We can't say we were lucky to have it happen now.
On the other hand, it's fabulous that it didn't come any sooner.
There's oftentimes a misconception that technology is what's limiting advancement,
and that is not the limiting factor.
The limiting factor in scientific advancement is ideas.
And ideas don't come from technology, ideas come from people.
We can accomplish a lot in a very short period of time
when everyone comes together and everyone's working together,
and really giving it their all.
Our superpower,
and I really believe this deeply, is our ability to cooperate.
Times of crisis push us to innovate, to adapt, and evolve.
How we respond today will shape our tomorrow.
To truly come together, we must break down barriers
and nurture alternate perspectives.
Science and technology offer the opportunity to fuel discovery and magnify our ingenuity.
These are some of the stories and people
whose ideas are carrying us forward to emerge resilient.
[RESILIENCE]
[Episode 1 Innovating To Understand & Act]
As COVID-19 hit,
the first thing we had to do was understand the virus
at both a molecular and societal level.
With massive amounts
of information
coming from all corners of the globe,
we had to get our arms around the data
before even thinking about potential technology solutions.
In the first episode of this series,
we take a look at some of the stories from the people
facing down the pandemic
and grappling with the question,
"What can I do?"
We're all part of the same family of RNA.
Even the viruses we fear, they're really us.
I watched the movie Outbreak when I was very young,
I really became scared of pandemics but I really liked how a virus evolved.
We're making things that are invisible, visible.
And once people understand something, they can also address it, they can tackle it.
I would definitely characterize myself as more of a biologist.
I feel like a neuroscientist
in artificial intelligence scientist's clothes.
I'm an astrophysicist trying to describe immunology,
so take it for what it's worth.
Many, many people
are very fixated on the numbers.
You know, enormous web traffic to various sites that track COVID.
Are they going down? Are they going up?
Because that affects whether your kids will go to school soon,
or whether you can go and see your parents.
That's why everybody's focused on them.
In the early days, people were fixated in the actual numbers.
Like my reaction to them was, right now the problem is not
how many deaths that you have today,
the problem is how fast this is growing.
For the first time,
we had like a sense of urgency
that we needed the data,
near real-time.
The last week of March last year, we started working with UW.
Our own hospital system
at the University of Washington
asked for our help to forecast potential surge.
They really wanted to get a reasonable sense of what was coming,
how bad could it get,
and when might it recede.
We always try
to look at problems
from a global perspective.
We think
that analyzing all the data from around the world
may yield insights that you wouldn't get otherwise.
About April 5 or 6,
we started to notice
in the northern parts of Italy,
that the decline
in Italy was very slow.
So the cases shot up,
reached the peak,
about exact timing from Wuhan,
but instead of coming down, it slowly descended.
And that's where we started to make the transition
to a transmission dynamics model
to figure out what might be predictors of transmission,
how much do people's behavioral choices change transmission,
how much does mask use change it.
And then we went live the first week of May.
Because the problem is complicated, the signal is also complicated.
And it is sometimes hard to distinguish between signal and noise.
When we do the COVID trend forecasting,
we use a parallel assemble of three types of models.
If these models can agree with each other,
can come to some consensus then we believe it is not a noise.
We can really get something useful, make a reliable prediction.
The number one reason why you need these type of dashboards
is for making sure people can get that information.
And we learn a lot on how to communicate that data
because, again, you want to make it easy for people to understand
the current situation.
Almost every study that we do,
we see things that we didn't expect.
And that's the nice thing
about aerodynamics is that
many times
it's counterintuitive.
Yeah, pandemic is by nature
a very multidisciplinary problem.
It's really a lot of fields
that are willing to go all the way.
Everybody has been doing much more than they actually committed to do.
Well, we need to work very hard,
across organizations, across disciplines,
otherwise we cannot really make substantial progress.
Many simulations are coming out about spreading of droplets,
especially when people are standing still at distances.
But then what was completely missing in the beginning
was equally valuable information from the aerodynamics point of view,
the engineering point of view,
nobody was looking into this aspect of the moving.
I realized, okay, we as aerodynamics experts taking particles out of the air,
we probably have a big role to play here.
How far do two people when they are running behind each other
have to stay apart to have the same exposure,
or non-exposure of droplets than two people standing still
talking to each other at six feet?
All of us immediately said, "Okay, yeah, we just have to do this,
we have to put this out."
So we published this paper on social media with actually a very moderate message,
people please keep exercising, just stay out of the slip streams
We all decided to communicate that
without waiting for the publication of the scientific paper.
And we considered that as an urgent response.
If you see how many people have been collaborating,
have been joining forces, have been dropping what they were doing
from academia to business to volunteers.
If you look a bit deeper, you also see some tiny beauty in all of that.
It's important to recognize that,
you know, we all play a role here
and we all can make contributions,
and at different times we're in positions to make greater contributions.
And when those times come,
we should take advantage of those opportunities,
because that's how we can meet the responsibility
that are privilege demands.
Because of the unprecedented pressures to do science and publish,
there wasn't the normal processes of peer review
and cycles took to vet scholarship.
So there was a deluge of information of all forms
that needed to be tools to navigate
not just topically what scientists were looking for
to build upon and to make connections with, but also to understand the quality.
The urgency of the pandemic gave us the push,
the fire, the drive to work hard and work fast,
but it also provided us with a huge amount of data.
CORD-19 was concept to bring together unprecedented,
massive corpora of scientific text,
journal articles on the coronavirus, going back decades.
All these players came together,
we said we can change the game
when it comes to search and retrieval.
To help scientists learn how to find things better,
to help us learn how to provide new kinds of search services to the world...
Biomedical search was all about.
Don't worry about keywords, just say the sentence,
give us the full text of what you're looking for.
We saw queries of the form
how does COVID-19 affect someone
with severe diabetes induced by pregnancy?
We found that you can get much more precision
and recall by training systems to not necessarily look for keywords,
but to look for the actual concepts
in what are called semi-supervised large scale neural models.
We wouldn't be able to do that without having access
to this massive dataset CORD-19.
I was attracted to astrophysics because it attempts to address
some of the grandest questions we as human beings have.
It really is a shift from, you know, mapping things at the largest scale, the galaxies,
to things at the smallest scales, human cells.
So each person's T cells tell a unique story
about their history of exposure to different diseases.
After they've reacted
to a pathogen,
they remain in your blood
for a long time.
So your T cells basically act as a record of the different diseases
that you've encountered in the past.
The Antigen Map Project is an attempt to see and understand
whether we can basically read the human immune system,
literally in some sense.
Because what we get when we see a T cell is its genetic sequence,
which is just a bunch of letters.
A few weeks after we started working from home
and I had moved to the Antigen Map team,
we decided that there were really significant gaps
in the understanding of the virus and of diagnostics surrounding the virus.
So we made the decision that we would actually add COVID
as one of the diseases that we were working on.
I was very closely involved with the T detect side,
which was and is the adaptive developed
for diagnosing whether someone's had a COVID infection or not.
T detect begins with getting just one vial of blood.
And from that vial of blood,
we can characterize hundreds of thousands
of T cells.
And then within those T cells, we can identify signatures
that are specific
to a disease of interest.
So we have a bunch of individuals that are fighting COVID,
or have COVID, and a bunch of people who don't.
And let me just ask which T cells overlap
in some statistically significant sense amongst these individuals?
If two different people have had the same disease in the past,
they may share some T cells in common.
And that's really the specific signature of shared T cells
that we leverage to build T-Detect tests.
It's the first time we've been able to have a clinical diagnostic based on T cells.
Now that we've seen that it really works in COVID,
we're really eager to expand the use of T-Detect to other diseases,
especially in areas like autoimmune disease,
where there's really significant unmet clinical need.
COVID accelerated
what was already a process well in place before I ever started,
which was the revolution of the T cell immunology that,
you know, it's really, we're hoping will change the way we do healthcare.
This pandemic is kind of like,
has the gravitational field of like Jupiter,
for so much innovation in science and technology.
As we swing past the pandemic and zip off in new directions, it changes things forever.
This is definitely not the end of the game.
Every one of us,
especially those people like us,
who have some experience and expertise to combat this pandemic,
we need to have our continued efforts to contribute.
There's no doubt about it, especially given the challenges
we're facing going forward.
But that innovation isn't going to be our savior.
It's not going to save us. We have to save ourselves.
The pandemic has tested us,
and in some instances we fallen short of rising to the challenge.
But we've also seen amazing successes,
and people have come together in ways we wouldn't have previously imagined.
Cooperation is the foundations of our resilience.
It always has been, it always will be.
It's the way we will learn how to deal with pandemics.
It's going to be the way we face climate.
It's the way we will face up and face off against cancer.
And it's the way we'll come to understand answers to some of our deepest questions.
[RESILIENCE]
[Microsoft]