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- Today, data and machine learning
are accelerating innovation
in virtually all industries and sectors.
From Olympic gold medals to advances in medicine,
organizations are using machine learning
to push the frontiers of what's possible.
Take the Australian Olympic swimming team,
the coaches knew that they had a treasure trove of data
on the swimmers, but they didn't know the best way
to use it to advance the training.
Once they could really use and apply this data
at the poolside, the positive results were clear
on the biggest world stage for sports, the Olympics.
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- [Announcer] Take your marks.
- The Olympics for swimming is the pinnacle,
it's the ultimate goal, it's what every swimmer strives for.
(people cheering) (water splashing)
In Australia, we're a water-loving nation.
There's a saying that swimming's in our DNA.
It's a really holistic thought, and every aspect matters,
physiological data, performance training data.
- Data had been coming to us in the early days
in reams of paper.
There'd be numbers everywhere, and a lot of times,
it just went into the wastebasket.
I just needed somebody to tell me
how to get that information and how to apply it.
- [Jess] When we started working
with the Amazon Machine Learning Solutions Lab,
it was a real eye-opener.
Machine learning data, that's their bread and butter.
The knowledge and experience
that they have is just invaluable
to enable us to do our jobs better.
- (laughs) You smashed it.
- With machine learning and the capacity
to scrape and capture data across the world,
say it's two days before a relay,
we can take performances of other athletes
in other countries in the real time,
and then we can match it up
with the performances of our athletes.
Really easy, like just put some numbers,
and bang, it's there.
It informs us how to put our teams together.
(people cheering)
- [Jess] To put all that training
to the ultimate test at the Olympics
was a really like pinch-yourself kind of moment.
- It was a record-setting nine gold medals,
and 21 overall medals.
- Being the most successful ever
Australian Olympic swim team
is a absolutely amazing achievement.
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And AWS and the Machine Learning Solutions Lab were part
of the foundations of the success of the team.
(people cheering)
- Whether it's measuring race times or election results,
machine learning can create efficiencies.
At Broadridge, where hundreds of millions
of shareholder votes are counted every year,
they have bottlenecks with reviewing
and extracting information from these votes at scale.
- The core business we have is proxy voting.
A lot of people care greatly
about environmental social governance issues,
about board diversity, and through proxy voting,
you can enact real change in the companies
that you own shares in.
And in 2020, over 150 million Americans voted
in the presidential election.
What a lot of people don't know
is that the proxy voting process is many, many times larger.
In the last 12 months, we distributed
over 400 million communications to shareholders.
It's a huge amount of data.
This was a natural project to think about AWS
and their advanced machine learning capabilities.
I remember the kickoff
with Amazon Machine Learning Solutions Lab,
looking around the table and just being amazed
at the talent, at the advanced degrees.
They listened and they took the time
to understand our unique needs.
Fast forward a few months, and we put a algorithm
and all the ML ops around it into production,
that has allowed us to cope with the massive volume
of the data and the seasonality spikes
and it's created efficiencies of about 30% cost savings,
and something that I'm really proud of that we've done
together with the Amazon Machine Learning Solutions Lab
through this project is provide a lot of data
that helps inform shareholders
to better make change happen in this world.
- Now more than ever, we need medical breakthroughs,
and we need them quickly,
but human trial and error can take valuable time
and might miss key insights into what makes safe,
effective, and transformational therapies.
In their partnership
with the Machine Learning Solutions Lab,
Janssen was able to harness the power of data
to serve patients faster and better.
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- For me, it's always been about the patients.
I grew up on three continents, you know,
by the time I was 18, and I've seen the impact
on human health from the most developed country
to the most developing country.
And I think there's a lot we can do
to level the playing field in terms of healthcare
and the impact for patients.
The combination of data science and science
is really advancing how we can help humans.
In order to develop a medicine, it takes us years,
but I think there's so much opportunity using data science,
AI, machine learning, to not just shave the time,
that's one aspect, but I think the more important aspect
is insight that lets you know early on
that something's not gonna be toxic,
that something is gonna have a better safety profile,
that something truly can be transformational.
And this led us
to the Amazon Machine Learning Solutions Lab.
Using some of the differentiated capabilities AWS has
from a data integration perspective, and then coupling that
with our know-how on chemistry data, on biological data,
adding a powerful search engine,
and then applying AI and machine learning
to be able to predict which of these molecules
would have the best chance of being a medicine.
With the open-mindedness and creativeness
of using data science, we're in the best position
in the central point to help patients.
That's what gets me out of bed every morning.
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- Core to our partnership is empowering customers
to continue on their machine learning journey independently,
knowing that they now have the knowledge
and robust infrastructure to support it.
Using our 20-plus years of experience in machine learning,
we are proud to help these companies
as they bring innovative and impactful changes to our world.
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