Latest / BREAK/FIX the Motorsports & Vehicle Enthusiast Variety Show / The Software Defined Car: The Death of Freedom

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The Software Defined Car: The Death of Freedom · BREAK/FIX the Motorsports & Vehicle Enthusiast Variety Show

• 0:00
  John Summers is the motoring historian.
• 0:02
  He was a company car thrashing technology sales rep that turned into a fairly inept
• 0:07
  sports bike rider hailing from California.
• 0:10
  He collects cars and bikes built with plenty of cheap and
• 0:12
  fast and not much reliable.
• 0:15
  On his show, he gets together with various co-hosts to talk about new
• 0:18
  and old cars driving motorbikes, motor racing, and motoring travel.
• 0:38
  Good day.
• 0:38
  Good morning, good afternoon.
• 0:40
  It is John Summers, the motoring historian.
• 0:43
  This episode ostensibly is gonna tie together two different
• 0:48
  presentations that I went to coincidentally, you know, back to back.
• 0:52
  I. And I thought, you know, just because they fell, you know, one on a
• 0:58
  Wednesday night, the other on a Thursday.
• 1:00
  It was, it was literally, it was just a couple of weeks ago and,
• 1:04
  and I thought it seemed worthwhile.
• 1:06
  So, you know, it seemed natural to compare them together since,
• 1:09
  especially since both of them look at the future of Autumn Mobility.
• 1:14
  I mean, guys, it's over, right?
• 1:16
  Let's make no mistake.
• 1:18
  It is over.
• 1:21
  The first presentation was by McKinsey and it was about the software to find vehicle.
• 1:28
  Fundamentally, this is no longer the car as a thing of independence.
• 1:35
  Now it's like your phone, it's the edge of the cloud.
• 1:39
  It's a connected device.
• 2:03
  It is only now when I say it that I realize how much I absolutely
• 2:07
  just loath the thought of that.
• 2:30
  The second presentation was, uh.
• 2:34
  One of the ones at the Nordic House organized by the Society of Automotive
• 2:38
  Engineers and, uh, SVE Beaker.
• 2:40
  Thank you again, sve for, for inviting me to these events.
• 2:44
  And this one was, uh, you know, again, one of these companies who are in the valley
• 2:50
  because there is a massive automotive presence in the valley and they're in
• 3:00
  the valley trying to understand the zeitgeist, trying to meet people, trying
• 3:05
  to understand and be part of the buzz, which is auto mobility in Silicon Valley.
• 3:34
  So to be clear then these two presentations are thinking about
• 3:40
  the future of auto mobility in in two different ways.
• 3:45
  McKinsey are thinking about the future of auto mobility in a sort of strategic
• 3:51
  kind of way, and in a way, which is where they're trying to look further and
• 3:57
  with greater perception than other guys.
• 4:01
  So, you know, they've rocked up.
• 4:03
  We've got the telescope, let's look through the telescope.
• 4:06
  What can we see through the telescope?
• 4:08
  It was applicable that that one came first.
• 4:10
  Really?
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  And, and you know that it's McKinsey who are this like outside
• 4:14
  consultancy firm who, uh, just getting fucking everywhere recently.
• 4:19
  If, and, and, you know, booty G the former transport secretary
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  there, he's a, a, a McKinsey guy.
• 4:26
  You know, my, my wife works for one of the magnificent seven corporates
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  and, you know, her life is full of McKinsey people and McKinsey Method
• 4:35
  and you know, at McKinsey we do it this way, kind kind of thing.
• 4:39
  You know, these guys.
• 4:41
  My students at Stanford, you know, they aspire to be a, a, these, uh, uh, uh,
• 4:47
  uh, the top consultancy firms and, and, uh, you know, in my day it was like
• 4:52
  Deloitte and Touch and Arthur Anderson.
• 4:55
  Now it's, it's Bain and, and especially McKinsey.
• 4:59
  So if anyone's able to tell you what the future's gonna look like,
• 5:03
  it should be these guys, right?
• 5:04
  Because these guys, uh, making millions outta the fact that they're being hired.
• 5:09
  By the car companies to tell them what the future should look like.
• 5:12
  So these guys are literally, literally, you know, these guys are
• 5:17
  Isaac Asimov or Arthur C. Clark.
• 5:20
  They're actually writing the future.
• 5:22
  'cause think about that, right?
• 5:24
  I used to feel like stuff was invented, but nothing's invented.
• 5:28
  You know, it's not like, you know, a mad scientist coming up with some
• 5:33
  magnificent invention like, I've done it now we can travel through time.
• 5:38
  No, it's not like that at all.
• 5:40
  It it's teams of software engineers and if the widget needs to watch
• 5:44
  it, if you spend enough money, the software engineers are able to
• 5:48
  develop the product that can do that.
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  So literally when you are designing a mainstream product like an
• 5:57
  iPhone or a new Tesla or a new Ford Transit, you were literally.
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  Designing the future because these are gonna be produced in their millions and
• 6:11
  sit around on every street corner or in everybody's pocket, or, you know,
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  the bios the unique way of starting the Model T Ford or the, you know, the
• 6:21
  Apple way of doing the phone versus the Android where the phone, this is
• 6:24
  something which is gonna be used by millions and millions of people and
• 6:28
  seep deep into the cultural zeitgeist.
• 6:32
  Look, and that's really what we're talking about here because I've been
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  watching a lot of Dave Freeberg road trips, a guy from Hot Rod Magazine, and,
• 6:42
  and he does these sort of road trips around Southern California on, uh, route
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  66 as part of, you know, his attempt to launch his own YouTube channel.
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  And, and, uh, I find these kind of road trips really enjoyable to,
• 6:58
  to sort of ride on along with him.
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  And I don't know why I was talking about him.
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  What Free Burger does is celebrate.
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  Automotive culture and what Freeberg does by visiting parts of Route 66 with
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  their quintessential gas stations, with the portico on, on the front of them.
• 7:46
  This is, this is the modern Bailey castle of the American West, right?
• 7:51
  This is is a piece of architecture which speaks so much to the
• 7:57
  formation of the nation.
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  And is just overlooked and forgotten and not really appreciated.
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  Not in the case of the Martin Bailey Castles.
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  There's no English heritage, no equivalent of English heritage looking
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  after these kind of properties.
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  And that's why I hesitate to call it work.
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  This sort of folk archeology, that freeberg indulges in where you
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  go and you look at the things and it's very nostalgia driven and it's
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  kind of a historical, sorry, Dave.
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  I love the work, but you're not, you're clearly not a trade historian, are you?
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  You're a, you're a Hollywood storyteller rather than somebody
• 8:34
  who's thought properly about history.
• 8:37
  'cause Dave Free Berger doesn't like the graffiti on buildings.
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  And whilst I understand that he doesn't like the graffiti, I was looking at
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  a, a, a piece of architecture the other day that's had graffiti on it.
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  And I, I feel like you have to be able to look.
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  Beyond the Graff, you can see the graffiti for the art that it is.
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  If it's good, sometimes it is, usually it isn't.
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  There's something in that.
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  And the idea of graffiti is an evolving art form that's really cool
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  and that young people want to do it.
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  That's really cool as well.
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  So, you know, there is something to be said for graffiti is, is what I'm saying.
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  And, and while I prefer, you know, free burgers, no graffiti on
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  these buildings just to see the.
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  Decline to see how it used to be to what he likes to do is that thing that
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  that headmaster of mine in elementary school used to like to do where he used
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  to imagine you were in the Roman bath when you were standing in the field, in
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  the reign of, of Middle England on the site of, of the ancient Roman villa.
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  And he would imagine that you were in the hot bath and you could,
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  you, you could, you could feel it.
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  Well, Freeberg likes to do the same thing.
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  He likes to imagine the cars that stopped here, the hot rodders
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  who stopped on the way out to Al Mirage at this long forgotten rest.
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  Hold it.
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  It's is really a, a, a, a interesting, uh, interesting how similar
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  that that kind of of history and freeberg kind of folk history is.
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  Although, as I say, Freeberg struggles with the notion of, in, in one episode
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  I watched recently, he talks about how is it, I think that graffiti's
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  cool if it's old, but not if it's new.
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  Failing to recognize that the paradox is you, Dave.
• 10:22
  The paradox is you, yourself, your attitude to it.
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  You can, you just happen to like some things and not others.
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  That's what's uh, uh, at work here.
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  It's interesting how being historian gives you greater insight just 'cause you've
• 10:37
  thought about things in a different way.
• 10:39
  So look, Dave celebrates the past and I try and celebrate the past,
• 10:43
  but recently I've talked a lot about the future and I've talked in recent
• 10:48
  pods an awful lot about new cars, even though they do the job well.
• 10:52
  But I don't really give a shit about them.
• 10:55
  This is quite an important presentation though, and quite an important topic.
• 10:59
  Um, because of this combining of the McKinsey vision with this very, very
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  narrow vision of this one single software house presenting their
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  suite of, of products to an audience of Silicon Valley people whom they
• 11:21
  are looking to get into bed with.
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  Let's not beat, ran the, the bush.
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  You know, that's why the CEO is there doing the, doing the presentation.
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  These guys were called acas Cas.
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  Any presentation you go to at the moment will talk about the volume of data,
• 11:38
  which is being generated by modern cars, you know, contemporary cars, let alone
• 11:44
  the, the kind of systems that, that are coming in future and, and, um, nobody's
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  looking after this data properly.
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  Fundamentally, nobody knows what to do with it.
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  These guys are offering half a dozen opportunities and.
• 12:02
  Fundamental, you know, some kind of, uh, uh, tools in some cases
• 12:08
  for products, but in some cases just some tools around how you can
• 12:13
  take advantage of all of this data.
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  So in other words, McKinsey gave you the big picture and then this software
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  house showed you the sort of sinus of what the financial and technological
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  infrastructure of these new software defined vehicles, data defined vehicles.
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  But software defined vehicles was the language that McKinsey used.
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  So that's how we'll we'll call it, they called it the SDV.
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  It took me a while to, to figure out that, that acronym, it's funny when you
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  figured it out, it's obvious, but it took me a while to to, to get to it.
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  So this is the software defined car.
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  V and well, you know, the software defined car versus data management and packaging.
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  In the second presentation, you know, to read from the notes
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  that I made before I started the presentation, the bottom line here is
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  that cars part of connected system.
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  In future they are, as I, so I think at the top of the show, they are edge
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  of cloud devices like your phone.
• 13:26
  So there's no independence and there's no freedom.
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  The freedom of the open road is gone.
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  I mean, I don't know what you need to do, like get out and a Chevelle now.
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  Like why you can is really, that's really the position that we're in.
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  I mean this, uh, fellow that presented at McKinsey, he was a charismatic,
• 13:53
  likable guy and like the auto live.
• 13:58
  Girl, Hannah, he claimed to be a car guy, but you know, he told a
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  story about fitting speakers to an E 36 when he was a teenager.
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  It was on the tip of my tongue to ask him if I still had the
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  car, but I knew he hadn't.
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  And this bloke came and talked to us for an hour or so about cars.
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  He made a point of getting to know us.
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  As I say, he was charismatic.
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  I liked him.
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  It was a good presentation.
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  He talked to us about cars.
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  When I left, I'm always the last person, one of the last people to leave.
• 14:30
  I was chatting with another person about formula, one of all things, which
• 14:34
  is really interesting conversation, interesting bloke that I, uh, I I met.
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  But anyway, the presenter was still waiting for his Uber.
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  He talked to us about cars and personal mobility, but he
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  himself is waiting for his Uber.
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  And the poor bastard's been standing in the rain in his nice
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  suit for 10 minutes waiting for the Uber to come because guess what?
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  These new fucking solutions don't work.
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  They don't work.
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  I, I'm not sure I'm, I'm increasingly feeling the, there was a. I, I felt
• 15:24
  that the pinnacle was the turn of the century, but I actually feel that
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  there was an extended pinnacle into this century, which ended when, about
• 15:34
  10 years ago, when manufacturers were forced to reintroduce emission standards.
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  And when we first start, you know, really tough emission standards.
• 15:43
  So when we first started getting, um, wet belt engines and, and
• 15:49
  these small capacity turbo engines,
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  the McKinsey presentation was called the Mobile Destiny of 2030, winning
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  the race in the Software Defined Era.
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  I put SDV in quotes up above.
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  And they're like, you know, black piece of paper is like something important.
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  So we talked about, uh, what software defined meant and how that's designed,
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  how that's development of the product, how that's upgrades on the fly, what they
• 16:42
  call OTA, like over the air upgrades.
• 16:46
  How in EVs, that's powertrain management.
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  When we talk about software defined, we're saying that, that the software
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  infrastructure of the vehicle is the bread of the pizza, right?
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  It's the most important thing about how.
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  The product is designed.
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  So you would say, is it like the steel of the car?
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  Well, I, I, I don't think it's like the steel of the car, but
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  I think it's because, you know, everyone makes the car outta steel.
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  But I think if we think about what has made the German product stand out
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  up to now, that there was a sort of better engineering integrity about the
• 17:33
  way that, you know, you didn't need to be a car guy, just sit in A BMW and
• 17:37
  know it drove better than a Chevrolet.
• 17:39
  Yeah, sure.
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  There were some Chevrolets that drove great, but by and large BMWs drove a
• 17:45
  certain way and you paid more to drive A BMW then you did to drive a Chevrolet.
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  That sort of differentiation that used to come from the powertrain and the
• 17:59
  interior and, and all, who knows, some of it may still come from that, but I.
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  In a software defined vehicle, the vast majority of that differentiation is going
• 18:12
  to come from software defined elements, which are going to be delivered over
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  the airwaves to a product which has that cap capability built into it already.
• 18:30
  Now, you may remember the BMW heated seats debacle of a few years ago.
• 18:36
  This is where BMW was selling cars that had the heated seats in them
• 18:42
  already, but you needed to pay an upgrade online to be able to use them.
• 18:50
  Well, people were pissed off that they work at the moment.
• 18:53
  You just need to enable them.
• 18:54
  I remember having a conversation with Mark Gamy who comes on the PO with his brother
• 18:59
  about it, who was absolutely incensed of the notion that, that you should have to,
• 19:04
  that you should have to pay for this some.
• 19:05
  BMW withdrew them.
• 19:06
  It's not gone anywhere, but, but this McKinsey fellow is basically,
• 19:10
  that is gonna have to happen.
• 19:13
  People are just gonna have to eat that shit sandwich because,
• 19:17
  um, this is how people are gonna make money out of cars in future.
• 19:22
  He talked about, I'll put this in quotes, extending the life of the hardware by
• 19:29
  making the software updateable on the fly.
• 19:34
  So he almost seemed to be, I found myself.
• 19:39
  Thinking about was announced quite recently that the B 52 is gonna have
• 19:44
  their life extended at least until 2050 or some kind of ridiculous date where,
• 19:50
  by which time the airframes are going to be older than the people crewing.
• 19:58
  And of course, yeah, the airframes are, but the software
• 20:00
  infrastructure and the engines.
• 20:02
  There, those things are gonna be completely state of the art.
• 20:06
  It's just the airframe, the building, if you like, the architectures the same
• 20:12
  and you know, it, it, it's interesting that planes can, can work like that.
• 20:16
  And it's interesting the, uh, to think that cars are, are gonna be able to,
• 20:21
  to, to work like, like that as, as well.
• 20:25
  And, you know, we are comfortable, you know, when you buy a car, you are
• 20:29
  comfortable with the idea that you might, you know, chip it for a bit
• 20:33
  more power, might you, and you are comfortable with the idea that you
• 20:37
  might fit aftermarket wheels, you might fit aftermarket suspension, you might
• 20:42
  do some things to, to personalize it.
• 20:44
  So although James Gamy was highly offended at the idea of having to pay
• 20:51
  for heated seats that were already fitted to the car, the notion of paying
• 20:55
  extra for he heated seats is not.
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  What upsets him, it's just having to pay for it when you've kind of already got it.
• 21:03
  There was just that kind of hub to get over.
• 21:06
  But you see, when everyone's used to a over the airwaves update on, on their
• 21:11
  car, they're not gonna feel like it in the same kind of, of, you know,
• 21:15
  Luddite way that, that James did.
• 21:17
  I'm sure you won't mind me saying that, Jamie.
• 21:20
  No.
• 21:20
  Something he talked about was how, there's always a question
• 21:24
  about how much compute is actually needed on the edge of the cloud.
• 21:28
  In other words, you know, what you want to do is just have like a green screen
• 21:33
  set up, but actually with cars you have to have some processing power there.
• 21:40
  On the edge because connectivity fades and there's latency and it's a high
• 21:47
  critical situation where you can't have, you know, latency in, in decision
• 21:52
  making with, in some cases, if the car's driving on the freeway and it needs
• 21:57
  to decide whether to swerve or not.
• 21:58
  There can't be any, can't be needing to connect to some
• 22:02
  computer over the internet.
• 22:04
  And if there's, you know, if there's the, you know, the spitting wheel
• 22:07
  of doom, you, you see what I mean?
• 22:09
  The car has to have some computing power actually on board, so it could
• 22:13
  make, it can make good decisions.
• 22:17
  And what the McKinsey fellow termed this as, as he termed this, as a
• 22:21
  centralized yet distributed system.
• 22:25
  So we had one slide that had six areas which were gonna define whether or not.
• 22:35
  You were gonna win or lose the race to a software defined automobile.
• 22:41
  It's not an automobile at that point, is it?
• 22:43
  It's just not.
• 22:45
  I mean, if a Tesla, whereas I wrote an article many years ago where I
• 22:49
  compared old Shavel with a Tesla and just said that, you know, it's just
• 22:54
  less of what I understand a car to be.
• 22:58
  It's just, you know, less, I know it's better as what we define a
• 23:05
  car to be, but it's not what I, you know, understand a a, a car to be.
• 23:11
  The Chevelle still fulfills that definition more than than a Tesla.
• 23:17
  It's Tesla's an awesome piece of technology.
• 23:19
  It's just not a car, as I've understood it.
• 23:21
  That was my attitude, sort of 10 plus years ago.
• 23:26
  Now I see that they redefined what the car is.
• 23:29
  Right now.
• 23:29
  Everyone's using them.
• 23:30
  They've just redefined what, what, what the, what, what the car is,
• 23:34
  where these, you know, software defined vehicles of the future are
• 23:37
  gonna do that more, more and more.
• 23:54
  The notion that the automobile is a place of personal independence and
• 24:04
  freedom, I think is gonna disappear.
• 24:08
  I think it's just gonna be another environment where you are
• 24:12
  connected and it's just gonna be another device like your phone.
• 24:20
  Yes.
• 24:20
  It's sick making, isn't it really is.
• 24:23
  You know, you, you want to try and.
• 24:26
  Put a brave face on it, but
• 24:36
  how you can talk enthusiastically about an E 36 BMW and then enthusiastically
• 24:43
  present this like computer on wheels.
• 24:48
  Shit, I just, I just,
• 25:04
  anyway, the first factor in determining whether or not you're gonna win the race
• 25:09
  to NT cars and invent these horrible mobility, mobile phone, meet cars, things.
• 25:17
  Um, the first area is gonna be, uh, hardware platform simplification.
• 25:24
  And that's a necessity, not a, a, a choice.
• 25:28
  Apparently Rivian have 17 ECUs in.
• 25:33
  I remember reading back in the days when I used to read car magazines, so least 10
• 25:38
  years ago, that you know, the wiring in a BMW seven series, if you stretch it out
• 25:44
  and ran it all around the world or ran it, it would stretch around the world.
• 25:47
  You know, there was that much bloody wiring in them.
• 25:51
  So you need to simplify that.
• 25:53
  And the parallel was the, like your phone, now your phone does everything.
• 25:59
  Used to have mice and printers and cameras and all of that stuff.
• 26:05
  And now you don't need calculators.
• 26:07
  You don't need any of those devices all like tied together on your phone.
• 26:12
  And that needs to happen in the design of automobiles and mobility devices.
• 26:21
  Or it will happen.
• 26:23
  The second area is that there needs to be more collaboration
• 26:29
  and and less competition.
• 26:32
  If you listen to my, uh, leadar presentation, the haw Wind and, and
• 26:37
  Leadar presentation I did a few months ago, one of the things that I was just
• 26:42
  gobsmacked by was that in this bleeding edge way, the autonomous vehicles are
• 26:48
  perceiving the world, which is are instead of companies pooling the research
• 26:54
  or sharing it or something like that, there's three competing German makers
• 26:58
  and they all have different protocol and they're all competing with each other.
• 27:02
  And each Volkswagen and BMW and Mercedes, they all are desperate
• 27:07
  to preserve some kind of sense of identity and competitive advantage.
• 27:13
  You know, we're doing the work three times instead of just once it's, and
• 27:16
  that just seems really bloody absurd.
• 27:19
  It seems to be how we did things in the 20th century, not how we.
• 27:22
  Need to do things now, it's so much wasted labor.
• 27:26
  Even if you think we need autonomous cars for three people to be working on the
• 27:30
  same piece of technology, which Tesla and Musk feel is not even needed at all.
• 27:36
  It just seems very, very, it seems likely to be misguided
• 27:41
  and wasteful, put it that way.
• 27:59
  The, the other example that, that I wrote down here around this more collaboration
• 28:04
  than, than competition area is that GPS is used for maps and, and, and safety
• 28:10
  around the world, and, and that's the sort of model that we need to work towards.
• 28:17
  There needs to be that kind of shared infrastructure.
• 28:20
  There
• 28:33
  again, right?
• 28:35
  I mean, BMW might be able to navigate it, but Chrysler Reno, like, are
• 28:42
  they gonna be able to navigate this kind of world against the Chinese?
• 28:48
  I mean, in 1960 it was hard to perceive that the British motor,
• 28:56
  indu motorcycle industry was going to be gone in 15 years, gone.
• 29:03
  The Australian motor industry ended in one year period.
• 29:08
  Within the last five years, there was all three.
• 29:12
  Uh, the big three were making cars there.
• 29:14
  One minute and now nothing at all.
• 29:17
  The sun is really setting.
• 29:19
  I mean, I don't wanna keep harping on the, it's over me, but guys, it
• 29:27
  really bloody is so, yeah, so, so one simplification of the hardware platform.
• 29:33
  So instead of what American cars were like, the fifties, a simple
• 29:38
  platform that's defined by, you know, the features that you have in it.
• 29:42
  Everyone has the same iPhone, but you know, some of you have different apps
• 29:46
  in it and you pay for more of the apps or for security or, or whatever.
• 29:51
  That's, that's how these things are gonna be differentiated
• 29:55
  for these things to work.
• 29:56
  We need not to be doing what the Germans are doing with Leadar.
• 29:59
  Everyone work there needs to be sharing of the data.
• 30:04
  Or at least of standards, you know, protocols, the way that
• 30:09
  we're gonna, you know, Android and Mac have what was fundamentally a
• 30:15
  Windows infrastructure, don't they?
• 30:17
  There's that kind of basic understanding of whether we're gonna drive on the
• 30:21
  left hand side or the right hand side of the road, or whether we're
• 30:24
  gonna steer with wheels or tillers.
• 30:26
  That's the kind of thing that, that needs to be, uh, figured out here.
• 30:45
  I can't read why I wrote for number three, but didn't write any notes around
• 30:49
  it Anyway, number four is cloud will be the engine powering automotive.
• 30:59
  He used this phrase, hyperscalers, which I've not used before, but was used in
• 31:05
  the second presentation as, as, as well.
• 31:08
  And by that they mean, you know, Amazon web services or basically people who
• 31:13
  give you compute power on demand.
• 31:17
  So this hyper scaling, getting that right, having the right partner
• 31:23
  with that, since it's not about the edge, it's more about the center.
• 31:28
  Making sure that what you've got at the center works properly is going to be key.
• 31:33
  Right?
• 31:33
  The cloud infrastructure is what's important.
• 31:36
  Far more important than what the design of the devices on the
• 31:41
  edge of, of the infrastructure.
• 31:43
  In, in, in other words, it is important to be Verizon or the network provider
• 31:49
  as it is to be Samsung or Noia.
• 31:54
  If they're still, you know, the, the, the blokes that actually make the devices.
• 31:58
  That you can see
• 32:11
  engineering must shift.
• 32:15
  I wrote, this is really interesting because this is a change that's
• 32:19
  reflected in my wife's place.
• 32:21
  My wife works at a, you know, magnificent seven company and it has been a shift
• 32:27
  where it used to be the product called the shots and sales sold what Product built.
• 32:34
  And you know, I've worked at Valley companies that were like
• 32:37
  that as well, where the engineers were all the C-level people.
• 32:41
  So, you know, they built what they wanted to build and they hired people to sell it.
• 32:45
  And then they were like, but why aren't you guys able to sell this stuff?
• 32:48
  And it's like, because you, you're fucking building what you want to build rather
• 32:52
  than what customers actually want to buy.
• 32:55
  Right, and that's what's happened is that sales have come along and said, no post
• 33:00
  pandemic sales have come along and said, no, you need to build what we wanna sell.
• 33:05
  Don't build this shit that we don't want, that our customers don't want.
• 33:09
  Sales is king, not product.
• 33:13
  The same is apparently called the McKinsey needs to happen in automotive.
• 33:18
  That, that traditionally it was the motor and chassis people who called the shots
• 33:23
  and decided how and what the car was like.
• 33:27
  But now software's king.
• 33:28
  Now the motor and chassis, they don't really matter.
• 33:31
  That's the real indictment, isn't it?
• 33:34
  The motor and chassis people don't matter.
• 33:37
  And if you think about it, you know, all the time it was my wife's place that sales
• 33:41
  were taking over and, you know, senior people were being fired and their jobs
• 33:47
  were sort of just being dumbed down and given to, to lower level people because.
• 33:53
  You know, it's just changing.
• 33:55
  AI's being used to do some things.
• 33:57
  The organization is just, you know, instead of doing everything to the nth
• 34:03
  degree, you're happy to do it to the less than nth degree, but for a better price
• 34:09
  with a, you know, lower caliber person.
• 34:11
  That's where we're going with this, around the notion of people are used
• 34:17
  to the idea of buying a chip to like improve their performance or, you know,
• 34:21
  the car's performance or some alloy wheels, but they don't wanna pay for
• 34:25
  the heated seeds that they perceived as already being built into the car.
• 34:29
  He said that he felt like makers needed to focus on what the delightful, what
• 34:35
  were the delightful experiences that you were gonna deliver to your customer.
• 34:41
  So the final one was, uh, the, in order to, you know, make the shift
• 34:48
  towards software and away from.
• 34:50
  Traditional engineering.
• 34:52
  And if you think of it, by the way, ages ago, I think in the,
• 34:56
  I went to a presentation, the zf, uh, the transmission, the
• 35:00
  German transmission people did.
• 35:02
  And, and I realized that there were two Zfs.
• 35:05
  There was the old ZF that made the gears, and then there was this new
• 35:07
  ZF that was, uh, called zf, but it was actually the software house that
• 35:13
  they'd acquired because EVs don't need normal gear boxes, do they?
• 35:18
  They need like programming and software.
• 35:21
  So ZF had completely changed what they needed to do, and it basically
• 35:26
  turned into a software house.
• 35:27
  And they're, you know, the guy that I was talking to who was their head honcho
• 35:31
  in America, was the CEO of the whole software house that they, you know,
• 35:36
  the software, boutique software house.
• 35:37
  They bought a few, you know, a year or so before in order to make this pivot
• 35:43
  from making cogs to making software.
• 35:48
  So, you know.
• 35:49
  You really need engineering talent for this.
• 35:51
  And I underline that because, you know, that's, this is what McKinsey was saying
• 35:56
  is that, that, you know, you're just not gonna make this pivot unless you
• 36:00
  get the, the right engineers on board.
• 36:03
  And, and a lot of them, so the revenue model here is
• 36:08
  business to business data sales.
• 36:11
  I, we talked a little bit about car advertisements and how already
• 36:16
  they'd pivoted away from talking about, you know, power and speed
• 36:21
  and far more They were about the journey that the consumer was on.
• 36:28
  That was the quote that he put in it.
• 36:31
  And I, I found myself thinking of these sort of Subaru adverts do this very well.
• 36:37
  If you were, you, you feel.
• 36:40
  The overwhelming feeling is the sort of person who owns a Subaru
• 36:45
  and you wanting to be that sort of person that owns the Subaru.
• 36:49
  The Subaru is just like the stage upon which the little like, you
• 36:55
  know, family, dog loving, you know, DEI family is playing out against.
• 37:03
  The example he gave was that the car will be like a TV where
• 37:08
  you buy streaming programs.
• 37:11
  I can't think of anything worse
• 37:24
  if you're gonna sell the car and then do over the airwaves upgrades
• 37:30
  to it, you know, in the way that you do a laptop or your phone,
• 37:35
  the device, the car has to have.
• 37:39
  Processing power headroom built into it.
• 37:57
  The software also has to have this sort of headroom built into
• 38:03
  it without one to jump ahead.
• 38:06
  One of the issues that the second presentation highlighted was the way that
• 38:12
  if there's a problem with the development of a particular piece of software with
• 38:16
  a car maker at the moment, they'll go to a consultancy and that consultancy
• 38:20
  would deliver a point solution and then.
• 38:23
  The car company will move on and design another model and maybe, you
• 38:28
  know, hire the same consultancy to do a different or another point solution.
• 38:33
  And these point solutions, they may be written in a protocol that means
• 38:36
  that they're just not updateable, they're just cast in stone.
• 38:40
  You know, they were a point solution that worked for that particular
• 38:44
  application, but that's all they were.
• 38:45
  There was no kind of, you know, future proofing, uh, around them.
• 38:50
  It's not just they need extra processing power.
• 38:52
  It's also the kind of this way in which the software's gonna have to be engineered
• 39:00
  to cope with the fact that these, that, you know, the software's gonna be coming
• 39:04
  out every couple of months, but the car's gonna be on the road for five, 10 years.
• 39:11
  So we, we had a sort of slide about what was a software defined vehicle.
• 39:16
  It's a business model.
• 39:18
  You know, you're making money, selling the data, not.
• 39:21
  Your car's doing better gas mileage than the other guys, or has got more horsepower
• 39:26
  or, you know, as nice as styling.
• 39:39
  I also wrote something about customers, the way the customers
• 39:42
  are, but I can't remember what I wrote, like I read my own writing.
• 39:46
  And then the third sort of characteristic of the software defined vehicle
• 39:51
  was the actual hardware itself.
• 40:05
  Next, he talked about security, how you have to create a sort of
• 40:10
  DMZ around systems like breaking.
• 40:14
  He had this fucking amusing metaphor.
• 40:19
  Where we'd add like a pasta dish at the restaurant we were in, where
• 40:23
  we were doing the presentation.
• 40:24
  It was, it was over in Oakland and it was looking out over the harbor
• 40:27
  and it was, uh, you know, it was at nice kind of picturesque there.
• 40:32
  And, uh, you gotta imagine this McKinsey bloke, uh, in his nice suit describing
• 40:37
  how each different heated piece of Italian pasta or ravioli or whatever it was,
• 40:45
  how each one of those was similar to the sort of DMZs that were required on cars.
• 40:51
  So in other words, if this one on the left here is your ice, you know, your
• 40:58
  in-car entertainment, streaming music, all of that kind of stuff, that is
• 41:03
  something which you would allow over the air updates to take place, right?
• 41:08
  Because ultimately if it doesn't work, it's annoying, but it's
• 41:11
  not the end of the world.
• 41:12
  Whereas the breaks, that is something which.
• 41:17
  If you were gonna do over the airwaves updates to it, you would need a
• 41:23
  system, uh, ensuring that those updates took effectively and that
• 41:29
  the system was gonna work properly all of the time, for obvious reasons.
• 41:35
  Just stop and think about that, right.
• 41:37
  The, the breaks.
• 41:39
  I mean, just in the, um, I did a poll a couple of weeks ago where I used the,
• 41:44
  the quote from 2001, A Space Odyssey.
• 41:47
  You know, I'm sorry, Dave, I can't let you do that.
• 41:51
  Where the computer thinks it's gonna, you know, the humans are gonna turn it off
• 41:55
  and it's like the mission's too important.
• 41:57
  Dave, I can't let you turn me off.
• 41:59
  The music, the machine's taking over, it's the classic, you
• 42:02
  know, plot spoiler for 2001.
• 42:05
  A Space Odyssey there guys, by the way, sorry about that.
• 42:24
  If every element of the car can be updated over the airwaves, when you get in it
• 42:29
  and you start it up and you back it out the driveway in the morning and it's had
• 42:33
  a new software upgrade, it's not even the same car as it was the night before.
• 42:38
  Is it, was it Star Trek or was like with the quote, it's
• 42:42
  life Jim, but does we know it
• 43:02
  Well?
• 43:02
  This is quite alarming.
• 43:04
  This is why I enjoy going to these kind of presentations as well, because it, it,
• 43:08
  it makes you, you realize where we are because of course there are certain areas
• 43:12
  that they don't know what's happening.
• 43:15
  I, I wrote down, it's not clear who owns the data and the data.
• 43:21
  We mean the data that's being generated from all the cameras that are on cars.
• 43:28
  Think about how many more there will be on, apparently the Waymo has 29.
• 43:33
  Pairs of eyes on the road.
• 43:34
  That's what the auto live engineer was, was saying, 29 pairs of eyes.
• 43:39
  So think about all the data which is streaming off that, that car,
• 43:44
  and think about how powerful that is if you can, you know, big data
• 43:48
  it with all of the, um, all of the data for all the vehicles all around.
• 43:53
  So it's not clear who owns the data.
• 43:55
  It's not clear who should store it, who should pay for it to be stored.
• 44:01
  It's not clear how it should be stored, you know, whether it should be nearline
• 44:06
  or that kind of method of storage, which is, you know, slower to get to.
• 44:10
  Gosh, this is reaching back into my own software sales past of, of
• 44:17
  where the things are online or near line, as we used to say, take backup.
• 44:23
  Tape backup.
• 44:25
  That's right.
• 44:25
  Youngins.
• 44:27
  Some motherfucker used to come to your premises and pick up
• 44:31
  tapes and take them off site, and that was your disaster recovery.
• 44:36
  If your factory burned down, you bought new computers, and then
• 44:40
  the dudes showed up with the tapes and your new systems always loaded
• 44:44
  absolutely perfectly without issue.
• 44:58
  The data issue is huge.
• 45:01
  Said the McKinsey guy.
• 45:02
  Then he left and had to wait 15 minutes for his Uber.
• 45:19
  So the second presentation was by these guys acas, ICAS.
• 45:25
  Nothing to do with ai.
• 45:27
  It's just a coincidence.
• 45:29
  The CTO and founder is named James Hunt.
• 45:33
  Faintly ironic about James Hunt being involved in the dein inventing
• 45:41
  of not just driving, but the whole, what happens in Vegas stays in Vegas.
• 45:47
  Freedom of the open road, freedom to.
• 45:51
  Grab a girl's ass without there being any repercussions.
• 45:55
  James Hunt, the motor racing driver personified that, didn't he personify
• 46:00
  that Playboy era of the 1970s, the freedom to do that kind of thing.
• 46:05
  Right or wrong, you know?
• 46:07
  'cause my freedom is a, you know, another person's oppression
• 46:11
  and all, you know, I, I get it.
• 46:13
  I'm not advocating for that.
• 46:14
  I'm just saying in the 1970s, we're a different place.
• 46:18
  And James Hunt was the personification of a way of living,
• 46:21
  which is far too misogynistic to be acceptable at the moment.
• 46:25
  And it's ironic that, uh, this blo who's invented this company with this
• 46:30
  technology That's, yeah, the opposite.
• 46:33
  I, I made that point, didn't I?
• 46:34
  Do I need to keep hammering it?
• 46:36
  I'm not sure I.
• 46:50
  So the acas presentation was called, is AI Ready for the Intelligent Vehicle Edge?
• 46:59
  I think about that.
• 47:00
  There's a lot going on there, isn't there?
• 47:01
  And the guy talked a little bit about the title in the presentation,
• 47:05
  and it's only now reading it back that I, I realize that, I'll say
• 47:08
  it again to help you ruminate it.
• 47:11
  Is AI ready for the intelligent vehicle edge?
• 47:16
  The fellow presenting was called, uh, Johans, Beerman German, president
• 47:21
  of the company, company based in Borough, which is a, a town, uh, not
• 47:26
  far from, from Frankfurt, where we actually have some friends who live.
• 47:30
  So that was, uh.
• 47:31
  It was a, a weird coincidence, but maybe not, you know, because really,
• 47:35
  um, this is the sort of automobile of Silicon Valley, you know, Ben's
• 47:40
  and Kta and the first car and all of that was not far from, from Carl's Ru.
• 47:46
  So were so interesting, uh, that, that there was that connection.
• 47:50
  So he began his presentation with a story, and I thought it was illuminating for as
• 47:54
  usual different reasons, for the reasons that he thought it was interesting.
• 47:58
  But I love an anecdote.
• 47:59
  He began with it.
• 48:00
  So, uh, you know, let me, uh, let me do it justice.
• 48:03
  And it was, it was that he'd driven a cyber truck.
• 48:06
  Um, he had friends up in Tahoe or somewhere like that and he'd, he'd
• 48:10
  driven a cyber truck in the time that he'd been here in, uh, in California.
• 48:15
  He, he, he, uh, was surprised that the size was manageable, which of
• 48:19
  course is a tribute to how much space there is in America versus in Europe.
• 48:24
  He'd described his first experience using full self-driving says he felt safe.
• 48:30
  Which is interesting because that's the experience I have watching
• 48:33
  people ride in Waymo's for the first time and then be like, whoa,
• 48:37
  it's actually a really good driver.
• 48:39
  But, you know, I know that feeling of bemusement is still that I
• 48:43
  had the first time I rode in it.
• 48:44
  That's only about her, you know, nine months or 12 months
• 48:48
  old or something like that.
• 48:49
  So I do remember how it felt to be like, wow, it can drive.
• 48:55
  This felt, so, this full self-driving really works.
• 48:58
  The other thing he said, and I thought this was really interesting because
• 49:02
  this speaks to the kind of thing that my students say when you talk to them about
• 49:09
  their interest in car design and product design and marketing and why they're
• 49:14
  doing a class, which is called Tales to Design Cars Buying a, a surprising
• 49:18
  number of, of people will, will, will talk about wanting to create a better
• 49:24
  situation for, you know, certainly a justification for autonomy is that people
• 49:32
  who are not able to drive are still able to lead independent, meaningful lives.
• 49:40
  And Johanna's here, I'm not, I think that's how you pronounce it.
• 49:43
  Apologies sir, if, uh, if I got it wrong.
• 49:46
  'cause your English was excellent.
• 49:47
  Obviously my German is, uh, really not, not there.
• 49:51
  Um, but look, the, the, the bottom line is that he said, I thought of my dad.
• 49:55
  I thought of him towards the end of his life.
• 49:57
  I thought, how much richer those later years, those last years of his life could
• 50:01
  have been, had this technology existed.
• 50:05
  I met somebody at Stanford some years ago, really impressive lady.
• 50:09
  She was interested in car design.
• 50:13
  You know, she was one of the first people that I'd had a candid conversation with
• 50:16
  at Stanford about the fact that, you know, they didn't care about Formula
• 50:20
  One, but they were really interested in car design from a completely
• 50:23
  different perspective, from the, the angle the the eye had had come from.
• 50:28
  She had two sets of grandparents, each of whom lived in, they lived in
• 50:32
  different parts of the country, but they depended on, uh, the automobile for a
• 50:38
  sense of community, for their friends to, you know, different lifestyles.
• 50:42
  But, you know, the, the point was that they were.
• 50:46
  Desperate not to lose their driving licenses.
• 50:49
  And if they lost their driving licenses, they felt like that was
• 50:52
  gonna be the end of their lives.
• 50:53
  'cause they couldn't get out and see people and socialize and, you know,
• 50:56
  because America's the distances are huge and, you know, all, all, all of that
• 51:00
  stuff that we, that we already know.
• 51:02
  So in other words, probably, probably 10 years ago now, she had that conversation
• 51:09
  with, with me and I realized that autonomy was a lot bigger than me.
• 51:14
  I like to drive, you know, I like the feeling of a car in the Benz.
• 51:18
  Um, it was a lot bigger than that.
• 51:19
  It was really about it improving people's quality of life.
• 51:24
  And I know I was cynical about that in the auto live presentation.
• 51:28
  'cause the, the safety thing, oh that is just so, uh, uh, you
• 51:33
  know, sends chills down my spine.
• 51:35
  But this is different from that because this is.
• 51:42
  The technology, the autonomy, actually delivering independence.
• 51:47
  It's extending, it's making people's lives more meaningful.
• 51:51
  It's saying you don't have to sit at home saying that you can, or you don't have to
• 51:55
  do like virtual chats with your friends.
• 51:58
  The bloody computer car can take you out to church or the bar or
• 52:03
  bowling or pickleball or you know, whatever the devil your poison is.
• 52:08
  So I thought it was.
• 52:10
  Interesting, his perspective on technologies, which, although he has this,
• 52:17
  he, you know, works for a leading German technology, software technology house.
• 52:24
  He felt, you know, he was like, wow, the fell full self-driving actually works.
• 52:29
  Like, wow, the truck's not too big.
• 52:31
  You know, he had a kind of a, a, a, a very European outsider kind
• 52:36
  of reaction to, to the cyber truck and to, to full self-driving.
• 52:40
  So that was really interesting.
• 52:41
  But what that made me realize was that it's not about being
• 52:45
  forward or behind, is it?
• 52:47
  'cause I remember going to England some years ago and everyone else, everyone in
• 52:51
  England tapping their card and me needing to slide it or something like that,
• 52:57
  and not having the tap functionality.
• 53:00
  You know, figured out.
• 53:01
  So I don't wanna somehow imply that, you know, oh, we in California
• 53:05
  are so forward with, uh, with our, you know, dangerous, sharp-edged,
• 53:09
  ridiculous, huge cyber trucks.
• 53:11
  I'm not trying to suggest that at all.
• 53:12
  I'm just saying that the comfort level with full self-driving, I found that
• 53:17
  really interesting that the German, even a German working in the industry
• 53:21
  didn't feel like that about it.
• 53:24
  What he said was, for a German, this is very advanced.
• 53:28
  I I just put the, we just don't test properly.
• 53:31
  You know, we just bloody beat at testing.
• 53:33
  'cause we, 'cause we are, if you look at the Tesla accidents, I don't wanna
• 53:36
  fall down this rat hole, but if you look at the accidents Tesla's had, it's
• 53:41
  where the full self-driving technology has not perceived the world correctly.
• 53:45
  But John, but John, are you seriously telling me that full self-driving
• 53:51
  as it stands at the moment is.
• 53:54
  More dangerous than actual drivers.
• 53:57
  More drivers would've been killed than full self-driving.
• 54:00
  As it stands, and that is true, isn't it?
• 54:03
  If you think about it, that the computers aren't perfect, but they're still better.
• 54:07
  Than most of the people than you know, all of the people all the time.
• 54:12
  They're not perfect, but they're better than, than we humans are.
• 54:16
  And, and I think, you know, we need to, to recognize that.
• 54:20
  I feel less like Elon Musk is beta testing full self-driving software on us.
• 54:25
  I think it's less beta testing.
• 54:27
  I just think it's like software.
• 54:29
  And we know that all kinds of software is, is buggy and that the method of
• 54:34
  doing patches and patches and patches and patches, this is, it's just you
• 54:39
  don't need to be a computer scientist to see how, you know, a bridge that
• 54:44
  you are constantly having to patch or a ship that you're constantly
• 54:47
  having to patch holes in the side of.
• 54:49
  That's it.
• 54:50
  Just, you know what I mean?
• 54:52
  The, the, the, I mean, yeah.
• 54:54
  Anyway, that is a whole separate, uh, separate rat hole, isn't it?
• 55:00
  Let me actually talk meaningfully about acas.
• 55:03
  The company's 20 years old.
• 55:05
  And they're about products, not services, and they operate
• 55:09
  like a licensing kind of model.
• 55:12
  I don't know if, does that mean they license their own technology
• 55:15
  or they license other people?
• 55:17
  Sorry if that's not clear.
• 55:18
  It wasn't clear to me automotive and QA in other sort of similar areas.
• 55:25
  So one of the things that he highlighted was, you know, luggage belts in, in
• 55:29
  airports, they have lots of customers.
• 55:31
  I mean, I took a photo of the slide, but you know, they're a
• 55:34
  significant player in, in the space.
• 55:38
  So at the moment, the kind of thing they do is over the air updates.
• 55:42
  OTA as the McKinsey guy taught me the, uh, the acronym they do data
• 55:48
  and software lifecycle management.
• 55:50
  So what that means is making sure that you know that this stuff's backwards,
• 55:55
  compatible, that, you know, um, you're not, that, yeah, that the stuff is
• 56:00
  backwards and forwards, uh, compatible.
• 56:03
  They do cloud and edge.
• 56:05
  Product.
• 56:06
  This is dense, but it bears applying your mind to it because it shows how
• 56:13
  this guy thinks about his business.
• 56:15
  Um, it's quite, quite dramatic really.
• 56:17
  Interoperability is an Internet of things challenge.
• 56:23
  Is ai, the silver bullet, in other words, making all of these different
• 56:29
  protocols and different software products all talked together properly is like
• 56:34
  a mind-boggling internet of things challenge, but AI with its capability to
• 56:40
  do many small tasks very, very quickly and hopefully pretty faultlessly, um,
• 56:46
  certainly better than human beings.
• 56:48
  Is this the silver bullet that's gonna enable us to, to, you know, deliver the
• 56:54
  kind of autonomy that everyone wants?
• 56:56
  You know, that that was what we were sort of, of floating around the idea of, and by
• 57:01
  the kind of autonomy that everybody wants.
• 57:02
  I mean, you go to a rock show, you get plastered at the rock show.
• 57:09
  You leave the rock show, you fall into your car and you say,
• 57:13
  take me home to San Francisco.
• 57:16
  And overnight while you sleep off the beer, the car drives you from Los Angeles
• 57:21
  to San Francisco, and you step out of the car in San Francisco and grab a
• 57:26
  cup of coffee, walk into the office.
• 57:29
  Jobs are good.
• 57:30
  That is the vision.
• 57:32
  Until autonomy can be that disconnected, you know, you're gonna sleep
• 57:38
  overnight, undisturbed comfortably, and you can be drunk in the car.
• 57:43
  It is not going to require you to take over until that level.
• 57:50
  I dunno if they call that level.
• 57:52
  I dunno whether that's level five or autonomy or quite what it is.
• 57:55
  That's, that's my measure of when true autonomy comes is,
• 57:59
  is, is when you can do that.
• 58:02
  He identified five ways AI can help with interoperability.
• 58:09
  Citing as examples, stellantis Ford and Volkswagen.
• 58:13
  He said that they have multiple platform software platforms that they're catering
• 58:18
  to and just to ingest the data, you need interoperability, you know, just to.
• 58:26
  Take it on board without you do any kind of analysis and, and scrape or, you
• 58:33
  know, try and package it up and sell it.
• 58:35
  This is that thing that I talked about earlier in the presentation where,
• 58:40
  because you need the interoperability, uh, car makers historically have asked
• 58:45
  system integrators to do piecemeal solutions, but then those piecemeal
• 58:50
  solutions aren't future proofed.
• 58:53
  It just becomes really, really messy, and you're in that world of patches.
• 58:58
  On patches.
• 58:59
  We can standardize this, we can platformized this.
• 59:04
  He said at the vehicle level, they can develop methods of saving only
• 59:11
  the useful data, not ev or not all the data that the vehicle produces.
• 59:17
  Think about that, right?
• 59:18
  Because what we're saying now is that.
• 59:21
  Waymo Cab, according to the Auto Live engineer, 29 pairs of eyes on the road.
• 59:28
  And at the moment, the Nvidia onboard and, you know, the Waymo data crunching
• 59:33
  back at, you know, Google HQ there.
• 59:36
  That is what's allowing the Waymo to make good decisions.
• 59:42
  What this guy's software is gonna do is empower the AI to not record
• 59:52
  certain things or to place it in a, in those, you know, never regions of, of
• 59:58
  computers that only engineers understand where, you know, you can extract them.
• 1:00:04
  Do you see what I mean?
• 1:00:05
  But you are, you we're fundamentally given the ai, the chance to censor
• 1:00:09
  itself, censor its own behavior.
• 1:00:12
  Yeah, we need to strike a balance between edge and cloud.
• 1:00:17
  This is a more sophisticated way of saying what the McKinsey
• 1:00:21
  dude was, was talking about.
• 1:00:23
  Whilst the cloud infrastructure's the most important thing, the product on
• 1:00:27
  the edge needs to have some compute, and this, the balance between edge and cloud.
• 1:00:33
  Is, is that expressed in, in another way?
• 1:00:36
  And, and hence again, this term of, of cloud hyperscalers.
• 1:00:41
  And, and it's interesting that whilst they used different terms, you
• 1:00:45
  know, the software defined vehicle data, you know, packaging, they,
• 1:00:49
  whilst they were approaching the same island from different angles.
• 1:00:54
  Some of the things that they said were the same and this cloud hyperscalers was,
• 1:00:59
  was something that I thought, you know, in other words, we can't do the data required
• 1:01:03
  for AI without the cloud hyperscalers.
• 1:01:06
  Right?
• 1:01:06
  Which is presumably why the street sees so much value in the Magnificent Seven
• 1:01:11
  because, uh, of the level of compute that's gonna be required to deliver
• 1:01:16
  the business solutions of the future.
• 1:01:18
  Johanna's highlighted the pandemic as being the time where cars really
• 1:01:25
  became more software defined.
• 1:01:28
  And the way that he framed it, and this is thinking like a businessman,
• 1:01:33
  I talk to VPs now, not directors at the OEMs like I used to.
• 1:01:39
  He says that the sales cycle is extremely long and that they need to
• 1:01:44
  be embedded early on in the process.
• 1:01:49
  You have to have the rigor to make sure that you do the right thing.
• 1:01:54
  And I wrote down afterwards that I felt like, you know, kind of Tesla haven't,
• 1:01:58
  but nonetheless, you know, I do feel like the full self-driving it is better than
• 1:02:06
  most of the people, most of the time.
• 1:02:07
  Is it faultless?
• 1:02:08
  No.
• 1:02:09
  Where do we draw the line?
• 1:02:11
  You know, I think we have to draw the line when the cruise drags the woman
• 1:02:15
  down the street underneath itself.
• 1:02:18
  I think at that point you have to say at that point, Hal needs to
• 1:02:22
  bloody well open the portal doors.
• 1:02:25
  I'm sorry Dave.
• 1:02:25
  I can't do that.
• 1:02:27
  I'm sorry.
• 1:02:27
  I'm homeless.
• 1:02:29
  Drunk woman stuck in the wheel arches.
• 1:02:31
  I'm gonna drive along over you anyway.
• 1:02:34
  You know, clearly that can't happen.
• 1:02:36
  But you know, the fact is a human driver.
• 1:02:40
  Yeah.
• 1:02:41
  Human drivers make more mistakes.
• 1:02:42
  Have I made that point over and over?
• 1:02:43
  I probably have, haven't I?
• 1:02:45
  And if I haven't made it over and over, I've now muffed the clarity
• 1:02:49
  of the point right there and then.
• 1:02:51
  This is the trouble with my delivery style.
• 1:02:53
  What I should do is say it more clearly and then edit out all the bits where I
• 1:02:57
  said it badly, but I'm just not like that.
• 1:03:00
  He made an interesting point that although V FAR can have lots and lots
• 1:03:05
  of technology in house, they still bought Rivian or they've invested
• 1:03:09
  heavily in Rivian for the data share.
• 1:03:12
  Right.
• 1:03:12
  That's what he's implying that there is.
• 1:03:16
  It's a land grab.
• 1:03:17
  It's what's going on for engineering.
• 1:03:19
  Talent.
• 1:03:20
  And, and it's also that thing that, you know, looking back to the 1920s,
• 1:03:27
  we can see very clearly the, the automobile was standardizing and
• 1:03:33
  many small companies with different solutions were consolidating.
• 1:03:38
  And that would happen in the postwar period as well, into a small
• 1:03:42
  number of, of very large companies.
• 1:03:44
  And this is to say that, you know, whilst they used to be like Oakland
• 1:03:47
  and Chevrolet, um, Oakland then became part of Chevrolet and, you
• 1:03:53
  know, adopted the Pontiac Moer.
• 1:03:55
  And then what Pontiacs were was slightly more at market from Chevrolet, and
• 1:04:00
  certainly not a Buick or a Cadillac.
• 1:04:02
  You know, there was, there was that differentiation taken place to achieve
• 1:04:08
  the AI and data interoperability.
• 1:04:12
  They create an abstraction layer.
• 1:04:15
  To automate many smaller integrations.
• 1:04:20
  That thing that we talked about a moment ago, the the way it does
• 1:04:24
  selective relevant data, the point he made is that however much processing
• 1:04:31
  and bandwidth you've got, it's still critical that you understand what
• 1:04:36
  data's important and what data isn't.
• 1:04:39
  To avoid latency, there's a standards organization called coa.
• 1:04:45
  It's interesting, right?
• 1:04:45
  'cause that's what SAE are.
• 1:04:47
  So it's interesting, what engineers need as they're developing their
• 1:04:52
  products is to create these kind of bodies that allow them to agree that,
• 1:04:59
  you know, we're all gonna use bolts that have the same kind of, of thread.
• 1:05:04
  We're all gonna use the same programming language.
• 1:05:06
  We're all gonna use the same fundamental architecture.
• 1:05:11
  In this case, what he's talking about doing is standardizing can data.
• 1:05:18
  So, so you know, the data that, that the car itself, you know, the language
• 1:05:23
  the car communicates with itself in if, if you like the local area
• 1:05:26
  network of the car, you know the hard.
• 1:05:29
  To share data costs money, different departments, so you know, the suspension
• 1:05:37
  guys don't necessarily wanna share their data with the navigation guys,
• 1:05:42
  even though it might be beneficial for both parties because they feel like
• 1:05:47
  they're giving up some of their internet.
• 1:05:49
  Intellectual property.
• 1:05:50
  So there's sometimes silos within car companies and, and even if, you know,
• 1:05:55
  they were enthusiastic to share the data, who paid for the infrastructure
• 1:06:00
  for the data sharing to take place?
• 1:06:02
  That whole stuff that I used to sell years ago, it's the storage, but it's
• 1:06:07
  also the safe and secure transfer and the safe and secure retrieval of the data.
• 1:06:14
  It's more than, you know, storage is more than just storage.
• 1:06:29
  I wrote in the margin that the guy looked like Harry Hill
• 1:06:33
  and had similar mannerisms.
• 1:06:35
  And I mentioned it because it became more off-put as the, uh, the evening went on.
• 1:06:39
  As I, at first I thought I sort of recognized him, and then I
• 1:06:43
  realized that this was Harry Hill's, serious German engineering cousin.
• 1:06:47
  And the more I thought of him being like Harry Hill, the more the mannerisms
• 1:06:52
  became, you know, it's literally, it could have been, he could have
• 1:06:55
  been Harry Hill's, sort of straight brother, really straight man, brother.
• 1:06:59
  And one of the most interesting parts of, of the evening was when,
• 1:07:03
  uh, he talked about partnering with a company called NXP.
• 1:07:08
  And in other words, this acas software sits on a NXP box.
• 1:07:14
  And, and actually if, if you Google around, if you Google NXP, um, acas
• 1:07:22
  appear as a sort of, you know, partner.
• 1:07:26
  On the MX NXP website, one of the guys NXP, also based in borough, one of the
• 1:07:35
  questions from the audience was, was about whether or not NXP could exist without
• 1:07:41
  a CAS or a CAS could exist without NXP.
• 1:07:46
  And what the guy was probing around was whether you actually, whether
• 1:07:51
  the OEMs actually needed the acas software or if they could just get
• 1:07:58
  away with just using the the NXP.
• 1:08:02
  And the answer to that was that you can just buy NXP.
• 1:08:05
  You don't need to have the acas.
• 1:08:06
  So, so the acas is, I wouldn't quite say a software, I, I wouldn't quite
• 1:08:12
  say a sunroof, but you know, it, it's more something like all wheel drive.
• 1:08:17
  It's, it's something which you need to decide quite early in the process
• 1:08:21
  of developing a car or which, you know, whether you're gonna have
• 1:08:25
  the belt and braces or, or, or not.
• 1:08:28
  The data's controlled by the customer, not acas.
• 1:08:32
  I mean, I, I wrote at this point in my notes that I'd realized
• 1:08:36
  that I was comparing the, the two to together and, and I felt
• 1:08:39
  like both of these presentations were about making money off data.
• 1:08:46
  Not about making money from motors, seats, bodies, nice interiors, any,
• 1:08:52
  all of that is just not on the table anymore, just as your computer has,
• 1:09:01
  you know, some importance as a device.
• 1:09:03
  But it's the software that the computer's running, which is really
• 1:09:07
  the important functionality and the important thing that you are ready
• 1:09:13
  to either pay for or not pay for.
• 1:09:16
  The, the device itself, there's a little bit of fashion accoutrement,
• 1:09:20
  uh, uh, about it, but, but beyond that, it's just a disposable thing that
• 1:09:24
  you just replace every now and again.
• 1:09:26
  It's certainly not something that you do any kind of maintenance on.
• 1:09:42
  Data is controlled by the customer, not acas as, and I'm emphasizing that
• 1:09:47
  because the way that spend framed that quite amusingly was he said, ah, you
• 1:09:52
  guys do the plumbing, but you're not responsible for what gets flushed.
• 1:09:56
  And that is an interesting analogy because that's sort of what we're talking
• 1:10:02
  about with these platforms like X and, you know, meta or, or, or whatever.
• 1:10:08
  And the, the level of, of censorship or mediation or whatever you want to call
• 1:10:14
  it, that we feel is it the platform's responsibility to ensure safety.
• 1:10:18
  That's what we're driving at here.
• 1:10:21
  And, and, uh, they're not offering a solution to who owns the data.
• 1:10:28
  They're not offering a solution to who stores the data.
• 1:10:33
  All their offering is a way in which you can package it up and
• 1:10:38
  make money out of it as a OEM.
• 1:10:41
  They're selling a way for OEMs to make money.
• 1:10:45
  You know, they're selling shovels in the gold rush of automobile
• 1:10:50
  makers rushing to sell data.
• 1:10:53
  This is, these are the shovels.
• 1:11:11
  Now, his version of, you know, the ravioli box being separate from
• 1:11:16
  the salad box, being separate from the, you know, salmon pasta box.
• 1:11:21
  Um, his version of that was z uh, the A zoned architecture.
• 1:11:26
  Well, he actually said a zoned architecture was evolving.
• 1:11:30
  So in other words, you know, that was, was already taking place.
• 1:11:33
  There was already, you know, already the, the salad of breaking was
• 1:11:38
  totally separate from the in-car entertainment of the river early.
• 1:11:56
  I was amused that both presenters used the same graphic when talking about,
• 1:12:02
  you know, different systems on the car.
• 1:12:04
  And they got some slide that had a car in profile with dots on it.
• 1:12:08
  And, you know, their bullet points going off from, from the, from the dots.
• 1:12:11
  And I was amused.
• 1:12:13
  I was amused.
• 1:12:13
  They used the same image.
• 1:12:15
  It's a recurring theme in automotive presentations that there are a couple of
• 1:12:21
  images which seem to get used over and over again and it makes you realize how.
• 1:12:27
  Linear.
• 1:12:28
  The narrative has been, if we are looking at the same photos over and over, our
• 1:12:33
  thinking seems to be very, very linear.
• 1:12:36
  And these two guys had the same image, you know, coincidence.
• 1:12:41
  Yes.
• 1:12:42
  But you know, maybe there's something more to it.
• 1:12:59
  So to that point that you get up in the morning, you back the car out the
• 1:13:03
  driveway, um, and you're set off to work, the car you're driving is not the
• 1:13:07
  same car as it was the night before.
• 1:13:10
  It's not right.
• 1:13:11
  It's not because the AI is what's updating over the airwaves.
• 1:13:18
  I. It's not that, oh, you know, not like your laptop at the moment where,
• 1:13:20
  oh, it's got like a new version of the software and you know, then you, you
• 1:13:25
  have to reboot and then you carry on.
• 1:13:27
  It's not like that.
• 1:13:28
  It's the, it's, so it's actually going to make different decisions
• 1:13:35
  now than it did the night before.
• 1:13:37
  Better decisions now, I'm sure.
• 1:13:40
  I mean.
• 1:13:41
  Driving is about control, isn't it?
• 1:13:44
  That is about completely yielding control and not even knowing you could
• 1:13:50
  get in the car and drive it, and the AI parameters could be changed completely.
• 1:13:54
  It could have changed into Junior Johnson mode, and you'd been none wiser.
• 1:14:14
  So to sum up, then, acas had.
• 1:14:17
  These five ways in which they, they could help.
• 1:14:20
  I did take a photo.
• 1:14:21
  I might link to it if I can, but you know, if you're listening to
• 1:14:26
  this presentation, it's enough.
• 1:14:28
  I think you know, the takeaway is, is that structure to make money outta
• 1:14:32
  the data is being put in place, even as the securing and legal clarity
• 1:14:41
  around who actually owns the data and who has the right to do what with it.
• 1:14:45
  Even as that remains completely opaque.
• 1:14:47
  The method to make money out of the data is taken shape.
• 1:14:52
  Thank you.
• 1:14:52
  Drive through
• 1:14:59
  black
• 1:15:03
  down your soul to the God's.
• 1:15:05
  Rock and roll
• 1:15:10
  black.
• 1:15:14
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