SlideShare a Scribd company logo
1 of 2
Download to read offline
Sebastian Thrun: Google’s Driverless Car 
As a boy, I loved cars. When I turned 18, I lost my best friend to a car accident. Like this. And then I 
decided I'd dedicate my life to saving one million people every year. Now I haven't succeeded, so this is 
just a progress report, but I'm here to tell you a little bit about self-driving cars.! ! 
男の子がみんなそうであるように 私も車が好きでした 18のときに 一番の親友を自動車事故でなくしま 
した あっけなく それ以来 私の使命になったのは 年に百万という人を 事故から救えないかということで 
す まだ未完成なので 中間報告になりますが 自動運転車について 少しお話しします! 
!I 
saw the concept first in the DARPA Grand Challenges where the U.S. government issued a prize to build 
a self-driving car that could navigate a desert. And even though a hundred teams were there, these cars 
went nowhere. So we decided at Stanford to build a different self-driving car. We built the hardware and 
the software. We made it learn from us, and we set it free in the desert. And the unimaginable happened: 
it became the first car to ever return from a DARPA Grand Challenge, winning Stanford 2 million dollars. 
Yet I still hadn't saved a single life.! ! 
この概念に初めて触れたのは DARPAグランドチャレンジでした 砂漠を切り抜けた自動運転車に アメリ 
カ政府が 賞金を出すことにしたのです 100以上のチームが参加したにもかかわらず ゴールにたどり着け 
たチームはありませんでした スタンフォード大では 新たに自動運転車を作ることにしました ハードとソ 
フトの両方を開発しました 人間から学習させ 砂漠に放ちました そして信じがたいことを実現しました 
DARPAグランドチャレンジで 戻ってきた初めての車となったのです スタンフォード大は 200万ドルの賞 
金を手にしました でもまだ誰の命も救ってはいません! 
! 
Since, our work has focused on building driving cars that can drive anywhere by themselves -- any street 
in California. We've driven 140,000 miles. Our cars have sensors by which they magically can see 
everything around them and make decisions about every aspect of driving. It's the perfect driving 
mechanism. We've driven in cities, like in San Francisco here. We've driven from San Francisco to Los 
Angeles on Highway 1.! ! 
それ以来 私たちは 自分でどこへでも行ける 自動運転車に取り組んでいます カリフォルニアのあらゆる 
通りを 22万キロ走ってきました センサーを搭載していて 魔法のように 周囲の状況を把握し 運転にかか 
わる あらゆる判断を行います 完全な運転機構を備えています ご覧のように サンフランシスコの 街中を 
走っています 州道1号線を サンフランシスコからロサンゼルスへと走りました! 
! 
We've encountered joggers, busy highways, toll booths, and this is without a person in the loop; the car 
just drives itself. In fact, while we drove 140,000 miles, people didn't even notice. Mountain roads, day 
and night, and even crooked Lombard Street in San Francisco. (Laughter) Sometimes our cars get so 
crazy, they even do little stunts.! 
(Video) Man: Oh, my God. What? Second Man: It's driving itself.! ! 
ジョギングする人にも出会い 混雑した高速道路や 料金所を通り 人手を介さずに 車が自分で運転してい 
ます 22万キロも走ったというのに 誰も気づかないのです 山道を越え 夜となく 昼となく 曲がりくねった 
サンフランシスコの ロンバード通りも 意に介さず (笑) 時にはちょっとした スタントまでやってのけま 
す! 
うわーっ マジすか? 車がやってるんだよ! 
!
Sebastian Thrun: Google’s Driverless Car 
Sebastian Thrun: Now I can't get my friend Harold back to life, but I can do something for all the people 
who died. Do you know that driving accidents are the number one cause of death for young people? And 
do you realize that almost all of those are due to human error and not machine error, and can therefore 
be prevented by machines?! ! 
友達のハロルドの命を取り戻すことはできませんが 亡くなったみんなのためにできることがあります 車 
の事故が 若者の死因の第1位なのはご存じですか? そのほとんどは 車の問題ではなく 人間のミスによる 
ということを? これは機械の力によって防ぎうることなのです! 
! 
Do you realize that we could change the capacity of highways by a factor of two or three if we didn't rely 
on human precision on staying in the lane -- improve body position and therefore drive a little bit closer 
together on a little bit narrower lanes, and do away with all traffic jams on highways? Do you realize that 
you, TED users, spend an average of 52 minutes per day in traffic, wasting your time on your daily 
commute? You could regain this time. This is four billion hours wasted in this country alone. And it's 2.4 
billion gallons of gasoline wasted.! ! 
人間の精度で 車道を走るのをやめれば 高速道路を走る車の量を 今の2倍から3倍に 増やすことができま 
す 車の位置を調整して もう少し車間を狭くし レーンの幅も狭めるなら 高速道路の渋滞はなくせます み 
なさんは 毎日の通勤のため 平均して 52分もの時間を 道路の上で 無駄にしています これは取り戻せる時 
間です アメリカだけで 40億時間の無駄です 91億リットルのガソリンが無駄になっています! 
! 
Now I think there's a vision here, a new technology, and I'm really looking forward to a time when 
generations after us look back at us and say how ridiculous it was that humans were driving cars.! 
Thank you. (Applause)! ! 
ここにビジョンがあり 新しいテクノロジーがあります 後の世代の人々が振り返って 車を人間が運転して 
いたなんて まったく馬鹿げていると思うようになることを期待しています! 
どうもありがとうございました (拍手)

More Related Content

Viewers also liked

5 sarah parcak archaeology from space worksheet
5 sarah parcak archaeology from space worksheet5 sarah parcak archaeology from space worksheet
5 sarah parcak archaeology from space worksheet
Meagan Kaiser
 
Marco tempest nikola tesla transcript
Marco tempest nikola tesla transcriptMarco tempest nikola tesla transcript
Marco tempest nikola tesla transcript
Meagan Kaiser
 
5 sarah parcak archaeology from space transcript
5 sarah parcak archaeology from space transcript5 sarah parcak archaeology from space transcript
5 sarah parcak archaeology from space transcript
Meagan Kaiser
 
7 ted birke baehr what's wrong with our food system 2012 pp
7 ted birke baehr what's wrong with our food system 2012 pp7 ted birke baehr what's wrong with our food system 2012 pp
7 ted birke baehr what's wrong with our food system 2012 pp
Meagan Kaiser
 
4 weight and length 2012
4 weight and length 20124 weight and length 2012
4 weight and length 2012
Meagan Kaiser
 
5 hans rosling global population growth transcript
5 hans rosling global population growth transcript5 hans rosling global population growth transcript
5 hans rosling global population growth transcript
Meagan Kaiser
 
Maps and world data worksheet
Maps and world data worksheetMaps and world data worksheet
Maps and world data worksheet
Meagan Kaiser
 
2nd year s literacy syllabus 2015
2nd year s literacy syllabus 20152nd year s literacy syllabus 2015
2nd year s literacy syllabus 2015
Meagan Kaiser
 
Equation word problems
Equation word problemsEquation word problems
Equation word problems
Meagan Kaiser
 
Gever tulley transcript
Gever tulley transcriptGever tulley transcript
Gever tulley transcript
Meagan Kaiser
 
8 jane chen embrace transcript
8 jane chen embrace transcript8 jane chen embrace transcript
8 jane chen embrace transcript
Meagan Kaiser
 

Viewers also liked (14)

5 sarah parcak archaeology from space worksheet
5 sarah parcak archaeology from space worksheet5 sarah parcak archaeology from space worksheet
5 sarah parcak archaeology from space worksheet
 
Marco tempest nikola tesla transcript
Marco tempest nikola tesla transcriptMarco tempest nikola tesla transcript
Marco tempest nikola tesla transcript
 
5 sarah parcak archaeology from space transcript
5 sarah parcak archaeology from space transcript5 sarah parcak archaeology from space transcript
5 sarah parcak archaeology from space transcript
 
7 ted birke baehr what's wrong with our food system 2012 pp
7 ted birke baehr what's wrong with our food system 2012 pp7 ted birke baehr what's wrong with our food system 2012 pp
7 ted birke baehr what's wrong with our food system 2012 pp
 
4 weight and length 2012
4 weight and length 20124 weight and length 2012
4 weight and length 2012
 
Equations worksheet
Equations worksheetEquations worksheet
Equations worksheet
 
Calculating by body
Calculating by bodyCalculating by body
Calculating by body
 
5 hans rosling global population growth transcript
5 hans rosling global population growth transcript5 hans rosling global population growth transcript
5 hans rosling global population growth transcript
 
Maps and world data worksheet
Maps and world data worksheetMaps and world data worksheet
Maps and world data worksheet
 
2nd year s literacy syllabus 2015
2nd year s literacy syllabus 20152nd year s literacy syllabus 2015
2nd year s literacy syllabus 2015
 
Equation word problems
Equation word problemsEquation word problems
Equation word problems
 
Gever tulley transcript
Gever tulley transcriptGever tulley transcript
Gever tulley transcript
 
8 jane chen embrace transcript
8 jane chen embrace transcript8 jane chen embrace transcript
8 jane chen embrace transcript
 
Numbers worksheet
Numbers worksheetNumbers worksheet
Numbers worksheet
 

More from Meagan Kaiser

9 10 academic communications i syllabus
9 10 academic communications i syllabus9 10 academic communications i syllabus
9 10 academic communications i syllabus
Meagan Kaiser
 
Slide presentation example
Slide presentation exampleSlide presentation example
Slide presentation example
Meagan Kaiser
 
Listening midterm test practice 2
Listening midterm test practice 2Listening midterm test practice 2
Listening midterm test practice 2
Meagan Kaiser
 
Equivalent fraction problems
Equivalent fraction problemsEquivalent fraction problems
Equivalent fraction problems
Meagan Kaiser
 
J imz xn-money_bills_coins_us
J imz xn-money_bills_coins_usJ imz xn-money_bills_coins_us
J imz xn-money_bills_coins_us
Meagan Kaiser
 
Typed writing special checklist
Typed writing special checklistTyped writing special checklist
Typed writing special checklist
Meagan Kaiser
 
Cat and dog examples
Cat and dog examplesCat and dog examples
Cat and dog examples
Meagan Kaiser
 
50 questions to get to know someone
50 questions to get to know someone50 questions to get to know someone
50 questions to get to know someone
Meagan Kaiser
 
Daily life plus grammar hunter
Daily life plus grammar hunterDaily life plus grammar hunter
Daily life plus grammar hunter
Meagan Kaiser
 

More from Meagan Kaiser (20)

9 10 academic communications i syllabus
9 10 academic communications i syllabus9 10 academic communications i syllabus
9 10 academic communications i syllabus
 
Monday communicative english
Monday communicative englishMonday communicative english
Monday communicative english
 
Listening fall practice test 2015 2016
Listening fall practice test 2015 2016Listening fall practice test 2015 2016
Listening fall practice test 2015 2016
 
Nikolai begg a tool to fix surgery transcript
Nikolai begg a tool to fix surgery transcriptNikolai begg a tool to fix surgery transcript
Nikolai begg a tool to fix surgery transcript
 
Quiz 1
Quiz 1Quiz 1
Quiz 1
 
Unit 2 quiz 1
Unit 2 quiz 1Unit 2 quiz 1
Unit 2 quiz 1
 
Elizabeth nyamayaro he forshe
Elizabeth nyamayaro  he forsheElizabeth nyamayaro  he forshe
Elizabeth nyamayaro he forshe
 
Untitled 10
Untitled 10Untitled 10
Untitled 10
 
Slide presentation example
Slide presentation exampleSlide presentation example
Slide presentation example
 
Listening midterm test practice 2
Listening midterm test practice 2Listening midterm test practice 2
Listening midterm test practice 2
 
Equivalent fraction problems
Equivalent fraction problemsEquivalent fraction problems
Equivalent fraction problems
 
J imz xn-money_bills_coins_us
J imz xn-money_bills_coins_usJ imz xn-money_bills_coins_us
J imz xn-money_bills_coins_us
 
Time and money
Time and moneyTime and money
Time and money
 
Typed writing special checklist
Typed writing special checklistTyped writing special checklist
Typed writing special checklist
 
Free talking mavs
Free talking mavsFree talking mavs
Free talking mavs
 
Signage 1
Signage 1Signage 1
Signage 1
 
Signage 2
Signage 2Signage 2
Signage 2
 
Cat and dog examples
Cat and dog examplesCat and dog examples
Cat and dog examples
 
50 questions to get to know someone
50 questions to get to know someone50 questions to get to know someone
50 questions to get to know someone
 
Daily life plus grammar hunter
Daily life plus grammar hunterDaily life plus grammar hunter
Daily life plus grammar hunter
 

Sebastian thrun google driverless car transcript

  • 1. Sebastian Thrun: Google’s Driverless Car As a boy, I loved cars. When I turned 18, I lost my best friend to a car accident. Like this. And then I decided I'd dedicate my life to saving one million people every year. Now I haven't succeeded, so this is just a progress report, but I'm here to tell you a little bit about self-driving cars.! ! 男の子がみんなそうであるように 私も車が好きでした 18のときに 一番の親友を自動車事故でなくしま した あっけなく それ以来 私の使命になったのは 年に百万という人を 事故から救えないかということで す まだ未完成なので 中間報告になりますが 自動運転車について 少しお話しします! !I saw the concept first in the DARPA Grand Challenges where the U.S. government issued a prize to build a self-driving car that could navigate a desert. And even though a hundred teams were there, these cars went nowhere. So we decided at Stanford to build a different self-driving car. We built the hardware and the software. We made it learn from us, and we set it free in the desert. And the unimaginable happened: it became the first car to ever return from a DARPA Grand Challenge, winning Stanford 2 million dollars. Yet I still hadn't saved a single life.! ! この概念に初めて触れたのは DARPAグランドチャレンジでした 砂漠を切り抜けた自動運転車に アメリ カ政府が 賞金を出すことにしたのです 100以上のチームが参加したにもかかわらず ゴールにたどり着け たチームはありませんでした スタンフォード大では 新たに自動運転車を作ることにしました ハードとソ フトの両方を開発しました 人間から学習させ 砂漠に放ちました そして信じがたいことを実現しました DARPAグランドチャレンジで 戻ってきた初めての車となったのです スタンフォード大は 200万ドルの賞 金を手にしました でもまだ誰の命も救ってはいません! ! Since, our work has focused on building driving cars that can drive anywhere by themselves -- any street in California. We've driven 140,000 miles. Our cars have sensors by which they magically can see everything around them and make decisions about every aspect of driving. It's the perfect driving mechanism. We've driven in cities, like in San Francisco here. We've driven from San Francisco to Los Angeles on Highway 1.! ! それ以来 私たちは 自分でどこへでも行ける 自動運転車に取り組んでいます カリフォルニアのあらゆる 通りを 22万キロ走ってきました センサーを搭載していて 魔法のように 周囲の状況を把握し 運転にかか わる あらゆる判断を行います 完全な運転機構を備えています ご覧のように サンフランシスコの 街中を 走っています 州道1号線を サンフランシスコからロサンゼルスへと走りました! ! We've encountered joggers, busy highways, toll booths, and this is without a person in the loop; the car just drives itself. In fact, while we drove 140,000 miles, people didn't even notice. Mountain roads, day and night, and even crooked Lombard Street in San Francisco. (Laughter) Sometimes our cars get so crazy, they even do little stunts.! (Video) Man: Oh, my God. What? Second Man: It's driving itself.! ! ジョギングする人にも出会い 混雑した高速道路や 料金所を通り 人手を介さずに 車が自分で運転してい ます 22万キロも走ったというのに 誰も気づかないのです 山道を越え 夜となく 昼となく 曲がりくねった サンフランシスコの ロンバード通りも 意に介さず (笑) 時にはちょっとした スタントまでやってのけま す! うわーっ マジすか? 車がやってるんだよ! !
  • 2. Sebastian Thrun: Google’s Driverless Car Sebastian Thrun: Now I can't get my friend Harold back to life, but I can do something for all the people who died. Do you know that driving accidents are the number one cause of death for young people? And do you realize that almost all of those are due to human error and not machine error, and can therefore be prevented by machines?! ! 友達のハロルドの命を取り戻すことはできませんが 亡くなったみんなのためにできることがあります 車 の事故が 若者の死因の第1位なのはご存じですか? そのほとんどは 車の問題ではなく 人間のミスによる ということを? これは機械の力によって防ぎうることなのです! ! Do you realize that we could change the capacity of highways by a factor of two or three if we didn't rely on human precision on staying in the lane -- improve body position and therefore drive a little bit closer together on a little bit narrower lanes, and do away with all traffic jams on highways? Do you realize that you, TED users, spend an average of 52 minutes per day in traffic, wasting your time on your daily commute? You could regain this time. This is four billion hours wasted in this country alone. And it's 2.4 billion gallons of gasoline wasted.! ! 人間の精度で 車道を走るのをやめれば 高速道路を走る車の量を 今の2倍から3倍に 増やすことができま す 車の位置を調整して もう少し車間を狭くし レーンの幅も狭めるなら 高速道路の渋滞はなくせます み なさんは 毎日の通勤のため 平均して 52分もの時間を 道路の上で 無駄にしています これは取り戻せる時 間です アメリカだけで 40億時間の無駄です 91億リットルのガソリンが無駄になっています! ! Now I think there's a vision here, a new technology, and I'm really looking forward to a time when generations after us look back at us and say how ridiculous it was that humans were driving cars.! Thank you. (Applause)! ! ここにビジョンがあり 新しいテクノロジーがあります 後の世代の人々が振り返って 車を人間が運転して いたなんて まったく馬鹿げていると思うようになることを期待しています! どうもありがとうございました (拍手)