A Conversation with the Jensen Huang of Nvidia: Who Will Shape the Future of AI? (Full Interview)

Summary

Jensen Huang, CEO of Nvidia, discusses how we are entering a new era of accelerated computing and AI. He explains how Nvidia GPUs have democratized high performance computing, enabling AI innovation. Huang advises governments to build AI infrastructure to activate researchers and companies to take ownership of developing national intelligence. He recommends focusing on digital biology and life sciences, stating we can now engineer solutions to previously unsolvable biological problems. Huang expresses optimism that AI will proliferate solutions for disease, resource limitations, and other global challenges.

Takeaways

• 💻 The transition from general-purpose computing to specialized, accelerated computing is essential for sustainable, energy-efficient, and high-performance computing, marking a new era in technology.
• 💡 AI's advancement is democratizing technology, making high-performance computing accessible to researchers worldwide, thus fostering innovation across various fields.
• 🚀 The importance of sovereign AI, where countries own their data and intelligence, is highlighted as essential for maintaining cultural, societal, and security integrity.
• 📚 The role of GPUs (Graphics Processing Units) in democratizing AI and high-performance computing is underscored, with NVIDIA's contributions being particularly emphasized for making advanced computing accessible to a broad audience.
• 📌 The concept of accelerated computing is not just about buying more computers but also improving their efficiency and performance over time, reducing the overall need for excessive hardware.
• 🔨 The imminent shift to AI requires infrastructure development akin to building farms for food production or generators for energy, emphasizing the foundational necessity of computing infrastructure for AI progress.
• 👨‍💻 Education in the AI era should focus less on programming skills and more on domain expertise, leveraging AI tools to amplify productivity and solve domain-specific problems.
• 📖 The potential for AI to democratize education and empower individuals with diverse skills to contribute to technology and innovation without traditional programming knowledge.
• 🛠 The discussion about regulating AI focuses on the use cases rather than the technology itself, advocating for safe development, application, and usage of AI in various industries.
• 🌱 The conversation about the future of AI and computing emphasizes the need for continued innovation, open-source development, and the democratization of technology to avoid centralizing power and capabilities.

Q & A

What major transitions is Jensen referring to that are happening simultaneously?

The end of general purpose computing and the beginning of accelerated computing, along with the rise of AI enabled by accelerated computing.

How has Nvidia helped democratize high performance computing over the past decade?

By developing gaming GPUs that could be used affordably by AI researchers worldwide to make breakthroughs in deep learning.

What does Jensen suggest is the first step a developing nation should take to mobilize AI?

Build the infrastructure for accelerated computing to activate researchers and industry to create AI models.

What does Jensen see as the most significant AI development in 2022 that activated regional research?

The release of open source large language models like LLAMa and Falcon which democratized access.

Why does Jensen say Nvidia GPUs are unique despite internal chips from large tech companies?

Because Nvidia GPUs are the only accelerated computing platform available democratically to researchers on any cloud or platform.

Why does Jensen say now anyone can engage with AI unlike any other time?

Because for the first time there is no technology divide - AI systems can understand natural language requests from any user.

What does Jensen see as the hottest area of study for students today?

Digital biology and life sciences, to turn biology into a true engineering discipline improved yearly like computing.

How can developing nations build AI capability despite limited budgets?

Leverage cloud-based accelerated computing which democratizes access to the needed infrastructure.

What is Jensen's vision for how AI will enhance applications across industries?

AI will automate intelligence and be augmented into existing products and services across sectors.

Why does Jensen believe life sciences innovation has lagged compared to computing?

Because innovations in computing are engineered yearly improvements but life sciences discoveries remain sporadic.

Outlines

00:00

🤝 Opening remarks and introducing Jensen Huang

The moderator welcomes Nvidia CEO Jensen Huang to the stage. He notes that Nvidia is at the center of artificial intelligence hype, possibilities and meaning. He asks Jensen to provide some insights, especially given Nvidia's upcoming GTC conference.

05:02

🚀 The AI revolution and infrastructure needed

Jensen explains we are entering a new era driven by specialized computing and AI. Countries realize they cannot rely on others for AI - they need "Sovereign AI" and to own their own data, models and intelligence. To activate AI, countries must build infrastructure to empower researchers.

10:02

📚 Codifying language and knowledge for AI

Jensen advises that countries should start by codifying their language and culture into large language models. But many AI revolutions are happening beyond language - in areas like biology, climate, materials, manufacturing etc. Infrastructure allows activation of researchers across domains.

15:02

⛔️ Avoid AI scaremongering

Jensen notes that scaremongering about AI being dangerous or overly complicated hurts progress. The most important recent event has been the release of open source models that allow more people to innovate. Safety, transparency and other innovations continue to advance.

20:03

🔬 Biology and engineering key future fields

Jensen suggests biology and "life engineering" will be vital fields, as biology is complex and impactful. Digital biology means engineering life systems - more sustinable, efficient etc. This will open new eras of engineering innovation versus sporadic scientific discovery.

Keywords

💡democratize

The term 'democratize' refers to making a technology more accessible and available to everyone. Jensen uses this term several times to state that Nvidia has helped democratize AI and high performance computing by providing powerful but affordable GPUs. This has enabled AI innovation by researchers all over the world. He argues countries should not restrict AI development but rather democratize it.

💡accelerated computing

Jensen introduces the concept of 'accelerated computing' to refer to a transition from general purpose computing using CPUs to specialized computing using GPUs and other accelerators. He states this is necessary for high efficiency, high performance computing needed to power AI. The shift to accelerated computing using GPUs is foundational for AI progress.

💡sovereign AI

Sovereign AI refers to the idea that countries should own, control, and refine their own AI technology, models and data rather than rely on other nations. Jensen argues every country needs to activate researchers and industry to develop sovereign AI ability based on their own language, culture and data.

💡generative AI

Jensen refers to 'generative AI' when discussing the next generation of AI capabilities being powered by accelerated computing in data centers. Though not defined, generative AI refers to AI that can generate content like images, video, text etc in an intelligent, customizable way.

💡industrial revolution

Jensen compares the rise of AI to previous industrial revolutions - the energy revolution with steam power and information revolution with PC/Internet. He states we are now experiencing an AI revolution focused on 'production of intelligence'.

💡digital biology

Jensen predicts that with AI, fields like biology and drug discovery will transition from 'life sciences' to 'life engineering' - where we systematically engineer biological solutions using technology. He refers to this as 'digital biology' - augmenting life sciences with data and AI.

💡language model

Jensen references the development of language models multiple times - which are AI models trained on enormous text data to generate human-like language. He states democratized access to these large, pre-trained models has activated AI innovation across the world.

💡safety alignment

While discussing regulation of AI, Jensen mentions innovations happening around safety alignment of AI systems to ensure they behave safely, avoid harm, and support human values.

💡transparency

To safely guide AI systems, Jensen notes extensive work on AI transparency - understanding and explaining their internal functioning as they interact with the world.

💡reinforcement learning

This refers to a machine learning approach based on an agent interacting with the world and getting feedback on its actions to achieve goals. Jensen lists innovations in reinforcement learning as an area of AI safety research.

Highlights

We are experiencing two simultaneous transitions - the end of general purpose computing and the beginning of accelerated computing

Accelerated computing is the most sustainable and energy efficient way of computing going forward

AI has been democratized and put into the hands of every researcher due to the advancement of accelerated computing

Every country needs to own the production of their own intelligence through data and AI models - this concept is called Sovereign AI

The most important thing that happened in AI last year was the release of open source models like LLAMa-2, Falcon, Mistr which activated AI researchers globally

The first thing to do is build the infrastructure for AI - it is not that costly or difficult and can activate researchers to create models

AI revolutions are happening simultaneously across language, biology, physical sciences, IoT, robotics, manufacturing etc.

Regulations need to be extended and augmented for the safe and ethical application of AI across industries, like with any powerful new technology

The technology divide has been closed - AI makes every person a technologist and resets technology leadership across countries

Our job is to create computing technology such that nobody has to program - AI makes everyone a programmer by closing the gap between humans and machines

One of the most complex and impactful fields enabled by AI is biology and medicine - it will shift from sporadic discovery to systematic engineering

Digital biology will become a field of engineering, not just science - building solutions in a reliable, repeatable way

The technology to turn life sciences into life engineering is now possible with the rise of AI

A whole new generation of people can enjoy working with biology to engineer solutions that are efficient, sustainable and solve problems

We are entering an era of accelerating discovery and invention to overcome limitations and challenges

Transcripts

it's my pleasure and privilege to be

sitting in front of all of you here

today to moderate a Pioneer not just in

the technology space but in the

artificial space as well artificial

intelligence space Jensen who um is

leading probably the company that's at

the center of the eye of the storm when

it comes to artificial intelligence the

hype the possibilities and what this

technology with mean Jensen it's a

pleasure being with you on stage here

thank you it's great to be here when I'm

amazing

conference I um just want to say that we

really appreciate you taking the time

especially since you have GTC in 6 weeks

in six weeks I'm going to tell everybody

about a whole bunch of new things we've

been working on the next generation of

AI every single year they just push the

envelope when it comes to artificial

intelligence and GTC so um we're hoping

to get a few Snippets out of this okay

so I'd like to start with a um question

that was going on in my mind how many

gpus can we buy for 7

trillion well apparently all the

gpus I I I think this is one thing I'm

I'm waiting to ask Sam about because

it's it's a really big number talk about

ambition we have a lot of ambition here

in the UA we don't lack ambition but is

there a view that you can give the

government leaders today with regards to

compute capabilities and artificial

intelligence how can they plan well

where do you think the deployment is

going to make sense and what advice you

have uh well first of all these are

amazing times these are amazing times

because we're at the beginning of a new

Industrial

Revolution production of energy through

Steam production of

electricity it and information

revolution with PC and internet then now

artificial

intelligence uh we are experiencing two

simultaneous uh Transitions and this has

never happened before the first

transition is the end of general purpose

Computing and the beginning of

accelerated Computing it's like

specialized Computing using CPUs for

computation as the foundation of

everything we do is no longer possible

and the reason for that is because it's

been 60 years we invented central

processing units in 1964 the

announcement of the IBM uh system 360

we've been writing that wave for

literally UH 60 years now and this is

now the beginning of accelerated

Computing if you want sustainable

Computing energy efficient Computing

high performance Computing cost effect

cost Effective computing you can no

longer do it with general purpose

Computing you need specialized domain

specific acceleration and that's what

driving at the foundation our growth

accelerated Computing it's the most

sustainable way of doing uh Computing

going forward it's the most energy

efficient um it is so energy efficient

it's so cost effective it's so

performance so performant that it

enabled a new type of application called

AI the question is what's the cart and

and the horse you know first is

accelerated Computing and enabled a new

uh new application there's a whole bunch

of applications that are accelerated

today and so now we're in the beginning

of this new uh New Era uh and what's

going to happen is there's a about a

trillion dollar withth of installed base

of data centers around the world and

over the course of the next four or five

years we'll have $2 trillion worth of

data centers um that will be uh uh

powering software around the world and

all of it is going to be

accelerated and and this architecture

for Accelerated Computing is ideal for

this next generation of software called

generative Ai and so that's really at

the core of what is happening uh while

we're repl placing the install base of

general purpose Computing remember that

the performance of the architecture is

going to be improving at the same time

so you can't assume just that you will

buy more computers you have to also

assume that the computers are going to

become faster and therefore the total

amount that you need is not going to be

as much otherwise the mathematics if you

just assume you know that that computers

never get any faster you might come to

the con conclusion we need 14 different

planets and three different galaxies and

you know four four more Suns and um to

to fuel all this but but obviously uh

computer architecture continues to

advance in the last 10 years one of the

greatest contributions and I really

appreciate you mentioning that um the

rate of innovation one of the greatest

contributions we made was advancing

Computing and advancing AI by 1 million

times in the last 10 years and so

whatever demand that you think is going

to power the the world you have to

consider the fact that it is also going

to do it one million times larger faster

you know more

efficiently don't you think that creates

a risk of having a world of halves and

Have Nots since we need to constantly

invest to ensure that we have The

Cutting Edge and to ensure that we are

able to create the applications that are

going to reshape the world and

governments as we know them do you think

that there's going to be an issue of

countries that can afford uh these gpus

and countries that can't and if not

because you know it' be surprising if

you said the answer is no if not what

are going to be the drivers of equity

excellent question um first of all when

something improves by a million times

and the cost or the space or the energy

that it consumed did not grow up by a

million times in fact you've

democratized the technology um

researchers all over the world would

tell you that Nvidia single-handedly

democratized high performance Computing

we put it in the hands of every

researcher it is the reason why uh AI

researchers uh Jeff Hinton in University

of Toronto Yan Lun I think Yan's going

to be here uh University of uh New York

um Andrew a uh in uh Stanford

simultaneously discovered us they didn't

discover us because of supercomputers

they discovered us because of gaming

gpus that they used for deep learning we

put accelerated Computing or high

performance Computing in the hands of

every single researcher in the world and

so when we accelerate the rate of

innovation we're democratizing the

technology the cost of building

purchasing a supercomputer today is

really negligible and the reason for

that is because we're making it faster

and faster and faster whatever

performance you need costs a lot less

today than he used to it is absolutely

true we have to democratize this

technology and the reason the reason why

is very clear there's an Awakening of

every single country in probably the

last six

months that artificial

intelligence is a technology you can't

be mystified by you cannot be terrified

by it you have to find a way to activate

yourself to take advantage of it and the

reason for that is because this is the

beginning of a new Industrial Revolution

and this Industrial Revolution is about

the production not of energy not of food

but the production of intelligence and

every country needs to own the

production of their own intelligence

which is the reason why there's this

idea called Sovereign AI you own your

own data nobody owns it your country

owns the data your cult it it it

codifies your culture your society's

intelligence your common sense your

history you own your own data you

therefore must take that data refine

that data and own your own National

Intelligence you can't cannot allow that

to be done by other people and that is a

real realization now that we've

democratized the computation of AI the

infrastructure of AI the rest of it is

really up to you to take initiative

activate your uh your uh industry uh

build the infrastructure as fast as you

can so that the researchers the

companies your governments can take

advantage of this infrastructure to go

and create your own

AI I I think we completely subscribe to

that Vision um that's why the UAE is

moving aggressively on creating large

language models IM mobilizing compute

and maybe work with other partners of

this let's try to flip the Paradigm a

little bit let's today assume that

Jensen hang is the president of of a

developing nation that has a relatively

small GDP and you can focus on one AI

application what would it be let's call

it a hypothetical nation and say that

you know you have so many problems that

you need to deal with what is the first

thing that you're going to approach if

you're going to mobilize artificial

intelligence in that scenario the first

thing you have to do is you have to

build infrastructure if you want to if

you want to mobilize the production of

food you have to build farms if you want

to mobilize the production of energy you

have to build

AC generators if you want to if you want

to operationalize information digital if

you want to digitalize your economy you

have to build the internet um if you

want to automate the creation of

artificial intelligence you have to

build the infrastructure it is not that

cost it's not that it's not that costly

it is also not that hard um companies

all around the world of course wants to

mystify terrify glorify you know all of

those uh those those ideas but the fact

of the matter is they're computers you

can buy them off the shelf uh you can

install it uh every country needs

already has the expertise to do this uh

and you you have to you surely need to

have the imperative To Go activate that

um the first thing that I would do of

course is I would codify the uh language

the the data of your culture into your

own large language model and you're

doing that here uh core 42 um Saudi

ramco

uh uh uh uh

uh sad sad um really doing uh important

work to uh codify the Arabic language

and creating your own large language

model um but simultaneously remember

that AI is not just about language AI

we're seeing several AI revolutions

happening at the same time AI for

language AI for biology learning the

language of protein prot and and

chemicals uh AI for physical sciences

learning the AI of climate materials

energy Discovery AI of iot the language

of keeping places safe computer vision

and such um AI for iot AI for Robotics

and autonomous systems manufacturing and

such there's AI revolutions happening AI

great breakthroughs happening in all of

these different domains and if you build

the infrastructure you activate the

researchers in every one of these

domains without the internet how can you

be

digital without Farms how can you

produce food without an AI

infrastructure how can you activate all

of the researchers that are in your

region to go and create the AI

models you touched upon um the

issue of I would say authentic ignorance

the fear mongering a I taking over the

world and um I I think there's a

requirement for us to clarify where the

hype is real and where artificial

intelligence really has the power to

create a lot of disruption and to harm

us and where AI is going to be good what

do you think is the biggest issue when

it comes to artificial intelligence

right now because I think the the the

problem of regulating AI is like trying

to say we want to regulate a field of

computer science or regulate electricity

you don't regulate electricity as a

invention or as a discovery you regulate

a specific use case what is one use case

that you think we need to regulate

against and that government should

mobilize towards e excellent question um

first of all whatever new incredible

technology is being created uh you go

back to the earliest of times uh it is

absolutely true we have to develop the

technology safely we have to apply the

technology safely and we have to help

people use the technology safely and so

uh whether it's um uh the plane that I

came in uh cars uh Manufacturing Systems

medicine all of these different

Industries are heavily regulated today

those regulations have to be extended

augmented to consider artificial

intelligence artificial intelligence

will come to us through products and

services it is the automation of

intelligence and it will be augmented on

top of all of these various Industries

now it the case that that there are some

interests

to scare people about this uh new

technology to mystify this technology to

encourage other people to not do

anything about that technology and rely

on them to do it and I think that that's

a mistake we want to democratize this

technology let's face it the single most

important thing that has happened last

year if you were to ask me the one

single most important event last year

and how it has

activated AI researchers here in this

region it's actually llama 2 it's an

open source model or falcon or Falcon

another excellent model very true uh

mistr excellent model uh a I just I just

saw another one uh a smog um there's so

many open source models Innovations on

safety

alignment um uh uh

Guard railing reinforcement learning so

many different reasoning so many

different innovations that are happening

on top of transparencies explainability

all of this technology that has to be

built all were possible because of some

of these open source languages and so I

think that

democratizing activating every region

activating every country to join the AI

Advance is probably one of the most

important important thing rather than ex

convincing everybody it's too

complicated it's too dangerous it's too

my mystical and only two or three people

in the world should be able to do that

that I think is a huge

mistake uh the the uh Focus I think that

we have done in the UAE is to focus on

open source systems because we do

believe that anything that we develop

here should be given as um a opportunity

for others that can't develop

it most of this is developed using gpus

so graphic processing units that you

guys um are are supplying the world what

do you think the next era is going to

depend on is it going to continuously be

built on gpus is there something else as

a breakthrough that we're going to see

in the future you think actually uh you

know that that in just about all of the

large companies in the world uh there

are internal developments uh at Google

there's tpus at um AWS there's tranium

at Microsoft there's Maya uh uh meta has

um uh chips that they're building uh in

China just about every single CSP has

chips that they're building the reason

why you mention Invidia gpus is NVIDIA

GPU is the only platform that's

available to everybody on any platform

that's actually the observation it's not

that we're the only platform that's

being used we're simply the only

platform that's used that democratizes

AI for everybody's platform we're in

every single Cloud we're in every single

data center we're available in the cloud

uh in your private data centers all the

way out to the edge all the way out to

autonomous systems Robotics and

self-driving Cars one single

architecture spans all of that that's

what makes Nvidia unique that we can uh

in the beginning when cnns were popular

we were the right architecture because

we were programmable Aruda architecture

has the ability to adapt to any

architecture that comes along so when

CNN came along RNN came along Along

lstms came along and then eventually

Transformers came along and now Vision

Transformers bir eye view Transformers

um all kinds of different Transformers

are being uh created a Next Generation

State space uh models uh uh which is a

uh probably in the next generation of

Transformers all of these different

architectures can live and breathe and

be created on invidious flexible

architecture and because it's available

literally everywhere any researcher can

get access to Nvidia gpus and invent the

Next Generation so so for those of you

who are non-technical and heard you know

a foreign language there with CNN and

and some of the other uh acronyms that

are being used the the thing about

artificial intelligence is it's going

through a lot of Evolutions over a very

short period of time so whatever the

infrastructure that was used probably 5

years ago is very different to the

infrastructure that's being used today

but what Jensen's point was I think it's

a very important point is NVIDIA has

always been relevant historically we see

companies that are relevant at one phase

of development and then as the

infrastructure changes they become

irrelevant but you guys were able to

innovate and and push through let's move

to a non- air related topic for a second

I want to talk about education so today

knowing what you know seeing what you

see and being at The Cutting Edge of the

technology what should people focus on

when it comes to education what should

they learn how should they educate their

kids and their societies wow excellent

question I'm going to say something and

it it's it's going to sound completely

opposite um of what people feel uh you

you you probably recall uh over the

course of the last 10 years 15 years um

almost everybody who sits on a stage

like this would tell you it is vital

that your children learn computer

science um everybody should learn how to

program and in fact it's it's almost

exactly the opposite it is our job to

create Computing technology such that

nobody has to

program and that the programming

language is

human everybody in the world is now a

programmer this is the miracle this is

the miracle of artificial intelligence

for the very first time we have closed

the Gap the technology divide has been

completely closed and this the reason

why so many people can engage artificial

intelligence it is the reason why every

single government every single

industrial conference every single

company is talking about artificial

intelligence today because for the very

first time you can imagine everybody in

your company being a

technologist and so this is a tremendous

time for uh all of you to realize that

the technology divide has been closed or

another way to say

it the te technology leadership of other

country has now been

reset the countries the people that

understand how to solve a domain problem

in digital biology or in education of

young people or in manufacturing or in

farming those people who understand

domain

expertise now can utilize technology

that is readily available to you you now

have a computer that will do what you

tell it to do to help automate your work

to amplify your productivity to make you

more efficient and so I think that this

is just a tremendous time um the impact

of course uh is is great and your

imperative to activate and take

advantage of the technology is

absolutely immediate um and also to

realize

that to engage AI is a lot easier now

than at any time in the history of

computing it is vital that we we upskill

everyone and the upskilling process I I

believe will be delightful surprising um

to realize that this computer can

perform all these things that you're

instructing it to do and doing it so

easily so if I was going to choose a uh

major and University as a degree that

I'm going to pursue what would you give

me as an advice for something to

pursue if I were starting all over again

um I would realize uh one thing that one

of the most

complex fields of science is the

understanding of biology human biology

not only is it complicated because it's

so diverse so complicated so hard to

understand living and breathing it is

also incredibly impactful complicated

technology complicated science

incredibly impactful for the very first

time and and remember we call this field

life

sciences and we call drug Discovery

Discovery as if you wander around the

univers ierse and all of a sudden hey

look what I discovered nobody in

computer science nobody in computers and

nobody in the traditional industries

that are very large today nobody says

car Discovery we don't say computer

Discovery we don't say software

Discovery we don't go home and say hey

honey look what I found

today this piece of software we call it

engineering and every single year our

science our computer science our

software becomes better and better than

the than the year before every single

year our chips get better every single

year our infrastructure gets

better however Life Sciences is

sporadic if I were to do it over again

right now I would realize that the

technology to turn life engineering life

science to life engineering is upon us

and that digital biology will be a field

of

engineering not a field of science it

will continue to have science of course

but not a field just of Science in the

future and so I I hope that that this is

going to start a whole generation of

people who enjoy working with proteins

and chemicals and and enzymes and um

materials and and they're engineering

these amazing things that are more

energy efficient that are lighter weight

that are stronger that are more

sustainable all of these inventions in

the future are going to be part of

engineering not scientific discovery so

I think we can end with a very positive

note hopefully we're going to enter an

era of Discovery an era of proliferating

a lot of the things that unfortunately

to they are challenges to us whether

it's disease whether it's limitations

and resources thank you so much Jess for

taking the time and being with us and I

know that we could have continued for

another hour but um thank you for taking

the stage and thank you for your Insight

thank you thank you

[Music]

everyone