SANJAY RAVI: Thanks for joining me
for On The Go,
where we take a look at what's
driving the future of Mobility.
I'm Sanjay Ravi.
I lead the automotive mobility
and transportation industry at Microsoft.
This week, I'm joined by
the CEO of Wayve, Alex Kendall.
Welcome Alex, thank you for being here.
ALEX KENDALL: Thanks Sanjay.
It's great to be on the show.
SANJAY RAVI: I absolutely
enjoyed my ride in one of
your autonomous vehicles in the public roads of
London a few months back and I noticed that
you did not do a lot of localization at first.
You and your team are doing
some groundbreaking work at Wayve in terms
of pushing the ages on AI and autonomous vehicles.
Why don't we start there and share with
us a little bit about what you're doing and why?
ALEX KENDALL: At Wayve,
we're really excited to see
the world into the age of autonomy.
For us to see that, we need autonomy and
autonomous driving to be
accessible if you're on everywhere.
That requires a fundamentally
different approach to autonomous driving.
We can't have a system that is
designed with a set of rules and maps,
work and geofenced effluent areas,
systems that are deployed in a very
small parts of the world.
We believe that we need a system that
is intelligent and has
the ability to coexist in
our complex and busy and dynamic worlds,
that can understand the needs of
transportation systems and really
provide the services that we need.
This requires autonomous vehicle that has
the onboard intelligence to be able to merge,
to interact, to navigate through our busy cities.
That's exactly what we're setting out to build at Wayve.
We think of this as AV 2.0
and next generation approach to autonomous driving.
Today, we've prototyped and built the system
here in the UK and are looking to scale it to the world.
We believe in its approach,
that's going to be
the first deployable autonomous driving
in over 100 cities.
SANJAY RAVI: That's great, Alex.
In fact,
I was actually going to ask
you and I've heard it from you.
Your aim to deploy autonomy
in 100 cities across the world.
I would love to know how is the journey coming
along and how are you making progress against that goal?
ALEX KENDALL: I feel like
today we're at a
point where we've validated
a lot of the core beliefs that we have.
We've shown that a system it can
learn to drive and do that safely on public roads.
We've shown that we can drive with a camera free system.
But more importantly, we have shown
the system can generalize.
Generalization is the idea of
applying a behavior to something new,
something you haven't seen before.
That's really the core problem of autonomous driving.
That's because you need to
see the same thing twice on our roads.
Every time you go, there's different weather,
you have different vehicles or
cars or pedestrians around you.
The key thing to be out of
developing autonomy is that you
have a system that can deal with
all these weird and wonderful new things that you see.
We refer to this in industry as generalization.
We've been able to show that autonomous driving stack and
your own network can generalize not only to new cities,
we have tried to drive in London,
we've taken other cities like Manchester,
Liverpool, Leeds,
other big UK cities and shown you can drive
here without having seen data from these cities before.
It's being able to generalize to new cities,
but also the different vehicle types.
We're initially trying the system on a passenger vehicle,
a Jaguar I-PACE,
and now we've transferred it to a electric van,
a 3.5 ton Nexus electric delivery van.
The same neural network is
driving both of these vehicles at
the same time. Going back to your question.
We've validated a bunch
of core assumptions in this new approach.
We believe it works and as the future.
Now, we're starting off on a journey
of building and deploying it at scale.
SANJAY RAVI: Alex, I
love how you're using
deep learning system for
autonomy over rule based approaches.
You said the missing piece for
the self-driving puzzle is intelligent algorithms,
not more sensors, rules and maps.
Let's talk a little bit about what you
mean by deep learning systems and
intelligent algorithms and how
supercomputing power is critical.
ALEX KENDALL: I couldn't be more
excited about what we're seeing
from deep neural networks today.
Even that really bought
an impressive business that Microsoft has been making.
We've seen in 2022,
we've seen this year the emergence of
foundation models is really
large-scale ginormous billion parameter
neural networks that had trained on
very diverse data and are able to
prefer really
generalized platforms to different problems.
Whether it's been a natural language processing,
image or video generation,
or what we're building an autonomous driving.
The key thing that I think
we've seen emerge is to build a foundation model and to
build a system that can really
disrupt and replace rule based approaches in a category.
It requires you to make
huge investments in data and compute.
That's exactly what we've looked to
do for autonomous driving.
We've partnered with three of
the largest fleets here in the UK.
Our partners are Cado as the MDPD Group.
Ones that we've partnered with to connect
really large-scale training data
with the fleets that they operate today,
and then we're tremendously excited to work on
supercomputing technologies with Microsoft to
be able to create the compute environment
that can train models of the scale.
To throw some quick stats at you.
I think training these foundation models on
autonomous driving data is going to require compute
that is beyond many that we've seen
before because you're dealing
with petabytes of video data.
You're dealing with challenges
around simulation workflows,
challenges around really high dimensional,
high representational data that
you need to pass to GPU notes very quickly.
It's an incredibly complex problem.
In short, the right investments in data and compute,
I think is what's required to
unlock these financial models.
SANJAY RAVI: Alex, with that said,
I think there is this notion
that autonomous driving should be
something we can deploy
quickly and easily across the globe.
In reality, as you mentioned,
there are hundreds and thousands of consideration
that goes into deploying
an autonomous vehicle and keeping it safe.
You have a deep background in robotics.
You have also brought forward
a lot of experience from that background.
What have you learned across
the process of trying to achieve
this huge goal given your background in robotics?
ALEX KENDALL: Well,
you're right, Sanjay.
I just
spent a number of years working
on machine learning or
robotics in computer vision technologies.
But actually, what most problem,
what has taught me is that it's
a very cross disciplinary challenge.
It's not one that's just going to be solved
by one really domain expert, but actually,
it requires innovations and hardware and software and
simulation and machine learning
and even non-technical areas.
It's incredibly challenging product question,
creating a business model,
that public policy and
actual consumer acceptance for this technology to work.
It's a complete disruption to
our lives and one that will bring extraordinary value,
but requires all of
those different skills to bring together.
I've been thrilled to learn from and build
up a team that has expertise in all of these areas.
I do think that there is a technology gap that
we need a more scalable approach
to bring autonomy to the world.
But once you have that approach,
it's actually another huge challenge
to create the conditions precedent to Linux to succeed.
This is what we've looked at to put together.
There are some interesting innovations
there that we think this is
a technology that we can bring to fleets quickly.
We think that it's a technology that can let
fleets adopt the power of autonomy, increase safety,
improve easy utilization,
improve efficiency of transportation,
but ultimately, it's not a single skill set challenge.
SANJAY RAVI: It's great to
see that innovation Alex,
that you are driving.
I also like the particular focus you are
putting on real important
business needs like supporting
fleets in commercial settings.
Alex, Wayve has been
a Microsoft partner from the beginning,
starting with our Microsoft for Startups Program.
Working with innovators like you is what
motivates us to continue to evolve
the intelligent Cloud and Edge Platforms to meet
new needs of which autonomous vehicles certainly is one.
Can you talk about your partnership with Microsoft,
your experience working with us?
ALEX KENDALL: Hey, Sanjay.
I remember first meeting
your team in 2018.
Back then, we were just a seed stage business.
We've been able to
show a prototype of the system on the roads,
but we had everything to gain,
nothing to lose and we were looking to take on the world.
For you to partner with us and to give us
a leg up in getting our systems from
a server in the back corner of
our office into Microsoft to Azure Cloud,
that was really formative in our journey.
I think since then, our partnership has
just grown as our business has scaled.
We've brought on $260 million of funding.
We're thrilled to have Microsoft support us in
our latest series B round of
funding deep in our partnership,
see more of our workloads come onto Azure.
Today, we have almost entire compute platform on Azure,
whether that's our simulation workflows,
machine-learning powered by Azure ML,
or even the supercomputing technology
that we're sitting off on the
junior developing now to bring
our next-generation foundation models to the road.
SANJAY RAVI: Alex,
it's been a great pleasure
for us to work with you
and your engineering team to drive innovation.
Like I mentioned before,
you guys are really helping us push some of that
just from a technology platform standpoint as well.
Bill Gates has said that most people
overestimate what they can do in one year,
and underestimate what they can do in 10 years.
Knowing you're going to continue to dream
and reach to drive bigger goals,
where do you think will be in
terms of autonomous vehicles in 10 years?
ALEX KENDALL: Wow, dare to dream. Well,
in 10 years, I think
we're going to be seeing ourselves
into the age of autonomy.
That's going to look like having
autonomous vehicles or more generally,
intelligent machines throughout our lives.
By then, we should see
our autonomous vehicles throughout
multiple different market sequence with
a single foundational machine learning model,
power in public transport, delivery, ride-hailing.
But not only they're starting to see this emerge
into other areas of embodied robotics.
Whether that's in domestic robotics,
factory, other forms of
transportation beyond ground transportation.
I think this is the start of
a complete revolution of
bringing machine learning and
embodying it in the physical world.
I'm really excited about seeing that.
We're beginning and focused on
autonomous driving because I think
it's the largest opportunity.
It's called the availability of data,
a clear value case for society.
We'll bring that to the world first, but in 10 years,
I think we're going to start seeing
this emerging and pushing
ourselves into the age of autonomy.
I'm excited to see that next.
SANJAY RAVI: It's again, amazing, Alex,
what you're doing and thank
you for joining us here today.
Best of luck as you continue to innovate,
and I can't wait to take
another ride in the Wayve vehicle
soon. Thank you so much.
ALEX KENDALL: Thanks Sanjay,
we cant wait
to host you here in London. Cheers.
SANJAY RAVI: That will do it for
this episode of On The Go.
Thank you for joining us today.
We will continue our conversation soon with
more leaders pushing the boundaries of Mobility.