About 50% Of Jobs Will Be Displaced By AI Within 3 Years

Summary

In a thought-provoking conversation, Kai-Fu Lee discusses the future of AI and its impact on humanity. He shares his insights on the potential of AI to surpass human intelligence and the implications for understanding our own cognitive processes. Lee also delves into the current state of AI, touching on the differences between the US and China in innovation and execution. He highlights his startup's mission to democratize AI and the importance of infrastructure in making AI accessible and profitable. Furthermore, Lee addresses the challenges and opportunities AI presents, including job displacement and the need to foster human qualities like empathy and trust in a world increasingly influenced by machines.

Takeaways

• 🧠 The speaker believes AI is a significant breakthrough for humanity and could lead to building something more powerful than the human brain, although it might not provide as much insight into how the brain works.
• 🚀 The concept of AGI (Artificial General Intelligence) is seen as a narrow-minded view since AI can surpass human intelligence without mimicking human brain functions.
• 🌐 There's a distinction between the capabilities of AI and humans; while AI can perform many tasks better than humans, it may lack certain human qualities like empathy and compassion.
• 💡 The speaker's startup aims to make AI accessible and open, in contrast to some major players in the field who are becoming more closed, and to prove China's prowess in execution.
• 💼 The company's strategy involves a small AI modeling team and a large infrastructure team to save on costs and make informed decisions before investing heavily in GPU resources.
• 📈 The speaker predicts that generative AI will be a game-changer, similar to the impact of electricity, the internet, and mobile technology, and that it could lead to significant wealth creation.
• 🏁 The speaker warns of the potential for job displacement due to AI advancements and emphasizes the need for society to prepare for these changes.
• 🌟 Open AI is praised for its execution and is predicted to become a trillion-dollar company in the near future, despite concerns about its closed nature.
• 🛣️ The speaker discusses the divergence between US and Chinese AI development, suggesting that they are in 'parallel universes' with separate innovations and challenges.
• 👨‍👧‍👦 For future generations, the speaker advises embracing AI as a tool and focusing on uniquely human qualities such as empathy, compassion, and the ability to form trust-based relationships.

Q & A

What was the main topic of discussion between Kai-Fu Lee and Alison during the conversation?

The main topic of discussion was the future of AI and its impact on humanity, including the potential of AI to surpass human intelligence and the implications of such advancements.

What did Kai-Fu Lee believe in 1983 regarding AI and understanding ourselves?

In 1983, Kai-Fu Lee believed that once we build an AI, we would understand how we think, which was his motivation to pursue the field of AI at that time.

What does Kai-Fu Lee think about the concept of AGI (Artificial General Intelligence)?

Kai-Fu Lee believes that AGI, defined as a superset of human intelligence, is a narrow-minded and narcissistic view because it assumes AI must operate exactly like the human brain to be superior.

What is Kai-Fu Lee's perspective on the future capabilities of AI compared to humans?

Kai-Fu Lee predicts that within the next two to three years, AI will be capable of more tasks than humans, but it may still lack certain human qualities such as awareness, love, empathy, and compassion.

What is the name of Kai-Fu Lee's startup, and what is its mission in the AI world?

The startup is called '01'. Its mission is to ensure that China is not left out of the AI revolution, promote an open approach to AI, and make AI accessible to everyone.

Why did Kai-Fu Lee decide to found '01' instead of investing in another company?

Kai-Fu Lee decided to found '01' because he felt that China should not be left out of the AI revolution and that it was time for China to prove its prowess in execution. He also wanted to counteract the trend towards closed AI development.

What is Kai-Fu Lee's view on the current state of openness in the AI industry?

Kai-Fu Lee believes that despite the namesake 'open AI', the industry is moving towards more closed practices. He criticizes companies like Google, Meta, and OpenAI for not being open enough and advocates for an open approach to AI development.

What is Kai-Fu Lee's strategy for '01' in terms of team structure and resource management?

Kai-Fu Lee's strategy for '01' includes having a small AI modeling team and a large infrastructure team. He emphasizes being very focused, making key decisions, and being diligent about resource management to save on GPU costs.

How does Kai-Fu Lee see the future of AI and its impact on job displacement and wealth creation?

Kai-Fu Lee is concerned about the accelerated pace of job displacement and the challenges it poses for smaller entrepreneurs and researchers. He believes that AI will create wealth but also warns of the potential for a few big players to dominate the industry.

What advice does Kai-Fu Lee give for preparing children to live alongside AI and machines?

Kai-Fu Lee advises embracing AI and using it as a tool to enhance capabilities. He also emphasizes the importance of human qualities such as trust, authenticity, teamwork, and high EQ, which he believes will remain unique to humans.

Outlines

00:00

🤖 AI's Role in Humanity's Future and Self-Understanding

The speaker, Kai-Fu Lee, discusses the potential of AI to be a significant breakthrough for humanity, comparing it to the final step in understanding ourselves. He reflects on his early belief that creating AI would reveal how human thought processes work, but now acknowledges that AI can be more powerful than humans without mirroring our brain's structure. Lee emphasizes the importance of collaboration between cognitive scientists and AI developers, hinting at the possibility of surpassing human intelligence without fully understanding our own cognitive processes.

05:01

🌟 The Vision and Strategy of 01AI Startup

Kai-Fu Lee, CEO and founder of 01AI, shares his motivation for starting the company, which includes providing China with access to AI technology and proving China's execution capabilities. He criticizes the closed nature of companies like Open AI and advocates for an open approach, making their models available on platforms like Hugging Face. Lee outlines 01AI's unique strategy focusing on infrastructure and applications, aiming for a stack that includes data, models, and infrastructure to drive profitability and sustainability, unlike the research-focused approach of other companies.

10:03

💡 Necessity Breeds Innovation in AI Infrastructure

Lee highlights the importance of infrastructure in AI, explaining the challenges of GPU reliability and the need for efficient utilization of these resources. He contrasts 01AI's approach with that of larger companies like Google, emphasizing the need for a smaller AI modeling team and a larger infrastructure team to manage costs and make informed decisions before investing in expensive GPU resources. He also discusses the importance of model flop utilization (MFU) and how 01AI has achieved a higher MFU than the industry average, showcasing their innovative approach under financial constraints.

15:05

🔮 Predictions on the Future of AI and Tech Giants

Kai-Fu Lee provides his insights into the future of AI, discussing the divergence of American and Chinese AI markets and the challenges of regulation in a parallel universe scenario. He reflects on his previous book 'AI Superpowers' and the accuracy of his predictions regarding data's value and the execution capabilities of China. Lee also shares his thoughts on the current state of tech giants like Microsoft, Apple, Google, and Open AI, expressing his bullish outlook on their future, especially praising Open AI's execution and predicting its potential to become a trillion-dollar company.

20:08

🚀 Opportunities and Challenges in the New AI Era

Lee discusses the immense opportunities presented by AI, likening it to previous technological revolutions but on a much larger scale. He suggests that both large companies and startups could see significant growth, with AI technologies advancing rapidly. However, he also raises concerns about the increasing dominance of a few big players and the challenges faced by smaller entrepreneurs and researchers due to the high costs of entry and the risk of job displacement. Lee emphasizes the need for accessibility in AI to help bridge the gap and create a more equitable landscape.

25:11

🛠 Preparing for an AI-Dominated Future

In the final paragraph, Lee addresses the future impact of AI on jobs and the importance of preparing the next generation. He argues against the notion that using AI tools like ChatGPT for schoolwork is cheating, advocating for embracing AI as a tool for enhancing productivity and creativity. Lee stresses the importance of human qualities such as empathy, compassion, and the ability to form trust, which he believes will remain uniquely human and invaluable in the workplace. He encourages nurturing these qualities in children and leveraging AI to complement, rather than replace, human skills.

Keywords

💡AI (Artificial Intelligence)

AI refers to the simulation of human intelligence in machines that are programmed to think and learn. In the video, AI is described as a revolutionary technology that has the potential to surpass human capabilities in various tasks. The speaker discusses the impact of AI on understanding human cognition and its role in future technological advancements.

💡AGI (Artificial General Intelligence)

AGI is a type of AI that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks, comparable to human intelligence. The video mentions that AGI is often viewed as the ultimate goal of AI development, but the speaker suggests that this is a narrow perspective and that AI can excel in areas without needing to replicate human cognition entirely.

💡Cognitive Science

Cognitive science is the interdisciplinary study of the mind and its processes, including how people think, learn, and remember. The speaker in the video indicates that despite AI's advancements, understanding human cognition still heavily relies on cognitive scientists and brain researchers, as AI does not perfectly mimic human brain functions.

💡GPU (Graphics Processing Unit)

GPUs are specialized processors designed to accelerate the rendering of images and complex computations, essential for training AI models. The speaker highlights the importance of GPUs in developing AI technologies, noting their high demand and critical role in executing large-scale AI computations efficiently.

💡Execution

Execution refers to the practical implementation and operationalization of technological innovations. In the video, the speaker contrasts the US and China, stating that while the US excels in innovation, China is superior in execution, meaning China can effectively implement and scale AI technologies more efficiently.

💡Open Source

Open source refers to software with source code that anyone can inspect, modify, and enhance. The speaker criticizes some leading AI companies for being closed off and emphasizes their company's commitment to open-source models, aiming to make AI technologies accessible to a broader audience and foster collaborative development.

💡Infrastructure

Infrastructure in the context of AI refers to the foundational hardware and software systems required to support AI operations. The speaker discusses the importance of having a robust infrastructure team to maintain and optimize GPU clusters, ensuring efficient AI model training and minimizing operational downtime.

💡Job Displacement

Job displacement refers to the loss of jobs due to technological advancements, such as automation and AI. The speaker predicts a significant impact on the job market, particularly in white-collar professions, and emphasizes the need for societal and governmental measures to address this challenge.

💡Compassion and Empathy

Compassion and empathy are human emotions that involve understanding and sharing the feelings of others. The video highlights that while AI can simulate these emotions, it cannot genuinely experience them. This distinction underscores the unique aspects of human intelligence that AI cannot replicate.

💡Economic Impact

The economic impact refers to the effects of AI on the global economy, including wealth creation, market dynamics, and job markets. The speaker discusses the potential for AI to drive unprecedented economic growth and create significant wealth, but also warns of the risks of increased inequality and the need for careful management.

Highlights

Discussion on the future of AI and its impact on humanity.

AI as the biggest breakthrough for humanity and its role in self-understanding.

The possibility of building AI more powerful than humans without mimicking the human brain.

The distinction between AGI (Artificial General Intelligence) and superhuman AI capabilities.

China's potential to prove its prowess in AI execution despite being blocked from accessing OpenAI.

The importance of open-source in AI development and accessibility.

The startup's billion-dollar valuation and its place in the AI world.

The strategy of focusing on infrastructure to reduce computational costs in AI.

The comparison between AI and human intelligence, emphasizing their different operational mechanisms.

Predictions on the future of AI and the competition between US and Chinese AI markets.

The potential for AI to replace 40-50% of jobs within the next 10-15 years.

The importance of embracing AI tools for future generations.

The unique aspects of human empathy, compassion, and EQ in contrast to AI capabilities.

The role of trust and authenticity in human success, which AI cannot replicate.

The future trajectory of wealth creation in the AI industry and its impact on capitalism.

The challenges faced by startups and researchers in the era of large AI companies.

The potential for generative AI to revolutionize data usage and problem-solving.

Transcripts

hu and I have been talking backstage and

we were deciding should we give you guys

some sweet dreams tonight or some

nightmares and we decided maybe a little

bit of both uh we have a lot to discuss

what the future looks like um what we're

building right now and how it will

impact us in the future um so really

excited for this conversation K thank

you so much for being here thank you

Alison so you've said AI is the biggest

breakthrough for Humanity um it is also

the final step to to understanding

ourselves so I'm curious Kyu why do you

think that and what exactly does that

mean to understanding ourselves I think

I wrote that in my PhD application in

1983 and yes I at the time I thought uh

once we figure out how once we build an

AI we'll know how we think and and that

was what drove me to go into AI at the

time uh was basically AI winter but what

I found out today is I think we can

build something much more powerful than

human not necessarily AGI but much more

powerful than human and it doesn't have

to follow exactly our brain so so the

good news is we can build something much

more powerful than I thought the bad

news it is that it may not give us as

much insight about how the brain works

we still have to rely on the cognitive

scientist and the Brain uh scientist in

the world so wait are you saying that

there's something Beyond AGI I thought

artificial general intelligence was like

the end all be all end point

when are we going to reach that and

what's beyond yeah AGI is defined to be

a superet of human intelligence

everything the human can do AI can do I

think it's a very narrow-minded and

narcissistic view because we are humans

so when you watch movies you want aliens

to be aliens want to become humans pets

be want to become humans monkeys want to

become humans but they don't you know AI

is this giant machine that gets better

with more gpus and computes and data it

can do so so so many more tasks so much

better than people but it doesn't mean

it does everything people do because

their brain operates differently from

our brain you know we don't compete we

don't compare um you know marathon

runners with cars right um and I don't

think we need to compare AI with us even

though it is exhibiting a lot of

intelligence so I'm certain so if we

look at what can humans do and what can

AI do uh five years ago humans can do a

lot AI can do a bit there's some overlap

um and today what AI can do is gotten

larger than what humans can do but but

it's not a complete superet I think in

the next two to three years uh if the

human circle of what human capabilities

is this big uh you know the AI will be

the size of Earth but it still may not

do what everything we can do it it may

not have awareness love um empathy

compassion um or other skills so

something super human greater than us

all that has no compassion it sounds

like a great great world we're building

great and it can fake compassion oh god

oh boy okay so we have a lot to discuss

you have startups you have a startup

you're running you are a VC have been

investing for years you've also worked

at just about every major tech company

Under the Sun um who's a leader in AI so

lots and lots to dig in there into there

but first I want to talk about 01 a okay

uh your startup which you're the CEO and

the founder spun up about exactly a year

ago you had no team today your a billion

dollar valuation no Revenue some Revenue

some Revenue some Revenue some revenue

on track for Revenue more Revenue um so

what is it and what is its place in this

AI world uh yeah I I felt that um you

know people in China cannot access

chpt um actually CH many of you may not

know this but um open AI blocks China

from ability to access

so I feel that China shouldn't be left

out of this Revolution and um I felt

that also I strongly believe as I stated

in the AI superpowers that uh us will

lead in breakthrough Innovations but

China is better at execution and I

thought a year ago the time has come for

China to prove its prowess in execution

and rather than investing in someone I

would do it myself this time so that was

the initial attempt uh the other is kind

of a frustration that the field is

moving toward more closed despite its

namesake open AI is not open at all it's

probably the most closed company in the

world even compared with Google and uh

Gro and meta and and and others so I

felt you know uh we need to work with

academics we want to open with work with

open source community and entrepreneurs

and people like yourselves and that we

should not only make AI work great and

make it create value but also make it

accessible to everyone and if the best

company in the bunch is closing all of

its Technologies never open source don't

publish then we can't engage and bring

in all the brilliant people in the world

so we decided uh we would also take an

open approach which is a bit unusual

because you know uh us is known to be

you American companies are known to be

more open than Chinese companies but

we've taken an open approach uh to date

every best model we have built from tax

model to multimodal model we've made

available in open source their on

hugging face and other sites because we

felt we wanted to um change the way

people think and make it accessible to

more people and then maybe lastly what's

unique is that uh I feel that this I'm

I'm kind of

seeing deu that what happened with um PC

and the phone I'm seeing again with AI I

know we're people love to talk about AGI

but practically speaking about making

money it's very analogous right PC was

uh creating a stack from CPU to uh to to

operating system to applications and

then to servers and to cloud and then to

the end user and to business and to C

and to be basically that whole stack

made Microsoft the amazing company

and made them incredible amount of money

and the phone more or less did that for

uh Google and apple and I think the same

opportunity exists but but I feel a lot

of the llm companies on out there are

run by researchers who care only about

making a great model and I think that

science fair phase needs to end um no

matter how much Brilliance and great

demos you make uh at some point there is

a uh a point of Reckoning when investors

are going to say what do you have to

show for yourself what's your p&l what's

your Revenue what's your growth when do

you break even and I I've learned a lot

of that myself having been a researcher

from the beginning but now that I've

been a VC for 14 years I feel like um I

can make this thing make money so we're

not spending a lot of time on it but

we're building the company with the

ambition that this company will have

have infrastructure model uh

applications and also data working as a

stack and we've come up with a number of

ways which we think in the future will

make money and we don't do it because we

want the money but we do it because we

see the need to continue to raise money

to afford our gpus and we want to do it

by not creating a bubble or promising

the moon um uh or through demos we want

to do it through through actual Revenue

growth and profit over time sounds very

expensive sounds like something Venture

Capital alone cannot fund I mean you

have Google with gazillions of dollars

at their disposal meta as well I how do

you even compete in that World um to

give you an example um when you think

about gpus and models most of you

probably just think okay he's they've

got so many gpus then they can do great

but actually Google has over 2,000

people just in its um deep Division and

those 2,000 people are competing for

gpus and resources and Google's uh

approach is let you know 100 flowers

bloom and that's why open AI leaped

ahead by betting on one approach uh with

as much less GPU than Google had years

ago now they have both have a lot so um

I I'm think I I think the approach we

think is we want a very small AI

modeling team and a very large

infrastructure team because if you have

too many researchers and a culture where

everybody can try ideas you'll quickly

run out of money as a startup as you

said but if we're very focused we want

these researchers to read every paper to

understand every technology to discuss

things um theoretically argue from first

principles and then build some

experiments to fight them fight it out

and then before we really spend the

expensive GPU we will have either

reached consensus or I would have to

make a decision so this is a very

different culture than what Google and

other companies try to do we're

basically trying to gather lots of data

and make um key decision so we don't

take as much GPU as an example you may

have read a paper by Steven Levy about

Huawei and the polar code I won't go

into details here but basically Huawei

asked this Engineers to read all the

papers and they found this Turkish

Professor who invented something called

the polar code and that made all the

difference and gave huawei's leadership

position in 5G we're taking that same

approach to be very very diligent to

save GPU then the infrastructure is one

of the least appreciated but most

important Technologies because these

these gpus don't work very well they

break 4% 4% of the time each GPU breaks

so if you have a cluster of 10,000 gpus

half of your month is gone because the

cluster every time a GPU goes down the

whole clust cluster goes down you've

heard Jensen hang talk about how

Blackwell has ways to recover well we

can recover today by patching H H 800s

that we have in in the company and also

uh there's a metric called mfu which

measures the uh model flop utilization

um most llm companies are around 40% um

you know Google Nvidia are slightly

better but we're at 63% so we basically

you know I think I truly believe that uh

necessity is the mother of innovation

and the necessity for a poor company

like us compared to a Google open AI

Force us to be diligent about how the

approach to take to be decisive about

which approach to take and also to build

a large infrastructure team to reduce

the cost of computes because we just

don't have that many got

it okay um well big journey ahead um

you're also called the tech Prophet so I

want to get some prophecies here from

you while I have you but let's look back

at you've written two books um both sort

of predicting the future in their

different ways superpowers um was sort

of the US versus China and who will win

um who will win uh where are we now

where are both and were you

right uh the our last last answer to

your last question is of course

yes uh the prediction I made in my book

was was First Data is the new oil that

makes all the difference and I think

look what generative AI is right take

all the data in the world to train using

generative as a way to uh solve the

objective function problem second

prediction in the book was that us was

better at Innovation breakthrough China

was better at execution and we saw that

in the earlier AI days and in the recent

Genai I think we're just about to see it

I think we'll have to see how this works

out but certainly uh taking my company

as an example we were eight years behind

a year ago now we're probably less than

one year behind of the top American

company so at least so far we've been

executing of course the last one year is

the hardest right because think about uh

what open AI has achieved in one year so

we we don't view it uh in any kind of um

um hubris or um uh taking for granted

but we have closed the Gap because we

did execute better in the past year uh

in my company and in other Chinese

companies um so I I believe in that

still the other point I made was well

when can us have an unsalable advantage

over China and the point I made in the

book was when the technology

became invented by some corporate

company uh by some corporate entity not

academics because academics were

published and that corporate entity

chooses to stop publishing which we are

seeing now so it's definitely plausible

that us can extend this leadership

because open Ai and to a lesser extent

Google have stopped publishing um but

but we'll see so are China and the US

headed on different paths here will they

even be competitive in their a

respective AI markets or will there be

the China option for the world to engage

with on on AI and the US version and

then if that's the case how the heck do

you regulate this all if they're

separate things yeah we're well beyond

that and we're in our parallel universe

this is not ideal none of us like it I

think but it is what it is and given

it's a parallel universe I think we're

going to uh see a lot of interesting

American solutions that won't make it to

China and interesting Chinese solution

that won't make it to us so as an

entrepreneur or VC or just a curious

mind it would make sense to look at both

worlds to see what's exciting in each

one because you'll while you compete in

your world whether it's the American

world or the Chinese world if you have

the advantage of actually having studied

the other parallel universe you will

have superpowers in the work that you do

but we don't have have any unrealistic

uh expectation that uh us and Chinese AI

companies will actually compete um in

the same country unless it's in a small

number of countries that are friendly

with both

countries um when you look at the

world's biggest tech companies today uh

you've worked for at least half of them

Apple Microsoft Google who is still on

top in 10 years or even 5 years Who

falls and which uh startups kind of

overtake them yeah um I think on the US

side um I mean right

now Microsoft is a darling and um uh

Apple's doing stuff and uh Google is uh

frustrated and a lot of negative uh

comment and then open AI is the upst

starter I would say that despite my

earlier comments on open AI I am very

bullish on their future uh they've

really done an admirable and

unbelievable job executing um even today

GPD 4 is still the gold standard you see

Gemini Ultra and cloth 3 and make these

claims but if you use these models GPD 4

and gbd4 turbo is unbelievably good and

a great balance for uh performance and

um uh cost so I I I I would say um you

know open AI will like be a trillion

dollar company in the not too distant

future how distant or how not so distant

two three years trillion dollars in two

or three years I think that's the likely

outcome of course they could Mis execute

or some some other company could do a

great thing but I I despite my concerns

about their lack of openness I have

great admiration for them so I would if

I could invest in any of them which I

can't but if I could I would do open a

ey uh Nvidia is another one that's a

safe bet it's obviously extremely

expensive but the processors they have

and the Cuda and the um Technologies

they have on um um the the ecosystem and

the libraries it's very hard for a

competitor to dislodge them they're

obviously very expensive but um you know

most of you know in secondary stock you

uh you buy high and sell higher rather

than Buy Low you none of these companies

are going to go low Microsoft is exe

exec it brilliantly um I am a little bit

disappointed at the Microsoft co-pilot

because it is

gluing gen to an existing product that

is a dinosaur that should be thrown out

uh but I understand why they did what

they did but I would rather see a new

product that throws away Microsoft

Office and that has AI do most of the

writing and human just kind of sit in

the back seat twe tweaking it a little

bit uh but nevertheless I think my

Microsoft's done an amazing job um on

selecting open a and partnering with

them and I think Sati has demonstrated

unbelievable leadership in trying to

bring in uh Sam Alman and then when that

couldn't gracefully letting him stay and

now getting um Mustafa it's just amazing

to see uh SAA has been the most

phenomenal uh CEO uh Google I'm still

somewhat bullish uh despite all the

issues we all know um it is still has

currently has the largest density of AI

talent in the world by far uh more than

open AI more than Microsoft more than

the others so I guess the question is

can they start to execute better so

um be that as they may the incumbents

are certainly in great position each of

them um with their War chest of cash but

it's a new era for entrepreneurs as well

yourself included um if you were well

you are an entrepreneur where do you

start um if you want to get into this AI

world and what kind of wealth creation

are we talking about here I mean wealth

in equity is already so vast you're

talking about this company open AI can

be worth trillions almost overnight a

couple years that's very fast what is

the trajectory here um for wealth

creation for capitalism in general for

the Haves and the Have Nots well it's

this is by far the most advanced and

most amazing technology compared to

anything by a factor of 10 right so if

we Look Backwards electricity internet

PC Mobile is nothing compared to this so

if you subscribe to that view right then

um then there's no reason why any of the

companies we mentioned large or small

couldn't go up by 10x right including

ours hopefully even more because we're

cheaper but the IM mature companies U I

don't see why they couldn't go go by 10x

uh because I think um there this is just

so and also many of the problems that

plague these systems like hallucination

we we I can predict uh that they will be

more or less solved in a year and a half

or so so um yes they hold things back

but I'm very bullish on these

Technologies moving forward um of course

on your other question I'm also worried

that uh a few big players will dominate

more than ever before um and um and that

if if one company dominates it would be

a really horrible thing if five or 10

companies are doing better that's a lot

better but even in that case uh it does

create an accelerated pace of um job

displacement and accelerated um set of

difficulties for smaller entrepreneurs

if you could only raise five or10

million and you decide to do an app um

take a look at Jasper right they built a

great app at the time but the foundation

model sucked in all the learnings and

the app became of much more questionable

value and that is not even by evil uh

Planning by the platform provider is

just the natural power of the

fundamental models to suck in all that

you feed it so that creates um I think

uh serious challenges for Have Nots the

and also researchers uh if you're

talking about lack of gpus I mean we I I

try to cry to you how much how few GP

CPUs we have but you know we have 100

times more than 99.9% of universities so

what will professors do so the halves

and Have Nots have become at the

Historical um Gap where professors

entrepreneurs and people who have um

don't have the skill sets and people who

are working on White Collar relatively

routine jobs I worry a lot about the uh

disparities uh for them and that's again

why on 01 I chose uh by you know making

this great technology accessible as our

mission and and the the underlying

emphasis on is on the word accessible

because I think all of us should do what

we can to avoid the case of an extreme

halves and half Nots and job

displacement I think we all know this is

coming um you had said around 2017 you

thought in 10 to 15 years about 40 to

50% of all jobs would be replaced by AI

is that still an accurate timeline in

your opinion um what the heck is

everyone going to do when they don't

have a job in three years if so it's

actually uncannily accurate people have

criticized me for being too aggressive

in the 2017 17 18 19 and I was a little

nervous at the time but when J ji came

came out I think everybody's on the

bandwagon and believing that is the

correct Pace um and I think the white

job collar jobs will go a lot faster

blue collar job maybe a little slower

because more people are shifting to the

software only

displacement and and I think it's a very

very significant problem and I think

finally some governments are waking up

and realize they have to do something

about this and in my AI 2041 I outlined

a number of um creative maybe not

necessarily workable Solutions that will

that was intended to get people thinking

so get a copy of the

book um well uh so we've got a lot ahead

somehow we're out of time and we need to

let these people eat but the one

question I do want to leave everybody

with is can we get some hope here um how

should we prepare our kids to live

alongside machines right um if this is

what's coming and it's coming fast you

know let alone all of our jobs we need

to be thinking about how to work this in

and and help employees and help

everybody but what do we do for our kids

when they say what should I be when I

grow up yeah I I think first thing we

all have to do and influence all the

people around us is to stop this

nonsense about kids are using chadd to

cheat right this is not cheating any

more than using word or photoshop the

kids when they go into the workplace are

going to be measured based on the final

output of their work they're not going

to be measured on what did you use chbt

did you use Google search so I think we

need to en encourage people to to

harness Ai and use all the tools so that

they can be the best that they can be

and also it's a great guide to uh what

things they can aspire to and what

things are not worth uh following I

think that's incredibly important is to

harness Embrace Ai and stop trying to

catch people cheating this is not

cheating this is um producing great

output it's not any more cheating than

um Fortune journalists using Microsoft

Word Spell checking or a um um a a

fortune photographer using Photoshop

this is chbt is a tool everyone should

use it and learn it learn from it uh and

embrace it and and the second thing is

that um I think there needs to be a

belief that there is something unique

about our Humanity I continue to hold

out that we have a soul the machine

every will that we have compassion and

empathy we have emotions and the ability

to love we have the ability to connect

to other people and create trust and win

trust and that all of you know as

successful people in your companies your

success is built more more than anything

more than your technical skills more

than your business skills the most

important skill that I tell any young

people for the last 20 years is that

winning trust from other people is most

important and winning trust is about uh

authenticity about teamwork about

sharing sharing um and it's about high

EQ not just the IQ so I believe in that

holds out something that we can all

Embrace uh you don't have to be a genius

to have a high EQ you don't have to be a

genius to to love and be compassionate

and in both of my books I talk about

that as the essence of our humanity and

I continue to believe it uh do I think

AI can fake it yes do I think people

will accept the faking AI at least for

the next 50 years no so that's long

enough for your kids to survive and

figure out the next step for their kids

okay our kids will survive and they'll

figure out something else later um thank

you so much Kaiu I wish this had been an

hour it was such a pleasure chatting

with you thank enjoy your meals