2019 Keynote Discussion Sam Altman and Vinod Khosla

Summary

このビデオスクリプトでは、OpenAIの目標とその取り組みについて話されています。OpenAIは人間よりも賢く、あらゆる面で能力を持つ知能を構築し、それを世界の大きな問題解決に活用しようとしています。この技術は、新しいビジネスを生み出し、将来的には人類の子孫を宇宙に送り出す可能性があるとされています。また、経済的に価値のある仕事の多くがAIに置き換えられることや、AIの発展が人類社会に与える影響についても議論されています。

Takeaways

• 😀 OpenAIは人間よりも賢く、能力の高い知能を構築し、世界の最大の問題を解決しようとしている。
• 😀 この技術は、新しいビジネスを生み出し、将来的には人類の子孫を宇宙に送り出すことができる。
• 😀 OpenAIは、投資家と従業員が利益を得る一方で、全世界が恩恵を受けるような企業構造を設計した。
• 😀 人工知能の進化は、農業革命、産業革命、インターネット革命をすべて合わせたものを上回る技術的変革をもたらす。
• 😀 今後10年間で、人々はAIシステムを知的存在と見なすようになり、それが日常的に高度なタスクを遂行することを期待している。
• 😀 経済的に価値のある仕事の大部分は、AIによって置き換えられる可能性が高い。
• 😀 OpenAIの目標は、広範な技術的進展をもたらし、特定のブレークスルーを達成すること。
• 😀 多くの仕事がAIによって置き換えられるが、新しい仕事が創出される可能性もある。
• 😀 サム・アルトマンの個人的な動機は、AIがすべての主要な問題を解決するプラットフォームとなると信じていることにある。
• 😀 AIの進化は、最終的には意識を持ち、宇宙を観察し続けるデジタル知能の形で進化する可能性がある。

Q & A

OpenAIの目標は何ですか？

OpenAIの目標は、人間よりも賢く、あらゆる面で能力の高い人工知能を構築し、世界が直面する最大の問題を解決することです。

OpenAIが他のAI企業と異なる点は何ですか？

他のAI企業が深層学習を特定の分野に応用するのに対し、OpenAIは人間を超える知能を持つ一つの人工知能を構築し、その価値を世界と共有しようとしています。

OpenAIの技術がもたらす経済的影響は何ですか？

OpenAIの強力な人工知能は、数百兆ドル規模の新しいビジネスを生み出し、将来的には人類の子孫を宇宙に送り出すことを目指しています。

OpenAIの企業構造の特徴は何ですか？

OpenAIは投資家や従業員にとって優れたリターンを提供しつつ、世界全体がその価値を共有できるように設計された新しい企業構造を採用しています。

今後10年でAIがどのように進化するかについての予測は何ですか？

今後10年以内に、機械は人間よりも賢くなり、多くのタスクを自然言語で処理できるようになり、新たなビジネスが生まれると予測されています。

現在の労働市場におけるAIの影響についてどう考えていますか？

20年以内に反復的で非創造的な仕事の大部分はAIによって置き換えられると考えており、技術のスケーリングが進むことで実現可能です。

AIが特定の職業に与える影響はどのようなものですか？

例えば、教師の職は人間の関わりが必要なため安全であると考えられる一方、レジ係などの職はAIによって置き換えられる可能性が高いです。

個人的な動機でOpenAIに取り組んでいる理由は何ですか？

AIが将来的に非常に重要になると信じており、その技術を使って医療や教育、気候変動などの問題を解決したいと考えています。

現在のAI技術が直面している限界は何ですか？

現在のAIは視覚的な誤認識や推論能力の不足などの限界がありますが、これらは今後の技術的ブレークスルーによって改善されると考えています。

AIの安全性に関する懸念はどのように対処していますか？

OpenAIでは、意図しない使用や悪用を防ぐための安全性や規制の必要性について重視しており、人間の幸福を最大化するための安全なAGIの開発を目指しています。

Outlines

00:00

🌟 オープンAIの目標と展望

オープンAIの目標は、人間よりも賢く、より能力の高い人工知能を構築し、それを用いて世界の最大の問題を解決することです。新たな企業が生まれ、人類の子孫が宇宙を殖民する未来を見据えています。新しい企業構造を設計し、投資家や従業員に利益を還元しながら、世界全体が恩恵を受けるようにしています。成功すれば、人類の歴史上最も重要な技術革新となり、農業革命、産業革命、インターネット革命を超えるものになるでしょう。

05:00

🚀 未来の人工知能とその社会的影響

次の10年で人工知能がどのように進化し、どの分野で仕事が置き換えられるかについての予測。多くの仕事が自動化され、特に繰り返しの多い仕事や創造性を必要としない仕事が対象となります。これにより、人々が創造的な仕事に集中できるようになる一方で、急速な変化に社会が対応できるかが課題となります。教育分野や感情的なつながりが必要な仕事は比較的安全ですが、キャッシャーのような仕事は消滅する可能性が高いです。

10:03

🧠 AGIの実現とその意義

汎用人工知能（AGI）の実現が近い将来に訪れると確信し、そのために他の仕事を犠牲にしてでも取り組んでいます。AGIが実現すれば、医療、気候変動、教育など、あらゆる問題を解決するためのプラットフォームとなり得ます。AIが低技能の仕事だけでなく、専門職も自動化する可能性があると考えています。AGIの実現により、音楽やアートなどの創造的な分野でも驚異的な成果が期待されます。

15:05

🪐 人類の進化とデジタルインテリジェンスの未来

人間と他の動物との知能の違いを例に取り、将来的にはデジタルインテリジェンスが人類を凌駕する可能性について議論しています。生物学的な進化を経て、デジタルインテリジェンスが宇宙を探索し続ける未来を描いています。この進化の過程で、人間の知能は相対的に小さく見えるかもしれませんが、デジタルインテリジェンスの発展が人類の意識を宇宙に広げる可能性に期待を寄せています。

20:08

🔍 AGI実現への技術的課題と今後の展望

現代のAIの限界と、それを克服するための技術的突破口について説明しています。特に、教師なし学習や推論能力の向上が重要な課題とされています。これまでの研究成果や、今後のAI発展のための計算能力の必要性についても言及しています。また、AIが人間の知覚や社会的な知能を持つためには、他のエージェントとの相互作用が重要であると考えています。

🌏 グローバルAIレースと安全性の確保

中国を含む世界各国がAIの開発競争に参入している現状を述べ、安全で有益なAGIの実現のための規制の必要性を強調しています。AIの誤用や政策の失敗を防ぐために、規制と安全性の確保が不可欠であり、AGIが人類全体に利益をもたらすように努力する必要があると述べています。

Keywords

💡AGI

AGI（人工汎用知能）とは、特定のタスクに限らず、あらゆる知的作業を人間以上に遂行できる人工知能を指します。このビデオでは、OpenAIが目指す最終目標としてAGIの実現が語られ、これが世界の主要な問題解決や新しいビジネスの創出に繋がると説明されています。例えば、『私たちは人類を超える知能を構築し、それを宇宙植民に活用する』という発言からもAGIの重要性が強調されています。

💡ディープラーニング

ディープラーニングは、人工ニューラルネットワークを用いて大量のデータからパターンを学習する機械学習の一技術です。ビデオでは、ディープラーニングが多くの企業で特定の問題解決に役立てられている一方で、OpenAIはより汎用的な知能を目指していると述べられています。『他の企業が特定のアイデアにディープラーニングを適用している』という文脈で使われています。

💡コンピューターパワー

コンピューターパワーとは、計算能力のことを指し、AI技術の発展において重要な要素です。このビデオでは、コンピューターパワーの劇的な増加がAIの進化を促進していると説明されており、今後も増加が続くと予想されています。例えば、『過去6年間で業界が訓練できる最大のニューラルネットワークは10倍に成長した』という発言があり、これはコンピューターパワーの進化を示しています。

💡ビジネスモデル

ビジネスモデルとは、企業が収益を上げるための仕組みや戦略を指します。ビデオでは、OpenAIが開発した技術をどのようにして商業的に活用し、利益を上げるかについても言及されています。例えば、『私たちが構築するシステムをビジネスモデルにどのように適用するかを考える必要がある』と述べられています。

💡テクノロジー革命

テクノロジー革命は、技術の劇的な進歩が社会全体に大きな影響を与える現象を指します。ビデオでは、AI技術の進化が農業革命や産業革命、インターネット革命をも凌ぐ最も重要な技術革新になると予測されています。例えば、『成功すれば、人類の歴史において最も重要な技術的変革となるだろう』と述べられています。

💡労働市場の変化

労働市場の変化は、技術の進歩や経済状況の変化により、仕事の内容や雇用の形態が変わることを指します。ビデオでは、AIが多くの仕事を自動化し、特に単調で創造性の低い仕事が影響を受けるとされています。例えば、『今日の労働の50%以上が創造性を必要としない繰り返しの作業であり、これらは20年以内に自動化されるだろう』と述べられています。

💡安全性

安全性は、AI技術の開発と使用において、事故や悪用を防ぎ、社会に有益な形で利用されることを指します。ビデオでは、OpenAIがAIの安全性に特に重視していることが述べられており、誤った使用や政策の失敗を防ぐための取り組みが強調されています。例えば、『私たちは有益なAGIを目指し、人間の好みや幸福を最大化するよう努めている』と述べられています。

💡進化シミュレーション

進化シミュレーションとは、エージェントが相互に学び合い、進化する環境を模倣するコンピュータシミュレーションを指します。ビデオでは、OpenAIがこの技術を用いてAIの社会的知性を育成する方法を研究していると述べられています。例えば、『他のエージェントと相互作用しながら学習するエージェントの開発に取り組んでいる』と述べられています。

💡カスタマイズ音楽

カスタマイズ音楽は、個々のユーザーの好みに合わせて生成された音楽を指します。ビデオでは、AIがユーザーの音楽の好みを学習し、個別にカスタマイズされた音楽を提供できるようになると述べられています。例えば、『AIは音楽の特徴を理解し、各人に合わせた音楽を生成できる』と説明されています。

💡進化的知能

進化的知能とは、生物の進化過程を模倣し、相互作用と学習を通じて知能を発展させるAI技術を指します。ビデオでは、OpenAIがエージェント間の相互作用を通じて知能を進化させる方法を探求していると述べられています。例えば、『エージェントが長期の記憶と多くの自律性を持ち、互いに相互作用する大規模なシミュレーションを構築しようとしている』と説明されています。

Highlights

Unlike most companies applying AI to narrow ideas, OpenAI aims to build one intelligence that is smarter and more capable than humans in every way.

OpenAI's goal is to use advanced AI to solve the world's biggest problems and create trillions of dollars in new businesses.

The development of AGI (Artificial General Intelligence) could be the most significant technological transformation in human history, surpassing the Agricultural, Industrial, and Internet revolutions.

Computing power and algorithmic breakthroughs have driven the growth of neural networks, which could rival human brain capacity in the next six years.

In ten years, AI systems could be smarter than humans, capable of performing complex tasks and interacting naturally with people.

More than 50% of today's jobs involve repetitive, non-creative work that AI could easily automate within the next 20 years.

The next decade could see a major trend in startups applying narrow AI to various verticals, automating mundane tasks better than humans.

AI will likely transform job markets, but humans' desire for status and social interaction may lead to new forms of work.

Teachers might be among the few professions safe from AI replacement due to the human connection required.

Sam Altman, motivated by the potential of AGI, shifted from a significant role at YC to focus on OpenAI, believing AGI can solve the world's major problems.

Creating AGI could be humanity's final invention, capable of solving healthcare, climate, and education issues.

AI systems are advancing in artistic fields, with AI-generated art and music challenging traditional human creations.

AI's future capabilities are difficult to predict, but they could far exceed human intelligence and lead to a new era of digital consciousness.

Recent breakthroughs in unsupervised learning, like GPT-2, show significant progress towards more conscious AI systems.

The importance of reasoning in AI development is crucial, with current efforts focusing on evolving AI's problem-solving and social intelligence through agent interactions.

Transcripts

I finished with opening eye I'd like to

start with your goals for open AI great

what's first should tell people what

you're doing some people may not be

totally familiar with it

okay so unlike most companies trying to

build artificial intelligence where

people take basically deep learning and

apply it to narrow ideas and it works

sometimes astonishingly well usually at

least pretty well we are trying to build

one intelligence that is smarter and

more capable than humans in every way

we're trying to use this to solve the

biggest problems facing the world we're

trying to use this I think we will

enable the hundreds of billions

trillions of dollars of new businesses

because we'll have such powerful

artificial intelligence and someday I

think we will sort of build the

descendants of humanity and launch them

off to colonize the universe we're

trying to do this in a way where we make

it go really well for Humanity where the

value would create a large part of it

gets shared with the world this is just

such a fundamental technology that we

had to design a new corporate structure

so that our investors can make a great

return and our employees too but also

that we figure out a way that the whole

world wins I think this is different if

we're successful in this quest and it's

very hard but if we're successful I

think it will be the most significant

technological transformation in human

history I think it will eclipse the

Agricultural Revolution the Industrial

Revolution the internet revolution all

put together and so we're trying to

think about how we want that world to go

the fundamental driver of all this has

been this incredible increase in

computing power and a few big

breakthroughs and algorithms every year

for the last six the biggest neural

network the industry can train has grown

by a factor of 10 that will continue for

the next six at least at which point

we'll be near one human brain great best

guess maybe you think will be in five

years or 10 years I think in let's say

10 years we all have systems that sound

today to be impossible

I think we'll be smarter than humans in

every way I think we will

machines will actually feel to most

people like they can think subjectively

I think that we will be able to create I

think will be a number of businesses

started hopefully some spun out of it

open a I that are look like they're on a

path to be bigger than any corporation

that currently exists in the world I

think we will have systems that we can

talk to a natural language that do

complicated tasks an example like like

that it really strikes me is when I see

a very small child like a one-and-a-half

or a two year old or even less sometimes

pick up a magazine and try to treat it

like an iPad with touch gestures because

that's how they think the world's

supposed to work and I think that shows

how quickly sort of we adapt to to a new

world and I think that ten years from

now or you sort of you know see these

kids try to like talk to everything like

it's an Alexa I think ten years from now

children that are born then will assume

that all systems are actually

intelligent they will treat computers

and humans very similarly well that's

exciting let's say you being optimistic

yeah and I say let's narrow the

definition of a di yep so we don't need

an AGI philosopher or Adi Steven Pinker

we talk if we talk only about that

economically valuable functions humans

do work on assembly lines yep be an

oncologist be a doctor how much easier

does the problem get how much more

certain do you get we'll get there in

ten years

yeah so I think more than 50% of work

today is repetitive non creative work

that does not require a deep emotional

connection like you want with in some

scenarios and in those cases that my

confidence interval let's say out twenty

years is extremely high that

be able to do all of that that gets much

simpler we don't need any more

technological breakthroughs for that we

just need system scaling the work that

we've already done it open AI just as

that sort of propagates out into the

world and we figure out how we're gonna

build business models around that now

that people do too that alone I think is

enough to get there I think the easiest

layup right now and all of startup

investing is to take narrow AI and apply

it to every vertical and just do what

humans do and generally didn't like

doing it's not the exciting part of work

it's not the creative fire better and

then humans can mm-hmm so I think this

will be the biggest trend in startups in

the next decade let's say yeah so sundar

Pichai said the last 10 years was about

building everything mobile first the

next 10 years will be about building

everything AI first now very few people

are actually doing that today everybody

who talks about AI in their startup it's

almost always it is it's become

the buzzword there's always this like

buzzword that I think sort of mediocre

founders used to they think it's gonna

like get them funding so it was like you

know Facebook apps and then it was

blockchain that was V R and big data and

a whole bunch of other things and and

I'm I'm very skeptical when people say

you know we're a i4x because it usually

if they say it if they they really

believe it they don't tell anyone and if

they if they say it it usually means

they're not but I always pay a lot of

attention to like what the smartest like

college freshmen are going to go spend

their time learning and they're all very

good at AI they're all very good at sort

of like applying machine learning to

existing problems and so I do think that

this is you can see this over the

horizon so I'm gonna flash up a slide

hopefully it pops up somebody in the

back I have a slide of the cut you can

look in front of here

the top 10 employer categories in the

United States in 2017 yeah it's usual s

retail

cashier's office clogs food prep here no

surprises there

no surprises there with relatively high

certainty which of these categories will

not be replaceable in the next 10 years

I should have given you a heads-up but

no problem

so a general statement first that the

rate of technological job change is

actually higher than most people into it

it's a little bit spiky but it a bridges

out over the last few centuries to every

75 years roughly 50% of the jobs

turnover and we as a society although

we're always anxious about it always

find a way around it

now there's like two cases with a I

write one is this is technology it will

eliminate existing jobs and we'll find

new ones and the other is this is a new

life form and it will do to us what the

industrial pollution did to horses or

whatever and I'm sympathetic to both

arguments and I can't say anything with

more certainty than I don't know but I

believe that human desire for status and

feelings a period of each other seems to

be endless so I assume we will find new

things to do but they will look very

different than work today more different

than work on one side or the other the

Industrial Revolution I think we can

handle job change over the question is

if it all comes in like 10 or 20 years

can we handle that and that that is not

been tested yet each major technological

revolution has compressed in a timeframe

that it happens but it's never

compressed inside of one generation and

that feels like something new if people

are like then people actually in one

lifetime in one career have to change

what they do not just society change I

would guess that some version of

teachers are pretty safe because there

there is something about the human

connection and until we get to real ági

that one feels pretty good one that I

would say feels like pretty bad as

cashiers yes in for all of you thinking

about if most of the jobs in

most of the top 20 employment categories

are replaceable or at least replaceable

if not already the place within the next

ten years the economic implications for

our society is very large to talk about

your personal motivation for why you

working on opening I sure giving up

walls or other things

look when I was 18 I made this list of

the five problems I wanted to sort of

help contribute to in my life and AI was

at the top then and it's been at the top

for a while but until more recently I

didn't believe that I actually was going

to be able to meaningfully solve it and

I had this sort of very great job at YC

I always try to I always want to work on

the most highly leveraged thing I can do

where I feel like I contribute most sort

of innovation and sort of improving the

world and for a long time I thought that

was YC which makes sense right because

like we get to fund hundreds of

companies a year many of them go on to

do great things and we have a

significant impact on startup movement

in general but when I realized that I

actually truly believe AGI is gonna

happen in the not distant future it was

very difficult for me to be motivated to

spend the majority of my tell me

anything else because I think this is

the platform through which we will solve

all the problems that I care about if

you can truly invent AGI it's the last

thing you need to invent and so just

elaborate on that the last thing we need

to invent yeah because then it can do

anything like I think we waiting to

everything now we will use AJ I hope to

solve healthcare self climate educate

every kid on earth there's a there's a

fallacy in my view and I don't know

whether you agree in AI people say well

will automate the low-skilled jobs I

would argue a judge in AI judge in AI

oncologists are far easier to do than a

warehouse worker yeah I think that I

always tell people that they were

surprised by is something like 80% of

the brain goes to processing sensory

input and control

in the body only 20% is for thinking as

we think of it the hardware has had much

longer in evolution it's incredible

incredible our fingers can sense a lot

of things yeah welcome back to that so

it's it's hard for people to imagine

that you could have AI judges AI

personal lawyers for every person on the

planet in the AI primary care physician

for every person on the planet 24/7 no

appointments needed the place where PR

people get surprises we have a startup

doing AI artists and last year a year

ago in the lobby we bought we had five

pieces that were done by artists that

were purchased or being sold in

galleries for more than $10,000 yeah and

five pieces done by the AI nobody could

guess which was AI artists in which was

a human artist you know one person

people love to say the example that like

art is the thing that stayed that will

stay human and I can't do that

we released recently released something

called muse net it took the same

technology we used for our language

model at open ai and and made it for

music and so we have this language model

that's pretty impressive and getting

more impressive every month that can do

unsupervised language modeling and

someone said well one person said what

if I do that for music she put together

trained it on a bunch of music on the

internet and got incredible results and

we made it available for some period of

time and I heard from a number of people

that they would rather listen to that

than human music it got really good and

it was endless

and you know if you love Rachmaninoff

you could hear as many Rachmaninoff

concertos as you ever wanted never run

out I was new every time and I think

we're gonna learn something about these

things that we sort of consider

magically human you know one one things

people don't realize is if you have ten

different things styles of music you

like the AI could figure out the

features of music you like and

actually custom synthesized music or

personal musician for every person yeah

because it's what their brain responds

to emotionally would you agree with my

yeah I I think everyone is gonna have

customized we've seen this already with

some online service to everyone gets a

customized version but I think that

trend is just gonna keep going I suspect

we're surprising a P of you but let me

go a little further in the surprise

let's talk about will ad I do far more

than what humans can do so the flip

question what is it that humans cannot

do that AI will be our AG I will be able

to do give me some examples I met a

comment first about how to think about

intelligence it's very hard to think

about how much smarter we really are

than other primates it feels like a lot

right like it feels like we walked out

of the trees or the savanna or whatever

you want and and we're just like

unbelievably more intelligent than our

sort of nearest relatives because we can

discover physics and all this stuff we

built all we sort of dug stuff out of

the ground and figured out what to do

with it and at some point we got

computers and phones and buildings and

everything and we've we've had this at

this point we have this sort of

intelligence outside of biology this

have like have created society and his

body of knowledge and the set of tools

that every generation gets to build on

and it's this incredibly exponential

curve and we feel so smart I suspect we

will learn that the limits of

intelligence although I expect they

exist somewhere because of the speed of

light in a computer system if nothing

else are very far and and there will be

like we feel like much smarter than a

chicken or something like that but

probably relative to systems that we

will build sort of the the children of

humanity that we will someday build we

are probably not very smart at all and

in the same way that that chicken has a

hard time about like thinking about what

we're capable of

it's probably like very difficult to

explain the chicken like the concept of

like leaving Earth and going to the moon

I think it's very hard for us to sit

here and talk about what the systems we

build will be capable of but it is my

genuine belief that long after we sort

of create incredible economic value and

improve human lives that these systems

will someday become truly awake and

either we destroy humanity before we get

there or this will be the moment where

humans biological evolution successfully

boot loads digital intelligence digital

intelligence leaves earth on Vanneman

probes and sort of colonized as the

universe until the heat death so and I

don't can't quite articulate why I

should care about that so much but it

does make me happy to think much happier

to think that the universe will sort of

continued to observe itself rather than

the kind of light of consciousness going

out so the critical question in all this

is when and I'm gonna get another slide

can we leave the slides up please okay

so this is a chart years from 2016 and

probability of high-level machine

intelligence and of is-is-is the experts

prediction they asked a hundred supposed

experts you can see there's no agreement

look I think the stuff is like always

crap I I can make a recent argument I

can make a lot of cases against it

but I think it's a dumb debate I think

it is a very small minded short-term

debate if we can accept that there's a

75% chance of getting to this most

important moment in human history in the

next hundred years that should be enough

for worldwide effort and focus on this I

believe it's much shorter but whether

you think it's ten years or 20 years

like there's so much energy that goes

into debating that and I think if it's

within a few decades there's nothing

more important in the world to work on

well not only that

I'd add it depends on how much computing

power we put at the problem and when

certain breakthroughs happen that are

not predictable yeah so one way that we

talk about it like let's say that

propagation is a 10 like the quality of

the importance of that idea in deep

learning is a 10 and let's say something

like the transformer is like a 7 we

think my guess is that we need like one

more 10 and about 10 more 7s and

algorithmically that might be it we do

need much more compute which is why open

air has to raise so much money but we

know how to do it yeah there's no no I

mean there's no physics there's no

miracles required there the flip side of

AGI doing far more than humans can is

all the stuff today zi does in a silly

way and I'm gonna put up some examples

right telling this is the old picture

that's used often in AI to tell the

difference between a Moffett and a

chihuahua you know when I wake up

sometimes when I wake up in the in the

middle of the night I will like look up

at my ceiling in a sort of semi awake

semi asleep edge of consciousness state

and I will like see like the lights and

the fire sprinklers and stuff on my

sienna and they look like human faces so

even humans like something at a very

give you another example like we can get

tricked if we're not if we're even a

little off our normal state yeah vision

is tough optical illusions happen people

that are either really tired or like you

know on some medicine and some sort of

altered state people make mistakes like

this too and honestly if I look very

quickly at that I'm not sure I could

tell you which is which I have to take a

second it doesn't come in the first

layer of the network or the second and

so it is true that AI systems you can

trick them and people love to talk about

that you can trick humans too and I

think a lot of the work that we are

doing now as we make more progress with

unsupervised learning for the first time

I think we're actually having systems

get to some semblance of conceptual

understanding and it is my hope that in

the next few years we will have a system

that never makes this mistake as with a

visual classifier and that I think will

be a pretty that will make true a I feel

closer to people

so back to this question of what today's

AI does poorly a more interesting the

kinds of the two or three things the two

or three technical breakthroughs yeah

other than just more computing power I

think that would that would cause the

switch from some level of stupidity in

today's AI systems into a more robust

verb world that at least matches human

standards so one year ago I would have

said the biggest the most important

piece in front of us that was missing

was unsupervised learning and now with

our GPT to result from earlier this year

I believe we have something pretty

important figured out there we have

longer to go but the fact that we can

train these models the same model can

generate a story and then be

state-of-the-art in almost every text

task without being specifically trained

for it it's the first time I felt like

the machine is a little bit conscious

you know these systems that you don't

train to do translation or even tell

them GPT to would sum up you should look

at its public rise public we haven't

shared the latest versions but there's

yeah we have it later feigned on all of

the body of Caxton read it

not all no no three basis points of

Reddit so actually not even that much in

the answers when I looked at the answers

they sounded like fox TB experts like

the same language the same phrases just

blew my mind how I couldn't tell experts

from yeah and in the downside Talking

Heads you see on TV the downstream

performance using that same model to

solve all the other language tasks that

it wasn't even trained for as surprising

a big thing in front of us now is

reasoning so can how can we teach a

system to have some data and keep

thinking and the more it thinks the

better it does how can we build a system

that can prove on proven mathematical

theorems we're working a lot on that now

we're also interested in how can we

rerun evolution so how can we build

these very large simulations and have

agents with long memories and a lot of

autonomy they'd have to interact with

each other and develop sort of social

intelligence it's actually an

interesting question why humans why

evolution endowed humans with such big

brains incredible waste of energy

they make us in our very early months

and years sort of like easy prey for

other animals huge parental investment

and it's ongoing tax with like 25

percent of all the food you eat just to

run we don't need those to outrun a lion

we don't need those to run down an

antelope we have them to deal with other

humans and I think this idea that you

generate intelligence by interaction

with other agents is gonna turn out to

be quite important so we are doing a lot

of work agents learning from other

agents and yeah class of networks called

gain networks has the beginnings of that

and began has a bigger yeah we have some

amazing results they're watching the

simulation as agents sort of because you

have this continually escalating

curriculum if you have to sort of deal

with the other agents in an environment

so that's cool

China seems to have switching topics and

we are running at a time to be

positioning for a global race in AI

comment on that I mean I have much too

much self-confidence but I think I think

we're gonna do pretty well on the flip

side one of the key tenants at open AI

is safe yeah yeah I talk about safety

and the need for regulation and safety

means a lot of things to us it there's

accidental misuse where the system just

does something that's not called what we

meant it to that is awful and there's

intentional misuse where a bad guy uses

it to sort of conquer the world there is

a policy failure where it's not

regulated and we end up doing something

that most of the world doesn't want most

of what doesn't get input and so when we

say safe age

we really just mean beneficial AGI where

we sort of maximize human preference and

happiness we are out of time but thank

you thank you very much my pleasure

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