Latest / BREAK/FIX the Motorsports & Vehicle Enthusiast Variety Show / Tech Transforms ... Racing! (Crossover)

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Tech Transforms ... Racing! (Crossover) · BREAK/FIX the Motorsports & Vehicle Enthusiast Variety Show

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Grand Touring Motorsports started as a social group of car enthusiasts,
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but we've expanded into all sorts of motorsports disciplines, and we
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want to share our stories with you.
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Years of racing, wrenching, and motorsports experience brings
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together a top notch collection of knowledge and information
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through our podcast, Brake Fix.
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Hi, thanks for joining us on Tech Transforms.
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I'm Carolyn Ford and I'm here with Mark Snell.
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Hello, Mark.
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Good morning, Carolyn.
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Good morning.
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Today's a fun one because
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we have invited our friend, Eric Monterostelli, to join
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us on a crossover episode for this morning's Tech Transforms.
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Well said.
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And his podcast is Break Fix.
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So thanks for being here, Eric.
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And we're super excited to talk to you today.
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That's right, folks.
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And it's not uncommon to see IT branding plastered across the side of race
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cars in many motorsports disciplines.
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Names like AWS, CrowdStrike, and SailPoint immediately come to mind.
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But for application performance monitoring and artificial intelligence,
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The relationship between technology and racing goes far beyond
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stickers and sponsorship dollars.
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So as Carolyn pointed out, this is a crossover episode between
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break fix and tech transforms.
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And I'd like to personally thank Mark and Carolyn for having us on their show.
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to explore this idea.
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Yeah.
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And like what you just said there, Eric, it's a little bit geeked out for me.
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I'm not going to lie.
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So let's just get really basic for me and talk about cars and racing first and
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tell me how you got into cars and racing.
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Just the basics.
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In general,
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I'll keep it brief because I think that could be a whole episode into itself.
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So for your audience, Grand Touring Motorsports was founded
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in late 2013, officially 2014.
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And our mantra is to continue to spread motorsports enthusiasm.
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The idea is that people understand that there's multiple disciplines to racing
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and racing is a big part of our world.
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Whether you believe it or not, the chemistry, the science, the technology,
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the engineering that trickles down into your daily car is incredible.
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And it all stems from manufacturers using the racetrack.
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As their test center to think about it from that perspective here at GTM,
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we want to continue to spread that enthusiasm because if we don't racing
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will dry up and that advancement in technology ceases to exist.
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We've been around now almost eight years.
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We have our own podcast break fix.
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We talk about all sorts of different things, ranging from these super
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technical episodes, all the way up to advice episodes like this.
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What should I buy and things of that nature.
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But personally, I got into cars by way of genetics, grandfather to my dad and
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now to me, and hopefully I get to pass it on to my daughters along the way.
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And so we've been tied into the racing community for a very long time.
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And myself included, I have been a high performance driving instructor now for.
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And then before that auto crossing before that it was a cart racer nationally,
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you know, things of that nature.
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So it's unfortunately in the blood, but what I find most interesting about it is
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that there's a huge intersection between the automotive world and the it world.
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And so I also followed in my father's footsteps, who was a mainframe programmer.
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So I had the it side.
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I also had the racing side, but.
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As a younger racer, I was also involved in things like timing and scoring.
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I went to work for British Aerospace where I tried desperately to get in
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on their helicopter division because I was actually working on engine
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management systems at another company.
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So again, data, technology, IT, racing, it's all very intertwined.
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But as I grew more into Pro am racing into time trials and other disciplines.
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I started to realize how valuable the data that we collect, not just from
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the cars, from the track and from the motors and all this stuff related to
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what I was doing in the sim and threat intelligence world, and also in the
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APM and artificial intelligence space.
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So there's this again, huge crossover there.
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And I want to be able to explore that with you guys.
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So Eric, it seems to me that in the sixties and seventies.
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The things that teams would do to increase their edge was around the mechanics
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and the infrastructure of the cars.
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It seems like over the last 20 years, there has been that shift to
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IT in leveraging technology to give racers an edge on the racetrack.
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So you're 100 percent right, Mark.
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And I'll use an example.
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Colin Chapman, the founder of Lotus, is infamously known for both pushing
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the boundary and cheating like crazy.
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Because what he did is he found loopholes in the rules where he could take
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experimental technology and push the boundaries of racing and engineering.
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So how do you control that?
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More rules get put into place.
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You try to squelch that you penalize people, all these kinds of things.
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But really what he was doing is he was moving everything forward.
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So back then in the sixties and seventies, and even still partially in the
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eighties, where you didn't have big data available, it was all trial and error.
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You know, let's use formula one as an example.
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You'll see cars back in the seventies with six wheels.
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You're like, why is that a good idea?
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Because somebody needed to try chaparral was famous for mounting fans
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on the bottom of the cars to try to absorb them into the pavement, right.
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Is it to create ground effects instead of doing studies and aerodynamics, right?
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Because the cars
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wouldn't fly off the racetrack.
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Exactly.
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So there's all this trickery and all this, this crazy stuff that they would
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do, but we've shifted away from that.
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We've shifted away to raw data to say, what is that tire doing in that corner
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under load at this pound of pressure?
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But if we change it.
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By half a pound.
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What difference does that make?
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How much more G can we pull in that corner?
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Right?
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We've gotten to the deeper layers of the science and the engineering to make
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these cars go faster, and that's why if you look at a Formula one car of today
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versus of 1960, it's completely different.
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So to bridge the physical to the digital cars have sensors, these microchips
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all embedded throughout the structure of the car to feed that data back.
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They do like even on the tires.
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Oh yeah.
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No.
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Yeah.
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So get this.
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So starting in about the 1990s, in the advent of something known as OBD 1.
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So now we all run OBD 2 or CAN bus.
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There's actually a port in the car that you can tie a laptop into
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and pull all sorts of information from all over the vehicle.
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More and more manufacturers are bringing Putting that up on the heads
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up displays and on the dashboards these days, which is fantastic.
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It's right there at your fingertips, but starting in the nineties, they
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needed a way to interface with the engine because they were putting
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in more and more sensors, thanks to electronic and programmable
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fuel injection engine management.
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It's also known as, so there's a sensor for water.
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There's a sensor for oil.
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There's a sensor for pressure.
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There's a sense for the rotational speed of the motor at the crank and
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at the cam and all this crazy stuff.
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It's very nit annoyed information.
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And it's all to keep.
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The engine running at maximum efficiency under multiple conditions.
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So just because you're tooling down the highway, that computer
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on board is making corrections in microseconds, if not faster.
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Wait, it's correcting itself.
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Yes.
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It is a self correcting computer.
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So the electronics we have are just a much more simplified version of that.
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Not correct.
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All cars, even your street cars.
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Have these self healing, self correcting computers.
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And the way it works is a lot of it is for emissions.
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A lot of it is for efficiency.
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A lot of it is for power.
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So for instance, in the old days, I'll draw a parallel to maybe some
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of our listeners will understand a carburetor is very static.
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You jetted it a certain way.
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Ram terribly when it was cold and the barometric pressure was wrong.
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And then you have to rejet it and tweak it and get under the hood
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to get it to purge just perfectly.
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Now with electronic fuel injection, it takes that into account.
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It takes into atmospheric pressure, air temperature, elevation, all this
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kind of stuff, and it makes corrections based on where you are, where the
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pedal is at any given time, in a sense,
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talking about AI,
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we're talking about mechanical, my
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car.
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Yes.
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Whoa.
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Okay.
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That's pretty cool, huh?
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Well, yeah, like I'm in my mind, I'm drawing all these parallels to what you
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do for work with the government and how these race cars and cars in general work.
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That's right.
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And so telemetry used in a race car finds itself on the back of
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a Humvee, finds itself in a tank, finds itself on an airplane.
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So weapon systems, navigation systems, all that can be tied back in some ways.
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To the automotive world, including GPS work because we do use GPS telemetry
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as well to calculate speed and distance and all sorts of additional telemetry.
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When objects are in motion,
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does the government use the data gathered on the race track?
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So I'll put it this way, I've worked on some projects that were
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tied into engine management on.
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Tanks and Humvees.
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So it is possible.
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I don't know that I can expand too much further on that, but the data
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collected there is very similar to the data that's collected in your
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passenger car as well as a race car.
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That's cool.
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I'd imagine this, it's probably more finely tuned for aircraft than for
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you think
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land vehicles.
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I would guess.
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I mean, I don't know.
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I'm, I'm I mean, I'm just thinking
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in the airplane.
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Yes, because you have to take into consideration yaw and pitch and
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elevation and all the atmospheric conditions, but that's also true
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in other disciplines of motorsport.
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So if I'm talking about off roading the terrain and the pitch and yaw of the
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vehicle is extremely important when I'm looking at using sensors to show the
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articulation of my suspension, right?
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How much suspension travel do I have?
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How much rotation per axle am I using?
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Like, do I need to transfer power from the front wheels?
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to the rear wheels.
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You see those commercials all the time from Audi and Subaru
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about how it does all this stuff.
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A lot of that is computer controlled.
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It's very much that mechanical AI making those decisions based
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on the sensors and the telemetry that it's collecting in real time.
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I imagine in the performance racing industry, when you're
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going at speeds at 200.
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Miles per hour or greater and decisions need to be made in milliseconds.
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It ups the ante a lot greater.
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That is
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very true.
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I mean, we're not at mock two or whatever, like a fighter gym,
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and you're absolutely correct.
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And in both cases, there's still that common denominator of what has we
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say in our world, the meat behind the steering wheel, there's still an organic.
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Computer making those minute by minute or second by second decisions with the,
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let's say, let's call it augmented reality of that AI in the vehicle, controlling
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those multitudes of different systems that are helping that person, that pilot,
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that driver be able to do what they do.
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You talk about a lot of tech companies plaster their names
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on the sides of cars, right?
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I'm not going to lie.
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I thought it was a testosterone thing, but you said something.
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You said there's this intersection between the racing and the tech world.
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Is it just an advertising ploy or is there more to it?
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Now, so if you ever speak to any race engineers, or if you happen to
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go to say IMSA race, where you can actually get really, really close to
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the pit boxes, like something like the Rolex 24 hours or the Salem six
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hours at Watkins Glen or something.
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That if you can get your eyes inside the booth, you'll see that
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it looks like a command center.
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You'd think you were at NASA.
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It's all screens, all data coming in real time over wireless into the booth.
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Race engineers are analyzing the data and they're also leveraging platforms like
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AWS and Azure to run their applications.
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So they need to be able to get this stuff immediately because what they can do
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from those, let's say control booths is also send corrections back to the car.
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Now, some drivers, let's say formula one, if you've ever looked
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at the steering wheel, they got.
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and knobs and they can make changes and they're talking back
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and forth with the pit constantly.
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Hey, the car's doing this and they're like, all right, give it a little bit of
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tweak on this dial and it'll make a change to the suspension as they're driving.
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But there's also other disciplines of racing, especially endurance
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racing, where they're watching the cars for longer periods of time.
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And they need to be able to manage them over the course of that race.
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They can send over the air changes to the vehicles.
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Are they correlating the data?
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Like in this command center, do they have a big seam that they're pulling
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everything in and cross tabbing and data analysis, or do you have specialists?
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Like one's looking at the tires and one's looking at the heat.
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I don't know what you
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have.
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You have both, you actually have both.
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And then you also have on track telemetry.
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So you've got folks that are responsible for certain parts of the car.
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Let's say the tires that are responsible for fueling.
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I mean, you can get really deep on many different parts Portions
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of that stack, let's call it the racing stack there that goes on on
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race day on the other side of it.
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It's also the telemetry from the track.
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There are people that are just watching the weather that are studying the
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weather and how the weather conditions, slight changes in temperature.
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The air are going to change the way the motor performs, like losing
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upwards of let's say 20 horsepower because there's one degree of weather
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change or rain is on its way, right?
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We've got to make changes.
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Strategic decisions on what tires we're going to use.
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How long are we going to stay out?
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We just passed Lamont's a weekend or two ago.
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And that track is famous for being rain on one side and being completely
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dry on the other because the full lap is almost nine miles long.
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So they have the one in
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Ford versus Ferrari.
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This is all I know.
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Absolutely.
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So there's a lot to take in.
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There's a lot of data.
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There's a lot of different, what I call sources of authority that
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are providing data, just like there would be in an IT ecosystem, right?
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You've got firewalls, you've got routers, you've got IPSs, active directory,
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you've got storage systems that are providing you with tons of metrics.
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And you have to have a way to correlate all that together and make sense of it.
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And if there's a problem, and if you happen to listen to Lamont's two
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weekends ago, they could pinpoint an issue on the car before even the driver
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could tell it was about to happen.
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And they're always talking back and forth.
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They're like, Hey, this is about to go down.
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You should bring the car.
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And we want to look at this particular thing.
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A sensor is telling us that there's an issue.
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The same is true of it.
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If you can forecast that, let's say, Hey, We've got an IOP degradation here
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on this particular, you know, SAN server.
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And it's going to cause this ripple effect.
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We're going to have to V motion.
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We're gonna have to do this.
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That's going to cause an outage.
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Now we're going to have looking at real user monitoring.
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We're going to have an issue where we're going to have people that are
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down are going to be stuck in limbo.
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The same is true on the racetrack.
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So there's this interesting intersection between these two worlds where racing
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is this more mechanical application performance monitoring versus what we're
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used to on the IT side of the house.
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View a race car as an application.
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GPU.
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The track as an ecosystem, very similar to your data center or to
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your mission application that you might be working on right now.
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I think I've melted Carolyn's brain.
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Maybe a little bit, just a little bit.
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I'm
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interested to see how you can maybe talk a little bit more
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about how you apply some of those.
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Disciplines from the performance racing side to I.
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T.
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That we see or that we're talking to government customers about
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there's always the physical side of racing, the car machine, the boat,
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the airplane, whatever it might be.
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But there's also the driver side.
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How do you determine a talented driver from another driver?
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There's also another sub component of data there.
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Is that like the end user?
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Absolutely.
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Lewis Hamilton, eight time world champion, formula one driver.
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He was good.
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He was naturally talented.
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If they left him where he was, you know, maintaining the status quo, he
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would have only gotten so much better.
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So then there's the telemetry of the driver.
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It coincides with the telemetry of the car, but it has to do with,
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you know, their physical abilities.
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It has to do with their risk mitigation.
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It has to do with how consistent they are on track.
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That's key on track is consistent lap times being not a second apart.
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Second is a light year.
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You need to be hundreds, if not tens of thousands of a second.
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Lap per lap.
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You need to be that precise.
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Racing is a precise sport.
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So that being said, there's other forms of telemetry that we use to
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better the drivers and help teach them and help educate them and
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get them away from the status quo.
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So I relate that back to continuous monitoring, CICD pipeline, all these kinds
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of things where not only is my driver, the end user, but he's also my mission app.
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And how do I make my mission app better?
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How do I make it more efficient?
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How are you monitoring the driver app?
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Is the driver hooked up to sensors?
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Sometimes?
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Yes.
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Actually in the longer endurance races, they do have health and status monitors,
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you know, because they are in the car for long periods of time in the race.
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Like Lamont, there's a minimum of three drivers per team.
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Sometimes there's four depending and they'll do double stints.
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They're out there for six hours or they're out there for three hours at a time.
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That's a lot to take in, right?
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You have to think health, hydration, nutrition, all that stuff.
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I mean, there's doctors on staff.
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So let's, let's take that out of the equation, but also how do I make that
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guy be consistent for three hours in the middle of the night when he's
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only running on two hours of sleep?
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I mean, obviously I could probably inject and periodically adrenaline.
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It's like the, think
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of the endurance of like doing an ironman, but when you're going
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200 miles per hour, 220 down a straightaway, you have to be alert.
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So it does make a difference.
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I think about the endurance where you sit in a car for eight hours.
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So to go back to your, your question and to your point, there's one system, even
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in my more grassroots world where I'm teaching folks that, you know, might be
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from the government or they might be from industry or they might be from wherever
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that, you know, they got this bucket list.
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Maybe they bought a Porsche, you know, they retire a Corvette and.
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They want to go out and experience the track.
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Well, how do I make them better?
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I can teach them how to be safe.
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I can teach them how to be fast, but if I want them to be perfect and
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be consistent, I have to use data.
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It's in my toolbox of things.
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There's been a go to product for a very long time known as the aim.
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It's an Italian product.
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Uh, they have a whole series, the aim solo and the smarty system and the
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MXs and the M and all these things.
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different pieces.
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And what it does is you attach it to the car, very simply.
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It's not something, you know, I have to tie in and integrate
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like an octopus into the vehicle.
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I can throw it up on the dashboard, leveraging internal gyros.
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It's in leveraging GPS to determine land speed, rate G forces and all
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this kind of stuff and show me laps.
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I can then bring all that telemetry in.
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Put it up on a screen and show a driver, this is the turn
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you're suffering the most on.
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Feels good, but it's, we're not going fast enough.
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This is where we need to fix your braking zone.
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You're off by X amount, you know, lap after lap.
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We can get in a little deeper.
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We can get a little closer.
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The car is telling us this, even though we're not integrated into the car,
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we can still make those connections.
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Now there's some more advanced tools.
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There's a system by Garmin now, which, you know, they're famous for standalone GPS
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systems for a multitude of applications.
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They just developed one for racing now, and it gives you immediate feedback.
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It actually uses AI to say that was good.
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That was bad.
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Do this, make these changes.
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It actually has the tracks preloaded in them with some baseline
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information to give you that feedback.
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And so a driver can kind of see that out of the corner of their eye.
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Or go back and review, I actually happened to be friends with Andrew
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rains, who's the owner of apex pro, and they actually use ML in their platform
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that can be attached to the car.
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And it learns on a turn by turn, lap by lap basis and gives the driver
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immediate feedback to say, you can go deeper into this corner, you can
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push harder and all this, and it's learning on the fly, it also has ways.
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To tie into that mechanical AI into the motor, as do the other
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two products I mentioned to pull engine data to pull sensor data.
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And that's what I'm saying.
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We can bridge the mechanical with the meat behind the steering wheel and
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make you a better driver using data.
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Everything you're talking about, it gets me really excited.
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So what you're doing in your day job for the government, basically.
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Same thing, you're monitoring what's going on or enabling that monitoring, right?
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With the tools that you use with the AI tools, with the APM tools to detect
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before the meat behind the computer,
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even knows there's something wrong.
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Those tools are going to detect and like send alerts.
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Exactly.
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When I talk about APM and artificial intelligence, I actually use a lot of
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Cross references into the racing world.
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For example, data logging, we use logs all the time in this world as well, right?
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It's one of the major sources of authority outside of networking
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data and host data, et cetera.
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So we do data logging as well, right?
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We're going to pull in all that log data from the system.
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We're going to look at that at the same time.
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It helps us make a decision, find out what that root causes to whatever the
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problem is, mechanical or physical.
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We also have what we call flight recorders.
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You see that in airplanes all the time.
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We APM space with session replay.
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I can go back and reconstruct.
19:58
I can tell you what gear they were in, what speed they were at, when they were
20:01
breaking, when they were accelerating, how much G they were pulling in a turn,
20:04
all this stuff, all through that data by pulling all that sensor data in.
20:09
So when I talk about APM, I use three terms.
20:12
I like rules of three applies to a lot of things in life.
20:15
I use the terms visibility.
20:17
Telemetry and fidelity, visibility, getting your eyes up, having that
20:22
situational awareness, understanding what's going on in your ecosystem, getting
20:25
your arms around all those pieces, all those tools, all those components, those
20:29
sensors, telemetry is that raw data that's coming in rather be the logs, whether
20:34
it be the network information, engine data, you know, track data, weather data,
20:37
whatever it is you're bringing in, it's all disparate, it has to be correlated.
20:40
Like you said earlier.
20:41
And then fidelity, fidelity is the granularity.
20:44
The usefulness of that information.
20:46
And I often draw a parallel on one of my slides.
20:48
I talk about a typical GPS that you'd use in your car versus bracing telemetry.
20:54
Typical GPS only needs three satellites to quote unquote triangulate on you,
20:59
but to do an object at high speed.
21:00
Speed, I need a minimum of eight, usually it's 12, by the way, that's the
21:04
fidelity that those eight satellites bring in gives me more granularity.
21:08
I can go from your exit is a hundred meters away to you're
21:13
traveling at 200 miles an hour.
21:15
And at this exact millimeter, you turn the wheel and this is where you loaded
21:20
up, you know, the front right tire.
21:21
So that fidelity is important because as I've always said, a database is only as
21:26
good as the questions that it can answer.
21:29
So what we're trying to do on both sides of the house, both APM and the racing
21:32
world is make data driven decisions.
21:35
That's the important part in all of this.
21:37
How do we make things better?
21:39
Well, we can't do it like in the sixties and seventies by trial and error.
21:42
We got to do it with data.
21:43
It's the only way.
21:44
You know, you could take this conversation that Eric is applying to raising,
21:49
you could just drop it right into a conversation that you're having with a
21:53
government application owner or digital experience officer, what have you, because
21:59
you have the full stack observability that you want to provide to the customer.
22:04
You have the end user experience, which is how they're experiencing
22:08
the service or the application that you're providing to them.
22:12
And then you have the AI ops, the CICD pieces of that help you find
22:18
problems before they become a problem so that you can avert the issue and
22:22
eliminate outages quicker, et cetera.
22:25
So Carolyn, at the top of our conversation, you asked me,
22:27
how did I get into racing?
22:29
I have to go back because it's, it's a bit of a chicken and egg.
22:33
So is it the allure and the.
22:34
Sound of the motors and let's say the appeal of cars in general.
22:38
Or was it the it side that drew me in and let you kind of think about that because
22:42
they both do go hand in hand and they are both applicable in each other's worlds.
22:46
Well, and this analogy, like listening to you talk, Eric, just makes me think about
22:51
how the technology in, in our lives, but in the lives of our government employees,
22:57
it makes, them better at their jobs.
22:59
It improves the efficacy of whatever technology they're using, whether
23:04
they're trying to make a tank work, whether they're trying to order a bar
23:08
of soap for the ship that they're on.
23:11
All of this monitoring is so important just to improve our lives.
23:16
Absolutely.
23:17
And one of the things that comes out of that is this concept of It started
23:20
as BYOD, bring your own device, and now we have IOT, the Internet of Things.
23:24
I hate the fact that people lump cars into that category of an appliance, where it's
23:30
like, yeah, I can IP enable my toaster, and it'll tell me how hot the toaster is
23:34
running, and how long it toasted the bread for, and it's still just toast bread.
23:38
But when you boil back and you peel back the onion of a vehicle, whether it's a
23:42
tank, whether it's an airplane, a ship, a car, any type of vehicle, truck, whatever
23:45
it might be, it's way more complicated than people realize that ecosystem is
23:51
tightly packed into a small space, but replicates these larger data centers
23:56
that we deal with day in and day out.
23:57
So it's kind of fun to peel that back and also important.
24:01
To engage younger folks so they understand the STEM that's also involved
24:05
in the motorsport and automotive world.
24:07
Like I mentioned earlier, chemistry, physics, engineering,
24:10
aerodynamics, thermodynamics.
24:12
I mean, the list goes on and on of the places that you can go niche.
24:17
And go deep and just geek out on in the automotive world.
24:20
But that also applies to what we do day in and day out supporting our government
24:24
customers, talking about APM, making these mission apps better and dealing
24:28
with the individual missions themselves.
24:30
I mean, on a regular basis, I talk to folks in the Navy about how we're going
24:34
to implement APM on a ship versus how they're using it at the PX, right?
24:39
They're dynamically different, but applicable in the same way.
24:43
Exactly.
24:43
And then you've got the whole dynamic of the meat behind the
24:46
steering wheel or the computer.
24:48
I don't know how I like being referred to as meat, but I'm going to go
24:52
well on Star Trek.
24:53
They would have called you a bag of mostly water.
24:55
So
24:59
that's funny.
25:00
This has been really fun.
25:02
We're to the part of the hour, our tech talk questions.
25:05
So just some quick,
25:07
well, good.
25:08
Cause I've got, I've got some pit stop questions for you
25:10
guys, so we'll go tit for tat.
25:12
All righty then.
25:13
Well, shall we do tech talk first?
25:16
Sure thing.
25:17
All right, Eric, what do you think the next big leap in tech will
25:20
be or what do you want it to be?
25:22
I want some of the technology that we're used to in the data center world
25:28
to find its way into the Soho world and Soho being small office, home office,
25:32
because we don't practice what we preach.
25:35
Where we want to make things better.
25:37
We want to protect ourselves.
25:38
And then suddenly you hear about, Oh, my data got compromised.
25:40
I got to buy this thing and protect my ID and all these kinds.
25:43
And it feels a little gimmicky.
25:45
I've been fed the whole antivirus thing for a long time.
25:47
I'd rather be able to present a box that provides a defense in depth strategy to
25:52
keep us all safe at home, especially now.
25:55
In the last two years where more people are working from home and we've had to
25:59
bring the office home with us, we don't have the same luxuries all the time that
26:02
we would in the, in the corporate space, we're still attached to those data centers
26:06
remotely through the cloud and people are monitoring this and whatnot, but it would
26:10
be nice to have that security blanket, that sense of protection against the
26:13
outside world by bringing some of that into the house and making it turn key.
26:17
I think that's the most important part about a lot of things in our space is
26:21
making them easier for everybody to use.
26:24
Yeah, it's got to be plug and play or I'm not using it.
26:27
I want to ask you back to racing.
26:29
Sure.
26:30
And this may be happening.
26:32
Do you see racing moving from combustible engines to electric?
26:36
So we call that the EV revolution.
26:38
We ask people that question a lot.
26:40
And so there is already a discipline in motorsport known as Formula
26:44
E that is basically Formula One cars with EV power plants.
26:48
Watching them evolve in the last couple of years has been fascinating because
26:52
that has been a jump in technology.
26:54
That's going to find its way into passenger cars.
26:56
They initially started out having teams of drivers representing countries.
27:01
It was kind of like the Olympics, right?
27:02
Or it's, or like international race of champions type of deal.
27:04
So you had team Britain, team Italy, team Germany, and they've all got their
27:07
cars and their liveries and everything.
27:09
And what they would do is when they would run out of power,
27:11
they would jump in another car.
27:13
The problem with that model is it's not sustainable because each car,
27:18
although created quote unquote equally doesn't perform equally much like
27:23
applications put into an Azure environment versus an AWS environment, right?
27:28
The back ends are slightly different and that kind of thing.
27:30
So what they did is they went through trial and error and
27:32
they looked at the data as well.
27:34
And they said, you know what?
27:35
We're going to keep the car the same, keep the drivers the same, and we'll
27:38
make the battery packs switchable and get it down to the point where we
27:42
can swap them in the same amount of time as it would take to swap tires
27:46
in a pit stop or do a fuel stop.
27:48
So that's incredible.
27:49
And that's been talked about in the EV world for passenger cars is why do
27:53
I have to drive to a sheets and plug in and wait 20 minutes to charge?
27:57
Why can't I go up to like a battery bank and switch one out and keep driving?
28:01
I would
28:01
buy an e vehicle today if I could do that.
28:04
So it's coming.
28:05
Would you, how would you feel about that though, Eric, if we got rid of
28:08
like the combustion engine, is it
28:12
internal combustion engine or ice engine?
28:15
So the biggest pushback I've heard from petrol heads is that what we will
28:19
lose is the sensory part of racing.
28:22
One of the big things is the auditory side of this, which is the sound of a motor.
28:26
If you've ever gone to an IMSA race, like Rolex or Le Mans, which
28:30
like we talked about just happened.
28:32
You can identify the different brands before you even see them.
28:35
You know the sound of a Corvette over a Ferrari over a Porsche.
28:38
They're very distinct because they're very differently built.
28:41
When you get an EV, what do you hear?
28:43
You get this high pitch wine from the transmission and otherwise it's air noise.
28:48
So that's the biggest drawback that people have presented.
28:51
Now, what I'm really curious to see is I believe it's next year.
28:54
The NHRA came out this year.
28:56
This is the drag race guys.
28:57
This is the folks that go in a straight line really, really fast.
29:00
They have put together an EV class.
29:02
And so there's a little bit of want one people going, I don't
29:05
know how I feel about this.
29:06
I'm excited to see it because a, I want to see what kind of data they're going to put
29:09
down, but B I want to see how it changes the dynamic of that discipline of racing.
29:14
I mean,
29:14
speed is speed,
29:15
right?
29:16
That's right.
29:16
That's right.
29:17
But if the fans are still tuning in and they're still going to races
29:20
with the Evie cars there, and they haven't totally turned their backs
29:23
and gotten another beer and a hot dog, then that's saying something.
29:26
And I think the proof will be live when we see that happen.
29:29
All right.
29:29
We've gone off script for the tech talk, but I do want to ask one more
29:33
tech talk question, but, and then we'll let you do your pit stop.
29:35
What's inspiring you in tech, which can cross over to cars.
29:40
I have now learned you've schooled me sufficiently.
29:43
What are you reading or watching or listening to?
29:47
That's inspiring you.
29:48
That's a twofold question because with my background, and I know we
29:53
didn't dive into that too deeply.
29:54
I've always been tied into cybersecurity.
29:58
The big thing for me has always been SIM and threat intelligence.
30:00
And now obviously APM, which they all go hand in hand.
30:03
They're very close cousins.
30:05
So I want to see where we go with that.
30:07
I'm keeping tabs on former companies and things like that, that I work for.
30:11
And some of the developments that they're doing there, especially
30:13
with how they're handling.
30:15
Zero day.
30:16
And there's a lot of talk about zero trust, how we're handling IOCs that
30:19
are popping up all over the place.
30:20
So I'm really kind of geeking out on that.
30:22
And thanks.
30:22
But where
30:23
do you geek out?
30:23
Like, what do you read?
30:25
What are you following?
30:26
Do they just need to follow you on LinkedIn and you'll start posting for us?
30:29
Yes,
30:29
that would be probably the easiest.
30:31
All right, there we go.
30:32
Yeah, I spend more time reading automotive journals than I do tech stuff.
30:35
I'll be honest about that.
30:37
On the other side of that, there's the whole, you know, we were all stuck
30:40
at home, binging Netflix and Hulu.
30:42
And, you know, I stumbled across something that I found to be inspiring in a
30:46
different way as a retrospective into the IT world, kind of looking back on where
30:51
we came from and how we got to today, and it does tie into sports cars just a
30:55
little bit and one of the main characters.
30:57
So if you haven't watched.
30:59
AMCs halt and catch fire, which is a reference to the old days when you would
31:03
put a computer into an infinite loop mode.
31:05
It tells the story of companies like McAfee, like Symantec, like Compaq,
31:10
like AOL, Yahoo, and et cetera.
31:12
And it's done in this dramatization kind of similar to Mad Men, if you appreciated
31:16
that, but without some of the odd.
31:18
The undertones that Mad Men has this started in the late seventies, early
31:21
eighties, and it goes for four seasons and it's absolutely incredible.
31:25
It's really fun to watch and it's really fun to see where these
31:27
companies came from the birth of cybersecurity and things like that.
31:30
So I highly recommend that if you want to geek out on something, maybe still in the
31:34
realm, but you don't have to put so much attention into and have a lot of fun with,
31:38
and the acting is absolutely phenomenal.
31:40
Perfect.
31:41
See, that's right up my alley.
31:42
I can watch it.
31:46
All right.
31:46
All right.
31:47
Flip the script here.
31:48
Ask you guys a couple of our more common pit stop questions.
31:52
Sexiest car of all time.
31:54
Mark.
31:55
Probably the stingray Corvette in the late 60s.
32:01
The
32:01
convertible.
32:02
Good choice.
32:03
Carolyn, convertible Ford
32:04
Mustang.
32:05
Oh, what year though?
32:05
There's so many different variations of the Mustang.
32:07
Yeah, so I like the earlier ones, not the 70 version, which
32:11
was my first car, by the way.
32:13
I'm
32:14
sorry for you.
32:15
A little bit earlier.
32:16
Hey, it was a Ford Mustang.
32:17
I was happy enough.
32:18
60,
32:19
64, 65,
32:20
66.
32:21
Whatever it takes.
32:22
The Iacocca era of Mustangs.
32:24
Yes.
32:24
Those are the, those are the good ones.
32:25
None of that Pinto based stuff.
32:27
So, ugliest car of all time.
32:30
Carolyn.
32:31
Oh, there's so many.
32:33
There's
32:33
so many.
32:34
I can't say.
32:35
I don't know.
32:37
Probably the Pinto.
32:38
Well, the Pinto is pretty ugly.
32:39
Pretty ugly.
32:39
I
32:40
mean the Gremlin, the Gremlin's pretty ugly too.
32:42
Oh
32:43
yeah, pretty ugly.
32:43
Maybe the thing.
32:45
Oh, the Volkswagen thing.
32:46
Yeah.
32:46
The also known as the Kübelwagen, which was a German military jeep.
32:51
I could nerd out on that for a while too, but no, that those are all good answers.
32:54
Very good.
32:55
So one of our favorites is what we call the three car garage and
32:59
or million dollar person question.
33:00
So if you had a million bucks or more, basically unlimited funds to fill a three
33:04
car garage, what would you put in it?
33:06
And maybe you guys have a combined garage if you can't come up
33:08
with three cars of your own.
33:10
So we'll go with Mark.
33:11
Well, I have an AMG now, so I like that.
33:14
I would keep that.
33:15
Probably more of a utility kind of SUV car for the more practical things in life.
33:22
And then I've always What's your crazy
33:27
poster on the wall kind of car?
33:28
You know, like I want to have
33:29
a Lamborghini.
33:31
Yeah, probably like a Porsche 911 Carrera or something like that.
33:37
Nice.
33:38
Very nice.
33:38
Yeah.
33:39
All right.
33:39
So my dad rebuilt from the floorboards up a Ford 46.
33:47
Oh, nice.
33:47
That would be in my garage.
33:49
I would have a truck because I always need one and I would have an electric
33:53
vehicle for getting around town.
33:55
How boring is that?
33:57
What, any, any specific Evie that has your attention right now?
34:00
Are you a Tesla girl?
34:01
Are you a Porsche fan?
34:03
I mean, I don't really care as long as it's Like spending
34:07
a hundred grand for a car.
34:09
Sorry, guys.
34:09
Like, that's just not, no.
34:13
Oh, big toys for big boys.
34:15
Like
34:16
I need it to be in my price range and I need it to be reliable.
34:22
Well, Tesla's apparently coming out with a very affordable car soon, I think.
34:27
Yeah.
34:27
I mean, it's fine.
34:29
Didn't they say that about
34:30
the model three though?
34:31
Yeah, exactly.
34:32
Also the windshield won't break.
34:34
That was in the truck.
34:35
And we all watched
34:36
the cyber
34:37
truck.
34:39
My dog needs to be able to get into all of them.
34:41
So it's got to be big enough for that.
34:42
Makes
34:43
sense.
34:44
If you have extra time and you want to learn about all the upcoming
34:46
EVs and things that are out there, tune into our monthly drive through
34:50
episode where my sister happens to be our resident, let's call her EV
34:53
expert, also executive producer.
34:55
And she covers a lot of what's on the horizon, not just Tesla's.
34:58
There's some interesting stuff hitting our shores from overseas.
35:00
So if you want to nerd out on EVs, check that out.
35:03
But with that being said, Mark and Carolyn, I cannot thank you enough
35:06
for having me on Tech Transforms for this crossover episode.
35:09
Yes.
35:10
And so folks, for more information on Tech Transforms, if you're listening
35:15
to this on the BreakFix podcast server, be sure to follow them on Twitter and
35:19
LinkedIn at Tech Transforms and tune into more Tech Transforms podcast
35:23
episodes, where they talk to you.
35:25
some of the most prominent influencers shaping the information technology
35:29
landscape to understand how they are leveraging technology to solve
35:33
complex challenges, while also meeting the needs of today's modern world.
35:38
Thank you, Eric.
35:40
Is that right?
35:42
Yes.
35:43
And tune in listeners to his break fix podcast for more,
35:49
very entertaining conversations.
35:51
And you can geek out on cars Thank you listeners for joining us today.
35:56
Please go out, smash that like button, follow us on LinkedIn and Twitter,
36:01
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36:03
Thank you guys.
36:09
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36:34
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36:37
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