a gym where instead of charging people
to show up, let people just show up for free.
We're going to connect all the machines to kind of
the power grid, and we're going to use the kinetic
energy that people had whenever they were exercising to generate power.
And I thought we could make a lot of money
(02:55):
from that. Now you will note that I did not
say that all three of his world changing ideas actually
succeeded in changing the world. I thought I was the
first person to have this idea. It turns out it's
a very old idea. It also turns out it doesn't work.
That's right, the pedal power Jim idea flopped. It turns
out this is not a good idea for many reasons,
the biggest one of which is that humans are just
(03:15):
not very good at creating energy. Oh, you just just
don't make a lot of money from this. There's another
reason why this doesn't work a lot. It turns out
Jim's make most of their money from people who don't
show up. Of course, here you kind of need people
to show up to be fair. He was pretty new
at the game when he had this first idea. And
how old were you at this point, twelve years old,
(03:36):
eleven years old. Things started going better six years later,
when he came to the United States to attend Duke University.
As the year two thousand dawned. Luis was at Carnegie
Mellon in his first year of working toward a PhD
in computer science, and one fateful day he went to
a talk by an Israeli computer scientist named Udi Manber,
(03:58):
who at this point was the chief scientist at Yahoo.
By the way, at end the year two thousand, Yahoo
was the biggest biggest tech company in the words like
the Google of today. And you know, he was giving
a talk about ten problems that they didn't know how
to solve inside inside the company. And one of those
ten problems that the greatest minds at Yahoo could not
(04:19):
solve was automated software spam bots signing up for free
Yahoo mail accounts. By the millions. Yahoo gave up free
email accounts, and there were people who wanted to send
spam from Yahoo accounts. But each Yahoo account only allowed
you to send like five hundred messages a day. If
you wanted to send millions of emails spam emails per day,
(04:40):
then what these people did is they wrote programs to
obtain millions of Yahoo accounts every day, and they didn't
know how to solve that problem, how to stop that.
So I started talking about it with a person who
had just become my PhD advisor. His name was Manuel
Blum or is Manolum. He's still he's most definitely still alive.
And you know, we started thinking, and this is where
this idea of a capture came up. The idea was this,
(05:03):
anytime you tried to sign up for a Yahoo Mail account,
you'd encounter a little puzzle, something easy for a person
to solve, but hard for a spambot. The way to
stop these spammers was to have a test that can
distinguish between whether you're a human or a computer. If
you are a human, then presumably you can't get millions
of email accounts because you get bored, whereas if you're
(05:26):
a computer, you can get millions. So if the only
entity is that we were giving email accounts to where humans,
then that would stop the spam. KAPTA, the name he
gave his online mini puzzle, is an acronym. It stands
for completely automated public touring tests to tell computers and
humans apart more or less. Not sure if you've heard
(05:49):
of the touring test, but it is incredibly famous among
computer scientists. It's this experiment proposed by British mathematician and
computer scientist Alan Turing, who's known as the father of
artificial intelligence. There was actually a movie about him called
The Imitation Game, where Benedict's Cumberbatch played Alan Tour. Would
(06:09):
you like to play play? It's a game, a test
of songs for determining whether something is machine or a
human being. Anyway, the Touring test is intended to set
a standard for determining if a computer has achieved true
artificial intelligence. When can we tell that a computer is
(06:33):
actually intelligent. This is kind of like a philosophical test
that said, like, look, we're going to have a human
judge ask questions to two entities. One is the computer,
one is the human. The computer and the human are
hidden behind two curtains. The judge can't see them. The
judge types in questions and then looks at the text
of the responses. If it's impossible to tell which answer
(06:55):
came from the person in which from the computer, the
computer has passed the Turing test. The judge can just
ask whatever questions they want, and if we really can't
distinguish them, we'll say the computer is really intelligent. To
this day, we have not made a computer that can
actually pass the turning test successfully. It's just it's just
too hard. The funny thing is, if you really think
about it, the capture problem is the opposite of the
(07:19):
touring test. The touring test is successful if the judge
can't tell the difference between a person and a machine.
The whole point of Louis Vanan's project was to create
a test that can tell the difference. There's another difference
between the two tests too. Here's the key. In this case,
the judge was a human. In our case for the capture,
(07:40):
what we needed to do is we needed the judge
to be a computer because we need we need the
computer to determine whether it's talking to a human our computer,
which is which is much harder in some sense, at
least for to grade it. So I think the hardest
thing was just coming up with this general idea that like, okay,
what we need is a test that can assume shroom
some computers, but that computers need to be able to grade.
Then after that we started coming up with like, okay,
(08:02):
what I think the computers are not very good at.
In the year two thousand, the answer was obvious, computers
are not very good at identifying what's in pictures. We
quickly owned in on images and just doing you know,
images of text, images of flowers, images of stuff. And
then after a while, the images of text were the
ones that seemed like the best idea. And then I
(08:23):
just went and developed a program that distorted random text
and that was the first version of a cap chow.
That's right. The test they came up with presents you
with the image of a typed word, but the letters
are all like twisted, bent and distorted, as though the
typist were severely drunk and typing on saran wrap. You
(08:44):
are supposed to interpret what that word is and type
it into a box on the website. Actually, computers in
the early two thousands were pretty good at OCR. That's
optical character recognition, meaning looking at a picture of text
and figuring out what the letters are. But the added
challenge of the twisty distortion really threw those OCR programs
(09:07):
off the track. Behind the scenes, I mean, what is it.
I mean there's got to be some I don't know,
sequel database or massive bank of little images. I mean,
actually there was no database at first. We would just
write a program that what it would do is it
would pick some first random characters, would put them on
an image, then it would distore him, and then we
(09:28):
would save that image. And then we just had I
don't know, a couple of million of those saved, not
even in a sequel database. Is just they were there,
so save as files. It worked brilliantly. The spambots didn't
have a chance. At the time. Vonn had no idea
if his invention would be of any commercial use. But
one guy he knew would be interested, Oodi Manber, that
(09:51):
Yahoo chief scientist who'd given the talk that started this
whole affair. We sent them an email saying, hey, we
think we can solve your problem, and he said, oh,
that that seems like it solves the problem. And then
in fact, pretty soon after that it was being used
by Yahoo, and then basically every website started using it,
and you know, there was millions of websites out there.
(10:11):
We're using it. Well, how wonderful Luis Spawn's ingenuity. One spammers,
zero Internet saved. And at first I was very kind
of proud of myself because, okay, look at the impact
that my work has had. Basically we stopped spams being
used by a lot of people. There was only one problem. Now,
(10:32):
people hated his invention. How many of you have had
to fill out some sort of web form where even
has to read a distorted sequence of characters like this, Yeah,
how many of you found it really really annoying. Okay,
that's standing. So I invented that. That's how he introduces
himself in a twenty eleven TEDx talk at Carnegie Mellon.
I would be at a party, and you know, people
(10:54):
would ask me what I did, and I would tell
them that I helped invent that thing. And people would
tell me, oh, I hate you. That's right. The inventor
of kapta is fully aware that people hate the thing.
I say, either well, I'm sorry, or I find it
annoying too. You've heard it right here, folks. Even he
finds them annoying. In fact, Louise can tell you exactly
(11:16):
how much of your time they waste. I did a
little back of the envelope calculation at the time, about
two hundred million times a day somebody type one of
these captures two hundred million times times ten seconds, which
is how long it takes to type one of these.
Humanity as a whole was wasting about five hundred thousand
hours every day typing these annoying captures. Great. So I
(11:36):
started feeling bad about that, and that's when I started thinking, Okay,
can we do something good with that time? See, the
thing is kind of similar to the gym idea. Can
we get millions of people to do something during that
time that is actually valuable. I'll give you a hint.
We're only at the halfway point in this story. After
the break, we'll tell you what he came up with
(11:57):
to make those half a million hours every day useful
to humanity. And one more plug here. I'm the author
of a book called How to Prepare for Climate Change.
It's a six hundred page paperback that's designed to be
(12:17):
a field guide to the new climate. It tells you
where to live, where to invest, what to grow, how
to reinforce your home, how to insure, how to talk
to your kids, and how to ride out wildfires, hurricanes, heatwaves,
and so on. If you live in a state whose
name contains a vowel, then you've been affected by climate
change already, and you should check out this book to
(12:39):
protect your health, your family, your home, and your finances.
It's How to Prepare for Climate Change. The book that's
exactly what it sounds like. Welcome back. By two thousand
and five, Louis vaughan An's invention the captcha test was
a huge hit. It reduced the world scumbag spammers to
(13:02):
blubbering losers. No longer could they bombard websites with phony
sign ups for the purpose of pursuing their pathetic spanny schemes. Unfortunately,
he had achieved this success by transferring the burden onto us,
treating us as though we were guilty until proven innocent.
Now we were the ones being challenged. We were losing
(13:25):
ten seconds per website typing in those stupid distorted letters. Now.
To be fair, history is full of examples like that,
where the actions of a few selfish, greedy idiots wind
up inconveniencing billions of innocent people for the rest of
our lives. You know, some dirtbag tries to put poison
into drug store tile on all bottles, and now the
(13:47):
rest of us are stuck with frustrating, plastic, wasteful bottle
lids forever. Some delinquent tries to blow up a plane
with a shoe bomb, and now we all have to
walk through the TSA scanners in our socks. Louise felt
bad that his hacker blockade wasted everybody's time, but at
least he could do something about it. So that's a
very valuable time, So can we use it for something?
(14:09):
And then I ended up coming up with this idea
that while you were typing a capture, you could be
helping digitize books. And here's here's kind of how that works.
So at the time, this is the year maybe two
thousand and five, two thousand and six, there were a
lot of projects trying to digitize all of the world's
books where where you know. The way that worked is
you start with a physical book and you want to
put it on the internet. And the way you do
(14:30):
that is you basically take a digital photograph of every
page of the book. Now these are pictures of text.
The next step in the process is that the computer
needs to decipher what's the text in there. In other words,
computers had to perform come on, you know, this term
ocr optical character recognition, and unfortunately, for books that are
(14:52):
older where maybe the ink has faded, computers could not
recognize many of the words. So the thought, the idea was,
let's take all those words that the computers could not
recognize while books are being digitized, and let's get people
to read them for us while they're typing a capture.
So what we started giving people where these words that
they con computer was not able to digitize and or
to recognize. So yeah, all this time you thought you
(15:15):
were typing random words. In fact, you were helping companies
digitize old books and articles and, by the way, helping
Luise's little company make money. The ideas we made a capture,
a system, a whole system that would help your website
be protected against BAM, and we gave that away for free.
And for example, Facebook use our capture and we gave
(15:36):
it away for free, etc. But always with a caveat
that if they are going to do that, then we
can see the answers that users are typing, so that
we helped digitize something. And the way we made money
is by charging people who needed digitization stuff. For example,
the New York Times was our client. The New York
Times had this old archive of all the editions of
(15:57):
the New York Times from you know, one hundred and
thirty years of the New York Times or something like that,
from the eighteen hundreds, and they needed this to help
digitize their whole archive. They were sending us all the
scans they had scanded already and we were sending them.
We were taking all the words that computer could not recognize,
and we were getting through the captures people who were,
for example, signing up for Facebook or Twitter or a
(16:18):
lot of websites that we're using our capture. They were
helping us digitize the New York Times, and we would
make money from The New York Times. It became very successful,
and then Google bought it to help their book digitization
whole project. The new system called recapture became an even
bigger hit. Here's how we described the aftermath in his
TEDx talk. So every time you buy tickets on Ticketmaster,
you hope to digitize a book. Facebook, every time you
(16:39):
add a friend, you help to digitize a book. Twitter,
and about three hundred and fifty thousand other sites are
all using recapture. And in fact, the number of sites
that are using recaptures so high that the number of
words that we're digitizing per day is really really large.
It's about one hundred million a day, which is the
equivalent of about two and a half million books a year.
And this is all being done one word at a
time by just people tapping captures on the Internet. There
(17:05):
are some people who are a little nervous about Google
being the owner of one of the most widely used
captive systems. I'm sure you've then asked about that. Yeah,
there are people who are nervous about that. I mean,
I understand, I think you know this is these are
very very tricky questions. I mean, personally, I think the
(17:25):
privacy fight US is over. I mean I I've given
up on my privacy against large companies a while ago. Wow.
Not only that, I also think after having been inside Google,
I saw with how much respect they treat user data
because they know that they are, you know, a few
scandals away from being in deep trouble, so they take
it with a lot of care, I think. And we
(17:47):
should point out that Google has said we do not
use data collected for advertising purposes. Yeah, that's the case,
and so and I actually believe them. Now. Remember Louise
said that the hard part was finding a test that
was too hard for a computer to pass, but easy
enough for a computer to judge whether the test had
been passed. That's been bugging me. If the computer chooses
(18:12):
a word that's so distorted that it itself cannot do
the ocr then how does it know if we're right. Yeah,
that's a great question. When we try to digitize books,
Here's here's what we do. We take a word that
the computer does not know. We actually pair it with
another word for which the computer does know the answer,
and we actually give people both words, and we say
(18:33):
please type both, and we don't tell them which ones which,
We just say, hey, please type both. If they type
the word for which we know the answer, if they
type that one correctly, we assume that they're human, and
we also get some confidence that they type the other
word correctly, and then what we do is okay, so
now we have a guess for what that other word is.
We give it to like ten other different people and
we see if they type the same thing, and if
(18:53):
they all type the same thing, we get with very
high accuracy what that word really is, and that works.
One hallmark of the recapture system in other words, is
that you have to type in two words. There's sometimes
also funny words that a funny combinations that happen, especially
because we are showing two words at a time. Oh boy,
(19:14):
I mean, you know, there's been all kinds of really
funny examples where it's just like, you know, a website
of a church that says like bad Christians and it's
just but these are just two randomly chosen words, so
we shouldn't infer any evil on your part. No, they're random. Now,
a lot has happened since two thousand when capture came along,
and since two thousand and six when you started unsuspectingly
(19:37):
helping Google in the New York Times digitize their old pages.
You know, early on in the first version of a
cap shop, computers were pretty bad at recognizing distorted text,
so they didn't have to be that distorted. But you know,
over time, computers got better and better, and in fact,
by now computers are in many cases about as good
as humans. Because of that, we have to make them
(19:58):
harder and harder. A lot of times, the puzzles are
so hard that even the human can't pass the challenge.
I'm sure you've been sent screenshots of words that are
so much no one can tell where it is. Yes,
that happens, I mean, it's rare that that happens, and
that's why the capture itself in true arms race fashion
(20:22):
has evolved. So what has happened is that for the
more secure things, the captures have moved away from these
distorted characters. And what is being used now are these
the puzzles are now things like you see a bunch
of pictures and you have to click the ones that
contain a stop sign right the traffic lights, the fire hydrants. Yeah,
it's exactly the same idea as recapture, except we're not
(20:45):
the story. We're not trying to digitize books. This a
lot of times comes from things like all the all
the mapping cars or the self driving cars. Basically, these
are cars that are driving around that are capturing images
of the whole world. They're trying to figure out what's
around them. Sometimes they cannot recognize what's in an image.
So it's a similar case. It takes the things like
is this a stopting I'm not sure, Okay, send it
(21:06):
to a human, and then when you get it and
you click on the store sign, you're actually helping either
the self driving car or the mapping software or whatever
know that there is actually a stop sign right here.
Oh so we're still doing good for the world as
we do this, still doing good for the world, or
for a company or for a company, but maybe not
digitizing books. But it's a similar ideas thing that a
(21:26):
computer cannot do. You've just solved a mystery for hundreds
of millions of people. Why it's always traffic lights and
fire hydrants we're supposed to choose and not bananas and puppies,
or it has to do with both self driving cars
and also mapping software. Okay, so now we kind of
get why we have to put up with these challenges,
or we did twenty years ago, but really nothing better
(21:50):
has come along since. Are we sure that there's nothing
less annoying that we could do to thwart these spammers? Yes,
there is. By now, it did become a lot less annoying.
I don't know if you've seen that of late, where
you know, there's a thing that's us recapture. We're just
trying to figure out whether you're a human, and they
just ask you to click somewhere, just click on this box.
(22:11):
That is much less annoying. So sometimes you don't see
anything except I'm not a robot by yeah, yeah, yeah,
I'm not a robot. This is something that is that
is done by Google. This actually comes from you know,
the original team, that is the company that they bought
from me. When you get that one, that means that,
in this particular case, probably means Google has figured out that, yeah,
(22:31):
you know what, we know you because you've been around
since twenty sixteen in this computer, and yeah, you have
a lot of Gmail emails, and you've done a lot
of Google search queries. You're a normal person, You're not
a spammer. So they just do a little thing that
just tries to double check that, you know, I can
move the mouse or whatever. So one thing that has
changed from the year two thousand and five to now
(22:53):
is that there are companies like Google or like Facebook
that for the majority of people on the Internet, they
kind of know who you are. If you have a
fresh computer that you've never used before, then you would
have to do the annoying capture. But for most of us,
you're unlikely to have to type these as much as
you you were back in say the year two thousand
and five. It has become a lot better, you know,
(23:16):
probably a little bit at the cost of your privacy. Okay,
but wait a minute, we now know that computers eventually
got too smart for the distorted text reading touring tests.
Won't they eventually get good enough to identify a few
stupid stop signs in a photo grid? It is, it's
a cat of mouse game. Now. Probably there's a bunch
of people working on making better recognition of stop signs
(23:37):
or something like that eventually. But eventually computers are going
to be able to do everything humans can, and so
at some point there won't be a test that kind
distinguished humans going to computer. Well wait a minute, does
that mean the end of the internet? I mean, what
happens if that, If there's no sort of touring tests
that works anymore. I don't think it's the end of
the internet, particularly because, like I said, more and more
(24:00):
these companies are going to know more and more about you,
and I just don't think there will be a humans problem. Okay, well,
whatever the end game is, why can't we do today,
Since we know it's an arms race, Since we know
that eventually we'll lose it to AI and computers, why
can't we jump to whatever we'll follow it? Now? I'll
(24:22):
tell you why this. By the way, it's like ninety
five percent of the way there. I mean, really, for
most of us, you know, Facebook knows who we are,
and Google knows who we are, So it's ninety percent
of the way there. The reason is not one hundred
percent of the way there is because there are some
people who really care about privacy, and you know, there's
there's always going to be a kind of a way
to browse privately. So for example, there's a chrome has
(24:42):
private browsing. So it's all the stuff when people care
about privacy, I mean there's there's a trade off here, right. Well,
the irony is it seems like most of the websites
to present me with a capture I'm trying to get
to in order to supply my name and address, like
like I'm signing up for something. Yes, it's funny. Why
do I need privacy when the whole purpose is to
(25:02):
supply my information? Yeah, that's funny. Now. I mentioned at
the beginning that Louis has had three world changing ideas.
You've heard about the gym membership that powers the grid,
and you now know about kapture. But what about his
third creation. It's Duo Lingo, the language training app. At
(25:24):
this moment, it has half a billion registered users learning
forty different languages, all for free. And from the very
beginning you could see the fingerprints of Luis Vaughnan, master
of crowdsourcing all over it. In early due Lingo, as
(25:46):
you were learning a language on dual Lingo, you're actually
helping us to translate stuff that computers could not translate.
In fact, CNN was a client, so CNN would send
us their news in English. We would then give it
to people who were Spanish speakers who were learning English,
and we would say, hey, you want to practice your English,
help us translate this CNN article into your native language
of Spanish. And so they would do it, and they
(26:08):
would be learning English and then we would get that translation,
and then we would send it back to CNN and
they would pay us for the translation. That was the
very first version of due Lingo. It turned out that,
just like the gym, it ends up being that it
just can't make much money from this, and so we decided, okay,
just go go to a business model where we actually
give you ads, and the way we make money is by,
(26:30):
you know, showing your ads. The dude just keeps doing that.
He keeps coming up with ideas that make the world
a better place, thwart the bad guys, and make a
lot of money. It's really a shame he gave up
that electrical grid gym thing. Are there ever things that
come to you in the shower that might be your
big third act? I mean, honestly, to have the impact
(26:53):
you've had twice is astonishing, But it makes me think
there's something in you that just has great ideas that
can go really wide. You know, as time passes, I
am a lot more interested in literacy and teaching people
how to read. I think with a computer, we should
be able to teach the whole world how to read
significantly better than humans can teach you how to read.
(27:15):
You know, the US, The US is fine, most adults
Indias know how to read, but many countries in the
world there's a significant fraction of people who don't know
how to read. In fact, there's about a billion adults
in the world that are illiterate. And I think we
can I think we can make a big dent, you know,
with a system to teach people how to read. So
we're working on that in the meantime. Now you know
why you have to encounter those infernal website challenges. You
(27:38):
know how they came about, and you now consider them
unnecessary evil. Well, maybe you do just for people who
are like, I don't know what it is. I just
don't like doing it. I can't even tell what's a
freaking draffic. Like, let's just lay out what would happen
if all these challenges went away tomorrow. What would happen
to the Internet. Most likely, you would get a lot
(28:00):
more spam in either your email spam or you'd get
a more kind of random Facebook follow words that are
not you know, real people. These fake accounts can start
boosting up that political messages. There would be probably more
fake news. They would probably be you know, more spam, right,
(28:21):
and from spam fishing and spywear and yeah, more spywear. Yeah.
The web would be a less safe place, all right.
So when you do explain this to someone at the
proverbial party, are they generally satisfied with the notion that? Yeah,
I think most people. I think most people realize that
(28:41):
it's like, you know, these things are kind of like
a like a key nobody nobody likes. It's not like
I love opening my door with the key. It's kind
of annoying, but yeah, that's there, and I understand it
just makes it makes my house safer. In this case,
it's kind of just makes the whole Internet safer. I
kind of gotta do it. Thanks for listening to this
second to last episode of the season. If you have
(29:03):
any interest in a second season, please spread the word,
subscribe to this podcast, leave a review on Apple Podcasts,
or a rating on Spotify. Unsung Science with David Pogue
is presented by Simon and Schuster and CBS News and
produced by PRX Productions. The executive producers for Simon and
Schuster are Richard Rohrer and Chris Lynch. The PRX production
(29:26):
team is Jocelyn Gonzalez, Morgan Flannery, Pedro, Raphael Rosatto, and
Ian Fox. Project manager Jesse Nelson composed the Unsung Science
theme music and Christina Robello fact checked my script. At
Unsung Science dot com, you can listen to every episode
we've ever made and read complete transcripts. For more of
(29:47):
my stuff, visit David Pogue dot com or follow me
on Twitter at Pogue Pogue. Thanks for the scene that
was an episode of Unsung Science from our friends at
CBS News. You can find more episodes of Unsung Science
wherever you get your podcasts.
Pushkin. Hi, It's Jacob Goldstein and I'm here today with
another podcast I think you might like. The show is
called Unsung Science and it's hosted by David Pogue. You
might know David from CBS Sunday Morning, where he's a
correspondent covering topics like science, tech, and innovation, topics like
the ones we talk about here on What's Your Problem.
(00:37):
In the episode You're about to hear, David chats with
Luis Vonon, the founder and CEO of the popular language
app Duolingo. You might recall I talked with Louise earlier
this year about Duolingo and language and the current limits
of artificial intelligence. But the show you're about to hear
is about what Louise did before he started Duolingo. He
invented this thing called Capsha. Capsha is that test that
(01:00):
you have to take all the time on the Internet
to prove that you're not a robot. And yes, Louise
knows that the test is super annoying. But the story
of capsha and what happened with it is really interesting.
It's got some great twists. By the year two thousand,
the Internet was already becoming a cesspool software bots were
(01:22):
signing up for millions of fake email accounts for sending
out spam. Luis Vaughan stopped them. He invented the CAPTA,
the website login test where you have to decipher the
distorted image of a word, where you have to find
the traffic lights in a grid of nine blurry photos.
The only problem we hate that test. I would be
(01:45):
at a party and you know, people would ask me
what I did, and I would tell them that I
helped invent that thing, and people would tell me, oh,
I hate you. I'm David Pogue And this is Unsung Science,
Season one, episode fourteen, The man who stopped the spammers.
(02:08):
In his forty three years on this earth, so far,
Luis vonn has had three ingenious innovative world changing ideas.
I guarantee that you've encountered his second one, probably hundreds
of times. Actually, most of us have zero world changing ideas.
Occasionally somebody has won, but three times. His first idea
(02:34):
came to him in Guatemala, where he grew up. They
wanted to start a gym where instead of charging people
to show up, let people just show up for free.
We're going to connect all the machines to kind of
the power grid, and we're going to use the kinetic
energy that people had whenever they were exercising to generate power.
And I thought we could make a lot of money
(02:55):
from that. Now you will note that I did not
say that all three of his world changing ideas actually
succeeded in changing the world. I thought I was the
first person to have this idea. It turns out it's
a very old idea. It also turns out it doesn't work.
That's right, the pedal power Jim idea flopped. It turns
out this is not a good idea for many reasons,
the biggest one of which is that humans are just
(03:15):
not very good at creating energy. Oh, you just just
don't make a lot of money from this. There's another
reason why this doesn't work a lot. It turns out
Jim's make most of their money from people who don't
show up. Of course, here you kind of need people
to show up to be fair. He was pretty new
at the game when he had this first idea. And
how old were you at this point, twelve years old,
(03:36):
eleven years old. Things started going better six years later,
when he came to the United States to attend Duke University.
As the year two thousand dawned. Luis was at Carnegie
Mellon in his first year of working toward a PhD
in computer science, and one fateful day he went to
a talk by an Israeli computer scientist named Udi Manber,
(03:58):
who at this point was the chief scientist at Yahoo.
By the way, at end the year two thousand, Yahoo
was the biggest biggest tech company in the words like
the Google of today. And you know, he was giving
a talk about ten problems that they didn't know how
to solve inside inside the company. And one of those
ten problems that the greatest minds at Yahoo could not
(04:19):
solve was automated software spam bots signing up for free
Yahoo mail accounts. By the millions. Yahoo gave up free
email accounts, and there were people who wanted to send
spam from Yahoo accounts. But each Yahoo account only allowed
you to send like five hundred messages a day. If
you wanted to send millions of emails spam emails per day,
(04:40):
then what these people did is they wrote programs to
obtain millions of Yahoo accounts every day, and they didn't
know how to solve that problem, how to stop that.
So I started talking about it with a person who
had just become my PhD advisor. His name was Manuel
Blum or is Manolum. He's still he's most definitely still alive.
And you know, we started thinking, and this is where
this idea of a capture came up. The idea was this,
(05:03):
anytime you tried to sign up for a Yahoo Mail account,
you'd encounter a little puzzle, something easy for a person
to solve, but hard for a spambot. The way to
stop these spammers was to have a test that can
distinguish between whether you're a human or a computer. If
you are a human, then presumably you can't get millions
of email accounts because you get bored, whereas if you're
(05:26):
a computer, you can get millions. So if the only
entity is that we were giving email accounts to where humans,
then that would stop the spam. KAPTA, the name he
gave his online mini puzzle, is an acronym. It stands
for completely automated public touring tests to tell computers and
humans apart more or less. Not sure if you've heard
(05:49):
of the touring test, but it is incredibly famous among
computer scientists. It's this experiment proposed by British mathematician and
computer scientist Alan Turing, who's known as the father of
artificial intelligence. There was actually a movie about him called
The Imitation Game, where Benedict's Cumberbatch played Alan Tour. Would
(06:09):
you like to play play? It's a game, a test
of songs for determining whether something is machine or a
human being. Anyway, the Touring test is intended to set
a standard for determining if a computer has achieved true
artificial intelligence. When can we tell that a computer is
(06:33):
actually intelligent. This is kind of like a philosophical test
that said, like, look, we're going to have a human
judge ask questions to two entities. One is the computer,
one is the human. The computer and the human are
hidden behind two curtains. The judge can't see them. The
judge types in questions and then looks at the text
of the responses. If it's impossible to tell which answer
(06:55):
came from the person in which from the computer, the
computer has passed the Turing test. The judge can just
ask whatever questions they want, and if we really can't
distinguish them, we'll say the computer is really intelligent. To
this day, we have not made a computer that can
actually pass the turning test successfully. It's just it's just
too hard. The funny thing is, if you really think
about it, the capture problem is the opposite of the
(07:19):
touring test. The touring test is successful if the judge
can't tell the difference between a person and a machine.
The whole point of Louis Vanan's project was to create
a test that can tell the difference. There's another difference
between the two tests too. Here's the key. In this case,
the judge was a human. In our case for the capture,
(07:40):
what we needed to do is we needed the judge
to be a computer because we need we need the
computer to determine whether it's talking to a human our computer,
which is which is much harder in some sense, at
least for to grade it. So I think the hardest
thing was just coming up with this general idea that like, okay,
what we need is a test that can assume shroom
some computers, but that computers need to be able to grade.
Then after that we started coming up with like, okay,
(08:02):
what I think the computers are not very good at.
In the year two thousand, the answer was obvious, computers
are not very good at identifying what's in pictures. We
quickly owned in on images and just doing you know,
images of text, images of flowers, images of stuff. And
then after a while, the images of text were the
ones that seemed like the best idea. And then I
(08:23):
just went and developed a program that distorted random text
and that was the first version of a cap chow.
That's right. The test they came up with presents you
with the image of a typed word, but the letters
are all like twisted, bent and distorted, as though the
typist were severely drunk and typing on saran wrap. You
(08:44):
are supposed to interpret what that word is and type
it into a box on the website. Actually, computers in
the early two thousands were pretty good at OCR. That's
optical character recognition, meaning looking at a picture of text
and figuring out what the letters are. But the added
challenge of the twisty distortion really threw those OCR programs
(09:07):
off the track. Behind the scenes, I mean, what is it.
I mean there's got to be some I don't know,
sequel database or massive bank of little images. I mean,
actually there was no database at first. We would just
write a program that what it would do is it
would pick some first random characters, would put them on
an image, then it would distore him, and then we
(09:28):
would save that image. And then we just had I
don't know, a couple of million of those saved, not
even in a sequel database. Is just they were there,
so save as files. It worked brilliantly. The spambots didn't
have a chance. At the time. Vonn had no idea
if his invention would be of any commercial use. But
one guy he knew would be interested, Oodi Manber, that
(09:51):
Yahoo chief scientist who'd given the talk that started this
whole affair. We sent them an email saying, hey, we
think we can solve your problem, and he said, oh,
that that seems like it solves the problem. And then
in fact, pretty soon after that it was being used
by Yahoo, and then basically every website started using it,
and you know, there was millions of websites out there.
(10:11):
We're using it. Well, how wonderful Luis Spawn's ingenuity. One spammers,
zero Internet saved. And at first I was very kind
of proud of myself because, okay, look at the impact
that my work has had. Basically we stopped spams being
used by a lot of people. There was only one problem. Now,
(10:32):
people hated his invention. How many of you have had
to fill out some sort of web form where even
has to read a distorted sequence of characters like this, Yeah,
how many of you found it really really annoying. Okay,
that's standing. So I invented that. That's how he introduces
himself in a twenty eleven TEDx talk at Carnegie Mellon.
I would be at a party, and you know, people
(10:54):
would ask me what I did, and I would tell
them that I helped invent that thing. And people would
tell me, oh, I hate you. That's right. The inventor
of kapta is fully aware that people hate the thing.
I say, either well, I'm sorry, or I find it
annoying too. You've heard it right here, folks. Even he
finds them annoying. In fact, Louise can tell you exactly
(11:16):
how much of your time they waste. I did a
little back of the envelope calculation at the time, about
two hundred million times a day somebody type one of
these captures two hundred million times times ten seconds, which
is how long it takes to type one of these.
Humanity as a whole was wasting about five hundred thousand
hours every day typing these annoying captures. Great. So I
(11:36):
started feeling bad about that, and that's when I started thinking, Okay,
can we do something good with that time? See, the
thing is kind of similar to the gym idea. Can
we get millions of people to do something during that
time that is actually valuable. I'll give you a hint.
We're only at the halfway point in this story. After
the break, we'll tell you what he came up with
(11:57):
to make those half a million hours every day useful
to humanity. And one more plug here. I'm the author
of a book called How to Prepare for Climate Change.
It's a six hundred page paperback that's designed to be
(12:17):
a field guide to the new climate. It tells you
where to live, where to invest, what to grow, how
to reinforce your home, how to insure, how to talk
to your kids, and how to ride out wildfires, hurricanes, heatwaves,
and so on. If you live in a state whose
name contains a vowel, then you've been affected by climate
change already, and you should check out this book to
(12:39):
protect your health, your family, your home, and your finances.
It's How to Prepare for Climate Change. The book that's
exactly what it sounds like. Welcome back. By two thousand
and five, Louis vaughan An's invention the captcha test was
a huge hit. It reduced the world scumbag spammers to
(13:02):
blubbering losers. No longer could they bombard websites with phony
sign ups for the purpose of pursuing their pathetic spanny schemes. Unfortunately,
he had achieved this success by transferring the burden onto us,
treating us as though we were guilty until proven innocent.
Now we were the ones being challenged. We were losing
(13:25):
ten seconds per website typing in those stupid distorted letters. Now.
To be fair, history is full of examples like that,
where the actions of a few selfish, greedy idiots wind
up inconveniencing billions of innocent people for the rest of
our lives. You know, some dirtbag tries to put poison
into drug store tile on all bottles, and now the
(13:47):
rest of us are stuck with frustrating, plastic, wasteful bottle
lids forever. Some delinquent tries to blow up a plane
with a shoe bomb, and now we all have to
walk through the TSA scanners in our socks. Louise felt
bad that his hacker blockade wasted everybody's time, but at
least he could do something about it. So that's a
very valuable time, So can we use it for something?
(14:09):
And then I ended up coming up with this idea
that while you were typing a capture, you could be
helping digitize books. And here's here's kind of how that works.
So at the time, this is the year maybe two
thousand and five, two thousand and six, there were a
lot of projects trying to digitize all of the world's
books where where you know. The way that worked is
you start with a physical book and you want to
put it on the internet. And the way you do
(14:30):
that is you basically take a digital photograph of every
page of the book. Now these are pictures of text.
The next step in the process is that the computer
needs to decipher what's the text in there. In other words,
computers had to perform come on, you know, this term
ocr optical character recognition, and unfortunately, for books that are
(14:52):
older where maybe the ink has faded, computers could not
recognize many of the words. So the thought, the idea was,
let's take all those words that the computers could not
recognize while books are being digitized, and let's get people
to read them for us while they're typing a capture.
So what we started giving people where these words that
they con computer was not able to digitize and or
to recognize. So yeah, all this time you thought you
(15:15):
were typing random words. In fact, you were helping companies
digitize old books and articles and, by the way, helping
Luise's little company make money. The ideas we made a capture,
a system, a whole system that would help your website
be protected against BAM, and we gave that away for free.
And for example, Facebook use our capture and we gave
(15:36):
it away for free, etc. But always with a caveat
that if they are going to do that, then we
can see the answers that users are typing, so that
we helped digitize something. And the way we made money
is by charging people who needed digitization stuff. For example,
the New York Times was our client. The New York
Times had this old archive of all the editions of
(15:57):
the New York Times from you know, one hundred and
thirty years of the New York Times or something like that,
from the eighteen hundreds, and they needed this to help
digitize their whole archive. They were sending us all the
scans they had scanded already and we were sending them.
We were taking all the words that computer could not recognize,
and we were getting through the captures people who were,
for example, signing up for Facebook or Twitter or a
(16:18):
lot of websites that we're using our capture. They were
helping us digitize the New York Times, and we would
make money from The New York Times. It became very successful,
and then Google bought it to help their book digitization
whole project. The new system called recapture became an even
bigger hit. Here's how we described the aftermath in his
TEDx talk. So every time you buy tickets on Ticketmaster,
you hope to digitize a book. Facebook, every time you
(16:39):
add a friend, you help to digitize a book. Twitter,
and about three hundred and fifty thousand other sites are
all using recapture. And in fact, the number of sites
that are using recaptures so high that the number of
words that we're digitizing per day is really really large.
It's about one hundred million a day, which is the
equivalent of about two and a half million books a year.
And this is all being done one word at a
time by just people tapping captures on the Internet. There
(17:05):
are some people who are a little nervous about Google
being the owner of one of the most widely used
captive systems. I'm sure you've then asked about that. Yeah,
there are people who are nervous about that. I mean,
I understand, I think you know this is these are
very very tricky questions. I mean, personally, I think the
(17:25):
privacy fight US is over. I mean I I've given
up on my privacy against large companies a while ago. Wow.
Not only that, I also think after having been inside Google,
I saw with how much respect they treat user data
because they know that they are, you know, a few
scandals away from being in deep trouble, so they take
it with a lot of care, I think. And we
(17:47):
should point out that Google has said we do not
use data collected for advertising purposes. Yeah, that's the case,
and so and I actually believe them. Now. Remember Louise
said that the hard part was finding a test that
was too hard for a computer to pass, but easy
enough for a computer to judge whether the test had
been passed. That's been bugging me. If the computer chooses
(18:12):
a word that's so distorted that it itself cannot do
the ocr then how does it know if we're right. Yeah,
that's a great question. When we try to digitize books,
Here's here's what we do. We take a word that
the computer does not know. We actually pair it with
another word for which the computer does know the answer,
and we actually give people both words, and we say
(18:33):
please type both, and we don't tell them which ones which,
We just say, hey, please type both. If they type
the word for which we know the answer, if they
type that one correctly, we assume that they're human, and
we also get some confidence that they type the other
word correctly, and then what we do is okay, so
now we have a guess for what that other word is.
We give it to like ten other different people and
we see if they type the same thing, and if
(18:53):
they all type the same thing, we get with very
high accuracy what that word really is, and that works.
One hallmark of the recapture system in other words, is
that you have to type in two words. There's sometimes
also funny words that a funny combinations that happen, especially
because we are showing two words at a time. Oh boy,
(19:14):
I mean, you know, there's been all kinds of really
funny examples where it's just like, you know, a website
of a church that says like bad Christians and it's
just but these are just two randomly chosen words, so
we shouldn't infer any evil on your part. No, they're random. Now,
a lot has happened since two thousand when capture came along,
and since two thousand and six when you started unsuspectingly
(19:37):
helping Google in the New York Times digitize their old pages.
You know, early on in the first version of a
cap shop, computers were pretty bad at recognizing distorted text,
so they didn't have to be that distorted. But you know,
over time, computers got better and better, and in fact,
by now computers are in many cases about as good
as humans. Because of that, we have to make them
(19:58):
harder and harder. A lot of times, the puzzles are
so hard that even the human can't pass the challenge.
I'm sure you've been sent screenshots of words that are
so much no one can tell where it is. Yes,
that happens, I mean, it's rare that that happens, and
that's why the capture itself in true arms race fashion
(20:22):
has evolved. So what has happened is that for the
more secure things, the captures have moved away from these
distorted characters. And what is being used now are these
the puzzles are now things like you see a bunch
of pictures and you have to click the ones that
contain a stop sign right the traffic lights, the fire hydrants. Yeah,
it's exactly the same idea as recapture, except we're not
(20:45):
the story. We're not trying to digitize books. This a
lot of times comes from things like all the all
the mapping cars or the self driving cars. Basically, these
are cars that are driving around that are capturing images
of the whole world. They're trying to figure out what's
around them. Sometimes they cannot recognize what's in an image.
So it's a similar case. It takes the things like
is this a stopting I'm not sure, Okay, send it
(21:06):
to a human, and then when you get it and
you click on the store sign, you're actually helping either
the self driving car or the mapping software or whatever
know that there is actually a stop sign right here.
Oh so we're still doing good for the world as
we do this, still doing good for the world, or
for a company or for a company, but maybe not
digitizing books. But it's a similar ideas thing that a
(21:26):
computer cannot do. You've just solved a mystery for hundreds
of millions of people. Why it's always traffic lights and
fire hydrants we're supposed to choose and not bananas and puppies,
or it has to do with both self driving cars
and also mapping software. Okay, so now we kind of
get why we have to put up with these challenges,
or we did twenty years ago, but really nothing better
(21:50):
has come along since. Are we sure that there's nothing
less annoying that we could do to thwart these spammers? Yes,
there is. By now, it did become a lot less annoying.
I don't know if you've seen that of late, where
you know, there's a thing that's us recapture. We're just
trying to figure out whether you're a human, and they
just ask you to click somewhere, just click on this box.
(22:11):
That is much less annoying. So sometimes you don't see
anything except I'm not a robot by yeah, yeah, yeah,
I'm not a robot. This is something that is that
is done by Google. This actually comes from you know,
the original team, that is the company that they bought
from me. When you get that one, that means that,
in this particular case, probably means Google has figured out that, yeah,
(22:31):
you know what, we know you because you've been around
since twenty sixteen in this computer, and yeah, you have
a lot of Gmail emails, and you've done a lot
of Google search queries. You're a normal person, You're not
a spammer. So they just do a little thing that
just tries to double check that, you know, I can
move the mouse or whatever. So one thing that has
changed from the year two thousand and five to now
(22:53):
is that there are companies like Google or like Facebook
that for the majority of people on the Internet, they
kind of know who you are. If you have a
fresh computer that you've never used before, then you would
have to do the annoying capture. But for most of us,
you're unlikely to have to type these as much as
you you were back in say the year two thousand
and five. It has become a lot better, you know,
(23:16):
probably a little bit at the cost of your privacy. Okay,
but wait a minute, we now know that computers eventually
got too smart for the distorted text reading touring tests.
Won't they eventually get good enough to identify a few
stupid stop signs in a photo grid? It is, it's
a cat of mouse game. Now. Probably there's a bunch
of people working on making better recognition of stop signs
(23:37):
or something like that eventually. But eventually computers are going
to be able to do everything humans can, and so
at some point there won't be a test that kind
distinguished humans going to computer. Well wait a minute, does
that mean the end of the internet? I mean, what
happens if that, If there's no sort of touring tests
that works anymore. I don't think it's the end of
the internet, particularly because, like I said, more and more
(24:00):
these companies are going to know more and more about you,
and I just don't think there will be a humans problem. Okay, well,
whatever the end game is, why can't we do today,
Since we know it's an arms race, Since we know
that eventually we'll lose it to AI and computers, why
can't we jump to whatever we'll follow it? Now? I'll
(24:22):
tell you why this. By the way, it's like ninety
five percent of the way there. I mean, really, for
most of us, you know, Facebook knows who we are,
and Google knows who we are, So it's ninety percent
of the way there. The reason is not one hundred
percent of the way there is because there are some
people who really care about privacy, and you know, there's
there's always going to be a kind of a way
to browse privately. So for example, there's a chrome has
(24:42):
private browsing. So it's all the stuff when people care
about privacy, I mean there's there's a trade off here, right. Well,
the irony is it seems like most of the websites
to present me with a capture I'm trying to get
to in order to supply my name and address, like
like I'm signing up for something. Yes, it's funny. Why
do I need privacy when the whole purpose is to
(25:02):
supply my information? Yeah, that's funny. Now. I mentioned at
the beginning that Louis has had three world changing ideas.
You've heard about the gym membership that powers the grid,
and you now know about kapture. But what about his
third creation. It's Duo Lingo, the language training app. At
(25:24):
this moment, it has half a billion registered users learning
forty different languages, all for free. And from the very
beginning you could see the fingerprints of Luis Vaughnan, master
of crowdsourcing all over it. In early due Lingo, as
(25:46):
you were learning a language on dual Lingo, you're actually
helping us to translate stuff that computers could not translate.
In fact, CNN was a client, so CNN would send
us their news in English. We would then give it
to people who were Spanish speakers who were learning English,
and we would say, hey, you want to practice your English,
help us translate this CNN article into your native language
of Spanish. And so they would do it, and they
(26:08):
would be learning English and then we would get that translation,
and then we would send it back to CNN and
they would pay us for the translation. That was the
very first version of due Lingo. It turned out that,
just like the gym, it ends up being that it
just can't make much money from this, and so we decided, okay,
just go go to a business model where we actually
give you ads, and the way we make money is by,
(26:30):
you know, showing your ads. The dude just keeps doing that.
He keeps coming up with ideas that make the world
a better place, thwart the bad guys, and make a
lot of money. It's really a shame he gave up
that electrical grid gym thing. Are there ever things that
come to you in the shower that might be your
big third act? I mean, honestly, to have the impact
(26:53):
you've had twice is astonishing, But it makes me think
there's something in you that just has great ideas that
can go really wide. You know, as time passes, I
am a lot more interested in literacy and teaching people
how to read. I think with a computer, we should
be able to teach the whole world how to read
significantly better than humans can teach you how to read.
(27:15):
You know, the US, The US is fine, most adults
Indias know how to read, but many countries in the
world there's a significant fraction of people who don't know
how to read. In fact, there's about a billion adults
in the world that are illiterate. And I think we
can I think we can make a big dent, you know,
with a system to teach people how to read. So
we're working on that in the meantime. Now you know
why you have to encounter those infernal website challenges. You
(27:38):
know how they came about, and you now consider them
unnecessary evil. Well, maybe you do just for people who
are like, I don't know what it is. I just
don't like doing it. I can't even tell what's a
freaking draffic. Like, let's just lay out what would happen
if all these challenges went away tomorrow. What would happen
to the Internet. Most likely, you would get a lot
(28:00):
more spam in either your email spam or you'd get
a more kind of random Facebook follow words that are
not you know, real people. These fake accounts can start
boosting up that political messages. There would be probably more
fake news. They would probably be you know, more spam, right,
(28:21):
and from spam fishing and spywear and yeah, more spywear. Yeah.
The web would be a less safe place, all right.
So when you do explain this to someone at the
proverbial party, are they generally satisfied with the notion that? Yeah,
I think most people. I think most people realize that
(28:41):
it's like, you know, these things are kind of like
a like a key nobody nobody likes. It's not like
I love opening my door with the key. It's kind
of annoying, but yeah, that's there, and I understand it
just makes it makes my house safer. In this case,
it's kind of just makes the whole Internet safer. I
kind of gotta do it. Thanks for listening to this
second to last episode of the season. If you have
(29:03):
any interest in a second season, please spread the word,
subscribe to this podcast, leave a review on Apple Podcasts,
or a rating on Spotify. Unsung Science with David Pogue
is presented by Simon and Schuster and CBS News and
produced by PRX Productions. The executive producers for Simon and
Schuster are Richard Rohrer and Chris Lynch. The PRX production
(29:26):
team is Jocelyn Gonzalez, Morgan Flannery, Pedro, Raphael Rosatto, and
Ian Fox. Project manager Jesse Nelson composed the Unsung Science
theme music and Christina Robello fact checked my script. At
Unsung Science dot com, you can listen to every episode
we've ever made and read complete transcripts. For more of
(29:47):
my stuff, visit David Pogue dot com or follow me
on Twitter at Pogue Pogue. Thanks for the scene that
was an episode of Unsung Science from our friends at
CBS News. You can find more episodes of Unsung Science
wherever you get your podcasts.
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