2019 Keynote Discussion Sam Altman and Vinod Khosla
Summary
TLDR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
🌟 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。
🚀 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。
🧠 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。
🪐 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。
🔍 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。
Mindmap
Keywords
💡AGI
💡ディープラーニング
💡コンピューターパワー
💡ビジネスモデル
💡テクノロジー革命
💡労働市場の変化
💡安全性
💡進化シミュレーション
💡カスタマイズ音楽
💡進化的知能
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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