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Speaker 1: All zone media. Wake up, everybody, I've got a new podcast.

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Speaker 1: This is Better Offline and I'm your host ed ze Tron.

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Speaker 1: Last week, the National Highway Traffic Safety Administration released a

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Speaker 1: damning report about Tesla's autopilot and its full self driving systems,

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Speaker 1: which the nhtdsay referred to as not adequately ensuring that

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Speaker 1: drivers maintain their attention on the driving task. One second, though,

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Speaker 1: to delineate between the systems, autopilot is more like a

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Speaker 1: sixty version of cruise control keipping your car and lanes,

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Speaker 1: changing lanes when you hit a thing, hitting the indicator,

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Speaker 1: and following the car in front of you on the

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Speaker 1: highway very basic. Full self driving is when your car

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Speaker 1: drives itself. It makes turns, you tell it where to

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Speaker 1: go on the GPS, and it goes through intersections, follows lights,

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Speaker 1: and a bunch of other things it appears to not

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Speaker 1: really be capable of doing, with the NHTSA saying that

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Speaker 1: both autopilot and full self driving created a trend of

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Speaker 1: avoidable crashes involving hazards that would have been visible to

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Speaker 1: an attentive driver. The report, which covers the period between

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Speaker 1: January twenty eighteen and August twenty twenty three, described a

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Speaker 1: critical safety gap to quote CNBC's Laura Colodney in the

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Speaker 1: autopilot's system, which contributed to at least four hundred and

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Speaker 1: sixty seven collisions resulting in at least thirteen fatalities and

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Speaker 1: forty nine injuries. Musk has recently tried to convince investors

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Speaker 1: that Tesla is now all in on AI and his

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Speaker 1: flimsy dreams of having a robotaxi company. This somehow also

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Speaker 1: resulted in Musk firing the majority of the team behind

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Speaker 1: the one Tesla product Everybody Likes It's supercharger network, leaving

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Speaker 1: the status of the North American charging standard created with

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Speaker 1: Tesla's help in jeopardy. To explain what the hell is

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Speaker 1: going on with Tesla, I brought in Ed Niedermeyer, who

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Speaker 1: has been writing and commenting on the auto industry and

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Speaker 1: mobility text since two an a. He's the author of Ludicrous,

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Speaker 1: The Unvarnished Story of Tesla Motors, and the co host

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Speaker 1: of the Autono cost He lives in Portland, Oregon. I'm

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Speaker 1: really happy to talk to him, okay, Ed, So please

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Speaker 1: tell me what has been happening in the world of

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Speaker 1: elon Musk. In the last two weeks, I want to.

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Speaker 2: Say, there's a lot, a lot of a lot has

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Speaker 2: been happening, and I think, you know, a lot of

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Speaker 2: it has really deep roots. Like a lot of the

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Speaker 2: things that are happening are are so dramatic right now,

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Speaker 2: but they've been sort of been building towards us for

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Speaker 2: a really long time. I would say, like at a

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Speaker 2: high level, what appears to be happening is essentially, you know,

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Speaker 2: Tesla as a as a stock, as a perception, as

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Speaker 2: a set of stories and dreams that that Elon Musk

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Speaker 2: has been weaving for for many years now has essentially

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Speaker 2: overtaken Tesla as as a as a company, as a

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Speaker 2: real thing. And I think, you know, from the very

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Speaker 2: beginning of sort of stumbling onto this company, the defining

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Speaker 2: characteristic of Tesla is this gap between perception and reality.

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Speaker 2: And you know, I've written a lot about the problems

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Speaker 2: that Tesla has as a company, and yet you know,

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Speaker 2: for five years, much longer really five years since my

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Speaker 2: book came out, you know, Elon Musk has been able

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Speaker 2: to sort of use perception to kind of make a

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Speaker 2: lot of those issues not matter through raising money or

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Speaker 2: you know, sort of creating diversions and all kinds of

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Speaker 2: other things. And I think what's happening now is that,

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Speaker 2: you know, the the problems with the car business are

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Speaker 2: so fundamental the and and there's nothing in place to

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Speaker 2: sort of solve them. And in the car business, you know,

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Speaker 2: things take time. Problems take time to solve, especially problems

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Speaker 2: like we don't have good new product that can compete

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Speaker 2: in the market. And so you know, we've sort of

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Speaker 2: reached this point now where it seems like Elon is

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Speaker 2: not even really trying to save the reality of this

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Speaker 2: business and is sort of all in on perception. And

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Speaker 2: that's sort of taking a bunch of different forms.

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Speaker 1: So in practice, though, what does it mean that it's

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Speaker 1: escaped reality?

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Speaker 2: So you know, Tesla's a very nearly a two million

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Speaker 2: unit a year car business, and having built that up

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Speaker 2: from nothing is like incredible, Like it's a historic achievement

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Speaker 2: in the world of cars. The problem is is that

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Speaker 2: that seems to have peaked, right, So they did about

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Speaker 2: one point eight five million last year, and essentially sales

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Speaker 2: are going down and they are slashing prices and slashing

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Speaker 2: margins as fast as they can to keep that decline

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Speaker 2: from getting any worse. But really what happened is that

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Speaker 2: is that during COVID they were able to print through

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Speaker 2: a number of sort of unique set of circumstances, they

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Speaker 2: were able to sort of print really impressive profits that

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Speaker 2: made this business seem very very real, and it was

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Speaker 2: very very real. The problem is has created this complacency.

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Speaker 2: In order to record those profits, they've basically been starving

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Speaker 2: research and development and new product investment in new product.

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Speaker 2: And so now now that sales are declining, you know,

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Speaker 2: they can cut the prices to kind of slow that decline,

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Speaker 2: but the only thing that's going to actually turn it

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Speaker 2: around is new is actual new product, and those investments

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Speaker 2: haven't been made. And and he had the opportunity on

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Speaker 2: the call to say, you know, we understand the problem.

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Speaker 2: We're taking it seriously. And he sort of vaguely mentioned

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Speaker 2: like new product is coming, but he did not sort

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Speaker 2: of describe it in in the kind of credible way

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Speaker 2: that that is, you know, sort of makes it clear

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Speaker 2: that that there is actually a plant to solve that problem.

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Speaker 1: And that was the latest invest the cult just to

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Speaker 1: be specifics yeah.

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Speaker 2: And and so instead of that, right, he's he's gone

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Speaker 2: all in on this idea that Tesla's an AI company,

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Speaker 2: that it's a you know that's self driving this. They're

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Speaker 2: going to show a robotaxi, you know, and and and

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Speaker 2: that's that's pumping the stock, right, that's doing the thing

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Speaker 2: that that traditionally happens. The problem is is that those

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Speaker 2: things don't make any money, Like, they don't even make revenue,

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Speaker 2: let alone profit, right.

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Speaker 1: And uh, the AI site lose the money.

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Speaker 2: Yeah, yeah, and and again you know what's what's really

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Speaker 2: puzzling and troubling about what's going on right now is is,

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Speaker 2: you know, Tesla has on paper something like thirty billion

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Speaker 2: dollars in cash a little bit less, right, which is

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Speaker 2: enough to really solve like a lot of these problems.

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Speaker 2: And if and if he gone on on that call

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Speaker 2: and said, you know, we're gonna we're gonna take ten

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Speaker 2: billion dollars and we're gonna use it to to really

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Speaker 2: like invest in a whole new generation of products and

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Speaker 2: give them some detail about what that was, you know,

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Speaker 2: I think things would be we would be having a

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Speaker 2: very different conversation right now. And instead they're spending what

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Speaker 2: are they spending money on? They've been spending on since

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Speaker 2: the pandemic, you know, the cyber truck, you know, and

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Speaker 2: and now sort of lots of GPUs. They they're in

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Speaker 2: like this race to buy more of an Nvidia's production

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Speaker 2: than you know, these other big and by the way,

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Speaker 2: very very profitable tech companies.

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Speaker 1: Can I just ask a quick question though? You say

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Speaker 1: these GPUs so like the ones used to train models

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Speaker 1: and run models like Cope and Ai. All these the

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Speaker 1: same GPUs that Mosk bought for Xai his AI company

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Speaker 1: attached to Twitter, or these a completely different set.

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Speaker 2: Presumably they're completely different. You know, Tesla is a publicly

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Speaker 2: traded a publicly traded company and X's is private. So

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Speaker 2: you know that said he does also very much, you know,

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Speaker 2: blur these these boundaries within his sort of empire, and frankly,

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Speaker 2: you know, in ways that are not always strictly legal.

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Speaker 2: So there may be it may be that Tesla is

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Speaker 2: using some of Xai's hardware and vice versa. It's hard

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Speaker 2: to know for sure.

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Speaker 1: So walk me through this NHTSA report what happened there?

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Speaker 1: Because it looks bad?

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Speaker 2: Yeah, so some history is kind of important here, right, So,

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Speaker 2: so first of all, you know, the Tesla has admitted

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Speaker 2: that crashes have involved autopilot including fatal one since twenty sixteen.

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Speaker 2: The very first time, right, and people don't always know

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Speaker 2: it was a guy in China whose family had the

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Speaker 2: brilliant idea of, you know what if we like maintain

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Speaker 2: chain of custody on the vehicle data. And that was

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Speaker 2: the first time that Tesla admitted, oh yeah, out of

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Speaker 2: pilot was actually involved. And so this may have been

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Speaker 2: going on for even longer than anyone realizes. NTSB, which is,

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Speaker 2: you know, this investigative body. They don't have any regulatory power,

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Speaker 2: but they're really good investigators. They mostly look at air crashes.

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Speaker 2: They were really early and looking at three fatal crashes

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Speaker 2: that happened between twenty sixteen and twenty eighteen. And they

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Speaker 2: concluded essentially that Tesla's system looks sort of self driving enough,

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Speaker 2: but it operates in areas you're allowed to use it

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Speaker 2: in places where it doesn't it's not designed for, and

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Speaker 2: people become complacent and they stop paying attention. It's not

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Speaker 2: good enough to trust your life to. It's just good

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Speaker 2: enough to kind of make you complacent and not paying

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Speaker 2: attention when when it runs into something it can't handle.

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Speaker 1: And these are the findings of the old report.

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Speaker 2: This is the NTSB. Yes, there's a different body, and

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Speaker 2: they recommend it to NITSA, who has maybe less good

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Speaker 2: at investigating stuff like this, especially with human factors, but

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Speaker 2: has all the regulatory power. And they said, look, this

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Speaker 2: is a problem, you know, And knits A had an

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Speaker 2: enforcement guidance at the time that said, you know, if

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Speaker 2: the a system like autopilot, you know, is prone to

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Speaker 2: foreseeable misuse, you know, that can be a defect and

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Speaker 2: we can recall it. And yet somehow that was never

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Speaker 2: used from twenty sixteen, and it wasn't until twenty twenty

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Speaker 2: one that NITSA finally said. You know, they did two

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Speaker 2: things essentially the summer of twenty twenty one, they opened

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Speaker 2: an engineering analysis of autopilots, sort of the first step

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Speaker 2: towards identifying a defect and ordering a recall. They also,

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Speaker 2: at the same time, and the connection here was not

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Speaker 2: always obvious, they started collecting data from across the industry

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Speaker 2: and so now when you have crashes that involve any

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Speaker 2: of the other sort of level two driver assistant systems

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Speaker 2: out there, you have to report that to the government.

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Speaker 2: So they've been simultaneously since the summer of twenty one

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Speaker 2: investigating Tesla specifically, but then also collecting data from the

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Speaker 2: rest of the industry to kind of get a sense

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Speaker 2: of of, you know, is this a unique problem to Tesla,

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Speaker 2: And pretty clearly the answer to that was yes, because

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Speaker 2: what we've learned is that in December of twenty twenty three,

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Speaker 2: you know, they they basically took you know, the these

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Speaker 2: findings that showed, you know, a good deal of of

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Speaker 2: crashes happening, including fatal ones, and basically forced Tesla to

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Speaker 2: do a recall. They did that in December over two

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Speaker 2: million vehicles, and they did it with an over the

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Speaker 2: air software update. And for me, you know, having watched

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Speaker 2: nits a sort of drag its heels frankly or at

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Speaker 2: least move very very slowly to address what I think

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Speaker 2: is a it's been a pretty understandable problem and and

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Speaker 2: a recall worthy problem for for a long time now.

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Speaker 2: I kind of thought, you know, okay, they're going to

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Speaker 2: take let Tesla do a software update, pretend like something

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Speaker 2: has happened, and sort of move on. The thing is

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Speaker 2: is that we were still seeing crashes happen. In fact,

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Speaker 2: there was a fatal crash literally the day before. Uh,

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Speaker 2: you know this this most recent earnings call. And so

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Speaker 2: now what what Nitsa's is doing is they're actually looking

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Speaker 2: into the remedy to that recall. They're saying, you know, well,

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Speaker 2: we're we because these things keep happening, we may we

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Speaker 2: think that maybe just updating the software wasn't enough to

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Speaker 2: actually fix this problem. That to me is it's a

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Speaker 2: very rare for NITSA to do one of these it's

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Speaker 2: called like a recall query. Uh, it's very rare for

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Speaker 2: them to do that. That strongly suggests that that that

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Speaker 2: they're really actually going to hold Tessel.

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Speaker 1: To account on recall query something that happened before this

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Speaker 1: new report, or is that what this current report is.

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Speaker 2: So this so what's really interesting is is that this

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Speaker 2: report is essentially the results of nitsa's investigation over since

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Speaker 2: since twenty twenty one essentially, And and they go through

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Speaker 2: and they describe sort of, you know, how they found

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Speaker 2: out about all these different kinds of crashes and how

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Speaker 2: they sort of analyze them and basically about half of

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Speaker 2: them they were able to kind of throw them out

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Speaker 2: right away, and then from the other half they're able

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Speaker 2: to drill down and identify, you know, a number of

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Speaker 2: kinds of crashes that to keep happening that are all

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Speaker 2: indicative of this problem that you know NTSB identified, you

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Speaker 2: know way back in twenty eighteen, twenty nineteen, twenty twenty

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Speaker 2: and and so so what was interesting is is that

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Speaker 2: data is they had taken that to Tesla and basically,

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Speaker 2: reading between the lines, strong arm them into the recall.

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Speaker 2: And that's often how recalls happen is that either either

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Speaker 2: the automaker does it voluntarily or the or the investigator

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Speaker 2: or the regulator brings a body of evidence to them

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Speaker 2: and says, listen, like you either do this or we're

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Speaker 2: gonna or we're gonna do it for you.

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Speaker 1: So, so this nh TSA report, is it does it

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Speaker 1: do anything? Or is it just is this something Tesla

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Speaker 1: received before it came out? Like how was this delivered

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Speaker 1: and what happens as a result of it.

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Speaker 2: So, so usually this stuff usually what happens is that

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Speaker 2: right they build up this this body of evidence, they

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Speaker 2: take it to the automaker, they essentially use it to

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Speaker 2: force them into a recall, and then once the recall happens,

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Speaker 2: usually you never see it. It doesn't become public. So

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Speaker 2: the fact that this is public is huge.

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Speaker 1: Yeah, that was what confused me. This feels like a

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Speaker 1: strange document for everyone to see.

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Speaker 2: Yeah, and it is absolutely I mean, look, everything about

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Speaker 2: this is kind of novel territory. NITSA has not really

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Speaker 2: gotten into this sort of automated driving driving assistant stuff before,

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Speaker 2: so there's no playbook here. But within the context of

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Speaker 2: automotive regulation, it is rare and and and what it

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Speaker 2: implies is that they forced this recall. Tesla did the

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Speaker 2: easiest thing possible, which is, we'll just update the software

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Speaker 2: over the air.

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Speaker 1: And NITSA, what did that update do if you if

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Speaker 1: you've used it?

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Speaker 2: So so it appears have been a couple of them.

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Speaker 2: And and I think and that's one of the things

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Speaker 2: Nissa's looking into is exactly what what did you do?

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Speaker 2: But but fundamentally, the only thing that they really could

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Speaker 2: do was to essentially create a lot more nags in

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Speaker 2: the system. And nature when you know, you have the

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Speaker 2: hands off the wheel or whatever, and and the system

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Speaker 2: is like, you know, take control, take control, take control.

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Speaker 2: What people love, what consumers love about autopilot is that

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Speaker 2: it doesn't do that very much, right. It kind of

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Speaker 2: lets you sort of sit back, which is which is

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Speaker 2: the problem. Right, people like the unsafety.

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Speaker 1: The feature and the problem it seems exactly yeah.

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Speaker 2: And so and so you know, and and by the way,

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Speaker 2: Tesla has has gotten around that sort of by making

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Speaker 2: a very very misleading safety claims, statistical safety claims about autopilot.

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Speaker 2: So people they're getting their cake and they're eating it too, right,

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Speaker 2: They're they're the system is designed really to look self driving,

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Speaker 2: so that kind of helps the stock price. It's it's

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Speaker 2: designed to enable you to kind of look away and

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Speaker 2: do other things that you shouldn't be doing while you're driving,

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Speaker 2: but it comes with this statistic that is comforting where

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Speaker 2: it's like, no, this is actually safer than a human too. So,

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Speaker 2: so Tesla is kind of that. This is why it's

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Speaker 2: so popular. It's the lack of safety with the veneer

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Speaker 2: of a of a fake you know, safety statistic is

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Speaker 2: what's made it so popular. And frankly, this is why

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Speaker 2: I've been skeptical that and it's a wood really do anything.

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Speaker 2: But the fact that they forced the recall. Tesla took

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Speaker 2: the easy route. NITSA could have just said, yeah, okay,

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Speaker 2: we we've gone through the motions here, let's let's move.

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Speaker 2: We've done yeah, let's move on right, But instead, because

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Speaker 2: these crashes are still happening, you know, NITSA feels the

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Speaker 2: need to to not just say, you know, we need

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Speaker 2: to look at at what you did to address this

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Speaker 2: recall and make sure that it's actually solving the problem. Implicitly,

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Speaker 2: we we don't think it is. But then it also

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Speaker 2: released this this data that that to the public now,

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Speaker 2: so now now all of us can go and look

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Speaker 2: and say, okay, yeah, like there's a reason that this

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Speaker 2: recall happened. This isn't just you know, you know, dark Brandon,

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Speaker 2: you know, cracking down on Elon because because you know,

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Speaker 2: you can't handle his realness or whatever. Yeah, yeah, like

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Speaker 2: this is not just some politically motivated thing like like

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Speaker 2: and this is the flip side of NITSA taking their

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Speaker 2: time on this. As frustrating as it's been, They've built

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Speaker 2: up a lot of data not just about Tesla but

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Speaker 2: about the rest of the industry that shows Tesla does

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Speaker 2: have a unique problem here. And I think you know

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Speaker 2: what they're going to show is that is that the

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Speaker 2: update they've done so far isn't going to be enough,

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Speaker 2: and that really leaves Tesla in a pickle because there's

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Speaker 2: not a lot of other great options for fixing these problems.

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Speaker 1: And it seems also that this report basically gives plaintiffs

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Speaker 1: the ability to sue Tesla on some level, it seems

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Speaker 1: like this will create a bunch of litigation oh against

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Speaker 1: the company.

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Speaker 2: Yeah, and there already has been you know Tesla just

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Speaker 2: right also right before this most recent call, they settled

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Speaker 2: a lawsuit dating back to a crash, back to a

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Speaker 2: twenty eighteen that you know that that lossuit have been

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Speaker 2: going on for a really long time. And I'm sure

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Speaker 2: what nis Is done has has played a role in that.

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Speaker 2: Absolutely all this data, everything that KNITSA has put out

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Speaker 2: in the public is just it's just like handing sort

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Speaker 2: of loaded ammunition clips to to all the lawyers out there.

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Speaker 2: And frankly, that's kind of how regulation in this country works.

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Speaker 2: You know, Uh, our regulators will do what they have

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Speaker 2: to when they have to, when when it becomes unfeasible

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Speaker 2: for them to sort of ignore stuff. But generally speaking,

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Speaker 2: a lot of regulation effectively happens through uh, you know, lawsuits,

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Speaker 2: through civil civil legal litigation.

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Speaker 1: So do you think that this leads to them actually

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Speaker 1: having to do something with the autopilot or are they

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Speaker 1: just gonna hope that that don't get sued too much.

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Speaker 1: It feels like they may. This feels like a normal

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Speaker 1: company would just pull Auto Pilot entirely.

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Speaker 2: Yeah, So, so I think that's it's gonna it's gonna

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Speaker 2: come to something like that. So because this over there

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Speaker 2: update didn't so, so so they did over their update

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Speaker 2: that that kind of keeps people being nagged more, right,

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Speaker 2: and and A it's anest stopping the crashes from happening,

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Speaker 2: but B it's really eroding what people like about the product.

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Speaker 2: And and essentially again like it gets back to Tesla,

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Speaker 2: you know, is willing to create products that lawyers at

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Speaker 2: other companies would just put the kabash on. They wouldn't

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Speaker 2: let it happen. So so Tesla kind of assuming that

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Speaker 2: nits a you know, is going to find that that

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Speaker 2: the current fix is insufficient. There are sort of two

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Speaker 2: basic routes that that Tesla can take. One is they

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Speaker 2: can dramatically reduce sort of the it's called the control

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Speaker 2: authority and the and the capabilities of the system. Essentially,

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Speaker 2: the the you know, a system, a driver assistant system

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Speaker 2: should be designed to assist the driver and the fundamental

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Speaker 2: flaw of of autopilot is that it actually is more

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Speaker 2: designed to look like it the car is almost self driving,

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Speaker 2: and those are two different things. So instead of the

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Speaker 2: automations assisting you.

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Speaker 1: Yeah, how would they different actually really get into that?

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Speaker 2: Yeah, so okay. So the feature that has the best

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Speaker 2: proven record of improving safety outcomes is called automated emergency braking,

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Speaker 2: And essentially people don't even know it's on the car.

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Speaker 2: But if you get yourself into a really sticky situation,

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Speaker 2: someone cuts you off something like that, the car will

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Speaker 2: there's forward collision warning. The car will warn you, and

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Speaker 2: then the car will actually break itself that combination of

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Speaker 2: those two things, and again people don't even really know

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Speaker 2: they're there for the most part. You know, something like

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Speaker 2: a forty percent reduction in frontal crashes. Okay, so like

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Speaker 2: proven statistical safety advantage, and it's because the critical piece

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Speaker 2: of it is that you can you don't rely on it.

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Speaker 2: No one sits there and says, oh, it's cool if

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Speaker 2: I just accelerate into you know, this semi truck.

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Speaker 1: Or whatever, I'm just going to crash into various objects

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Speaker 1: and see what happens.

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Speaker 2: Yeah, you don't get this over reliance. But when with

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Speaker 2: these level two systems, and it's a combination of how

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Speaker 2: the system is designed, right, it's designed to look as

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Speaker 2: if it's self driving, convince people itself driving, and then

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Speaker 2: puts the driver in what's called a you know, a

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Speaker 2: vigilance task, which which means, you know, and people are

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Speaker 2: constantly talking about what bad drivers humans are. The reality

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Speaker 2: is we're actually considering we're not evolved to move at

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Speaker 2: these speeds and everything. We're actually pretty darn good at it.

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Speaker 2: We just drive a lot of miles and over those miles,

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Speaker 2: bad things happen. The the what we're worse at than

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Speaker 2: driving are these vigilance tasks. And we know this from

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Speaker 2: research going back one hundred years. And like you know,

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Speaker 2: radar operators in World War Two. You know, you sit

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Speaker 2: there and you force someone to watch a screen and

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Speaker 2: then when you know, one little, you know thing happens,

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Speaker 2: you know, you have to respond within a very very

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Speaker 2: short amount of time. This is called a vigilance task.

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Speaker 2: We're terrible at that. And if you think about, you

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Speaker 2: know what that can mean. You know, things happen fast

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Speaker 2: on the freeway if you're even slightly not paying attention,

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Speaker 2: and all of a sudden there's a situation. You have

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Speaker 2: to be able to read what's going on, decide on

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Speaker 2: the right course of action, and then implement it properly.

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Speaker 2: I mean, this is insanely hard for people to do

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Speaker 2: and and and it creates, you know, these kinds of

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Speaker 2: thing fafety problems. So so you know, I think fundamentally

401
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Speaker 2: this is this is the challenge that tessels up against, right,

402
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Speaker 2: is that is that they're selling this as a safety thing,

403
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Speaker 2: but there's no safety record. You know, IAHS has all

404
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Speaker 2: of the insurance data and they say there's no record,

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Speaker 2: there's no evidence that that any level two system, which

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Speaker 2: is what what these are called, has any measurable impact

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Speaker 2: on safety.

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Speaker 1: And is level four completely autonomous?

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Speaker 2: Yeah, Level four is completely autonomous within a restricted area.

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Speaker 1: Two.

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Speaker 2: Level two is essentially uh automated assistance of of of

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Speaker 2: two axis of control. It's it's kind of confused, but

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Speaker 2: essentially it's it's adaptive cruise control. A lot of cars

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Speaker 2: have adaptive cruise control, and that's where you you have

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Speaker 2: cruise control. It holds the speed and then if there's

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Speaker 2: an obstacle in front of it and matches speed with that.

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Speaker 2: So that's the longitudinal control. And then and then you

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Speaker 2: have lane keeping, which essentially keeps you within a lane.

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Speaker 2: And and then you know, they build on that a

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Speaker 2: little bit by by having you know, a nowtigation. You know,

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Speaker 2: so if you're going to take an exit, it'll start

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Speaker 2: getting you over into the next lane instead of just

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Speaker 2: holding you in one lane. But essentially, you know, these

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Speaker 2: level two systems exist in other brands. Tesla's is the

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Speaker 2: most popular because they've implemented it in a way that

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Speaker 2: makes it seem more self driving than others. And again,

427
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Speaker 2: right that that element is what makes it unsafe. And

428
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Speaker 2: so it sounds hyperbolic, but there's really a very direct

429
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Speaker 2: through line between you know, design decisions that endanger people

430
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Speaker 2: and you know, the stock, because that's what it's for, right,

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Speaker 2: It's not to keep people safe, it's to convince people

432
00:22:39,480 --> 00:22:41,760
Speaker 2: that Tesla's a leader in self driving car technology, which

433
00:22:41,760 --> 00:22:42,399
Speaker 2: they actually aren't.

434
00:22:42,440 --> 00:22:44,960
Speaker 1: Seems not kind of a sham, like he's just trying

435
00:22:45,000 --> 00:22:47,679
Speaker 1: to make it seem autonomous when it's not even good

436
00:22:47,720 --> 00:22:50,760
Speaker 1: at autonomy. Because the people who buy stocks don't seem

437
00:22:50,800 --> 00:22:51,520
Speaker 1: to pay attention.

438
00:22:51,960 --> 00:22:54,480
Speaker 2: Yeah, So I mean it's it's a fascinating situation where yeah,

439
00:22:54,520 --> 00:22:57,920
Speaker 2: like the word right, So then there's the Really it's

440
00:22:57,960 --> 00:23:01,320
Speaker 2: a way of building up this this frankly scam of

441
00:23:01,359 --> 00:23:04,000
Speaker 2: self driving, right, because that's they're getting people to pay

442
00:23:04,119 --> 00:23:07,080
Speaker 2: ten fifteen thousand dollars a car for this full self

443
00:23:07,160 --> 00:23:11,240
Speaker 2: driving you know add on. And people wouldn't do that

444
00:23:11,440 --> 00:23:15,360
Speaker 2: unless they had some reason to think that that, you know,

445
00:23:15,720 --> 00:23:20,399
Speaker 2: this is something that is somewhat near and essentially, again,

446
00:23:20,480 --> 00:23:23,200
Speaker 2: like they have to endanger people to create that perception.

447
00:23:23,440 --> 00:23:26,960
Speaker 2: So a scam is just sort of ripping people off.

448
00:23:27,280 --> 00:23:30,120
Speaker 2: This does more than that. This endangers people in order

449
00:23:30,160 --> 00:23:31,760
Speaker 2: to rip them off. It's almost like we need a

450
00:23:31,800 --> 00:23:34,720
Speaker 2: new word for for how bad this is. You know.

451
00:23:36,320 --> 00:23:41,040
Speaker 1: Yeah, it's interesting because any other company, someone would be

452
00:23:41,119 --> 00:23:44,200
Speaker 1: in prison, someone would be arrested, maybe someone would be

453
00:23:44,240 --> 00:23:46,960
Speaker 1: sued by the government for like billions of dollars. This

454
00:23:47,040 --> 00:23:51,959
Speaker 1: feels like it will continue to kill people unless something changes.

455
00:23:51,960 --> 00:23:54,160
Speaker 1: But it also doesn't sound like Elon Musk will actually

456
00:23:54,280 --> 00:23:54,879
Speaker 1: change anything.

457
00:23:55,160 --> 00:23:57,920
Speaker 2: Well yeah, I mean he's going all in on self driving, right,

458
00:23:57,960 --> 00:23:58,440
Speaker 2: I mean.

459
00:23:58,760 --> 00:24:00,480
Speaker 1: He doesn't seem to be. When he's going all in

460
00:24:00,560 --> 00:24:02,600
Speaker 1: on it, it doesn't seem to be doing anything to might

461
00:24:02,680 --> 00:24:03,520
Speaker 1: get better.

462
00:24:03,720 --> 00:24:07,560
Speaker 2: Well yeah, and that's because fundamentally, the you know, Tesla's

463
00:24:07,600 --> 00:24:10,600
Speaker 2: approach to the technology. They had to find a way

464
00:24:10,640 --> 00:24:13,800
Speaker 2: to make self driving technology work with their existing business model,

465
00:24:14,119 --> 00:24:17,400
Speaker 2: and they did that by using very cheap hardware. Essentially,

466
00:24:18,160 --> 00:24:20,040
Speaker 2: so if you look at way Wayme's really the only

467
00:24:20,080 --> 00:24:22,920
Speaker 2: company that is really actually doing self driving. They have

468
00:24:23,000 --> 00:24:25,639
Speaker 2: robotaxis in San Francisco, and like you may love them

469
00:24:25,720 --> 00:24:28,600
Speaker 2: or hate them, but like it is incredibly impressive to

470
00:24:28,600 --> 00:24:31,080
Speaker 2: be in a completely drivers vehicle in somewhere like downtown

471
00:24:31,119 --> 00:24:34,080
Speaker 2: San Francisco. They're doing it, and they do it through

472
00:24:34,119 --> 00:24:37,480
Speaker 2: two things, like fundamentally, one is that they limit the

473
00:24:37,480 --> 00:24:40,240
Speaker 2: domated operates in so it only operates in San Francisco.

474
00:24:40,320 --> 00:24:42,680
Speaker 2: And then they're you know, they're expanding to new markets.

475
00:24:42,800 --> 00:24:45,240
Speaker 2: But it's not a general solution. You create a model

476
00:24:45,280 --> 00:24:48,919
Speaker 2: that works in a specific area, and then the and

477
00:24:48,960 --> 00:24:50,280
Speaker 2: the other thing you have to do. It's sort of

478
00:24:50,280 --> 00:24:52,679
Speaker 2: like turning it into a board game, right, Like like

479
00:24:53,359 --> 00:24:55,560
Speaker 2: you beat a human, you have to bound the complexity.

480
00:24:55,960 --> 00:24:58,719
Speaker 2: Like in the bounded complexity of go or chess, an

481
00:24:58,760 --> 00:25:01,480
Speaker 2: AI can beat us. The other thing that AI needs to

482
00:25:01,520 --> 00:25:04,480
Speaker 2: beat us at a game is perfect intelligence, I'm sorry,

483
00:25:04,520 --> 00:25:07,720
Speaker 2: perfect information rather which means right in chess or go

484
00:25:07,880 --> 00:25:11,320
Speaker 2: or whatever. You know, everyone knows exactly where each piece is.

485
00:25:11,359 --> 00:25:14,040
Speaker 2: There's no confusion about it. And WEIMO does that with

486
00:25:14,119 --> 00:25:18,520
Speaker 2: these really really robust sensor systems incorporate ldar and radar and.

487
00:25:18,760 --> 00:25:22,159
Speaker 1: Also and where it goes.

488
00:25:22,680 --> 00:25:25,120
Speaker 2: Yeah, so it's the combination of those two things. And

489
00:25:25,119 --> 00:25:27,560
Speaker 2: and the problem is that those two things are incompatible

490
00:25:27,640 --> 00:25:30,919
Speaker 2: with cars. No one is going to spend you know,

491
00:25:30,960 --> 00:25:33,080
Speaker 2: maybe someone would spend three hundred thousand dollars on a

492
00:25:32,960 --> 00:25:35,280
Speaker 2: on a car that they didn't have to drive, but

493
00:25:35,680 --> 00:25:38,600
Speaker 2: but not if it only works in San Francisco. Right

494
00:25:38,800 --> 00:25:40,680
Speaker 2: that live cars have to be able to go wherever

495
00:25:40,760 --> 00:25:42,760
Speaker 2: we want them to go, and they have to have

496
00:25:42,800 --> 00:25:45,600
Speaker 2: a market. You know, they can't be too expensive. And

497
00:25:45,680 --> 00:25:48,600
Speaker 2: so the things that you need to make real self

498
00:25:48,640 --> 00:25:52,480
Speaker 2: driving work just aren't compatible with self driving. And and

499
00:25:52,640 --> 00:25:57,719
Speaker 2: so essentially what they've done is is just use you know,

500
00:25:58,080 --> 00:26:03,880
Speaker 2: cheap hardware that that isn't too expensive and that does

501
00:26:04,080 --> 00:26:06,480
Speaker 2: just enough to make people think that it's self driving.

502
00:26:06,520 --> 00:26:08,120
Speaker 2: And I think you know, one of the things we've

503
00:26:08,200 --> 00:26:12,199
Speaker 2: learned is is, you know, people we bring forward our

504
00:26:12,200 --> 00:26:15,359
Speaker 2: ideas about driving from humans. If you see a human,

505
00:26:15,720 --> 00:26:18,920
Speaker 2: like if you see a kid driving and like doing

506
00:26:18,920 --> 00:26:21,520
Speaker 2: a driver's test, right, Like if you if you can

507
00:26:21,520 --> 00:26:24,159
Speaker 2: do a driver's test, that means for a human that

508
00:26:24,280 --> 00:26:25,919
Speaker 2: you have the basic skills that you can sort of

509
00:26:25,960 --> 00:26:28,600
Speaker 2: generally apply them everywhere. But the problem is that machine

510
00:26:28,640 --> 00:26:32,879
Speaker 2: learning doesn't work that way. Right with machine learning, you

511
00:26:32,920 --> 00:26:37,520
Speaker 2: there's nothing the generalizability of AI is you know, it's

512
00:26:37,520 --> 00:26:40,240
Speaker 2: a huge topic, right, everyone wants to believe in it,

513
00:26:40,600 --> 00:26:43,760
Speaker 2: but certainly when it comes to something that is safety critical,

514
00:26:44,040 --> 00:26:46,040
Speaker 2: where you know, it's it's one thing for a large

515
00:26:46,080 --> 00:26:48,520
Speaker 2: language model to screw up and hallucinate and everyone laughs

516
00:26:48,560 --> 00:26:52,280
Speaker 2: and you know, haha, that's funny when it comes to driving, right,

517
00:26:52,359 --> 00:26:56,080
Speaker 2: what you're doing is you're reconciling a probabilistic system with

518
00:26:56,400 --> 00:26:58,920
Speaker 2: the need for ninety nine point nine nine nine nine

519
00:26:59,240 --> 00:27:00,240
Speaker 2: percent reliability.

520
00:27:00,600 --> 00:27:03,879
Speaker 1: And that point one zero zero zero one percent is

521
00:27:03,880 --> 00:27:05,560
Speaker 1: where people die, yes.

522
00:27:05,640 --> 00:27:09,000
Speaker 2: Because because we drive millions and millions and millions of miles, right.

523
00:27:08,960 --> 00:27:11,800
Speaker 1: And Americans drive too much as well, so that's dangerous

524
00:27:11,880 --> 00:27:16,800
Speaker 1: to our roads are worse and so yeah.

525
00:27:16,680 --> 00:27:19,600
Speaker 2: So what's amazing is is that is that you know

526
00:27:19,680 --> 00:27:22,879
Speaker 2: humans are bad at babysitting. You know, that's essentially what

527
00:27:22,960 --> 00:27:24,600
Speaker 2: it would have forced you to do right, you're babysitting

528
00:27:24,640 --> 00:27:27,440
Speaker 2: like a teenager. Essentially, who's driving. You put a teenager

529
00:27:27,480 --> 00:27:30,160
Speaker 2: behind the wheel, you babysit them. We're not necessarily good

530
00:27:30,160 --> 00:27:33,359
Speaker 2: at that, But from Tesla's perspective, it doesn't matter, because

531
00:27:33,400 --> 00:27:37,520
Speaker 2: what's important is that we get the liability. Right they

532
00:27:37,720 --> 00:27:39,200
Speaker 2: so and like a vehicle.

533
00:27:39,000 --> 00:27:41,679
Speaker 1: Except this report is going to potentially change how that

534
00:27:41,840 --> 00:27:42,840
Speaker 1: is viewed by judges.

535
00:27:43,600 --> 00:27:46,879
Speaker 2: Well, yes, so, so you know Tesla is not so

536
00:27:47,080 --> 00:27:49,959
Speaker 2: so a vehicle becomes self driving when the when the

537
00:27:50,080 --> 00:27:54,040
Speaker 2: manufacturer or the owner operator takes legal liability for it,

538
00:27:54,359 --> 00:27:56,680
Speaker 2: right and and and so essentially, none of what Tesla's

539
00:27:56,720 --> 00:28:00,679
Speaker 2: doing is is is self driving, because it's stakes humans

540
00:28:00,680 --> 00:28:04,080
Speaker 2: with the consequences. And Madeline and Claire at least had

541
00:28:04,080 --> 00:28:06,920
Speaker 2: a great paper a number of years back called moral

542
00:28:06,960 --> 00:28:09,360
Speaker 2: crumple zones. And that's essentially what Tesla's doing is easy

543
00:28:09,480 --> 00:28:13,320
Speaker 2: humans as moral crumple zones. And and and that's you know,

544
00:28:14,200 --> 00:28:16,960
Speaker 2: the way they've architected the system. It's it doesn't give

545
00:28:17,040 --> 00:28:20,800
Speaker 2: us a good chance of catching the system's mistakes. But

546
00:28:20,840 --> 00:28:22,840
Speaker 2: again it doesn't matter because we're just there as the

547
00:28:22,880 --> 00:28:26,399
Speaker 2: crumple zone. We're just there to take the blame for

548
00:28:26,440 --> 00:28:29,680
Speaker 2: the system's mistake from from Tesla's perspective.

549
00:28:29,680 --> 00:28:33,080
Speaker 1: Taking a step back, what does Tesla actually do now?

550
00:28:33,359 --> 00:28:36,800
Speaker 1: What will will they change? Will they just keep sitting there?

551
00:28:36,840 --> 00:28:38,840
Speaker 1: And Ela mus say, it's actually epic that the cause

552
00:28:38,920 --> 00:28:41,360
Speaker 1: kills people. It's good we need we need more babies,

553
00:28:41,400 --> 00:28:43,800
Speaker 1: but we need less adults. Yes, Like what is it?

554
00:28:44,160 --> 00:28:46,680
Speaker 2: So? So, what's happening right now? Right? So sales have

555
00:28:46,760 --> 00:28:49,880
Speaker 2: peaked and they're cutting into their prices in their margins

556
00:28:49,920 --> 00:28:52,520
Speaker 2: in order to keep it, you know, sort of from

557
00:28:52,560 --> 00:28:55,800
Speaker 2: from falling even further. Uh. The problem is is that

558
00:28:56,080 --> 00:28:59,440
Speaker 2: what's left of those margins depend very heavily and and

559
00:28:59,560 --> 00:29:01,960
Speaker 2: just the so the volume, demand and the and the

560
00:29:01,960 --> 00:29:04,480
Speaker 2: profit margins depend very heavily on autopilot and full self

561
00:29:04,560 --> 00:29:08,320
Speaker 2: driving because these are like unique to Tesla, and they're

562
00:29:08,400 --> 00:29:11,520
Speaker 2: unique reasons to buy a Tesla. And and frankly, you know,

563
00:29:11,600 --> 00:29:15,000
Speaker 2: with with full self driving, that's ten fifteen thousand dollars

564
00:29:15,000 --> 00:29:18,760
Speaker 2: per car in an industry where like you know, people

565
00:29:18,840 --> 00:29:21,560
Speaker 2: have massive fights at the at the development level over

566
00:29:21,600 --> 00:29:24,680
Speaker 2: pennies per car. To add ten thousand dollars in pure

567
00:29:24,720 --> 00:29:27,640
Speaker 2: profit on a car, this paper's over a multitude of

568
00:29:27,680 --> 00:29:32,600
Speaker 2: sins financially, you know. And and so if the prospects

569
00:29:32,760 --> 00:29:36,200
Speaker 2: here is that not only are Tesla sales falling, will

570
00:29:36,240 --> 00:29:40,640
Speaker 2: continue to fall, you know, without because there's nothing, there's

571
00:29:40,640 --> 00:29:43,040
Speaker 2: no new product to turn that around. But then also

572
00:29:43,160 --> 00:29:47,720
Speaker 2: you take away this incredible uh, you know, advantage in

573
00:29:47,800 --> 00:29:50,080
Speaker 2: terms of profit margin, right this ten to fifteen thousand,

574
00:29:50,080 --> 00:29:52,960
Speaker 2: even at the take rate is ten percent ten thousand

575
00:29:52,960 --> 00:29:54,800
Speaker 2: and fifty thousand dollars per car. Is you spread that

576
00:29:54,920 --> 00:29:59,000
Speaker 2: over your whole fleet, and and it's it's by auto industry,

577
00:29:59,040 --> 00:29:59,840
Speaker 2: and it is a huge profit.

578
00:30:00,280 --> 00:30:02,760
Speaker 1: But will they have to pull autopilot out.

579
00:30:02,640 --> 00:30:05,760
Speaker 2: If they do? And I again my sense is that

580
00:30:05,840 --> 00:30:08,520
Speaker 2: this is where N's is going. If they pull autopilot,

581
00:30:08,720 --> 00:30:10,760
Speaker 2: you know, all of those same problems also apply to

582
00:30:10,760 --> 00:30:14,080
Speaker 2: full self driving. All of a sudden, Tesla sees another

583
00:30:14,160 --> 00:30:17,240
Speaker 2: reason for their volume to go down. Right, there's people

584
00:30:17,280 --> 00:30:19,200
Speaker 2: who are now not going to buy the car because

585
00:30:19,520 --> 00:30:22,800
Speaker 2: they know it's it's autopilot, isn't safe, and it doesn't

586
00:30:22,800 --> 00:30:25,719
Speaker 2: have those things. But then it turns into a negative margins.

587
00:30:25,880 --> 00:30:28,280
Speaker 2: And the thing is their margins have been compressing, compressing, compressing,

588
00:30:28,720 --> 00:30:29,960
Speaker 2: and they're at the point now.

589
00:30:29,840 --> 00:30:32,440
Speaker 1: It turns into negative margins. Though the auto the car

590
00:30:32,480 --> 00:30:34,800
Speaker 1: business might be the car business. So is there a

591
00:30:34,840 --> 00:30:37,760
Speaker 1: delineation between full self driving and autopilot or are they

592
00:30:37,800 --> 00:30:38,360
Speaker 1: the same thing?

593
00:30:38,440 --> 00:30:41,120
Speaker 2: They're fundamentally the same thing. It's just the autopilot you're

594
00:30:41,160 --> 00:30:43,160
Speaker 2: only supposed to use it sort of on freeways, and

595
00:30:43,160 --> 00:30:46,040
Speaker 2: full self driving you use it sort of on city

596
00:30:46,080 --> 00:30:49,200
Speaker 2: streets and everywhere else. So it's the differences in what's

597
00:30:49,200 --> 00:30:53,040
Speaker 2: called operational design domain. But also the difference is autopilot

598
00:30:53,400 --> 00:30:55,880
Speaker 2: is like the price is built into the cost of

599
00:30:55,880 --> 00:30:58,840
Speaker 2: a Tesla, whereas full self driving is an optional extra

600
00:30:58,880 --> 00:30:59,520
Speaker 2: on top of that.

601
00:31:00,240 --> 00:31:01,640
Speaker 1: So what would get pulled out then?

602
00:31:02,360 --> 00:31:04,200
Speaker 2: I mean, in theory both of them, because they both

603
00:31:04,240 --> 00:31:07,520
Speaker 2: have the same sort of fundamental problem, right, and.

604
00:31:07,160 --> 00:31:10,040
Speaker 1: And Elon actually do this? Though would he actually do

605
00:31:10,080 --> 00:31:13,320
Speaker 1: it is my question because he's he's a dickhead, as

606
00:31:13,360 --> 00:31:16,360
Speaker 1: we well know. But also this is the one thing

607
00:31:16,400 --> 00:31:19,160
Speaker 1: he spent the last month or so, just like autopilot

608
00:31:19,280 --> 00:31:21,440
Speaker 1: is the best part of the business. We don't even

609
00:31:21,480 --> 00:31:24,560
Speaker 1: need the car, like he seems to be selling this

610
00:31:24,680 --> 00:31:25,680
Speaker 1: hard Yeah.

611
00:31:25,760 --> 00:31:29,360
Speaker 2: Yeah, no, So so the Nitsa does you know they

612
00:31:29,640 --> 00:31:32,920
Speaker 2: move so slowly, they're so tentative. They're so uh, you know,

613
00:31:33,240 --> 00:31:36,480
Speaker 2: hesitant to confront an Elon Musk type character, which is

614
00:31:36,480 --> 00:31:39,680
Speaker 2: why this is all taken so long. But they have

615
00:31:39,720 --> 00:31:42,320
Speaker 2: an immense amount of power essentially they can do. They

616
00:31:42,320 --> 00:31:44,960
Speaker 2: can order a mandatory recall, and then they can even

617
00:31:45,440 --> 00:31:48,200
Speaker 2: order a mandatory stop sale. They can say it's illegal

618
00:31:48,240 --> 00:31:52,680
Speaker 2: to sell Tesla's in this country until you essentially deactivate

619
00:31:52,680 --> 00:31:55,520
Speaker 2: the system or or or implement some kind of fix

620
00:31:55,600 --> 00:31:57,360
Speaker 2: that we deem is appropriate.

621
00:31:57,600 --> 00:32:00,240
Speaker 1: So that's probably impossible to fail.

622
00:32:00,240 --> 00:32:04,280
Speaker 2: Though, so so fixing right, So, so there's two ways

623
00:32:04,320 --> 00:32:07,480
Speaker 2: to fix. One is that you dramatically reduce the capability

624
00:32:07,480 --> 00:32:11,840
Speaker 2: of the system and probably increase the nags even further

625
00:32:12,000 --> 00:32:14,880
Speaker 2: and so basically destroy the value that people want. That's

626
00:32:14,880 --> 00:32:17,240
Speaker 2: one way, and that's probably the most likely way. The

627
00:32:17,280 --> 00:32:20,200
Speaker 2: other way is to actually implement like better hardware for

628
00:32:20,280 --> 00:32:22,160
Speaker 2: driver monitoring, because Tesla.

629
00:32:21,920 --> 00:32:24,280
Speaker 1: Uses which would cost tests or a great deal of money.

630
00:32:24,000 --> 00:32:27,560
Speaker 2: And it's really hard, if not impossible, to essentially pull

631
00:32:27,600 --> 00:32:30,880
Speaker 2: your entire fleet in and like actually install hardware that

632
00:32:30,960 --> 00:32:32,840
Speaker 2: you know, you don't have the wiring harnesses for it,

633
00:32:32,880 --> 00:32:35,040
Speaker 2: you don't it In theory, it could be done, but

634
00:32:35,080 --> 00:32:37,920
Speaker 2: I think it's basically economically impossible, and so then you

635
00:32:37,920 --> 00:32:40,360
Speaker 2: have this prospect of all of a sudden, Tesla can

636
00:32:40,400 --> 00:32:44,480
Speaker 2: no longer do autopilot and full self driving, and given

637
00:32:44,600 --> 00:32:46,880
Speaker 2: what's happening with their margins now, Tesla then becomes a

638
00:32:46,920 --> 00:32:49,840
Speaker 2: negative margin business, which means you don't make it up

639
00:32:49,840 --> 00:32:52,880
Speaker 2: on volume. Right, every car you sell you lose money

640
00:32:52,880 --> 00:32:56,480
Speaker 2: on and and one of the ways that I'm you know,

641
00:32:56,520 --> 00:32:58,600
Speaker 2: and I'm I'm sort of along with everyone else, trying

642
00:32:58,600 --> 00:33:02,040
Speaker 2: to puzzle through sort of some of the decisions that

643
00:33:02,080 --> 00:33:05,680
Speaker 2: are being made here. But one one scenario that kind

644
00:33:05,680 --> 00:33:09,000
Speaker 2: of potentially makes this all make sense is that Elon

645
00:33:09,120 --> 00:33:11,640
Speaker 2: kind of gets it that this is going to happen,

646
00:33:11,800 --> 00:33:14,320
Speaker 2: that that NITSA is not screwing around. They don't want

647
00:33:14,360 --> 00:33:17,200
Speaker 2: more deaths on their hands. They're going to they're going

648
00:33:17,240 --> 00:33:20,720
Speaker 2: to force the issue on this, and that that that

649
00:33:20,760 --> 00:33:22,960
Speaker 2: the margins will go negative and there's no new product

650
00:33:23,000 --> 00:33:26,760
Speaker 2: to turn it around. Maybe, you know, Elon really like

651
00:33:27,520 --> 00:33:29,880
Speaker 2: it could explain some of his behavior if he's just

652
00:33:29,920 --> 00:33:32,640
Speaker 2: sort of come to terms with with, you know, the

653
00:33:33,120 --> 00:33:35,480
Speaker 2: core business is going to die and sort of like

654
00:33:35,520 --> 00:33:38,680
Speaker 2: with Twitter, right, you know, he thinks in the way

655
00:33:38,720 --> 00:33:41,040
Speaker 2: his mind works he thinks he can sort of go

656
00:33:41,080 --> 00:33:43,880
Speaker 2: and tell Earth, like, oh, the regulators or the adverage.

657
00:33:43,960 --> 00:33:45,520
Speaker 2: Right in the case of Twitter, he's like, he's like,

658
00:33:45,560 --> 00:33:48,120
Speaker 2: I'm just gonna tell you know, Earth that the advertisers

659
00:33:48,160 --> 00:33:50,800
Speaker 2: killed Twitter. I don't remember that that interview.

660
00:33:51,040 --> 00:33:53,280
Speaker 1: Yeah, so oh oh, I've got it engraved in my brain.

661
00:33:53,440 --> 00:33:56,200
Speaker 2: He he may pull that like. That's that's one of

662
00:33:56,240 --> 00:33:58,920
Speaker 2: the you know, we have to like sort of put

663
00:33:58,960 --> 00:34:02,120
Speaker 2: ourselves in the mind of of someone who's obviously not

664
00:34:02,320 --> 00:34:02,880
Speaker 2: very normal.

665
00:34:04,120 --> 00:34:07,200
Speaker 1: Yeah, I'll say it's my podcast, I don't care.

666
00:34:07,840 --> 00:34:10,239
Speaker 2: Yeah, so so I mean that that may be one

667
00:34:10,239 --> 00:34:12,400
Speaker 2: way to explain all of what's going on, because.

668
00:34:12,160 --> 00:34:14,040
Speaker 1: Otherwise I would just go out and say that the

669
00:34:14,120 --> 00:34:17,480
Speaker 1: wokes of stop Torto pilot, but he would actually pull it.

670
00:34:17,680 --> 00:34:19,239
Speaker 1: You think, well, I mean I.

671
00:34:19,200 --> 00:34:21,120
Speaker 2: Think you would have no choice but to put like

672
00:34:21,120 --> 00:34:25,600
Speaker 2: like I think he's I think right, because because if

673
00:34:25,600 --> 00:34:27,800
Speaker 2: it gets pulled, if he if you can't have autopilot

674
00:34:27,800 --> 00:34:30,560
Speaker 2: and full self driving, it hits the right, it hits

675
00:34:30,560 --> 00:34:32,880
Speaker 2: the volume of sales, it has, the hits the profit

676
00:34:32,920 --> 00:34:34,920
Speaker 2: margin on each sale, and it hits the stock.

677
00:34:35,120 --> 00:34:37,239
Speaker 1: It hits and it kills the Robotaxi idea which was

678
00:34:37,280 --> 00:34:40,000
Speaker 1: already completely stupid. It just kills that you can't have

679
00:34:40,080 --> 00:34:40,640
Speaker 1: that anymore.

680
00:34:40,800 --> 00:34:43,600
Speaker 2: Yeah, yeah, no, and and and even that is a

681
00:34:43,640 --> 00:34:46,239
Speaker 2: weird thing to pivot to as well, because.

682
00:34:46,120 --> 00:34:48,879
Speaker 1: It's just a stupid It's just to be clear, every

683
00:34:48,880 --> 00:34:51,520
Speaker 1: single journalist who wrote about the robotaxi thing without rolling

684
00:34:51,600 --> 00:34:54,360
Speaker 1: their eyes and writing that they were doing so committed

685
00:34:54,440 --> 00:34:57,080
Speaker 1: some level of malpractice. In my opinion, it's just not

686
00:34:57,160 --> 00:34:58,560
Speaker 1: going to happen. It's complete bullshit.

687
00:34:59,800 --> 00:35:03,440
Speaker 2: Yeah, yeah, yeah, I completely agree. I mean, look the

688
00:35:03,600 --> 00:35:06,960
Speaker 2: idea that you know you can do sort of level

689
00:35:07,000 --> 00:35:10,360
Speaker 2: five self driving, which means fully you know, automated, no

690
00:35:10,520 --> 00:35:14,760
Speaker 2: human monitoring or anything, and not in a limited domain,

691
00:35:14,800 --> 00:35:17,360
Speaker 2: but everywhere, Like, no one else is even selling this.

692
00:35:17,760 --> 00:35:20,680
Speaker 2: Tesla's been selling it since twenty sixteen. No one else

693
00:35:20,760 --> 00:35:23,000
Speaker 2: is even selling it. If it were possible, wouldn't one

694
00:35:23,040 --> 00:35:25,239
Speaker 2: company want to compete on it? Right?

695
00:35:25,320 --> 00:35:30,000
Speaker 1: Yes, economics logic, surely this seems very like if you're

696
00:35:30,000 --> 00:35:33,880
Speaker 1: saying that cars are generally thin margin businesses and you

697
00:35:33,920 --> 00:35:36,120
Speaker 1: suddenly have a way to sell software on it, surely

698
00:35:36,160 --> 00:35:38,640
Speaker 1: someone else would try. Someone like Forward, for example, who

699
00:35:38,680 --> 00:35:42,400
Speaker 1: has tons of cash, government subsidies, tons of brand power.

700
00:35:42,560 --> 00:35:45,400
Speaker 1: They would also do this, except if it was too dangerous.

701
00:35:45,520 --> 00:35:47,919
Speaker 2: Yeah, exactly. And so what you do see from Ford

702
00:35:47,960 --> 00:35:49,719
Speaker 2: in general motors and others is that they do they

703
00:35:49,719 --> 00:35:52,320
Speaker 2: have level two systems like autopilot that are for the freeway,

704
00:35:52,360 --> 00:35:55,000
Speaker 2: but they have much more robust driver monitoring and things

705
00:35:55,040 --> 00:35:57,440
Speaker 2: like that. And they're not going around saying, you know,

706
00:35:57,800 --> 00:35:59,600
Speaker 2: you'll be able to you can buy a car that

707
00:35:59,640 --> 00:36:03,160
Speaker 2: will some day drive itself completely by its own, uh,

708
00:36:03,200 --> 00:36:07,640
Speaker 2: anywhere you want to go. Everybody in the business knows

709
00:36:07,680 --> 00:36:09,799
Speaker 2: that that is not serious and has known for a

710
00:36:09,800 --> 00:36:13,800
Speaker 2: really long time. And unfortunately we're in a weird situation

711
00:36:13,920 --> 00:36:16,759
Speaker 2: where it's like no one has called it out, and

712
00:36:16,840 --> 00:36:19,840
Speaker 2: so you know, he's again. It'll be eight years this

713
00:36:20,000 --> 00:36:23,840
Speaker 2: fall that they've started since they've started taking money for

714
00:36:23,840 --> 00:36:27,200
Speaker 2: for this just blatant scam. And and I think the

715
00:36:27,280 --> 00:36:29,480
Speaker 2: reason that people have got that they've gotten away with

716
00:36:29,520 --> 00:36:32,920
Speaker 2: it so far. Obviously it's nothing to do with with

717
00:36:33,080 --> 00:36:35,640
Speaker 2: technical plausibility, although it does sort of tie into, you know,

718
00:36:35,680 --> 00:36:37,920
Speaker 2: the AI hype that we see elsewhere, so people think

719
00:36:37,960 --> 00:36:40,319
Speaker 2: that AGI is near. You know, it kind of makes

720
00:36:40,360 --> 00:36:42,040
Speaker 2: sense why they might think that it might.

721
00:36:41,960 --> 00:36:43,840
Speaker 1: Be because the shadows on the walls of the cave

722
00:36:43,880 --> 00:36:45,280
Speaker 1: that suggests it's possible.

723
00:36:45,600 --> 00:36:48,719
Speaker 2: Yes, But but the real reason, I think is that

724
00:36:49,160 --> 00:36:52,280
Speaker 2: you know, when you say the word self driving car,

725
00:36:53,760 --> 00:36:56,520
Speaker 2: what people would Americans in particular, think is a car

726
00:36:57,040 --> 00:36:58,520
Speaker 2: that drives itself and what is it?

727
00:36:58,640 --> 00:37:01,000
Speaker 1: I mean, that's probably because those the gold damn words.

728
00:37:01,760 --> 00:37:05,000
Speaker 1: But that's the thing. No, No, it's misleading in its face.

729
00:37:05,160 --> 00:37:08,239
Speaker 2: Yeah, yeah, exactly. But but what people don't understand is

730
00:37:08,280 --> 00:37:13,239
Speaker 2: that where autonomous driving actually does work is in these

731
00:37:13,320 --> 00:37:18,520
Speaker 2: robotaxis that are fundamentally different than cars. Right, a car

732
00:37:18,920 --> 00:37:21,000
Speaker 2: you have to be able to buy it and own it,

733
00:37:21,960 --> 00:37:24,600
Speaker 2: and a car also goes anywhere you want to go,

734
00:37:25,600 --> 00:37:28,640
Speaker 2: right and so and so where this technology works, the

735
00:37:28,680 --> 00:37:32,320
Speaker 2: way in which it works is fundamentally different than a car.

736
00:37:32,600 --> 00:37:35,640
Speaker 2: So that's why no one else is trying to make

737
00:37:35,719 --> 00:37:40,080
Speaker 2: a self driving car, right, It's because it's impossible. But

738
00:37:40,080 --> 00:37:41,640
Speaker 2: but Elon's willing to do it. And he gets away

739
00:37:41,640 --> 00:37:44,360
Speaker 2: with it because it's like he's selling a piece, a

740
00:37:44,400 --> 00:37:47,280
Speaker 2: puzzle piece that fits into the empty spot in people's brain.

741
00:37:47,520 --> 00:37:50,480
Speaker 2: He's the only person who's selling the mental model that

742
00:37:50,520 --> 00:37:53,840
Speaker 2: people have for self driving car. And this is why

743
00:37:54,040 --> 00:37:56,280
Speaker 2: with like Wimo is actually doing it. They have actual

744
00:37:56,360 --> 00:38:00,279
Speaker 2: driverless vehicles, you can get actual rides in and and

745
00:38:00,320 --> 00:38:02,719
Speaker 2: no one stops and is like, wait a second, how

746
00:38:02,800 --> 00:38:04,560
Speaker 2: is how is it that they're able to do this?

747
00:38:05,800 --> 00:38:08,880
Speaker 2: You know? But every year Elon says this is ready

748
00:38:08,880 --> 00:38:10,799
Speaker 2: and then and then it's not, like what's the.

749
00:38:10,800 --> 00:38:13,080
Speaker 1: Disconnecting IM saying it would be ready since like twenty

750
00:38:13,160 --> 00:38:15,279
Speaker 1: nineteen as well, he has been talking at his US

751
00:38:15,280 --> 00:38:16,840
Speaker 1: whole about this a minute.

752
00:38:16,520 --> 00:38:19,840
Speaker 2: Yeah he has, he's I mean, even before the official

753
00:38:19,880 --> 00:38:21,680
Speaker 2: announcement of full self driving, he had a number of

754
00:38:21,760 --> 00:38:23,680
Speaker 2: quotes saying he thought it was going to be you know,

755
00:38:23,719 --> 00:38:27,560
Speaker 2: within a year or two. And there's just these long,

756
00:38:27,640 --> 00:38:30,680
Speaker 2: long lists of his quotes. No one has been as

757
00:38:30,719 --> 00:38:34,200
Speaker 2: wrong about this technology as he has. And yet he

758
00:38:34,280 --> 00:38:39,520
Speaker 2: continues to get more confidence and faith, you know, certainly

759
00:38:39,560 --> 00:38:42,640
Speaker 2: from financial markets then even the companies that are like

760
00:38:42,840 --> 00:38:46,120
Speaker 2: proving it and doing it the right way. And I

761
00:38:46,160 --> 00:38:49,640
Speaker 2: think that's a really like troubling commentary on sort of

762
00:38:49,680 --> 00:38:52,360
Speaker 2: the relationship between technology and capital and in our society

763
00:38:52,400 --> 00:38:52,839
Speaker 2: these days.

764
00:39:05,960 --> 00:39:11,040
Speaker 1: So changing subjects slightly, Elon also very recently laid off

765
00:39:11,080 --> 00:39:13,560
Speaker 1: most of the Supercharger team, which to me is one

766
00:39:13,600 --> 00:39:17,160
Speaker 1: of the funnier things he's done because the supercharger network

767
00:39:17,239 --> 00:39:21,000
Speaker 1: for Tesla appeared to be a completely unregulated monopoly where

768
00:39:21,000 --> 00:39:24,520
Speaker 1: everyone gave him free money, and the entire industry had

769
00:39:24,520 --> 00:39:26,560
Speaker 1: started to like, most of the industry had started buying

770
00:39:26,560 --> 00:39:29,359
Speaker 1: into his charging standard. And then they'd said, you know what, Elon,

771
00:39:29,400 --> 00:39:31,600
Speaker 1: we'd actually like you to have more power. Please just

772
00:39:31,960 --> 00:39:34,279
Speaker 1: run this whole thing, and then he fired most of them.

773
00:39:34,320 --> 00:39:35,360
Speaker 1: What the hell happened?

774
00:39:35,920 --> 00:39:39,360
Speaker 2: Yeah, So, at a high level, the weirdest thing about

775
00:39:39,360 --> 00:39:43,600
Speaker 2: all of this is that you know, Tesla has money,

776
00:39:43,680 --> 00:39:46,800
Speaker 2: Like Tesla on paper at least there's almost thirty billion

777
00:39:46,800 --> 00:39:50,279
Speaker 2: dollars in cash, and so it should be spending its

778
00:39:50,280 --> 00:39:51,960
Speaker 2: way out of its problems and not cut it. But

779
00:39:52,000 --> 00:39:55,840
Speaker 2: instead Elon And this is why I think this is

780
00:39:55,880 --> 00:39:58,399
Speaker 2: as much just sort of about him and sort of

781
00:39:58,520 --> 00:40:00,759
Speaker 2: who he is now rather than anything to do with

782
00:40:00,800 --> 00:40:04,040
Speaker 2: the business. Is that he he likes He just cuts

783
00:40:04,040 --> 00:40:06,920
Speaker 2: stuff that's his. It's like, oh, you know, we're having trouble, Like,

784
00:40:07,000 --> 00:40:09,359
Speaker 2: let's get rid of the dead way, let's get rid

785
00:40:09,400 --> 00:40:12,120
Speaker 2: of cost. The problem is is that is that this

786
00:40:12,160 --> 00:40:17,200
Speaker 2: doesn't solve any of his problems. I think with supercharging,

787
00:40:17,320 --> 00:40:22,040
Speaker 2: it's a little different. So so supercharging, like Tesla itself is,

788
00:40:22,440 --> 00:40:25,320
Speaker 2: was a really critical piece of this sort of going

789
00:40:25,440 --> 00:40:27,919
Speaker 2: zero to one with the EV business. Like I think

790
00:40:28,080 --> 00:40:30,960
Speaker 2: you know, when Tesla at first got started, they had

791
00:40:31,000 --> 00:40:33,319
Speaker 2: to do something like the supercharger network, right, it was

792
00:40:33,400 --> 00:40:35,480
Speaker 2: there was it wasn't really optional, like if it was

793
00:40:35,600 --> 00:40:37,279
Speaker 2: key part of growing their market.

794
00:40:37,200 --> 00:40:39,040
Speaker 1: Yeah, because none could judge the cause otherwise.

795
00:40:39,160 --> 00:40:42,359
Speaker 2: Yes, And as long as it was Tesla exclusive, it

796
00:40:42,400 --> 00:40:46,040
Speaker 2: was an increasingly over time as competition got got better,

797
00:40:46,480 --> 00:40:50,439
Speaker 2: it became sort of the reason to buy Tesla's When

798
00:40:50,480 --> 00:40:54,319
Speaker 2: he opened it to others, that changed, right then all

799
00:40:54,360 --> 00:40:57,000
Speaker 2: of a sudden, it's no longer you know, well, if

800
00:40:57,000 --> 00:40:59,080
Speaker 2: you want access to Tesla superchargers, you have to buy

801
00:40:59,080 --> 00:40:59,440
Speaker 2: a Tesla.

802
00:40:59,560 --> 00:40:59,680
Speaker 1: No.

803
00:40:59,680 --> 00:41:01,120
Speaker 2: No, you can buy a Rivian, you can buy a

804
00:41:01,239 --> 00:41:03,719
Speaker 2: Ford and you get access to those things. It's no

805
00:41:03,800 --> 00:41:07,279
Speaker 2: longer a unique selling point for Tesla, and I think

806
00:41:07,280 --> 00:41:10,200
Speaker 2: that's one of the reasons you've seen demand fall off. Right.

807
00:41:10,200 --> 00:41:12,200
Speaker 2: There's a lot more competition now, and a lot of

808
00:41:12,200 --> 00:41:16,840
Speaker 2: that competition can use the same chargers. I think, you know,

809
00:41:17,239 --> 00:41:21,640
Speaker 2: because it's been so good and so reliable, people assume

810
00:41:21,719 --> 00:41:24,160
Speaker 2: that it's also a good business I'm not sure that

811
00:41:24,160 --> 00:41:27,200
Speaker 2: that's actually the case. Real estate is very expensive. It

812
00:41:27,239 --> 00:41:30,640
Speaker 2: ties up a lot of capital. Yes, they're making probably

813
00:41:30,680 --> 00:41:33,080
Speaker 2: some gross margin on the electricity. They probably sell the

814
00:41:33,120 --> 00:41:35,239
Speaker 2: electricity for more than they buy it for. So there

815
00:41:35,280 --> 00:41:37,360
Speaker 2: is some kind of a business there. But whether or

816
00:41:37,480 --> 00:41:39,960
Speaker 2: not that's paying off the cost of capital in a

817
00:41:39,960 --> 00:41:42,280
Speaker 2: way that would actually be attractive as a standalone business

818
00:41:42,320 --> 00:41:44,840
Speaker 2: is not clear, And I think there's reasons to suspect

819
00:41:44,880 --> 00:41:48,799
Speaker 2: it may not because it is essentially a it's like

820
00:41:48,840 --> 00:41:51,800
Speaker 2: a feature for Tesla cars. It's like sort of putting

821
00:41:51,800 --> 00:41:54,080
Speaker 2: cash on the hood or something like that. Potentially, so

822
00:41:55,239 --> 00:41:58,759
Speaker 2: the business of supertruging has never really been fully disclosed,

823
00:42:00,040 --> 00:42:04,960
Speaker 2: and you know, essentially it seems like maybe this may

824
00:42:05,040 --> 00:42:07,960
Speaker 2: actually be one of the more rational decisions. And in that,

825
00:42:08,680 --> 00:42:11,160
Speaker 2: you know, the business itself may just not be that good,

826
00:42:12,160 --> 00:42:15,120
Speaker 2: you know, Tesla. By opening it up, they'll they'll get

827
00:42:15,160 --> 00:42:20,080
Speaker 2: revenue from other, you know, owners of non Tesla vehicles,

828
00:42:19,600 --> 00:42:23,040
Speaker 2: and in order to make that business look good, they

829
00:42:23,040 --> 00:42:26,680
Speaker 2: simply can't invest more. There's no incentive in them to grow.

830
00:42:27,160 --> 00:42:29,439
Speaker 1: There have been estimates that suggest it's worth like ten

831
00:42:29,480 --> 00:42:32,920
Speaker 1: to twenty billion dollars, like it's actually generating real revenue,

832
00:42:32,960 --> 00:42:34,239
Speaker 1: but we just don't know, do we.

833
00:42:34,560 --> 00:42:37,400
Speaker 2: Yeah, Like a lot of things with Tesla, the accounting

834
00:42:37,480 --> 00:42:39,960
Speaker 2: is very opaque, right, and again, like you know, they

835
00:42:40,000 --> 00:42:42,319
Speaker 2: supposedly have thirty billion dollars in cash or almost thirty

836
00:42:42,360 --> 00:42:44,000
Speaker 2: billion dollars of cash on their books, and yet they

837
00:42:44,080 --> 00:42:47,080
Speaker 2: somehow don't seem able to like meaningfully spend their way

838
00:42:47,080 --> 00:42:49,279
Speaker 2: out of some of these problems. So I you know,

839
00:42:50,080 --> 00:42:51,560
Speaker 2: I'm not a friendsic account and I'm not going to

840
00:42:51,560 --> 00:42:53,480
Speaker 2: make any allegations about them like cooking their books, but

841
00:42:53,520 --> 00:42:57,080
Speaker 2: I do know there's been a lot of suspicion about

842
00:42:57,080 --> 00:43:00,719
Speaker 2: that over the years, and certainly when it comes to Superchargers,

843
00:43:01,120 --> 00:43:03,000
Speaker 2: it's never been broken out in a way that would

844
00:43:03,000 --> 00:43:05,320
Speaker 2: allow you to say, oh, yeah, this is definitely something

845
00:43:05,520 --> 00:43:08,880
Speaker 2: that can stand alone. Frankly, if it were like like

846
00:43:09,200 --> 00:43:11,879
Speaker 2: if he, if it were a standalone business, it would

847
00:43:11,920 --> 00:43:14,680
Speaker 2: be something you could spin out right now or sell

848
00:43:14,680 --> 00:43:15,880
Speaker 2: to a competitor or something.

849
00:43:16,120 --> 00:43:18,320
Speaker 1: Surely it would be something you would volunteer the information

850
00:43:18,440 --> 00:43:20,360
Speaker 1: for as well to show how good Tesla was.

851
00:43:20,440 --> 00:43:23,120
Speaker 2: But you also wouldn't fire the entire team before doing it.

852
00:43:23,520 --> 00:43:25,880
Speaker 1: You also would not do that. No, but talking of

853
00:43:25,960 --> 00:43:29,359
Speaker 1: broken how about that cyber truck? What the hell is

854
00:43:29,400 --> 00:43:30,600
Speaker 1: going on there? Yeah?

855
00:43:30,680 --> 00:43:34,120
Speaker 2: So so again, you know, it's a question of priorities.

856
00:43:34,400 --> 00:43:38,359
Speaker 2: You know, the car business is a capital in tons

857
00:43:38,360 --> 00:43:41,640
Speaker 2: of business. And you know Tesla's been They've had a

858
00:43:41,640 --> 00:43:44,200
Speaker 2: lot of things go well for them, but they've been

859
00:43:44,280 --> 00:43:48,040
Speaker 2: resting on their laurels and and you have to invest

860
00:43:48,080 --> 00:43:50,600
Speaker 2: your money in something in order to keep growth going

861
00:43:50,680 --> 00:43:52,880
Speaker 2: in the car business either, right, you keep explaining the

862
00:43:52,880 --> 00:43:54,839
Speaker 2: superchargers or the you invest in.

863
00:43:54,719 --> 00:43:57,440
Speaker 1: New cars or must cars.

864
00:43:57,520 --> 00:44:01,080
Speaker 2: Yeah, and so the soup, so the the cyber truck

865
00:44:02,360 --> 00:44:05,440
Speaker 2: like in some ways there was it was it was

866
00:44:05,480 --> 00:44:08,200
Speaker 2: a brilliant idea to make a big truck because if

867
00:44:08,239 --> 00:44:11,120
Speaker 2: you can only compete in one car market in the world,

868
00:44:11,400 --> 00:44:14,160
Speaker 2: the combination of volume and profit margin in full sized

869
00:44:14,200 --> 00:44:17,320
Speaker 2: trucks in America is the number one best business period

870
00:44:17,719 --> 00:44:21,440
Speaker 2: right right that that business keeps the Detroit automakers going.

871
00:44:21,480 --> 00:44:23,560
Speaker 2: They barely make any money on anything other than trucks.

872
00:44:23,600 --> 00:44:26,840
Speaker 2: The trucks essentially subsidize most of the rest of their businesses,

873
00:44:27,719 --> 00:44:31,040
Speaker 2: and so and so, you know, targeting that segment was smart. Uh,

874
00:44:31,440 --> 00:44:35,759
Speaker 2: Targeting with essentially a meme was not smart. And I

875
00:44:35,800 --> 00:44:39,160
Speaker 2: think that to me, the cyber truck is a symbol

876
00:44:39,320 --> 00:44:43,680
Speaker 2: of sort of uh, you know, Elon's ego, sort of

877
00:44:43,719 --> 00:44:47,680
Speaker 2: hitting escape velocity, uh, and essentially reaching a point where

878
00:44:47,760 --> 00:44:51,520
Speaker 2: he can no longer take advice, like whether it's just

879
00:44:51,560 --> 00:44:54,200
Speaker 2: in terms of the styling, you know, like like you

880
00:44:54,239 --> 00:44:57,120
Speaker 2: could have you could have done a wedgie truck like

881
00:44:57,160 --> 00:44:59,719
Speaker 2: that and and not made it look like such garbage.

882
00:44:59,760 --> 00:45:02,640
Speaker 2: If if he'd listened to his his dialist Printsman whole

883
00:45:02,640 --> 00:45:05,719
Speaker 2: thousand is certainly talented enough to have made a much

884
00:45:05,760 --> 00:45:08,880
Speaker 2: better design or version of that concept. It was clear

885
00:45:09,080 --> 00:45:11,960
Speaker 2: Elon was like, no, I wanted to be flat and

886
00:45:12,040 --> 00:45:15,160
Speaker 2: straight lines, and I wanted to look like low polygons,

887
00:45:15,400 --> 00:45:15,879
Speaker 2: like like.

888
00:45:15,800 --> 00:45:18,480
Speaker 1: A video game, like the game of Flashback.

889
00:45:19,040 --> 00:45:21,400
Speaker 2: Yeah. And I think it's like in his mind the

890
00:45:22,520 --> 00:45:26,160
Speaker 2: difference between a rendering and reality is like blurry to him.

891
00:45:26,200 --> 00:45:28,239
Speaker 2: I think for him, like if it looks good in

892
00:45:28,280 --> 00:45:31,200
Speaker 2: a rendering, well of course it's gonna it's gonna look

893
00:45:31,239 --> 00:45:34,080
Speaker 2: good in reality. And and you know, the rest of

894
00:45:34,440 --> 00:45:37,600
Speaker 2: all of Tesla's designs have been you know, you can

895
00:45:37,680 --> 00:45:40,520
Speaker 2: definitely tell the quality problems if you know what to

896
00:45:40,520 --> 00:45:42,760
Speaker 2: look for. But they've got these curves and these different

897
00:45:42,760 --> 00:45:43,960
Speaker 2: panels and these things going.

898
00:45:43,760 --> 00:45:46,759
Speaker 1: On, and the guy other than designing them.

899
00:45:47,480 --> 00:45:49,640
Speaker 2: Yeah, well, I mean obviously, as you know, they have

900
00:45:49,680 --> 00:45:53,560
Speaker 2: a designer. It's just that Elon won't listen to anybody.

901
00:45:53,600 --> 00:45:55,839
Speaker 2: I think that's I don't know of any other way

902
00:45:55,840 --> 00:46:00,520
Speaker 2: to explain, right, Like, like the product play, any team

903
00:46:00,560 --> 00:46:03,399
Speaker 2: would tell him. Listen, Elon, Like, we know this full

904
00:46:03,400 --> 00:46:05,640
Speaker 2: sized truck segment. It's so huge. We can build our

905
00:46:05,680 --> 00:46:08,120
Speaker 2: next wave of growth if we get the right product

906
00:46:08,200 --> 00:46:08,840
Speaker 2: to this segment.

907
00:46:09,200 --> 00:46:11,960
Speaker 1: Right, Yeah, they made the model s for trucks like

908
00:46:12,000 --> 00:46:15,560
Speaker 1: an eight eight or one hundred grand fucking brilliant truck,

909
00:46:15,600 --> 00:46:17,680
Speaker 1: which they are fully capable of doing, surely.

910
00:46:17,960 --> 00:46:20,480
Speaker 2: Yeah, well except that, except that Elon doesn't believe in

911
00:46:20,520 --> 00:46:24,520
Speaker 2: market research, rightft true, and and and he goes with

912
00:46:24,600 --> 00:46:26,920
Speaker 2: his gut. And it's like if he thinks it's cool,

913
00:46:27,080 --> 00:46:30,160
Speaker 2: then it's going to work. And I think, right, like,

914
00:46:30,480 --> 00:46:34,320
Speaker 2: this has been true enough for a long time.

915
00:46:34,239 --> 00:46:36,799
Speaker 1: But has it? Okay, I actually want to push back

916
00:46:36,800 --> 00:46:40,800
Speaker 1: on that. Has that actually been true since like twenty sixteen?

917
00:46:41,120 --> 00:46:44,839
Speaker 1: Because what cool idea has Elon Musk had that's worked

918
00:46:44,920 --> 00:46:45,600
Speaker 1: in that time?

919
00:46:47,200 --> 00:46:50,920
Speaker 2: Well since twenty sixteen, So I mean I've always argued

920
00:46:50,920 --> 00:46:54,080
Speaker 2: that that, you know, full self driving was also one

921
00:46:54,080 --> 00:46:56,040
Speaker 2: of the It was really the first time where he

922
00:46:56,160 --> 00:46:58,640
Speaker 2: sort of hit this escape velocity, like he's always had

923
00:46:58,680 --> 00:47:00,000
Speaker 2: these these hypeie kind of things.

924
00:47:00,600 --> 00:47:02,560
Speaker 1: Yeah, it's a good idea. I'm not saying it's not.

925
00:47:02,719 --> 00:47:05,280
Speaker 1: It's just the way he manifest today is the problem.

926
00:47:05,400 --> 00:47:08,440
Speaker 2: Yeah. And and I mean, you know, I think throughout

927
00:47:08,480 --> 00:47:10,200
Speaker 2: the history of the company, right, like so like the

928
00:47:10,719 --> 00:47:13,440
Speaker 2: Tesla Roadster, you know, like originally it was just gonna

929
00:47:13,440 --> 00:47:15,200
Speaker 2: be uh, the original one was just gonna be like

930
00:47:15,239 --> 00:47:17,759
Speaker 2: a lotus of lease with batteries and an electric motor

931
00:47:17,800 --> 00:47:21,680
Speaker 2: shoved into it. Elon kind of both turned it into

932
00:47:21,920 --> 00:47:25,840
Speaker 2: a better product and a product that really established Tesla's brand,

933
00:47:26,200 --> 00:47:28,719
Speaker 2: but also killed the financial viability of it at the

934
00:47:28,719 --> 00:47:32,239
Speaker 2: same time. Uh, you know, and and and and at

935
00:47:32,280 --> 00:47:35,040
Speaker 2: that point, right it was all about building up hype.

936
00:47:35,040 --> 00:47:37,000
Speaker 2: It didn't have to perform as a business. He could

937
00:47:37,320 --> 00:47:40,799
Speaker 2: he could emphasize sort of brand building and looks and

938
00:47:40,840 --> 00:47:44,480
Speaker 2: feel over the profitability because it was an early stage.

939
00:47:44,480 --> 00:47:46,719
Speaker 2: It was you know there they're pure play. You know,

940
00:47:46,760 --> 00:47:49,719
Speaker 2: it's it's experimental. Yeah, yeah, so we just use it

941
00:47:49,719 --> 00:47:51,480
Speaker 2: to raise more money. And then and then we'll get

942
00:47:51,480 --> 00:47:52,760
Speaker 2: serious right the process.

943
00:47:52,800 --> 00:47:55,040
Speaker 1: They've just never released the second Road stuff. It's just

944
00:47:55,120 --> 00:47:57,879
Speaker 1: never coming out. No, No, it's fucking insane. Like there's

945
00:47:57,920 --> 00:47:59,439
Speaker 1: so many people have written about this thing.

946
00:47:59,360 --> 00:48:01,520
Speaker 2: Well, and people put money down on it. Remember the

947
00:48:01,760 --> 00:48:04,399
Speaker 2: Founder's edition, people put down fifty at the entire full

948
00:48:04,440 --> 00:48:06,319
Speaker 2: price two hundred fifty thousand dollars up.

949
00:48:06,360 --> 00:48:09,360
Speaker 1: It's good. That is bonkers. That is come on.

950
00:48:10,000 --> 00:48:12,279
Speaker 2: But but like this is the thing with Tessel too, though,

951
00:48:12,320 --> 00:48:14,520
Speaker 2: is that like, once you get away with something for

952
00:48:14,560 --> 00:48:18,360
Speaker 2: a while, how do you then decide, Okay, this is

953
00:48:18,360 --> 00:48:20,480
Speaker 2: not actually acceptable? And I think this is kind of

954
00:48:20,520 --> 00:48:23,520
Speaker 2: the problem that full self driving an autopilot are having, right,

955
00:48:23,640 --> 00:48:26,239
Speaker 2: and I think hopefully knits A, you know, will take

956
00:48:26,280 --> 00:48:28,319
Speaker 2: action and that will be it. It's the government, right,

957
00:48:28,400 --> 00:48:32,880
Speaker 2: like they should be the ones who step in. And frankly,

958
00:48:32,920 --> 00:48:34,480
Speaker 2: I think, you know, if you want to look at

959
00:48:34,960 --> 00:48:38,479
Speaker 2: you know, who's what what does this whole story sort

960
00:48:38,480 --> 00:48:41,600
Speaker 2: of point to in terms of being the underlying problem.

961
00:48:41,680 --> 00:48:44,440
Speaker 2: It's not Elon really in the sense that Elin's just

962
00:48:44,480 --> 00:48:47,520
Speaker 2: following incent his incentives, Like he's come out of a

963
00:48:47,560 --> 00:48:50,200
Speaker 2: situation where it's okay to kind of lie and and

964
00:48:50,600 --> 00:48:54,200
Speaker 2: exaggerate and in order to make yourself wealthy. And he's

965
00:48:54,239 --> 00:48:55,960
Speaker 2: been good at that, and so he's just kind of

966
00:48:56,120 --> 00:49:00,000
Speaker 2: continuing to follow the incentives there. The real failure is

967
00:49:00,120 --> 00:49:03,799
Speaker 2: is law enforcement and regulators, right, Like, as a society,

968
00:49:04,360 --> 00:49:07,080
Speaker 2: you know, you have someone who's endangering what's already a

969
00:49:07,160 --> 00:49:11,760
Speaker 2: very dangerous activity, making roads even less safe, while lying about,

970
00:49:12,160 --> 00:49:15,319
Speaker 2: you know, claiming that it is safe and doing it

971
00:49:15,360 --> 00:49:19,839
Speaker 2: to become wealthy. Like even if you think it should

972
00:49:19,880 --> 00:49:22,080
Speaker 2: be okay for Elon to do this because he's magic

973
00:49:22,160 --> 00:49:26,080
Speaker 2: and special, the example that it sets right then it

974
00:49:26,120 --> 00:49:28,680
Speaker 2: tells everyone else this is an okay way to become

975
00:49:28,680 --> 00:49:30,919
Speaker 2: the richest man in the world is by endangering other

976
00:49:30,960 --> 00:49:35,319
Speaker 2: people and lying. You know, that is an example. There's

977
00:49:35,320 --> 00:49:37,640
Speaker 2: a society. I don't think we can afford to let

978
00:49:37,719 --> 00:49:39,839
Speaker 2: sort of sit unchallenged, And so I think the real

979
00:49:39,880 --> 00:49:42,880
Speaker 2: failure there here is is just it's the government.

980
00:49:51,120 --> 00:49:52,719
Speaker 1: So I thought that was a really good point to

981
00:49:52,840 --> 00:49:57,360
Speaker 1: end the interview, because while Musk has and continues to

982
00:49:57,400 --> 00:50:00,239
Speaker 1: be and probably will for WHOA, He'll continue to a

983
00:50:00,280 --> 00:50:03,319
Speaker 1: horrifying man that constantly tests how far a billionaire can go.

984
00:50:03,760 --> 00:50:06,560
Speaker 1: The failure to hold Tesla accountable is one that lands

985
00:50:06,560 --> 00:50:09,040
Speaker 1: at the feet of the government and really the media.

986
00:50:09,800 --> 00:50:13,520
Speaker 1: For years, the press has given Musk fairly unquestioning press

987
00:50:13,760 --> 00:50:16,360
Speaker 1: even to this day, though there are some exceptions, people

988
00:50:16,440 --> 00:50:19,920
Speaker 1: like Ednita Bayer, Lourical, Odny Thenett, Lopez al and Nonsmann,

989
00:50:20,360 --> 00:50:23,040
Speaker 1: Preston Grind Ryan Mack. If I left you out, I'm

990
00:50:23,080 --> 00:50:25,800
Speaker 1: really sorry, but this sounds like a lot of people.

991
00:50:26,400 --> 00:50:28,440
Speaker 1: But there are so many more members of the media

992
00:50:28,560 --> 00:50:32,800
Speaker 1: who have just huffed Musks farts. Even last week, Alex

993
00:50:32,880 --> 00:50:38,399
Speaker 1: Cantrowitz of Big Technology. I really really respect Alex. I've

994
00:50:38,560 --> 00:50:41,400
Speaker 1: loved his work since BuzzFeed. I think he's phenomenal, except

995
00:50:41,400 --> 00:50:44,439
Speaker 1: for this. He uncritically published an email from Mask about

996
00:50:44,440 --> 00:50:47,280
Speaker 1: his plans for Grok, the large language model he's bolted

997
00:50:47,320 --> 00:50:50,319
Speaker 1: onto Twitter, and how it will interface with Twitter's news feed,

998
00:50:50,400 --> 00:50:55,439
Speaker 1: generating stories stories from tweets. Now, the big miss here,

999
00:50:55,600 --> 00:50:58,759
Speaker 1: other than just copy pasting something Elon Musk said, was

1000
00:50:58,840 --> 00:51:02,280
Speaker 1: leaving out the fact that Grog has been doing stories already.

1001
00:51:02,320 --> 00:51:07,239
Speaker 1: It's been summarizing the news, including multiple hallucinated stories like

1002
00:51:07,280 --> 00:51:11,160
Speaker 1: one about basketball player Klay Thompson allegedly vandalizing places with

1003
00:51:11,200 --> 00:51:15,680
Speaker 1: bricks after Gok misunderstood that people were referring to him

1004
00:51:15,840 --> 00:51:19,520
Speaker 1: bricking shots in a basketball game very basic English, and

1005
00:51:19,600 --> 00:51:21,880
Speaker 1: even then Grok can't get it. Alex, what the hell

1006
00:51:21,920 --> 00:51:22,399
Speaker 1: are you doing?

1007
00:51:22,440 --> 00:51:22,840
Speaker 2: Mate?

1008
00:51:22,960 --> 00:51:24,640
Speaker 1: I said this on Twitter and I'll say it on here.

1009
00:51:24,800 --> 00:51:26,680
Speaker 1: What are you doing? You are smarter than this. I

1010
00:51:26,760 --> 00:51:29,040
Speaker 1: do not know why you're doing this. No one should

1011
00:51:29,080 --> 00:51:31,319
Speaker 1: be doing this. If Elon must send you something, you

1012
00:51:31,400 --> 00:51:33,520
Speaker 1: give it a critique, you look at it through the

1013
00:51:33,600 --> 00:51:37,439
Speaker 1: fair lens. Because this man is not trustworthy. Elon Musk

1014
00:51:37,600 --> 00:51:41,240
Speaker 1: he half asks everything, He rushes, he tricks, he cheats,

1015
00:51:41,520 --> 00:51:45,200
Speaker 1: he half explains him moreover, he lies. Elon Musk is

1016
00:51:45,280 --> 00:51:47,439
Speaker 1: not someone to take it a word or to treat

1017
00:51:47,440 --> 00:51:50,560
Speaker 1: with the benefit of the doubt. Every time that we

1018
00:51:50,640 --> 00:51:53,719
Speaker 1: buy into whatever weird narrative or made up thing he

1019
00:51:53,920 --> 00:51:56,200
Speaker 1: has about how Tesla will work itself out of a

1020
00:51:56,239 --> 00:51:59,120
Speaker 1: jam or how X will be big. We're helping a

1021
00:51:59,160 --> 00:52:02,920
Speaker 1: man who has acted disingenuously and dangerously and will continue

1022
00:52:02,960 --> 00:52:06,160
Speaker 1: to do so. A man who platforms actual nazis a

1023
00:52:06,239 --> 00:52:10,640
Speaker 1: man that retweets anti Semitic things. This is who we're

1024
00:52:10,640 --> 00:52:13,879
Speaker 1: dealing with. And as I've said before, though, governments must

1025
00:52:13,960 --> 00:52:17,160
Speaker 1: also take Musk a lot more seriously, and they should

1026
00:52:17,160 --> 00:52:20,759
Speaker 1: cut him out of subsidies and programs. I'd say permanently,

1027
00:52:20,960 --> 00:52:23,240
Speaker 1: but at least as long as he continues to release

1028
00:52:23,280 --> 00:52:29,440
Speaker 1: this buggy dangerous software and platforms, racists and insane freaks

1029
00:52:29,440 --> 00:52:32,279
Speaker 1: who would kill people like me. I am Jewish, and

1030
00:52:32,400 --> 00:52:34,399
Speaker 1: I'm confident that some of the people he shared would

1031
00:52:34,400 --> 00:52:37,560
Speaker 1: absolutely murder my ass dead. And that's the thing. This

1032
00:52:37,719 --> 00:52:41,680
Speaker 1: is the guy. This guy has billions of dollars. Elon Musk.

1033
00:52:41,840 --> 00:52:44,760
Speaker 1: He's a liar, he's a scam artist. And it doesn't

1034
00:52:44,960 --> 00:52:48,200
Speaker 1: matter that he's got billions of dollars. One can still

1035
00:52:48,200 --> 00:52:51,279
Speaker 1: be corrupt, selfish, and a complete fucking idiot with that

1036
00:52:51,360 --> 00:52:53,919
Speaker 1: many zeros in the bank. While the threat of Elon

1037
00:52:54,040 --> 00:52:57,360
Speaker 1: Musk is something to take very seriously, though his ideas

1038
00:52:57,400 --> 00:53:00,520
Speaker 1: are most certainly not so, I challenge you, as a

1039
00:53:00,520 --> 00:53:03,680
Speaker 1: member of the media, as a listener, as a consumer,

1040
00:53:04,040 --> 00:53:06,359
Speaker 1: to look at everything he does in the same way

1041
00:53:06,400 --> 00:53:08,719
Speaker 1: you would a teenager that has been lying to you

1042
00:53:08,800 --> 00:53:11,479
Speaker 1: for months. That's who Musk is, and he's been lying

1043
00:53:11,520 --> 00:53:13,799
Speaker 1: a lot longer than a few months. He's been lying

1044
00:53:13,840 --> 00:53:16,800
Speaker 1: for the best part of a decade, and he manages

1045
00:53:16,840 --> 00:53:21,120
Speaker 1: to make money and spiked Tesla's stock every single goddamn time.

1046
00:53:21,400 --> 00:53:25,759
Speaker 1: People like Jim Kramer and his ilk fuel his murderous,

1047
00:53:25,800 --> 00:53:31,000
Speaker 1: genuinely dangerous ideas. I challenge you, whoever this is listening,

1048
00:53:31,360 --> 00:53:41,920
Speaker 1: to think very critically about this man. Thank you for

1049
00:53:41,960 --> 00:53:44,600
Speaker 1: listening to Better Offline. The editor and composer of the

1050
00:53:44,640 --> 00:53:47,719
Speaker 1: Better Offline theme song is Matasowski. You can check out

1051
00:53:47,760 --> 00:53:51,360
Speaker 1: more of his music and audio projects at Mattasowski dot com,

1052
00:53:51,560 --> 00:53:56,600
Speaker 1: m A. T. T OsO w Ski dot com. You

1053
00:53:56,640 --> 00:53:59,120
Speaker 1: can email me at easy at Better Offline dot com

1054
00:53:59,239 --> 00:54:01,080
Speaker 1: or visit better off Line dot com to find more

1055
00:54:01,120 --> 00:54:04,479
Speaker 1: podcast links and of course, my newsletter. I also really

1056
00:54:04,520 --> 00:54:06,719
Speaker 1: recommend you go to chat dot where's youreaed dot at

1057
00:54:06,840 --> 00:54:09,279
Speaker 1: to visit the discord, and go to our slash Better

1058
00:54:09,320 --> 00:54:12,480
Speaker 1: Offline to check out I'll Reddit. Thank you so much

1059
00:54:12,520 --> 00:54:16,320
Speaker 1: for listening. Better Offline is a production of cool Zone Media.

1060
00:54:16,480 --> 00:54:19,319
Speaker 1: For more from cool Zone Media, visit our website cool

1061
00:54:19,360 --> 00:54:22,759
Speaker 1: Zonemedia dot com, or check us out on the iHeartRadio app,

1062
00:54:22,800 --> 00:54:25,480
Speaker 1: Apple Podcasts, or wherever you get your podcasts