About 50% Of Jobs Will Be Displaced By AI Within 3 Years
Summary
TLDRIn 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
🤖 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.
🌟 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.
💡 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.
🔮 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.
🚀 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.
🛠 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.
Mindmap
Keywords
💡AI (Artificial Intelligence)
💡AGI (Artificial General Intelligence)
💡Cognitive Science
💡GPU (Graphics Processing Unit)
💡Execution
💡Open Source
💡Infrastructure
💡Job Displacement
💡Compassion and Empathy
💡Economic Impact
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
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