‘Everything is Going to Be Robotic’ Nvidia Promises, as AI Gets More Real
Summary
TLDRNvidiaのCEOは、AIを活用し産業を革命化するロボットの未来を示唆。AIは物理法則を理解し、工場内を動くロボットをコントロールし、製品を組み立てる。AIは自己改善も行い、デザインやソフトウェア開発を支援。また、マルチモーダルLLMはロボットが世界を理解し、行動計画を立てることを可能にする。AIは言語モデルを通じて会話生成やビデオゲームキャラクターとの対話を実現。さらに、ハイパーローカルな天気予報、ロボットが働くカフェ、音響ジェネレーターなど、AIの多様な応用が示されている。一方で、AIによる職業の未来について懸念も示され、AIは特定のタスクにおいては人間に代わって高生産性をもたらす一方で、賃金不平等や利益増加につながるとの見方も示されている。
Takeaways
- 🌟 NvidiaのCEOは、企業を最終的に巨大なAIに発展させたいと語り、AIの可能性を展示しています。
- 🤖 AIは産業を革命化するロボットの次の波をもたらすとNvidiaは予測しており、物理的なAIを駆使したロボットが産業を変えるでしょう。
- 🔧 NvidiaはAIを通じてチップ設計やソフトウェア開発、バグの特定と修正を自動化し、組織全体をAI化したいとしています。
- 📈 AIの能力は人間のデモンストレーションから学ぶことだけでなく、ロボットの物理的制御を向上させる多様なモデルを活用しています。
- 🎮 デジタルヒューマンの基礎となるAIモデルは、多言語の音声認識と合成、会話の理解と生成を組み合わせたもので、ゲームキャラクターとのリアルタイムインタラクションが可能になるでしょう。
- 🎨 AIは現在、リアルタイムのリップシンクを可能にし、デジタルキャラクターの皮膚の透過感を模倣する高度な技術を備えています。
- ☕️ AIはコーヒーショップのように、少数の人間が監督するロボットが多数働くビジネスを可能にしています。
- 🌡️ AIは超地域的予測を実現し、都市インフラの影響を考慮した天気シミュレーションを通じて局地的な気象現象を予測するでしょう。
- 🎵 11 Labsなどの技術は、任意の音を生成することができると示しており、AIは効果音生成にも応用されています。
- 💼 AIは既にグラフィックデザインなど特定の分野で職業を置き換え始めており、雇用への影響は懸念されるべきです。
- 📊 AIの影響は職業の消滅ではなく、生産性向上や賃金格差の拡大、そして所有者の利益向上につながるとの見解もあがっています。
- 🛑 AIの悪い用途に関する報道では、モデルの効果が低く評価されることがある反面、ベンチマークの重要性が強調されています。
- 🔮 AIの未来は予測不能であり、学術的分野における急速な発展と実際の社会での影響は異なる可能性があります。
Q & A
NvidiaのCEOはどのような未来を想定していますか?
-NvidiaのCEOは、自社の企業を最終的には巨大なAIに発展させたいと述べています。また、最近ではAIが実現する可能性のある一連の能力を展示しています。
AIが産業界にどのような影響を与えるとNvidiaは予想していますか?
-Nvidiaは、物理AIによってロボットが産業界を革命化すると予想しています。工場がロボットをオーケストレーションし、ロボット同士が製品を組み立てることになるという斬新な予測をしています。
NvidiaはAIをどのようにして企業全体に展開させたいと考えていますか?
-NvidiaのCEOは、AIを積極的に使用し、企業全体を一つの巨大なAIに変えていくことを望んでおり、AIを通じてチップの設計やソフトウェア開発、バグの特定と修正を効率化するなど、多岐にわたる業務にAIを適用する予定です。
AIが人間のデモンストレーションから学ぶ方法についてどのように説明されていますか?
-AIは人間のデモンストレーションから学び、それに基づいてグロスおよびファインモータースキルを使用して世界と相互作用するスキルを習得できますが、実際はAIはさらに高度なタスクを実行するための低レベルの物理制御をプログラムする能力も持っています。
デジタルヒューマンの基礎となるAIモデルにはどのような要素が含まれていますか?
-デジタルヒューマンの基礎となるAIモデルには、多言語の音声認識と合成、会話を理解し生成するLLMが含まれています。これにより、リアルタイムでのリップシンクが可能になります。
AIが持つ最も重要な能力とは何ですか?
-AIが持つ最も重要な能力は、シミュレーションを通じて何千ものイテレーションを並列で行い、満足のいくプログラムを作り出すことができることです。
AIが現実世界においてどのような影響を与えると予想されていますか?
-AIは現実世界において、例えば超局所的な天気予報、デジタルツインを使用した気象予測、コーヒーショップでのロボットによるサービスなど、様々な分野で影響を与えると予想されています。
AIが職業市場にどのような影響を与えると予想されていますか?
-AIは職業市場において、コピーライティング、税務処理、カスタマーサービスなどの業務が大幅に自動化されると予想されていますが、実際の影響は予測が難しいとされています。
AIが悪用された場合、その影響はどの程度ですか?
-AIが悪用された場合、例えばデジ털詐欺や不正な宣伝活動などを行う場合でも、その影響は限定的であり、実際にはあまり効果がなかったと報告されています。
AIの能力を測定するためのベンチマークとは何ですか?
-AIの能力を測定するためのベンチマークは、モデルをゲーム不能にしたり、汚染したり、バイアスをもたさずに測定するものであり、実際の使用ケースに基づいてベンチマークを評価することが重要です。
AIが持つ可能性と現実のギャップについてどのように考えていますか?
-AIが持つ可能性は膨大ですが、それが現実社会においてどのように実現されるかはまだ不明であり、今後の展開は予測が難しいとされています。
Outlines
🤖 AIとロボット工学的進化
NvidiaのCEOは、AIを通じて企業を巨大なAIに発展させたいと語り、最近のデモンストレーションではAIが実現する可能性のある機能を多数提示しました。AIの将来についての3つの大きな約束と、現在のAI技術が実現しているデモを見せています。AI企業の幹部は、3~5年で雇用の形が大きく変わると予測していますが、これは若干過大評価されていると指摘。また、AIの限界も示すデモンストレーションとして、スパムキャンペーンの失敗も紹介されています。Nvidiaはロボット技術によって産業を革命化すると予想しており、物理的なAIを通じてロボティクスが次のAIの波を担うと述べています。しかし、具体的なモデルについてはまだ曖昧で、AIが物理法則を理解し、人間と協調して働くことができるという点に焦点が当てられています。また、Nvidiaは自社をAI1つに統合し、AIを通じてチップ設計やソフトウェア開発、バグの特定と修正を行っていると発表しました。AIの能力についての30秒のクリップでは、多機能型言語モデル(mlms)がロボットに学び、周囲の世界を認識し、行動計画を立てることができると紹介されていますが、これはAIの能力を低く評価していると指摘。実際、AIはロボット技術を大幅に向上させると、特にロボットドッグのバランス維持の例を挙げています。
🎮 デジタルヒューマンとリアルタイムの相互作用
ビデオゲームのキャラクターとリアルタイムで相互作用するという長年の約束に加えて、デジタルヒューマンの基礎となるAIモデルは、多言語の音声認識と合成、対話生成のためのllmsを活用しています。口の同期の正確性とデジタルヒューマンのリアリティが向上し、リアルタイムで追跡される皮膚のサブスーフース散乱効果が光を模擬するなど、技術の進歩が示されています。しかし、デジタルヒューマンがリアルタイムでリアルな外観で話すという技術は、まだ数十年後の出来事のように感じるかもしれませんが、私の人生中に実現するかもしれないと述べています。さらに、AIのデモンストレーションとして、超地域的な天気予報、Nvidia Earth 2のようなデジタルツイン、数十人のロボットが働くコーヒーショップ、そして11 Labsによる効果音ジェネレーターの例が紹介されています。これらの技術は未来的な印象を受けるが、実際に起こっていることもあります。AIは人間の訓練データが必要ですが、継続するためや進行するためにはそれ以上必要なく、グラフィックデザイナーがAIによって職を失った例も紹介されています。これはAIが進化し続ける上での重要なポイントです。
👥 AIによる雇用形態の変化と社会への影響
AIが職業に与える影響について、アンソロピックのCEOの秘書が3年以内に雇用形態が大きく変わると予測し、経済的、政治的な比較において、AIが最も優れているかではなく、そのタスクをこなす予定の人間よりも優れているかが重要だと指摘しています。コピーライティング、税務処理、カスタマーサービスなどが大幅に自動化されると予想されていますが、AIが職業に与える影響が過大評価されることがあることも指摘。例えば、オープンAIの報告書では、悪意のある利用者がGPTモデルを使ってディスインフォメーションキャンペーンを行っていたが、その影響はほとんどなかったと報告されています。これは、AIがネガティブな用途であるとされている場合、モデルがあまり役に立たないとされていることに皮肉な面があると感じます。一方で、スケールAIが公正で操作不能なベンチマークとリーダーボードを提供するイニシアチブが評価されており、これはモデルを独自のユースケースでベンチマークするべきだと述べています。AIが学術分野で急速に増加しているものの、それが社会や職業、具現化された物理AIでどのように機能するかはまだ不明です。
🌟 AIの未来についての見解
AIの未来に関しては、誰もがそれには予測不可能であると同意しています。学術論文では、ほぼすべての分野で指数関数的に増加していることがわかりますが、それが現実社会でどのように機能するかは不明です。AIが職業に与える影響もまた、現在わかっていません。しかし、AIの発展を見守るために、常に最新の情報を集めていきましょう。
Mindmap
Keywords
💡AI
💡Nvidia
💡ロボット工学
💡デジタルヒューマン
💡言語モデル
💡マルチモーダルLLM
💡シミュレーション
💡ハイパーローカル予報
💡デジタルツイン
💡AIによる失業
Highlights
Nvidia CEO aims to transform the company into a giant AI entity.
AI is currently capable of a range of capabilities showcased in recent demos.
Prediction of the end of employment as we know it within 3 to 5 years, which is considered overstated.
AI failures highlighted, such as a failed spam campaign.
Nvidia anticipates a robot revolution in industry through physical AI.
Factories will become robotic, with robots building other robots.
AI is improving itself and aiding in the design and software development processes.
Nvidia's use of AI for bug detection and resolution within code.
AI's ability to learn from human demonstrations and execute complex physical tasks.
LLMs (Large Language Models) are advancing robotics capabilities.
AI models are being developed for digital humans with multilingual speech recognition and synthesis.
Advancements in lip-syncing technology using AI, creating highly realistic digital humans.
Nvidia Earth 2, a digital twin that combines AI, physics simulations, and observed data.
Hyperlocal weather forecasting taking into account city infrastructure.
Robot-staffed coffee shops with minimal human oversight as a current reality.
AI's impact on jobs with a graphic designer losing their job to AI automation.
AI's need for human-generated training data to start but not necessarily to continue.
Predictions of job automation in areas like copywriting, tax preparation, and customer service.
OpenAI's report on the ineffectiveness of AI-generated disinformation campaigns.
The need for better benchmarks and unbiased leaderboards in AI performance measurement.
The unpredictability of AI's impact on society, jobs, and physical AI.
Transcripts
the CEO of Nvidia revealed that he wants
his company to become ultimately one
giant AI even if that feels a little
ways away he did Showcase in the last
couple of days a string of capabilities
that are possible now with AI yes we're
going to hear three big promises about
the future of AI but we're going to see
a host of demos of things are possible
right now I'll bring in clips from some
recent interviews I've conducted and
we'll hear from the chief of sta half of
one prominent AI company predicting the
end of employment as we know it in 3 to
5 years which I think is a tad
overstated speaking of which you'll also
see some AI fails as a Spam campaign
flops hard so what about those three
promises I mentioned from the CEO of
Nvidia which looks set to become the
largest company in the world if current
trends hold well first we heard and saw
that Nvidia anticipates robot
revolutionizing
industry the next wave of AI is here
robotics powered by physical AI will
revolutionize
Industries that's still pretty General
though right so how about the prediction
that everything is going to be robotic
let me talk about what's
next the next wave of AI is physical ai
ai that understands the laws of physics
AI that can work Among Us of course when
I say robotics there's a humanoid
robotics that's usually the
representation of that everything is
going to be robotic all of the factories
will be robotic the factories will
orchestrate robots and those robots will
be building products that are robotic
robots interacting with robots building
products that are robotic and of course
we don't just have robots building
robots we have artificial intelligence
improving artificial intelligence here
is Jason hang on a separate less
reported occasion promising to turn
Nvidia into one giant AI we can't design
a chip anymore without
AI at night our AIS are exploring design
spaces uh vast and wide that we would
never do ourselves because it cost too
much money to explore we can't write
software without without AI anymore we
have to explore all the you know the the
design space of of of optimizing
compilers is too large uh we use AIS to
uh file bugs so our bug you know our
bugs database uh actually tells you
what's wrong with the code who's likely
involved and activates that person to go
fix it you know so and so I I think uh
we I want everybody every organization
our company to use AI very aggressively
I want I want to turn into a one giant
AI but it's well past time that I become
a bit more concrete about what models
can do right now today here is a
30-second clip from Nvidia that actually
undersold what AI is capable
of multimodal llms are breakthroughs
that enable robots to learn perceive and
understand the world around them and
plan how they'll act and from Human
demonstrations robots can now learn the
skills required to interact with the
world using gross and fine motor skills
but how was that under selling the
capabilities of AI it looked pretty
impressive right well they focused on AI
learning from Human demonstrations but
if you've watched my Dr Eureka video
recently you'll know that it's not just
about llms coming up with high level
plans and then relying on human
demonstrations to exercise fine grained
robotic control in this case of a robot
dog llms are actually really good at
programming the robo dog to in this case
stay balanced on a moving rolling yoga
ball and I spoke with Jason Mah the lead
author of The Dr Eureka paper which was
made in collaboration with Nvidia about
how that will only accelerate robot
capabilities will be bootstrapped by
large language models and I think that's
the most interesting thing of using all
for robotics honestly like there's a lot
of work in using large language models
for robotics in the high level planning
category I could plan the sequence of
tasks the robot needs to do but I think
fundamentally the bottleneck for robot
it's still like lowlevel physical
control right the AL can tell the robot
to cook some food but if the robot can't
even pick up a knife properly it's not
going to work but I think a lot of eure
line work where my work is focused on
how to we use this highly capable
reasoning coding text models multimodal
models to supervise the lowle learning
so the robots can do the very complex
tasks in the first place and I think
that will only accelerate the key Edge
that AI has is that it can iterate
thousands and thousands of times in
parallel in simulation until it's got a
program it's happy with and dipping back
into the virtual world for a moment how
about the long awaited promise of being
able to interact live with video game
characters the foundation of digital
humans are AI models built on
multilingual speech recognition and
synthesis and llms that understand and
generate
[Music]
conversation
[Music]
for and speaking of realism before I get
to the latest clips from Nvidia here's
me speaking 6 weeks ago about how good
lip syncing was getting using just a
single photo of you we can now get you
to say anything have you ever had maybe
you're in that place right now where you
want to turn your life around and you
know somewhere deep in your soul there
could be some decision that you have to
make I have to remind myself that these
aren't projections this is what is
currently possible imagine that accuracy
of lip syncing on a digital human of
this level of realism lifelike
appearances enabling realtime path
traced subsurface scattering to simulate
the way light penetrates the skin
scatters and exits at various points
giving skin its soft and translucent
appearance I do wonder sometimes how
many decades away we are from a time
where you could be speaking to someone
and not be entirely certain in the real
world whether or not they are embodied
AI I might previously have said that's
100 years away but now I think it might
be in my lifetime but I'm off track cuz
I promised more demos of things that are
possible with AI today so how about a
weather report that's localized to your
building your pavement but we are not
stopping there the next Frontier is
hyperlocal forecasting down to tens of
meters where the effects of City
infrastructure are taken into account
when combined with weather simulation
windfields it can model the air flow
around buildings we expect to predict
phenomena such as down watch where
strong winds funnel down to street level
causing damage and affecting
pedestrians Nvidia Earth 2 an excellent
example of a digital twin that fuses AI
physics simulations and observe data can
help countries and companies see the
future and respond to the impact of
extreme weather or what about a coffee
shop which is staffed by dozens of
robots with just one or two humans to
oversee things wait that's happening
right now all of these things feel
futuristic and far away until they
actually happen and how about a sound
effect generator that can generate any
sound well that is possible today with
11 Labs actually I'm going to test it
with something like a robot being
crushed let's see if it comes up with
something interesting or not so far
about five six 7 Seconds not too bad and
how is
it
whoa not perfect obviously but if you
feel that all of this is in the future
let me bring you a video from a a
graphic designer who lost his job
recently to AI they just lost my job um
and I lost it to AI which is very
unfortunate I think many people joke
about the you know the fact that oh AI
is going to take all our jobs and we're
all going to get replaced and especially
within my industry which is graphic
design and it turns out basically all of
the material that I've provided over the
past 6 years is now being fed to Ai and
templated
um so a design that would take me 30
minutes now takes AI 30 seconds uh as
it's been trained on all my templates
essentially I think it just literally
reuses my templates and then they can
input the hex codes they want the email
or the website designed to be drag and
drop in the client's logo upload the
client's font and boom it will generate
uh my template but using their brand
assets it's a reminder that even though
almost all AI need needs human generated
training data to get started they don't
necessarily need more of it to keep
going or to put it another way this is
the worst the AI embodied or not will
ever be which is probably why some
people including the chief of staff to
the CEO of anthropic makers of the claw
chatbots think that this will massively
impact the short-term outlook on
employment this article by that Chief of
Staff Avatar balwit came out just two
weeks ago while I think the Outlook
isn't quite this Stark here's what she
had to say she predicted these next 3
years might be the last few years that I
work I stand at the edge of a
technological development that seems
likely should it arrive to end
employment as I know it and she makes
the point that would have been relevant
to that graphic designer we just heard
from the economically and politically
relevant comparison on most tasks is not
whether the language model or I would
say the embodied AI is better than the
best human it's whether they are better
than the human who would otherwise do
that task doesn't have to be perfect in
other words just has to be a bit cheaper
she makes the somewhat common prediction
by now that things like copywriting tax
preparation and customer service will be
heavily automated but let me give you
two examples how the future is a bit
more unpredictable than it can sometimes
seem first I remember the frenzied
reporting on this report from the think
tank the IP here in Britain according
ording to the headlines at least they
were warning of an AI jobs apocalypse
but the very next day I contacted the
lead author caraston young and we had a
detailed discussion for AI insiders
first he said head on that he was
disappointed by the media's coverage no
I'm I'm not fully happy with how this is
being covered both our report but in
general because it can sound very scary
and I think just scaring people doesn't
necessarily lead to incremental
thoughtful policy progress when people
talk about jobs apocalypse I think some
people might just switch off and throw
up their hands and say oh God we're all
doomed whereas what we try to do in the
report is actually to say there's a
range of scenarios and it's not some
kind of external event like a pandemic
that's like happening to us and it's all
doom and gloom but it's actually a thing
that totally depends on Decisions by
policy makers but also by organizations
that Implement AI then we discussed how
a more likely medium-term outcome is
wage inequality in short low wages for
many but not for those who utilize AI to
boost their productivity so those that
remain in work their productivity will
be hugely aided by AI so you have this
wage inequality aspect but then of
course and I think this is also Sam
alman's point is that profits are likely
going to go up so we have lower labor
costs AI likely is able to do things
more cheaply so profits will go up so
those that own companies will have
higher returns and so wealth inequality
will likely go up and the second caution
retail about how ai's impact say on jobs
can sometimes be overhyped actually
comes from open AI itself albeit
unintentionally when we're talking about
good things we talk about customer
service being revolutionized and
productivity accelerating but when the
focus is on people using AI for
nefarious purposes suddenly the AI is
kind of useless this was a report
released by openai a few days ago about
how some Bad actors were trying to
generate disinformation campaigns on
mass openai terminated those accounts
but gave a summary of the impact of
these campaigns using the GPT models
there was no significant audience
increase due to our services hm later on
in the report they say this so far these
operations from places like Russia
Israel and China do not appear to have
benefited from meaningfully increased
audience engagement or reach as a result
of our services they basically describe
how these guys came up with a load of
spam but people weren't buying it for
the most part it was because the spam
just wasn't very good I don't know it
might be me but I just find it a little
bit ironic that when we're talking about
a negative use of the technology the
party line is that the models are kind
of useless of course what we really need
are better benchmarks and so I was
pleased to see this initiative from
scale AI they describe these benchmarks
and leaderboards that can't be gamed are
uncontaminated and unbiased according to
these benchmarks at least Gypsy 40 is
not a million miles ahead of other
models this initiative reminds me at
least how we should always Benchmark
models on our own use cases because
leaderboards chop and change quite a lot
notice how the table on the left is
quite different to the one that open AI
put out on release that initiative by
the way isn't the only reason to be
optimistic about benchmarks which I
covered in this video on patreon in
short though I think just about the only
thing we can all agree on is that the
future is about as unpredictable as it
has ever been in terms of at least
referring to AI in academic papers you
can see the recent exponential increase
across virtually every field how this
all actually plays out though in the
real world in society with jobs with
embodied physical AI we simply don't
know thank you though for being here
with me as we watch it all unfold have a
wonderful day
浏览更多相关视频
Microsoft's new "Embodied AI" SHOCKS the Entire Industry! | Microsoft's Robots, Gaussian Splat & EMO
Introducing Generative Physical AI
急速に進化する人型ロボット〜フィギュアAIとUnitree H1
【就活】仕事の将来性を語る:AIエンジニアやデータサイエンティスト【転職】
ソフトバンクグループ・孫正義氏「去年、父をがんで亡くし悔しい」「悲しい出来事を無くす技術・道具がついに生まれた」進化するAIが変える医療への思い【サンデーモーニング】
【セレブリックス】営業×生成AI/営業は商談以外の時間が多すぎる/正しいセールスプロセスを設計/最短5分で商談準備/生成AIと対話しながら模擬商談/AIを優秀な営業パーソンに
5.0 / 5 (0 votes)