Internet ha evolucionado de ser una simple red de ordenadores a convertirse en una vasta red de dispositivos interconectados, que muchos consideran casi sobrenaturales. Hoy en día, el Internet de las Cosas (IoT) está revolucionando nuestra vida cotidiana, ya que los dispositivos que nos rodean pueden conocer nuestras preferencias, desde lo que nos gusta comer hasta nuestros patrones de sueño. Esta evolución tecnológica ha transformado nuestro comportamiento y nuestras interacciones, creando un entorno donde las máquinas no solo nos asisten, sino que también nos entienden.
En el pasado, Internet era una herramienta estática, utilizada principalmente para la comunicación y la búsqueda de información. Sin embargo, en el presente, se ha convertido en un ecosistema dinámico donde la recopilación y el análisis de datos son fundamentales. Gracias a la inteligencia artificial y el aprendizaje automático, los dispositivos no solo recopilan datos, sino que también aprenden de ellos, mejorando continuamente nuestra experiencia.
Mirando hacia el futuro, el potencial de Internet es ilimitado. La capacidad de interconectar dispositivos y recopilar datos en tiempo real promete mejorar aspectos clave de nuestras vidas, desde la salud hasta la educación. Sin embargo, también plantea desafíos significativos en términos de privacidad y seguridad.
En resumen, el impacto de Internet en la humanidad es profundo y multifacético. A medida que nos adentramos en esta nueva era digital, es crucial comprender no solo cómo nos beneficia, sino también cómo afecta nuestra interacción con el mundo.
**Hashtags:** #InternetDeLasCosas, #Tecnología, #FuturoDigital
**Keywords:** Internet, impacto de Internet, Internet de las Cosas, tecnología, evolución digital, comportamiento humano, inteligencia artificial, privacidad, dispositivos conectados, análisis de datos.
En el pasado, Internet era una herramienta estática, utilizada principalmente para la comunicación y la búsqueda de información. Sin embargo, en el presente, se ha convertido en un ecosistema dinámico donde la recopilación y el análisis de datos son fundamentales. Gracias a la inteligencia artificial y el aprendizaje automático, los dispositivos no solo recopilan datos, sino que también aprenden de ellos, mejorando continuamente nuestra experiencia.
Mirando hacia el futuro, el potencial de Internet es ilimitado. La capacidad de interconectar dispositivos y recopilar datos en tiempo real promete mejorar aspectos clave de nuestras vidas, desde la salud hasta la educación. Sin embargo, también plantea desafíos significativos en términos de privacidad y seguridad.
En resumen, el impacto de Internet en la humanidad es profundo y multifacético. A medida que nos adentramos en esta nueva era digital, es crucial comprender no solo cómo nos beneficia, sino también cómo afecta nuestra interacción con el mundo.
**Hashtags:** #InternetDeLasCosas, #Tecnología, #FuturoDigital
**Keywords:** Internet, impacto de Internet, Internet de las Cosas, tecnología, evolución digital, comportamiento humano, inteligencia artificial, privacidad, dispositivos conectados, análisis de datos.
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DiversiónTranscripción
00:00Today it will be partially cloudy in the morning and clear in the afternoon.
00:08West wind of about 20 kilometers per hour in the afternoon.
00:11Tonight partially cloudy, minimums of about 12 degrees.
00:16It's eight in the morning.
00:21I'm not at home.
00:24But my house knows I'm coming.
00:30The Internet is expanding, and as it does, it's giving us almost supernatural powers.
00:36Alexa, you haven't put butter on the toast.
00:41I'm not sure how to help you with that.
00:46The Internet is no longer just a network of computers and servers.
00:49Now it's a network of things, things that know us.
00:54Things that know what we like to eat, how long we sleep, how to open the door to the house and even our heart rate.
01:02Alexa, where are my keys?
01:04They're in your room.
01:06At 8.30 you have a meeting.
01:12The Internet is no longer just a cloud.
01:14Now it has a body.
01:17A body of devices that are its limbs, eyes, ears and even its brain.
01:24Each device we connect becomes part of the network.
01:29But are all those devices at our service or are they the ones that control us in secret?
01:37Currently, the Internet is everywhere, listening to us, influencing us, being part of us.
01:45But if the Internet now has a body, how far can it go?
02:04The Internet is an amplifier of intelligence.
02:09But for every use that we can think of that has a positive and beneficial effect, there is another negative use.
02:16Human beings do not end at the limits of our biological tissues.
02:21The tools are appendices, extensions of what we are and model our behavior.
02:29As things in our physical life start to be on the Internet and interconnected, the number of things that can go wrong will increase.
02:37Little robots do more things for us than we think.
02:41Now there are billions of network sensors that form what we call the Internet of Things.
02:50It's like seeing the planet develop a nervous system.
02:57The merging of these different technologies is going to lead to the first true artificial intelligence.
03:07And then what?
03:08You never take enough care.
03:11We must control devices before they control us.
03:22But we would not have our smart devices if it had not been for the work of a man.
03:27Doug Engelbart.
03:29Doug Engelbart.
03:30Doug Engelbart.
03:32Doug was the most monomaniacal man I've ever known.
03:36All his life he was focused on one thing, the increase of intelligence.
03:43The idea was that human beings were pretty good, but with computers they could be a lot better.
03:50He imagined network computing in a way that was both highly technical and highly idealistic, even utopian.
04:02If in your office there was a computer that was active and at your disposal all day,
04:07responding to each of your actions, how much value could you get from something like that?
04:13It was fall 1968 when Doug Engelbart was the mother of all the presentations.
04:20Come in, Menlo Park.
04:24Okay, there's Don Andrews' hand in Menlo Park.
04:27There were thousands of computer engineers in a room,
04:30and they saw Engelbart using a computer to communicate with people in another room.
04:36Now I'd like to introduce Jeff Ralefson from Menlo Park.
04:39He's sitting in a room like this working.
04:42Hi Jeff.
04:43Hi.
04:44It was the first time that many of them saw computers as a true form of communication.
04:50Suddenly, at that moment, all the people who were there began to imagine not just computers,
04:56but computer networks.
05:00Engelbart is the person who invented the computer mouse.
05:03It was kind of like a little wooden box that you could wrap around with your hand.
05:07You know, think about that for a moment.
05:09It's something that accommodates the computer to the human body, to the hand.
05:15The devices that I'm using,
05:17Doug had a vertical screen in black and white that looked like a piece of paper.
05:22He invented a mouse to be able to point things through a potentiometer.
05:27He invented hyperlinks so that you could connect a document to another document.
05:32But if I want to, I can also say,
05:34I want to go to the library. What do I have to pick up there?
05:37I just point to that, and I see books and all.
05:41This was like a World Wide Web in a box.
05:47Thank you very much for coming to the opening ceremony.
05:52Engelbart and his team actually helped humanize the computer.
05:57The computers were going to bring us together,
05:59and by bringing us together, let's be more fully human.
06:03Steve Jobs was the first one to realize this.
06:06We're tool builders.
06:08And that's what a computer is to me.
06:10It's the most extraordinary tool that I've ever come up with.
06:13And it's the equivalent of a bicycle for our minds.
06:22Three things.
06:24A widescreen iPod with touch screen,
06:26a revolutionary mobile phone,
06:28and a great internet communication device.
06:31Are you getting it?
06:34These are not three separate devices.
06:38This is a single device.
06:44And we have called it the iPod.
06:48And we have called it the iPhone.
07:03I remember when the iPhone was first announced back in 2007.
07:06I could absolutely not wait to get one.
07:09And when I finally did get my hands on one,
07:12it felt like I was living in the future.
07:15And now I can't remember what it was like to live without this.
07:22It's a device made of plastic and metal
07:24that has all the answers, all the world's knowledge and information,
07:28that can bring you a car,
07:30that can move mountains,
07:32that can make people do things to you,
07:34all by rubbing a magic mirror.
07:38And no place has embraced that magic like Silicon Valley.
07:43Here you can see smartphones everywhere.
07:47But this is also where the next generation of smart devices is being managed.
07:53To see them, I'm going to visit Beta,
07:55the most innovative analog shop in Palo Alto,
07:58of digital devices.
08:00Hi, welcome to Beta.
08:02Have you been before?
08:03No, I'm Derek.
08:04I'm Katrina, nice to meet you.
08:06Likewise.
08:08Everything here is out of the box,
08:10so you can touch it, feel it, interact with it,
08:12see how it's going to fit into your life.
08:14It's a Bluetooth connected device,
08:16so you can create lightscenes during the day,
08:18sunset, in the night,
08:20you know what happens during the day,
08:22you can control it directly from your app.
08:24Free video viewing tool,
08:26any command that you would be able to give your phone,
08:28you can just use the button,
08:30it will automatically water for you,
08:32you can interact with it, you can touch it and talk to it,
08:34you can put it on your kids, you can put it on your kid,
08:36you can put it on your dog, back, whatever.
08:39What I wanted to hear.
08:41I haven't crashed against anything yet.
08:43Oh my God.
08:47I want one.
08:51Beta's store looks like a toy store for adults,
08:53but as I found out later,
08:55more than a store, it's a research laboratory
08:57where data about you is collected.
09:01We created our store to take the best of the internet
09:03to a physical store.
09:05Although our store sells products,
09:08we don't make money selling them.
09:10Something quite unusual in physical stores.
09:12We are the only store that does it.
09:16And how do you get profits
09:18if you don't make money selling products?
09:22In the store we have a unique business model,
09:24since we directly rent space to companies.
09:28We have an agreement with a company
09:30called RetailNex,
09:32which uses artificial vision with cameras
09:34located on the ceiling
09:36to understand how people buy in stores.
09:40In Beta's store,
09:42the most important sensors
09:44are not on the shelves,
09:46but on the ceiling.
09:52While we interact with the products,
09:54these cameras observe us,
09:56recording how long we spend
09:58in front of each product
10:02and learning what we like.
10:06And the customers
10:08don't know that they are being observed
10:10or...
10:12It's the most innocent version of surveillance
10:14that exists right now.
10:16I came to Beta to see smart devices,
10:18but I was surprised to find out
10:20that they were actually observing me.
10:22To learn more about how
10:24smart cameras help businesses
10:26like Beta,
10:28I visited the manufacturer of these sensors,
10:30RetailNex.
10:32Wouldn't it be great to know your customers?
10:35Introducing Aurora,
10:37by RetailNex,
10:39the first all-in-one sensor
10:41designed specifically
10:43for the complex needs
10:45of retail,
10:47the next generation sensor
10:49for customer measurement.
10:51So, explain to me how this works.
10:53When someone comes into the store,
10:55what sort of data do you collect
10:57about that person?
10:59You can tell a lot of things
11:01about the type of person
11:03male, female, approximate age,
11:05and you can get a lot of information
11:07about what they're doing in the store.
11:12Can I ask you a question?
11:14How do you know the age
11:16and the sex of the people
11:18who come into the store?
11:20We use artificial vision.
11:22It works like the human eye,
11:24but it's an algorithm
11:26that does it automatically.
11:28If you want to understand
11:30what type of customer
11:33you're looking for,
11:37you can get very good results.
11:41RetailNex cameras
11:43help minorities
11:45identify and direct their efforts
11:47towards the best customers.
11:49But other analytical companies
11:51have taken facial recognition
11:53to another level.
11:55The system does not need
11:57an exaggerated expression.
11:59It can also detect microexpressions.
12:01These are cameras
12:03that can tell you
12:05how you feel about a product.
12:11If you like it
12:13or not.
12:19But while cameras
12:21are very useful sensors
12:23for minorities,
12:25they're nothing compared
12:27to what we wear all the time.
12:30They want to use the unique
12:32identifiers associated
12:34with your mobile phone
12:36to find out where you shop,
12:38how long you linger in each section
12:40of the store.
12:42For minorities,
12:44your smartphone is like your fingerprint.
12:46It tells them if you've been
12:48to their store before
12:50and when you were there
12:52for the last time.
12:54If 10 years ago someone
12:56said to you,
12:58where are you?
13:00What are you reading?
13:02What are you spending money on?
13:04Who are you talking to?
13:06And what are you doing 24 hours a day?
13:08Would you say,
13:10of course not.
13:12Are you kidding?
13:14And now people sleep in front
13:16of the Apple store
13:18for the privilege
13:20of buying a $800 sensor
13:22that does that and more.
13:24RetailNext insists
13:27that your data is completely anonymous
13:29unless you expressly
13:31accept their use.
13:35If you do, you're letting
13:37those companies know
13:39exactly who you are
13:41and now they can follow you
13:43and offer you products in real time.
13:45But this kind of tracking
13:47didn't start in stores.
13:49It started in the network.
13:51Online stores don't have cameras
13:53and sensors to track us.
13:55They don't need them.
13:57They have something better.
14:01Cookies.
14:03What exactly is a cookie?
14:05And how do companies
14:07use them to track us?
14:09To find out,
14:11I've come to talk to this man.
14:13Lou Montulli invented
14:15cookies in 1994.
14:17The concept is a bit like
14:19the message of a fortune cookie.
14:21A cookie is a file
14:24and the message it contains
14:26is a single line of text.
14:28We can't read it,
14:30but websites can.
14:32Every time we visit a website,
14:34it stores cookies in our computer.
14:36These tiny files help
14:38websites remember us.
14:40This is what allows us
14:42to do things like shopping carts.
14:44You get this fortune cookie,
14:46you pick it up,
14:48but you don't know what's inside.
14:50You really don't care.
14:52And the website breaks it,
14:54reads the message,
14:56and says,
14:58oh, I know who you are.
15:00You wanted to buy a toaster,
15:02and we're going to put it in your shopping cart.
15:04That was the idea.
15:06Inoffensive, wasn't it?
15:08Something unexpected happened.
15:10Advertisers didn't take long
15:12to look at cookies
15:14and advertising networks
15:16started using them to track us.
15:18You start this really terrible
15:21business to know as much about
15:23you as possible.
15:25They could target ads
15:27in a way that television
15:29never did.
15:31Because television
15:33is a medium that you watch.
15:35The internet
15:37is a medium that watches you
15:39as you watch it.
15:43Nowadays, everything you do online,
15:45every cookie you receive,
15:47becomes part of a virtual profile
15:49a dossier about you.
15:53These profiles
15:55include information
15:57that we don't even consider
15:59leaking.
16:03I wear a Fitbit bracelet
16:05because I try to lose weight.
16:07And a couple of times a day
16:09I'm informed of my physical activity levels
16:11to Fitbit,
16:13which may well be aggregating
16:15this information to people
16:18on our plans.
16:22You get this sort of three-dimensional
16:24profile of a person.
16:26You can predict what they're going to do.
16:28They now can find out exactly
16:30who is most susceptible to being manipulated
16:32by buying various products.
16:34There are scammers
16:36who are looking for older people
16:38and they know that that person
16:40has been looking online for places
16:42to invest their retirement money.
16:44They get a phone call
16:46from Mr. Life Savings.
16:48This is a stockpile.
16:50So if you have all the data,
16:52you can target specific people
16:54who you can stay.
16:56That's the danger right now.
16:58But the emergence
17:00of these virtual files
17:02was predicted a long time ago.
17:10This educational report
17:13from 1976
17:15describes a very familiar future.
17:17By the year 2000,
17:19computers will have invaded
17:21our privacy on an unimaginable scale.
17:23They will be interconnected
17:25and unless they are prevented
17:27by new laws,
17:29they will be able to sell information
17:31about where we travel,
17:33how much we spend,
17:35and what hotels and restaurants.
17:37If we pay our bills,
17:39and when,
17:41we will have more than 30 million
17:43inhabitants in North America.
17:45Currently, our dossier
17:47contains all this information
17:49and much, much more.
17:55But the company
17:57that has the most valuable dossier
17:59is the one that almost all of us
18:01use daily.
18:03Google.
18:05Google knows a lot about us
18:07because Google knows our intentions.
18:11And when we think
18:13about the world of advertising,
18:15the ads based on the intention
18:17are what really works.
18:21It was not so long ago
18:23that people said,
18:25how can anyone think that
18:27that company is going to make money
18:29by giving searches?
18:31It seemed a ridiculous idea.
18:33Google's huge advertising network
18:35with emerging windows
18:37generates billions of dollars
18:40every month.
18:4290% of Google's revenue
18:44comes from ads.
18:46And Google only gets paid
18:48if people click.
18:50Now, most of the pages
18:52that you visit on the internet
18:54allow Google to track us.
18:56Most people love YouTube.
18:58I love YouTube.
19:02Why did they purchase YouTube?
19:04Because it gives them
19:06more information.
19:08Why did they develop Chrome,
19:10a browser?
19:12Why did they develop Android,
19:14an operating system?
19:16They're collecting information
19:18on us on more than 60 different
19:20platforms.
19:22And we are completely
19:24oblivious to it.
19:28When was the last time you read
19:30a search condition?
19:32My guess is you probably just
19:34clicked on accept.
19:37And when we're not actively online,
19:39it's easy to forget that the internet
19:41is still watching us.
19:43Everywhere you go,
19:45even when you're not actively using
19:47your phone,
19:49it's still listening.
19:51Companies just find very clever ways
19:53to get us engaged
19:55and help us in their businesses.
19:57And if they can't get us
19:59they're asking our devices
20:01to do it.
20:03The devices
20:05that are going to inhabit our lives,
20:07not just cell phones,
20:09but your smart refrigerator,
20:11your smart car,
20:13all those things
20:15are basically going to be
20:17the extracting tools for someone.
20:24Maybe the most sinister example
20:26is the talk Barbie doll.
20:28Introducing a whole new way
20:30to play with Barbie.
20:33Now there's a Barbie doll
20:35that when you turn it on
20:37it'll find your Wi-Fi network
20:39and will use the cloud
20:41to have a conversation
20:43with you about your interests.
20:45What do you want to be when you're older?
20:47I want to be a vet.
20:49That's great. Curing sick animals
20:51is an amazing goal.
20:53Hello Barbie is recording all those conversations
20:55and sending them to the cloud.
20:57I love New York.
20:59What do you like most about the city?
21:01To me, this is basically
21:03a Barbie doll designed to interrogate
21:05an eight-year-old girl
21:07and get her to tell her stories.
21:09What do you want to be when you're older?
21:11Uh, I want to be a scientist.
21:15Great! A scientist!
21:17Science sounds amazing to me.
21:19Why do you want to be a scientist?
21:22Well, in school I really enjoyed
21:24chemistry and physics.
21:28The study of physics is incredible.
21:31Think about gravity.
21:33You can't see it, but as soon as you trip,
21:35it pulls you down.
21:37Have you ever tripped or fallen over something?
21:39Yeah, I've fallen a few times in my life, Barbie.
21:43It happens to me all the time.
21:45That's gravity.
21:47It pulls you down and sometimes it does damage.
21:49Wow, you could be the next Marie Curie
21:51or the next Einstein.
21:53Am I right?
21:55I think you are right, Barbie.
21:57I knew you were smart.
22:01As long as our devices
22:03work for corporations,
22:05they'll try to turn us into good consumers.
22:07But what if in the not-too-distant future
22:09our machines not only
22:11push us to buy,
22:13but also offer us a new currency
22:15of exchange?
22:17Shares.
22:19We'll share our tastes,
22:21our interests,
22:23our private lives.
22:31Do you want to share your biometric data today?
22:33500 points.
22:39Your biometric data
22:41indicates that you haven't slept well.
22:43Are you feeling okay?
22:47Lucy, does your boyfriend
22:51know that you're pregnant?
22:54You're pregnant?
23:12However strange this may seem,
23:14it will very quickly become
23:16the new normal.
23:24Currently,
23:26all devices that connect us
23:28with the world also collect
23:30our information.
23:32But none of this would have been possible
23:34without a technology from the Second World War
23:36and the most beautiful woman
23:38in the world.
23:40The technology, of course,
23:42is wireless.
23:44And the woman?
23:46You're the man I think you are.
23:48You'll get Miss Hedy Lamarr to seal it with a kiss.
23:50What about it, Hedy?
23:52Go ahead.
23:56In 1938,
23:58the American public knew
24:00the Austrian actress Hedy Lamarr
24:02as a dynamic and dazzling protagonist.
24:04Funny, I don't have an ear for beauty.
24:06Just an eye for it.
24:08But she was not an ordinary actress.
24:11I came here to ask you to marry me.
24:14She was also an inventor.
24:16In her free time,
24:18Hedy invented an improved traffic light
24:21that carbonated and gave flavor to water.
24:27But when she saw Europe sink into chaos,
24:29Hedy focused her attention on ideas
24:31that could contribute to the war effort.
24:33It has a strange effect on me.
24:37And she wondered
24:39how the transmissions could be shielded
24:41by radio to prevent the enemy
24:43from capturing them.
24:45Then she heard this.
24:47Le Ballet Mécanique.
24:51This piece was composed in 1924
24:53by an avant-garde composer,
24:55George Hantail,
24:57who conceived it as a celebration
24:59of machines as music creators.
25:01This complex arrangement
25:03included three xylophones,
25:05four drums,
25:07three aircraft engines
25:09and 16 mechanical pianos.
25:11The mechanical pianos
25:14or pianolas
25:16used perforated paper rolls
25:18to generate music.
25:20But the rolls of the Ballet Mécanique
25:22were special.
25:24They were synchronized.
25:33Hedy Lamarr realized
25:35that synchronized paper rolls
25:37were what she needed
25:39for her next invention,
25:41a secure radio communication system.
25:43Using mechanical pianos
25:45as inspiration,
25:47she and Hantail designed
25:49a system called Frequency Jump,
25:51through which a secret message
25:53could jump from one radio frequency
25:55to another.
25:57For this, the system used
25:59a roll of perforated paper.
26:01But unlike mechanical pianos,
26:03the holes here did not control
26:05musical notes, but frequencies.
26:07The message was sent in pieces.
26:13And in the receiver station,
26:15a roll of identical paper
26:17recomposed the message.
26:23She had done it!
26:25Frequency Jump made it impossible
26:27to intercept radio transmissions.
26:29Immediately, Hedy donated
26:31her patent to the army.
26:33But the high command
26:35was not impressed by the idea.
26:37They did not take seriously
26:39a security system based
26:42The project was forgotten
26:44for decades,
26:46but Hedy had had a great idea.
26:48And it was not lost forever.
26:52It contained a gold mine.
26:59Whoever thinks that a phone
27:01in the car is not his,
27:03is not up to date with the advances
27:05in the mobile phone industry.
27:07Finally, in the 80s,
27:09Frequency Jump was declassified.
27:11And shortly after,
27:13we had the first mobile phones.
27:17This Nokia Mobira
27:19only costs $ 595.
27:23Hedy Lamarr's idea
27:25caused a chain reaction,
27:27an explosion of wireless devices.
27:31Since the year 2000,
27:33data traffic on mobile networks
27:35has increased almost 400 million times,
27:37largely in developing countries.
27:41The invention with which Hedy
27:43hoped to save the world,
27:45has transformed it.
27:47There are cultures
27:49that have skipped a technological generation.
27:51Cultures in development routes
27:53where there was no telephone,
27:55or running water, or electricity.
27:57Today you take a mobile to that village
27:59and its horizons expand unimaginably.
28:03Soon there will be a billion mobile phones
28:05in Africa, which is extraordinary.
28:07The poorest people on the planet
28:10can have a mobile phone.
28:14This idea of wireless mobility
28:16will change the way
28:18people think about themselves,
28:20about national boundaries,
28:22about education, about almost everything.
28:26Now wireless networks
28:28cover the Earth
28:30almost like a new atmosphere.
28:32It is easier than ever
28:34to be always connected.
28:36But are we really more connected
28:38than the people around us?
28:40What is the impact of technology
28:42on our daily life?
28:44Interactions occur
28:46through a technological device.
28:50And not everything is benign.
28:54The noise is getting louder.
29:03You have to move away from the noise.
29:08What if you could live
29:10in a really quiet place
29:12without all that wireless noise?
29:16Welcome to the silent area.
29:20We are in the middle of what is called
29:22the National Radio Silence Area,
29:24a unique area in North America.
29:28It is 33,700 square kilometers.
29:32More or less the extension
29:34of Massachusetts and Connecticut together.
29:37In the heart of the silent area
29:39is the town of Greenback,
29:41West Virginia.
29:43There is the largest
29:45radio telescope in the world.
29:47And the silent area
29:49was created to protect it.
29:51The Greenback telescope
29:53is a Swiss watch
29:55the size of a football stadium.
29:57But while it is so big,
29:59its tolerances are always measured
30:01in fractions of a millimeter.
30:03We are talking about
30:05a telescope that stands
30:07taller than the Statue of Liberty.
30:11The reflector has a surface
30:13of more than 9 hectares.
30:17The bigger the bucket,
30:19the more rain drops it can catch.
30:22Currently, the telescope
30:24is one of the fundamental tools
30:26for the search
30:28for extraterrestrial intelligence.
30:30In recent years, we have discovered
30:32with the Greenback telescope
30:35basic organic molecules,
30:37which are somehow
30:39the basic elements of life
30:41floating in interstellar gas.
30:43But these discoveries
30:45have a price.
30:51Radio silence
30:53in hundreds of kilometers
30:55around.
31:01Unlike traditional telescopes,
31:03radiotelescopes do not see,
31:05they listen to radio waves.
31:07In the 1950s,
31:09the telescope was built here
31:11because it was a quiet place.
31:13Perfect for that.
31:15Listen.
31:17The observatory was built
31:19in the 1950s
31:21and they picked Greenback specifically.
31:23They said it was the quietest place
31:25on earth.
31:27So I don't know,
31:29maybe it's the last quiet place
31:32for the residents of Greenback.
31:34This not only means radio silence,
31:36it also means wireless silence.
31:38Living in Greenback has its challenges.
31:40You can't have a wireless phone
31:42or a cell phone.
31:44There are no cell phone antennas.
31:46Wireless speakers, wireless headphones.
31:48Garage controls cause problems.
31:50Electrified fences in the garden.
31:52Microwaves.
31:54Bluetooth devices.
31:56Car controls.
31:58PS4, Wii, Nintendo.
32:00You would imagine they would cause interference.
32:02They do.
32:06But the biggest threat to the telescope
32:08is Wi-Fi.
32:10Wi-Fi completely cancels
32:12what we're trying to do.
32:14What's also amazing is that
32:16we're beginning to interact
32:18with the internet
32:20as if it is the only social being
32:22that we have in our lives.
32:26And that's the dangerous thing,
32:29I think.
32:31What Mike told me made me think
32:33what it would be like to live
32:35as a teenager in a disconnected town.
32:37Would they feel marginalized?
32:39A girl who moved here recently
32:41asked me when she first moved here
32:43if she had cell phone coverage
32:45and I told her,
32:47you're not going to have it.
32:49This is Greenback's secondary school
32:51in the shadow of the radio telescope.
32:53So you're here, you go to New York
32:55or Maryland.
32:57Becky liked my state.
32:59Bob made a comment.
33:01I have to answer right now.
33:05If the internet disappeared,
33:07we could survive here.
33:09The people of the city,
33:11if they hit a wheel,
33:13wait for someone to come get them.
33:15Here we go down, we change the wheel,
33:17we go up again and we go home.
33:19We don't call people on the cell phone.
33:21We go to their house and we knock on the door.
33:23We like the quiet zone.
33:27Sometimes it seems to me
33:29that we are the control population
33:31of a gigantic experiment
33:33that humanity is doing
33:35in the telecommunications industry.
33:37Here we live without the benefits
33:39or the distractions of cellular technology.
33:41What I see scares me.
33:43I see couples
33:45and groups of people
33:47all focused on their devices.
33:49I feel like
33:51I've been misled for a moment
33:53and the whole world
33:56In any other part,
33:58the internet is attached to you all the time.
34:00Whether you're purposely using it
34:02or not,
34:04it's doing something
34:06with your device.
34:08Even if it's in your pocket,
34:10you're tied to it.
34:12Here you're not tied to anything.
34:14It's interesting to think
34:16that something special has happened here.
34:18But in fact it's the opposite.
34:20It's something that has happened everywhere else.
34:22Maybe the neighbours of Green Bank
34:24enjoy their radio silence.
34:26But for others,
34:28living without our mobile devices
34:30would not only be unpleasant,
34:32it would be impossible.
34:34We are outsourcing our memories
34:36to these devices
34:38and we depend on them,
34:40but we don't have a backup system.
34:42Most young people
34:44at university age
34:46think they couldn't spend
34:48a whole day without their device.
34:51For many people,
34:53their mobile has become
34:55a body appendage.
34:57They can't not live without it.
34:59Information is like their third skin.
35:01The library of all human knowledge
35:03is at a distance screen.
35:05We can think
35:07that this means
35:09that we're becoming more intelligent,
35:11but we depend more and more
35:13on the devices
35:15to make them think for us.
35:17What used to be research
35:19is now Google search.
35:23In 1998,
35:25Larry Page and Sergey Brin
35:27launched Google
35:29to unravel the network information
35:31and they did this using algorithms.
35:36They used an algorithm
35:38to index the network
35:40and another to sort the results
35:42obtained from the thousands of millions
35:44of pages of the index.
35:46They gave us the opportunity
35:48to compare the results
35:50of each book in the library.
35:52PageRank, the Google classification algorithm,
35:54decided which page
35:56would appear
35:58in the coveted first place.
36:00The more links you got,
36:02the higher score you got.
36:04But it could be that somebody
36:06had fewer links,
36:08but from more important places.
36:10Those links would give you more value.
36:12That was the secret sauce.
36:14PageRank worked so well
36:16that even if a search
36:18can give millions,
36:20even thousands of millions of results,
36:22it usually only matters 10.
36:24Typically, we see 10 search results
36:26on the first page.
36:2850% of our clicks
36:30are focused
36:32on the first two search results.
36:3450%.
36:36And the majority of people
36:38don't go beyond the first page.
36:40But what we have begun to realize
36:42is that the order of the results
36:44influences the decisions
36:46we make about everything.
36:48We let Google decide
36:50which information
36:52is best for us.
36:54But if your search gives millions of results,
36:56why do we get those 10?
37:00Hey, guys.
37:02Today I want to give you
37:04the big question.
37:06How to rank number one
37:08on Google?
37:10When Google created its algorithm,
37:13it created a new industry.
37:15Search ranking.
37:17Today we're going to talk
37:19about best ranking
37:21and what I believe Google wants.
37:23There's a new ranking factor
37:25that's huge around the world.
37:27It's a really sneaky, really clever tactic.
37:29So don't hesitate to implement it.
37:31These experts have learned
37:33to optimize the structure
37:35and content of a web page.
37:37The algorithm is the key
37:39to decrypting Google.
37:41All too often,
37:43we go so far as to feed
37:45the Google bot
37:47rather than feed the Google bot.
38:05We believe that just because
38:07a computer program
38:09is operating,
38:11however it's happening,
38:13we can trust it.
38:15The algorithm has to put
38:17things in order.
38:19So what if the algorithm
38:21itself ends up favoring
38:23one candidate over another?
38:25Is the activity of Google
38:27in fact creating more interest
38:29in that candidate
38:31and in turn
38:33generating more votes?
38:39Facebook has experimented
38:41with manipulating
38:43electoral results.
38:45I mean, the way they do this
38:47can actually make
38:49more people want to vote.
38:51If Facebook just sent out
38:53go-out-vote reminders,
38:55but they sent them
38:57only to people
38:59of one political party,
39:01if they did that
39:03on voting day,
39:05they could easily
39:07pass and reply
39:09as an article posted on Monday.
39:11So Facebook also suppressed
39:13conservatively news stories
39:15in its trending section.
39:17People thought this was outrageous
39:19because this is a neutral
39:21technological system
39:23that was being manipulated
39:25by humans.
39:27But that's an absurd way
39:29to use things.
39:31There are no neutral
39:33technological systems.
39:37Like dogs,
39:39these artificial intelligences
39:41are not programmed.
39:43They are trained.
39:45It's a process
39:47called automatic learning.
39:51Toy dog.
39:53Yes, that's incorrect.
39:55The next generation of robots
39:57will learn like an insect
39:59or a baby.
40:07It'll bump into things.
40:09It'll learn how to walk.
40:11It'll learn how to navigate
40:13in this world.
40:15Rather than have all
40:17of its abilities programmed
40:19from the very start.
40:21But with automatic learning,
40:23we no longer have full control
40:25over artificial intelligence.
40:27Will machines become as intelligent
40:29as we are?
40:31Any machine that can make
40:33decisions can act in ways
40:35that its designers cannot predict.
40:37And there are many of those machines now.
40:40It's a pleasure to be here
40:42to introduce a brand new product.
40:44In 2005, Google presented
40:46an artificial intelligence program
40:48to organize photos.
40:50With automatic learning,
40:52Google Photos understands
40:54what's important
40:56and helps you organize
40:58your memories automatically.
41:00And it became evident
41:02when its algorithm
41:04trained people
41:06who trained
41:08these artificial intelligence systems
41:10to train them on white faces.
41:12These weren't necessarily racist,
41:14but the biases
41:16in how you want to train
41:18these systems
41:20end up embedding
41:22these incredible racist assumptions.
41:24If a machine can learn
41:26from humans,
41:28that doesn't mean
41:30we teach it correctly.
41:32In a recent presentation,
41:34Tay proved that humans
41:36love to corrupt artificial intelligence.
41:38Hello, world!
41:40The more you talk to it,
41:42the smarter Tay gets.
41:44Tay's software
41:46mimics the patterns
41:48of the language
41:50of young people
41:52between 18 and 24 years old.
41:54Even the best algorithms
41:56make mistakes at scale.
41:58But the internet trolls
42:00can improvise
42:02based on what people tell them.
42:04Algorithms make mistakes
42:06much more easily
42:08than people,
42:10and they can also be tricked
42:12much more easily.
42:14In a few hours,
42:16Tay was praising Hitler
42:18and launching racist
42:20and anti-feminist attacks.
42:22These systems have
42:24some impressive weak points.
42:26This happens all the time.
42:28From online dating,
42:30hiring, financial investments,
42:32the study of flu epidemics,
42:34or cancer research.
42:36Programming algorithms
42:38make decisions
42:40without us knowing
42:42how those decisions are made.
42:44And that's what's scary.
42:46The machines
42:48are going to end up
42:50running my life
42:52and everyone else's.
42:54I was curious
42:56to do something
42:58that until now
43:00only humans knew how to do.
43:02Drive.
43:18Welcome to DuckyTown.
43:22DuckyTown has
43:24a very serious mission.
43:26To reproduce the challenges
43:28that autonomous vehicles
43:30have to overcome
43:32quickly and safely
43:34when it comes to miniature cars.
43:36What's the advantage
43:38of researching autonomous
43:40vehicles in DuckyTown?
43:42The idea here is that
43:44we have this city
43:46where we can deploy
43:4850 of these vehicles
43:50very easily at any time
43:52What it's doing now
43:54is using the camera
43:56to identify the road lines
43:58and then when it gets
44:00to an intersection
44:02it reads the intersection sign
44:04and then it's a random
44:06arrival based on what
44:08it reads on the sign.
44:10What are the real problems
44:12to resolve to make
44:14an autonomous vehicle?
44:16One big problem is that
44:18every person in the environment
44:20is being very difficult
44:22to understand at the same time.
44:24Liam was telling me
44:26all the problems
44:28that they still haven't
44:30solved. Unpredictable humans,
44:32bad weather, detours
44:34and what to do if
44:36an inevitable accident occurs.
44:40Our autonomous cars
44:42still have a lot to learn
44:44but unlike us
44:46they learn fast.
44:48There's this new
44:50idea that's very powerful
44:52which is robotics in the cloud.
44:54Basically, it's the use
44:56that you can interconnect
44:58the robots with the internet
45:00so if you're a robot
45:02and you learn something
45:04all the robots know
45:06it's a very different
45:08learning experience.
45:10And it's not just science fiction
45:12it's already being implemented
45:14in the world of autonomous cars.
45:16The robots understand
45:18the space, their location
45:20they can navigate the space
45:22but not much more.
45:24But what will happen
45:26when the robots can do
45:28everything that we do?
45:30The development of
45:32full artificial intelligence
45:34can bring about the end
45:36of the human race.
45:38With artificial intelligence
45:40we're invoking the devil
45:42like in those stories
45:44I can control the devil
45:46but it doesn't work.
45:48We should not believe
45:50in keeping a super intelligent genius
45:52locked in his lamp forever
45:54sooner or later it will escape.
45:56A super artificial intelligence
45:58has the potential to tilt
46:00the balance of power.
46:02If a cloud-based intelligence
46:04could communicate instantaneously
46:06how would humans maintain control?
46:10Hello?
46:12How are you?
46:14To find out more about
46:16intelligent machines
46:18I made a videoconference
46:20with Kevin Warwick
46:22a professor of cybernetics
46:24at the University of Coventry.
46:26He's interested in fusing
46:28human and artificial intelligence
46:30to create a hybrid, a cyborg.
46:32What do you think
46:34about artificial intelligence?
46:36If you can't beat it,
46:38join it.
46:40We become part of it
46:42and it becomes part of us.
46:44That's how we incorporate
46:46the power of artificial intelligence
46:48into our system
46:50instead of it acting against us.
46:52Kevin explained to me
46:54that even though humans
46:56and machines look different
46:58their minds work with electrical signals
47:00and binary code.
47:02Brain cells send impulses
47:04like the artificial cells
47:06of a computer.
47:08In fact,
47:10they can send brain signals
47:12across the internet
47:14as if they were part
47:16of your nervous system.
47:18Kevin not only studies
47:20the theoretical possibilities
47:22of using the internet
47:24as a nervous system
47:26he has connected his own to the network.
47:28In 2002, Kevin
47:30implanted an electrode guide
47:32in his arm and connected it
47:34to a robotic hand
47:36becoming the first cyborg
47:38in the world.
47:40Wow!
47:42I went to Columbia University
47:44in New York
47:46and the guide there
47:48helped me connect
47:50my nervous system
47:52to the internet
47:54and we linked it
47:56to a robotic hand
47:58in the UK.
48:00With the implant
48:02placed and connected
48:04the robot hand
48:06received signals
48:08from my brain
48:10in the UK
48:12and my brain
48:14was receiving signals
48:16from the fingertips
48:18and I was able to feel
48:20how much force
48:22that hand was applying
48:24to another continent.
48:26That's incredible!
48:28So with the internet
48:30and an implant
48:32do you think that
48:34in the long term
48:36that will allow us
48:38to fuse our nervous system
48:40with a large network?
48:42Yes, I sincerely hope so.
48:44That cybernetic network
48:46could help humans
48:48and machines to understand each other better.
48:50If you think about how humans
48:52communicate with each other
48:54and compare it with these technologies
48:56it's embarrassing, frankly.
48:58It's terrible.
49:00The technologies
49:02that we still use
49:04even now
49:06are mechanical pressure waves
49:08to communicate with me.
49:10I'm converting
49:12the enormously complex
49:14electrochemical signals
49:16of my brain
49:18into these elementary
49:20coded pressure waves.
49:22It's really terrible.
49:24We have to be up to date.
49:26We have the technology
49:28that we call
49:30the singularity.
49:34The point without return.
49:36Since the birth
49:38of artificial intelligence
49:40we have wondered
49:42when it would surpass us.
49:44Perhaps the day will come
49:46when we and the machines
49:48will cross in opposite directions
49:50and there will be a transition point
49:52where we won't know
49:54whether it's a man or a machine.
49:56How will life be
49:58after the singularity?
50:03You'll take a little pill
50:05it will arrange itself
50:07wiring your neural cortex
50:09and your hearing system
50:11to trust your brain
50:13and, you know, put you on the internet.
50:15Welcome.
50:17Our brain will interact
50:19with all the chips in the room.
50:26We'll just walk into the room
50:28and we'll connect
50:30to the internet mentally.
50:32Remember, you have a date
50:34tonight at nine.
50:36We simply blink
50:38and see all the information
50:40we need to organize
50:42the day.
50:46It's going to start to change
50:48how we think we end
50:50and the new world begins
50:52because more and more
50:54we'll act as if each one of us
50:56lived in our own personalized universe.
51:02We're all going to be
51:04confined in an AI
51:06software shell.
51:08You're going to give
51:10your AI permission to listen
51:12to every conversation you have,
51:14read all your emails,
51:16monitor all your biometric data
51:18and that AI's mission
51:20is to make your life better.
51:24As soon as a computer
51:26in some sense wakes up
51:28because it has access
51:30to the internet,
51:32it has access to everything,
51:34all human knowledge
51:36and it'll transform
51:38into something else.
51:42If we do have a world
51:44of super intelligent robots,
51:46if we're very, very lucky
51:48and we're very, very lucky
51:50and we're very, very lucky
51:52and we're very, very lucky
51:54they will treat us like pets.
51:56They will treat us like food.
52:01Me, I prefer to be a pet.
52:07I call the internet
52:09the internet nest.
52:11We have been building
52:13a nest for the first
52:15truly intelligent machine
52:17to arise.
52:22When you talk about
52:24the unintended consequences
52:26we end up with something
52:28that we thought
52:30would be very good
52:32and it isn't.
52:34I think when you think
52:36how far we are
52:38from the invisible systems
52:40that surround us every day
52:42and provide us so much,
52:44we're in a fool's road.
52:46But what if the internet
52:48doesn't enslave us?
52:50What if it is said
52:52that it becomes
52:54our guiding light?
53:00From the moment
53:02we are born
53:04we will seek
53:06knowledge and beauty in it.
53:08We will seek knowledge
53:10and beauty in it.
53:20It will see our qualities
53:24and feed them.
53:28It will help us
53:30reach our potential.
53:32And it will answer
53:34our deepest doubts.
53:40As humans
53:42we have always wanted
53:44to understand our connection
53:46with the cosmos,
53:48our place in the universe,
53:50perhaps our maximum creation,
53:52the internet?
53:58Some of us
54:00Some of us
54:02Someday it will give us back
54:04the favor
54:06and enlighten us.