How does 500 petabytes make ADAS smarter? | with Nimrod Brickman of Mobileye

Recorded live at AutoTech 2026, this episode of The Garage features Sonatus host John Heinlein and Mobileye VP Nimrod Brickman discussing the evolution of ADAS and autonomous driving technologies. They explore Mobileye's growth into a comprehensive tier-one supplier, its advanced AI approaches, and how the integration of safety-critical features is making autonomous capabilities more accessible for lower-cost vehicles.

Creators and Guests

Host

John Heinlein, Ph.D.

An experienced technology and marketing leader, John brings his background from startups and established companies to Sonatus. He worked for 14 years at Arm, most recently leading Automotive Partnerships for North America where he engaged OEMs, Tier-1s, and others to deploy Arm-based solutions into automotive applications, including autonomous vehicles. His team was integral to launching the SOAFEE industry initiative for software-defined vehicles of which Sonatus is a member. Earlier he served as VP and Chief of Staff to the CEO and led a group responsible for competitive strategy. For three years, he was VP of Corporate Marketing where he led centralized outbound marketing, spanning marketing campaigns, press, events, web, digital marketing, ecosystem programs, and working closely with investor relations. Prior to Arm, John had an 11-year tenure at microprocessor startup Transmeta where he held several senior roles spanning business development, marketing, and customer success, among others. John earned his B.S. in Computer Engineering from Carnegie-Mellon University and an M.S. and Ph.D., both in Electrical Engineering, from Stanford University.

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Today in The Garage, we're
recording live at AutoTech 2026

in Novi, Michigan in
the Detroit metro area.

As one thinks about advanced
technologies in vehicles,

it's impossible not to think
about ADAS and autonomous driving.

And we're seeing incredible
advances in those technologies

all the time with things
like lane keeping and,

active cruise control becoming
more and more commonplace,

active emergency braking being
required in more and more

geographies in the future.

And then, of course,

it's big brother autonomous
driving where we're seeing

robotaxis with
literally no driver.

I know I see them driving
near my office all the time.

To talk about that, we
wanted to bring in experts.

And my guest today
is Nimrod Brickman.

He's Vice President of Business
Development with Mobileye,

an industry leader in ADAS
and autonomous technologies.

We really cover a wide range
of topics and about how their

technologies have advanced in
the past years and how they're

bringing these capabilities to more
and more vehicles all the time.

Let's go!

Welcome to The Garage.

I'm John Heinlein, Chief
Marketing Officer with Sonatus.

We're here at Auto Tech
2026 in Novi, Michigan.

Nimrod, Welcome to the podcast.

Hey. You said it right.
Hey. Thanks, John.

Thanks for having
me. My pleasure.

And look, we're thrilled
to have you here.

Start by introducing yourself
and telling us about you.

Sure.

So my name is Nimrod Brickman
I'm the VP of Business

Development in Mobileye.

So I've been leading the
business development in

Mobileye for the
past three years.

I've been with the company
for the past nine years.

A bit about my background maybe,

so I've I came from basically
investment banking, working with

technology companies.

So I've worked with technology
Israeli technology companies

trying to bring capital from
different places around the

world, focusing on China.

So I've been working with
China for many many years.

And then I started working with
some automotive companies back

then, and I got
really intrigued.

Really interesting
technologies, interesting

companies coming, trying, you
know, to swim in this very,

very intense industry,

And this is what got me trained
into automotive overall. Yeah.

That's great.

So many amazing technology
companies coming out of Israel.

Yeah. Yeah. It's exciting
to see the journey.

You have to start by telling
us a fun fact about you.

Okay. So going on with
this China path. Right?

So the first deployment
from Mobileye, basically,

my first relocation
position was to China.

Oh, wow.

Yeah. I was relocated to China.

It was twenty seventeen,
twenty eighteen, pre COVID.

I've lived there for
a couple of years.

I've actually studied Mandarin
back back from high from high

school and then
through university.

It was quite useful.
Which city were you in?

I lived in Beijing.

I had some time pre-Mobileye
in Shanghai as well.

But I've lived in
Beijing for three years.

Amazing experience. Such
a different culture.

Amazing.

That must have been such
an exciting experience.

My fun fact, I always share
a fun fact back to my guests.

I did an assignment in Japan,
in Tokyo. Also amazing.

Quite a few, about twenty
years ago actually,

which was incredibly rewarding.

I like you, you'd
studied Chinese.

I had studied Japanese
not in school,

but I had been studying
Japanese with a lot...we did a

lot of work with
Japanese partners...at

Transmeta. This was several
companies ago at Transmeta.

And we had a number of
Japanese partners and I've been studying

Japanese quite
intently and in fact,

I've been doing a lot
of business development.

So an opportunity came up to do
a very senior role in our Japan

office and I was
excited to do it.

Amazing. Also very difficult
language, Japanese.

Well, we can have a whole
conversation about that.

Japanese and Chinese are
differently difficult.

I00 percent.

They're they're both
interesting in their own

respects and they have
different and unique they're

actually, the difficulties
between the two are different.

Very interesting.
Very interesting.

So that's thank you
for sharing that.

Now tell us for our listeners
who may not know about

Mobileye.

Mobileye is incredibly successful
company and probably very well known.

But for those listeners
who might not know,

could you tell us about the company
and a bit more about your role?

Sure.

So let's start first
with the company.

So Mobileye has been around
for the past twenty five years.

We've basically,

the company introduced computer
vision for advanced driver

assistance systems starting in
1999 with first projects coming

into play in 2007 and onwards.

Basically, it's been a a world leader
in the computer vision industry.

And I think that just
to give you some taste,

by now we have more than two hundred
and thirty million EyeQ chips sold.

Two hundred and thirty million.

Over that. Yeah.

That's impressive.

It means that more than two
hundred and thirty million

vehicles are equipped
with our our system.

Roughly one in every every
eighth vehicle is using our

technology, we're very proud of.

And now we we have multiple
engagements with OEMs,

which are customers, companies
that we're working with.

The company has grown
throughout the past few years,

moving from a tier-two tech
provider into a more of an

holistic role, delivering a
full solution of level two

plus, level three, level four.

We're basically one
of the companies

one of the only companies who
were working from base ADAS,

meaning the very basic
technology up to level 2+,

level three and even
to autonomous mobility.

So this is with regards
to the company itself.

That's great.

I think we're going to get
into all of those topics.

And your role specifically is?

So I'm leading the business
development activities.

So basically everything which
is pre-nominated, pre-sourced,

I'm in charge of all the
advanced development activities

and engagements with global
OEMs and just managing the

relations and trying to get
more deeper connections with

our OEM partners and
expand our business.

This is basically the role.

And you're based in the
headquarters, is it Tel Aviv?

It is in Jerusalem.

So I'm based in Israel,

but we have multiple locations around
the globe with multiple representatives.

We have in the States, in
Detroit here, and, and Paris,

and Munich, Shanghai,
Korea, Japan.

So we have teams
across the globe.

Basically, in every hub
that there is a big,

OEM or a big part
of the industry.

So you've been with
Mobileye for nearly decade.

ADAS has really changed a
lot since you've joined.

Can you tell us about that
evolution? What are you seeing?

So it's quite amazing because
when I started back then in

China, you know, it's it was
all about meeting regulation,

front facing camera business,

very basic compared to
what we see right now,

what we're seeing right now.

And it's a significant leapfrog jump
that we're seeing within the industry.

Basically, what the OEMs and the
consumer are expecting from their system

to deliver is
completely different.

Right?

If we're looking at, you know,
all of the level two plus,

level three capabilities
that we're seeing out there,

hands off, eyes off solutions,

a decade ago that was just
made almost science fiction.

It was very imaginary.

Right now, it's it's actually how
OEMs are looking at their roadmap.

And throughout your engagement,

it's a very interesting role that
we're we're engaging right now.

You just finished a keynote
just a short time ago here at

AutoTech talking about Mobileye.

I mean, can you share with us
the journey you're you're on and

some of the things you
shared in your keynote?

Sure.

So first, I think it's very much
linked to this shift that we're seeing

right now and why the industry
and the OEMs are taking this

direction of of bringing
higher levels of

autonomy into the market.

I think the interesting part
here was how we're taking

different components that
were used to be separated and

segregated into the whole
centralization approach.

Right?

There's the whole SDV approach
and the whole centralization

approach, bringing more
components into the same one.

So within the keynote,

I've scanned through the
different technologies that we

have, parking, driving,
driving monitoring system

capabilities that we are integrating
altogether into the same system.

And basically, it means that we're
trying to balance in between three

different, pillars within
the OEMs challenge.

One is to bring a very high,

performance of of
the function itself.

Two is to bring it in a
very fast time to market.

And three, for for it to be very
cost effective and efficient.

And this is how I
address, you know,

the key pillars that Mobileye delivers
in this market into an actual product.

Maybe additional fact here is
when the industry is looking

then at those technologies,
they're focusing, like,

five to ten years ago,
they were looking at,

is it possible to deliver
those technologies?

Right now, they're looking at
how you can do it at scale.

Yeah.

And this is what I've
addressed in our in our

And and you mentioned
earlier that you'd

historically had been more
of as a tier two supplier

providing a component
into another subsystem,

but more and more you're
emerging as pretty much a tier

one supplier providing a more
complete subsystem or in fact

multiple subsystems.

Is that a good way to
think about your evolution?

Correct.

An interesting point here is
just that we're we've gained a

lot through our developments
around level two plus, level

three, and level four,

which helped us in creating
this kind of a holistic full

turnkey solution around driving.

So basically, if OEMs looked at us as
a key technology partner for one of

their components,

they're now looking
at us as a holistic

supplier for their
advanced solutions.

You mentioned L2+/L3.

I think that's probably the
biggest journey that the

biggest hurdle that the
industry is is looking at.

As the industry is looking to
get to that higher level of

autonomy and and perhaps you
want to start by explaining for

our listeners those
those those levels mean.

Hundred percent.

What do you see as the biggest
technical challenges to

achieving those higher levels?

So first, you you pointed
out a very good point. Right?

Let's start by explaining what
what does it mean level two

plus and level three.

So level two plus
and level three,

the main differentiation is basically
who is responsible for driving.

So level two plus,
level two plus plus,

there's a lot of
abbreviations around that.

So the driver is
always responsible.

The driver is always need to
be attentive and supervise the

system itself even though
if it's hands free,

or you can let the system drive,

you need to be
responsible for it.

But level three is when the system
itself takes over in certain ODDs,

operational design domains that
the vehicle needs to operate in.

Now this is a significant
leapfrog jump in terms of

technology that you
need to deliver.

First and foremost, you need to
have much more sensors, Right?

Much more compute in order
to allow that to happen.

And basically, what we're
trying to to change in between

level two plus and level three,
it's not the driving function.

It's the mean time
between failure. Right.

We're calling it in the
industry the MTBF. Sure.

So the mean time between
failure needs to be much

higher, so it will allow the
system to take over for the

specific driving task.

Right.

I think that's a really
interesting way to think about

it because most vehicles today,

the majority of vehicles
that have lane keeping,

and I know I'm not gonna
name any specific systems,

but many of these systems are
generally l two plus because

the expectation is at a
relatively short amount of time

within a few seconds,

the driver needs to be able to
take control if let's say the

system either doesn't
understand what to do or is an

emergency comes up.

With a a level three,

I'm assuming that there needs
to be now much more extended

period of time that the system needs
to be reliably able to handle things.

Correct.

So you need to, to
detect for much longer,

and also you need to
take into consideration what will happen

if there is some sort of
failure in one of the systems.

Right.

This is the way that we
approach the level three as

most of the industry is you
have a main system and in

addition to that, have
a fail operation system.

So it's very it's a very
delicate topic and it's a very

safety oriented,
discussion, not only the

performance itself,
safety first always.

Of course.

And I I think
so much excitement is around,

ADAS and autonomous driving.

It's obviously, it's a spectrum.

And so much advancements
in the past few years,

it's been incredible to see how fast
the pace of innovation is going.

In general, obviously,

we're seeing so much AI
coming into vehicles,

not the least of which,
of course, is autonomous.

As you're bringing AI into there,
understanding that, you know,

AI systems are fundamentally
nondeterministic and that's their strength.

But it also can be a
technical challenge.

What are the things that
you see as opportunity and

challenges to bring in
AI, and making them,

as you just said a second ago,

safe and and secure
and reliable in this

mission-critical environment?

So I think there is two ways
to look at this AI revolution that

we're seeing ahead of us.

One is conceptual
and one is practical.

The conceptual part is whether
you're taking a a single

monolithic approach
of end to end AI.

Basically, we're calling it in
the industry from pixel to torque

or from pixel to control.

When you have one single brain,

which is a bit less on the
safety oriented approach

according to how we see it.

And the other approach to
that would be a compound AI

approach, which is how
Mobileye is looking at it,

and I'll double click
on that in a moment.

The other aspect of it is very,

very much not non
conceptual, but practical.

How do you take huge
language models,

visual language models,

and visual language action
components and put them in an

online system, which
also supposed to meet

these both safety criterias
and cost criterias

of an automotive system.

Right.

So mobilized approach to that
is is using a compound AI

approach, which is basically a
fusion in between both worlds.

We're basically relying
on the safety element on

the core long learnings that
we've had for the past twenty

five years with the
composable algorithms,

which are getting always
better and better,

introducing more and more
components into the these systems.

And in addition to that,

we have a frontier
aspect of innovation

in in end to end and
large language models and

visual language models aspects
that's currently where we're

integrating them together.

Right?

So we're in a
compound AI approach,

we're just merging in between
the two and enjoying both worlds.

Should we think about that
as you're more fusing the

models or that the models each
have a specific function that

then they collaborate?

What's the best way
to think about that?

So we can think about it that
the main semantic or human like

driving will be done as
tasks by or tasked by the end

to end model itself.

Right? So the more human
natural type of behavior.

However, you would still want
the guardrails or the the

boundaries of the system to
be maybe a bit more rule based

because there is the there's
always the long tail problem

that you would
wanna recover from.

So basically, this is
this is the approach.

We're just mixing
in between them.

I think it's very very clever.

So shall I think about that as kind
of AI is watching over other AI?

It's like there's some
deliberate separation so that

there's someone kind of looking
over your shoulder or in a manner?

You can think about it
as yet another envelope,

safety envelope on top of your
core brain that will help to

make sure that what you're
doing is the right thing to do.

And in

a way that you could look
back on it and track it back.

Yeah.

And not just, you know, it's
not like an open ended loop.

That's right. We've done some
work with safety certification.

A year ago, we announced we'd
been ASIL-D certified for a

safety monitor for
one of our products,

which a very similar idea was
that the safety monitor was

able to look over the actions
of one of our of one of our

products before it took an
action and say that it is or

isn't functionally
safe in that situation.

So it's it allows you to
not have to, in our case,

functionally safety
certify the entire product.

But you certify the
the safety monitor.

It's a common approach
in the industry. Correct.

Sounds like it's a
somewhat similar approach.

Very much.

It's very much so that you
are homologating the safety

oriented system
and not the whole

system as is.

So it's well known that
Mobileye has one of the largest

driving databases in the world.

I hope you can tell us
a little bit about that.

But because you've been
in operation for so long,

how does that database give you
advantages and what are some of

the ways you use that database
to help your train and teach

your your algorithms?

So basically, this is one of the core
assets of Mobileye that we're proud of.

We've been around for twenty
five years, as I mentioned,

and we have different
types of, of datasets.

We have more than,

five hundred petabytes of data
that we're we've aggregated

throughout the world.

It is, combined through,
computer vision data,

driving behavior
data, and also RAM,

which is a Mobileye road
experience management.

This is a sparse information
data that we're harvesting on a

crowd source base.

And we're utilizing this
in two to three main ways.

One, this huge dataset
is helping us to train

our end to end networks,
our algorithms,

and make them better.

And we have real world data
and use cases to to tackle with

using this dataset.

This is one.

Other one is that we have a
huge dataset to validate what

we're developing.

This is yet another
very powerful tool.

Other companies in the industry
are working on simulators

because they do not have this
access to that much of data

that we have as Mobileye has.

A third point is is how do we
tackle the long tail problem.

Right now, when we're talking
about end to end models,

we're seeing the long tail
problem of edge cases.

And right now using this
vast amount of data that we

have, we can be exposed to many,

many different use cases and
train our data to extreme

scenarios.

And we can basically improve
our system dramatically.

It's so important to point that
out because I think if you if

you think about maybe
if you as a driver,

if you think about
your own experience,

if you could imagine sort
of mentally recording your

driving, like ninety five
percent of it's utterly boring.

A hundred percent. Maybe
it's ninety eight percent.

But there's two percent that's
totally terrifying or super

important or safety critical.

And that opportunity gives you
the ability to find those two

percent times millions
of trips Exactly.

Accelerate the study
of those corner cases.

So right now, we've also this is
a great point because right now,

in order to to tackle
this long tail problem,

we've also just recently announced
the CEO and the CTO of the company,

Professor Amnon Shashua and professor
Professor Shai Shalev-Shwartz,

just published a new article
about two new tools that

we have in order to find
those exact use case cases

within the this vast amount
of data that we have.

One tool is Meteor, one
one additional tool is Generio.

These are two different tools
that we're using to basically

using visual language models
to extract those unique

cases that are reproducible
and can really create a

significant change in the safety

cases of those long tail cases.

Wonderful.

And, you know, as of
course, as ADAS has evolved,

one of the things that
you're seeing is in certain

geographies, certainly in the US
and in in Europe with, you know,

NHTSA standards in US and the
the equivalent standard in

Europe.

You're seeing now certain
classes of ADAS features like

automatic emergency braking
notably and some others that

are becoming standard in
2027 and beyond, for example.

So how are you helping
to bring your capability,

which of course can be very
powerful at the high end down

to wider price points as that's becoming
more standardized across the line?

So I think this is a very good
point when we're looking at

systems like I've just talked
about today, the surround ADAS.

It's basically the idea is
to bring multiple components and

bring them into a
single compute unit.

The surround ADAS that I've
mentioned a moment ago is based

on EyeQ6 High.

This is the brain of Mobileye.

EyeQ6 High basically allows us
to bring different components

of driving, parking,
visualization, and integrate them.

So basically, if
you think about it,

an OEM would previously would
have to spend hundreds and of

hundreds of dollars on
different segregated

compute units that now can be
integrated into a single one

and deliver much
more with much less.

So with with integration,
the cost can come down.

You still have high end
solutions for some of the

higher autonomous
driving levels.

But for lower end cars that
just need the basic compliance

requirements, you can meet that
with different cost solutions.

So we can do that and we
can even upgrade low trim

vehicles to additional
additional higher levels of

autonomy with lower cost.

So just take as an
example Volkswagen.

This is a partner that
we've also announced a partnership

with a couple of years ago that is
taking the surround data center market.

It is not well known for
it to be a premium brand,

but it's taking still taking
this ADAS level two plus

into a lot of his
vehicle brands.

That's great. Yeah.

L2+, you know, as you said,

that's sort of below the line where
the driver is still responsible.

But one of the things that you
often see in L2+ is lane keeping.

It's sometimes adaptive cruise
control depending on the vehicle.

And once you've used a
lane keeping and adaptive cruise

control, it really takes the burden
out of, let's say, highway driving.

And, you know, in a
traffic jam, for example,

I've you know, in the
Bay Area where we live,

there's tons of traffic jams.

And I used to [think]
"oh, it's a traffic jam!"

Well, now, of course, I'm still
I still have to pay attention,

but the drudgery of a traffic
jam is almost eliminated

because the car does ninety
percent of the work and you're

looking for, oh, do
I have to take over?

It's really very, very pleasant.

I think if you've
experienced this function,

like going on a highway and
just you don't need to worry

about the driving itself.

Obviously, you need
to supervise it.

But you can relax your body
and just just ensure that the

ride is going
smooth and even even

potentially also
active lane changes.

Right?

That is also something which
is very useful and until you

experience that, you don't
really understand what it is.

But once you experience it,
it's a significant change.

Active lane change,

and my vehicle has that
and I love that feature.

And as a listener who
maybe who hasn't had that,

it might seem gimmicky, but
actually it's really not.

Because one of the things
that's a very frequent source

of accidents is lane changes and
hitting a car in your blind spot.

I know my vehicle when I do a a lane
change when I'm in lane keeping and and

adaptive cruise control, it will
wait until there's a safe spot.

In fact, a matter of fact,
has a cool animation.

It says, I've found a safe
spot. I'm going over to there.

But it has made sure that there's
no vehicle in the blind spot.

So it's actually more
safe, not less safe,

and it's not a gimmick.

It's actually a very powerful
feature that I love very much.

Think about it that you have
additional eyes and additional

sensors on top of the
two that you have.

Yeah.

And it basically helps you
to create a three hundred and

sixty degrees environmental
model around the vehicle and

helps you basically

to be more to have a more pleasant
driving, but much, much more safe.

Yeah.

And and it's so easy to think,
"oh, I'm a better driver."

But the reality is every time
I'm in adaptive cruise control

lane keeping, the car is much
safer than what I'm driving.

And I'm big enough
to admit that now,

that's why I use it
every chance I get.

This has been such an
enjoyable conversation.

Congratulations on all the
incredible success you've had

and on your recent keynote here.

We wish you the best of
success in the future,

and and thank you for bringing
your technology to bear in in

more and more
vehicles all the time.

Thanks for having
me, John. Thanks.

If you like what you're seeing,

please like and subscribe to
see more episodes like it both

here at AutoTech and our
other shows around the world.

We look forward to seeing
you in another episode of The

Garage very soon.