WEBVTT

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at unprecedented scale.

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Next speaker is, ladies and gentlemen,

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Mr. Alexander Wong, Chief AI Officer at

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Meta, the founder of Scale AI. Alexander

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Wong built the data infrastructure that

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powers much of the modern AI industry

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before joining Meta as Chief AI Officer.

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So, with a round of applause,
please welcome Mr. Alexander Wong.

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Thank you so much for having me.

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Namaste. Uh it's fair
to say my upbringing wasn't

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typical. My parents
were physicists in a town

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called Los Alamos in New Mexico.

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Los Alamos is a government lab town
where for decades scientists have come

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to push the boundaries of what's
possible in mathematics, in

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supercomputing, in human genome studies,
vaccine research, space explorations,

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and material science.
My mother studies how plasma behaves

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inside stars. At the dinner
dinner table, we'd talk

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about physics problems, scientific
tradeoffs, the reasoning behind how

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systems work.
One kid in my town made huge balls of

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plasma in their garage for a science
fair project. You know, normal high

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school stuff. Growing up
in a place like Los Alamos

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leaves two things deeply ingrained in you.

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A belief that anything is possible

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and that science should serve society.

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Those ideas are what led me to study AI

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while I was at I was at college at MIT.

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They led me to start
my own company, Scale AI.

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And last year, they led me to Meta
where I'm now the Chief AI Officer.

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If you believe that anything is possible,

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Meta is one of the few companies with

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the resources, talent, and ambition
to push the science of AI forward at

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scale. If you want to make technology that

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serves society, Meta has an incredible
opportunity to get this technology in

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into people's lives.
Three and a half billion people use at

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least one of our apps every day.

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That blows my mind. It's more than half

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a billion people in India alone.

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People are already using
our AI to do amazing things.

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Across India, creators use our AI to

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automatically translate Reels into
the language of the person watching.

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Small businesses talk to customers
through WhatsApp business agents that

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they create in 10 minutes on their phones,
and they use our GenAI tools to

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create ads and reach customers way more
efficiently than they ever could before.

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And India has world-class developers
building genius things to solve societal

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challenges. For example,
there are more than 20

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million people with disabilities
in India who are locked out of education,

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jobs, and digital services because the

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digital world wasn't designed for them.

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So, I-Stem built voice-first, AI-powered

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infrastructure that helps people with
disabilities to learn, discover careers,

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and complete digital tasks independently,
like converting textbooks

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into usable formats or giving
personalized career guidance that takes

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into account their disability.

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In healthcare, researchers
at Ashoka University used

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our SAM 3 model, which
is trained on billions of natural

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images to speed up the identification
and segmentation of cancer tumors and

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at-risk organs.
Their model, OncoSeg, can help

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radiologists and radiology oncology
teams do in seconds what it takes hours

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to do manually. The beauty
of general-purpose models is

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the same technology that can segment
tumors in the brain can segment leaves

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to help farmers assess the health of

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their crops, as AgriPoint has done.

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We recently open-sourced our omnilingual

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models, which recognize speech across
more than 1,600 languages and can

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rapidly adapt to new languages
with just a few audio samples.

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It's not a fantasy that in a few years
we'll have real-time voice-to-voice

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translation for every
spoken language on Earth.

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Now build that into your glasses,
real-time translation in any language

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just for you.
That's transformative. Perhaps most

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especially in countries like India where

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so many languages are spoken.
In fact, language is an area where we're

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collaborating with the
Indian government on.

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Through its AI Kosh platform, we're
providing data sets in 10 major Indian

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languages so people can build AI models
that deeply understand Indian languages

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and context. I'm sure you're
used to people from big

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tech world making lots of grand
but vague assertions about what AI will be

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able to do. But we don't
have to be vague. People

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use our AI right here, right now.

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They're getting value from it and they're
building amazing things with it.

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And that gives us confidence
about what we're building towards.

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We're releasing new models this year
with the first coming in the next couple

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of months. These will be
deeply integrated with our

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products in a way we're
really excited about.

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We're optimistic about
the trajectory we're on.

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The first models will be good and as the
year goes on, I think we're going to be

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pushing the frontier.
Our vision is personal super

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intelligence.
AI that knows you, your goals, your

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interests, and helps you with
whatever you're focused on doing.

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It serves you, whoever
you are, wherever you are.

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We all lead busy lives.
I'm sure you'd want to do more

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if only you had the time and head space.

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That's how I think about
personal super intelligence.

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Say you want to be healthier.
Your personal AI could help you see

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through a personal health plan covering
diet, exercise, and sleep in your daily

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routine. Or you have
a project you'd like to get

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done like putting on an event.
You can track your progress, reach out to

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venues, arrange invites, remind you of

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things you haven't considered and more.

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If you love to go fishing or paint
or want to travel more, it can help free

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you up so you can do more of these things.
And it can give you advice when

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you need it and or help you show up as a

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better friend or in your community.

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It won't just do your admin, it'll be an

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extension of you so you can be you more.

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I get that some people will worry
uh what companies that what companies

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like Meta really want is to get you
hooked and leave you passively staring

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at screens.
But the whole point of personal

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superintelligence is the opposite.

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It's about helping you be more active
in your life, in pursuing your goals, and

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deepening your relationships.
I know people are going to be skeptical

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when I say we're doing we're
going to do this work responsibly.

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But you don't have to take us at our word,
take us at our incentives.

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This is a competitive space, which
is why we're seeing so much innovation.

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Given how intimately your
personal AI will know you,

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people aren't going to hire us for the

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job if we're not doing it responsibly.

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Our AI needs to work the way we say it

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does, as well as we'd say it does, and
as safely and as securely as you need it

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to. It needs to help
you in your life and if

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it doesn't, people simply won't use it.

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We'll lose customers, we'll lose
public trust, and we'll lose out to our

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competitors. That's why
we're transparent about our

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models. We publish model cards
and evaluation benchmarks and data so you

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can see how they work, their intended use,
and how we assess their performance.

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And as they get more advanced,
we're looking at ways to share even more.

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It's why we invest in the
science of model evaluation,

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both improving the existing tests
and building new ones for risks we haven't

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yet confronted.
And it's why over many years

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we've developed ways to identify
and mitigate potential risks. Before we

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release a model through risk
assessments, scaled evaluations, red

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teaming, and fine-tuning.

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And we can monitor aggregate trends
in how people use AI in our apps. So, we

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have a feedback loop that can flag
potential risks and help us improve our

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models.

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As the models improve, the governance

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around them has to keep pace. So, we're
innovating with how they learn and apply

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principles and how they're tested and
evaluated using AI to strengthen checks

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and balances. Realizing
the full promise of AI is as

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much a matter of getting policy
right as it is investment.

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There are four building blocks for AI.

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Talent, energy, data, and compute.

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Governments and industry
need to work together

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to make sure there's access to each,
so we can realize AI's potential and do it

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in a way that means you can
build for your needs, not ours.

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That's in part about having bold

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national AI strategies and policies that
encourage innovation, not patchworks of

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inconsistent regulations
that make it harder.

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But above all, it's about
collaboration between public

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and private sectors to deliver these
four building blocks. And to design and

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deploy AI that works for your
citizens and your economies.

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I don't want these amazing
technologies to be one-size-fits-all.

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I want them to serve your needs,
designed for the challenges and

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opportunities that are unique to India,
to societies across the global south,

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and all over the world.
I want them to serve you as an

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individual, no matter who
you are, where you live,

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what language you speak,
or what culture you're a part of.

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That's only going to be possible if
the public and private sector are on the

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same side. We need to be partners
working together in a spirit of openness

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and collaboration.

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And with a sense of shared ambition.

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I truly believe we're on the cusp
of a moment where really anything is

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possible. We want to work
with you to build AI

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that serves our societies.
I hope you'll work with us. Thank you.

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Thank you, Mr. Alexander Wang. Our

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heartfelt gratitude to you for your

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remarks, for sharing your findings as

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well. And well, your vision for AI and

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innovation. It does inspire many of us.