Q2 Earnings Call, Robotaxi Trials, & Tesla Diner | Tesla Motors Club Podcast #75 - Tesla Motors Club Podcast

Episode Transcript
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Louis (00:00):
Hey there.
Welcome to another Tesla MotorsClub podcast.
My name is Lewis.
I'm Doug.
In today's episode, we're gonnacover the recent Q2 earnings
call for Tesla.
We'll also go over some TeslaRobotaxi updates.
There's quite a few of them.
Elon is fundraising more forXAI yet again.
There's a new Model Y variant,and possibly more.

(00:22):
And the Tesla Diner has nowopened in LA.
All those things and more inthis episode 75 starts now.
Hey.
That was so many things.
Just to make a note, we don'thave Mike with us today, but he
will be back.
He had a conflict, so he's onvacation.

(00:43):
He is on a vacation with hisfamily right now.
We miss you, Mike.
We look forward to you comingback.
How are we doing?

Doug (00:48):
Doing all right.
I'm in Maryland.
The last time we had our show,I was in California.

Louis (00:54):
Yeah.

Doug (00:54):
And it was just before they did the robotaxi trials in
Austin, where you are.
Yes.
And so we were speculating howthis would go.
And so how has it gone?

Louis (01:05):
So first I'll say that no, I have not ridden in it, nor
do I have access yet, becauseas one could guess, they were
overly optimistic on when theywould open it up to more people.
So it's still limited to apretty small set of influencers
and Tesla enthusiasts.
They let you sign up.
Yes, or signed up.
Uh-huh.

(01:26):
I just don't have access.

Doug (01:28):
They didn't turn it on.
You would think it wouldincrease.
A lot of those influencers havegone home now.
But I think they only have likeless than a dozen actual cars,
or at least the last time Ichecked.
And they've increased theservice area.
At some point, you got to havea critical density of cars,
right?
If you make the service areabigger, the next guy that plans

(01:50):
to use the service is going tobe waiting for a while because
there's not a car available orit's too far away.
So they should get more cars.
Of course, in the currentsetup, we should say, since we
didn't know last time we did theshow, they have a what are they
calling them?
A safety monitor?

Louis (02:06):
Yeah.
Some kind of monitor or safetysupervisor, maybe person in the
car.

Doug (02:11):
Yeah.
That person sits in the frontpassenger seat.
So they're not in the driver'sseat.
So you get the spectacle of thecar appearing to drive itself.
But that guy is there to, Idon't know, stop the car if
necessary.
There are a couple buttons onthe screen where you can tell it
to stop in lane or in trip orthose sort of things.
And also the monitor, we'llcall them that safety monitor.

(02:33):
That person sits in thatpassenger seat and they have
their finger over the door openbutton.
The door opens.
Which kind of feels like anemergency stop sort of thing.
There's been a lot of talk andspeculation about what it
actually does, but my guess isit does that, or it could just
be as simple as recording likesomething weird happened here.
Let's pay special attention atthis moment.

(02:54):
So have you been following itall?
How do you feel about it?

Louis (02:57):
So my understanding, again, having not ridden in
them, there's quite a fewinterventions that have
occurred.
I saw some tweets out aroundTesla claims there's only these
interventions, but we want toget more from other people that
have been in them because wethink there's been more.
So like citizens are trying tocollect the data because Tesla
hasn't released it or publishedit yet.

(03:18):
But yes, from social media,there's definitely been a number
of interventions from theinfluencer drives that have
gotten out.
I would say definitely doesn'tseem ready for prime time,
right?
We have Waymo here in Austin,and there's not daily things
going wrong with that.

Doug (03:34):
I've heard people aren't reporting on the daily things
that happen with Waymo.
I'm sure Waymo does weirdthings, and we have seen such
things.
I will say I appreciate theinfluencers.
They definitely have a positivebent, but I feel like they've
been relatively open and honestabout the things that have
happened.
Joe Tegmar mentioned anintervention where the car was

(03:55):
about to drive through arailroad crossing, and he didn't
have recording of it, but hereported on it.
So I think people have beenfairly open and honest.
Another one, Kim Java, I thinkher name is.
Like in the previous episode,we were talking about sun glare
and how Elon had said, Oh, we'vesolved this problem.
And I'm like, I don't think youhave.

Louis (04:13):
We have photon detector cameras, whatever.

Doug (04:16):
He said, Yeah, photon counters, yeah.
Or counters, yeah.
Yeah, but it looked like hercar, and she had video of it.
The car did the phantom brakingthing, but it seemed like it
happened because the sun wasright there, so there's some sun
glare.
Now I'm still on hardwarethree.
You know, our cars haven'treally had much of an update,
but it feels like the same kindof errors that we have, it feels

(04:36):
like those are still happeningin the robo taxi.
Right.
And those things are like thecar not being aware of signs, it
knows the shape of a stop sign,but it doesn't know no right
turn on red, like it's notreading that sign.
Maybe there's some map datathat it sometimes will know that
you can't turn right here, butit's not actually taking in that

(05:00):
kind of information from theenvironment and not really being
aware of how to deal with arailroad crossing.
I think that's uh that's animportant thing to be able to
do.
And if you look at thevisualization, if other people
have videos of it, it doesn'tpay any attention to the bar
that's dropped.
It may pay some attention tothe flashing red lights that you
get at a railroad crossing, butI think it interprets that as

(05:21):
guess what, a stop sign, right?
Because that's what we normallydo.
When we see flashing redlights, you treat that as a stop
sign.
Right.
But it doesn't know that, oh,this is actually a railroad
crossing.
It doesn't seem to acknowledgethe bar at all.
And then the train going by, atleast on the visualization, is
interpreted as a bunch ofsemi-trucks going by, and it

(05:42):
doesn't necessarily know wherethe proper stop is, so it will
stop and then try to continuethrough the bar.
Say you have a parking lot thatis closed, and often people
will close a parking lot by juststringing a chain across.
Doesn't seem to know aboutthat.
It looks like it's ready to runright through that.
That might be a little toosmall for the cameras to really
register as somethingworthwhile.

(06:03):
And these are things that Ipersonally am dealing with.
I think one of the first majorinterventions, it actually
wasn't an intervention, theydidn't do anything, but it was
an error was that the car neededto make a left turn, but the
left turn wasn't at the nextintersection, it was at the
intersection after that.
And so the car went into theleft lane already.
So it's a left turn only lane,but it needs to go straight.

(06:25):
So it's in the left turn onlylane, and it just continues
going straight and it actuallyfreaks out for a bit.
Do I go left or do I gostraight?
Do I go left?
And we've seen that sort ofindecision before, and then it
ends up just going straight.
And by going straight, it's nowin oncoming traffic for a bit
until it gets to the next leftturn pocket, and then it takes
this left turn.
Yeah.

(06:46):
You know, I use FSD in my carregularly, and there's a certain
part where I always have thaterror all the time.
It's like I'm going to thegrocery store, it needs to make
a right turn, and it gets intothe right lane about 50 yards
too early.
And okay, but now that's theright turn only to go into some
parking lot.
Fortunately, there's no curbthere, but it wants to just

(07:06):
continue through.
It's going too early.
Yes, you need to be in theright lane, but you're going too
early.
And uh every time I send areport about it, but I don't
think I don't think thosereports are going anywhere with
my car.
I've had no updates, I don'tknow, for months now.
And I feel like the hardwarefour people are reporting that
they're not getting any updateseither since Robotaxi launched,

(07:26):
because probably they'respending all their time trying
to fix things with Robotaxi.

Louis (07:31):
Yeah, to be honest, I feel like the Robo Taxi program
that they're doing right now isa good idea in the sense that
it's going to greatly acceleratethem focusing on the problems.
Trial by fire.
We all have our cars with FSDand we're there and we correct
the issues manually.
So you just kind of keep makingprogress.

(07:51):
But when you're doing arobotaxi and there is no driver,
you have no choice but to fixevery edge case, every
intervention that's required.
It's definitely going tohopefully accelerate their
learning.
And we have our fingers crossedthat it's going to accelerate
their remedy, their improvement,and solving those interventions
and those challenges.
But yeah, yeah, the problem iswhen you bundle that with, hey,

(08:16):
we're claiming that we're goingto get it out and it's going to
be lots of people are using itand we're going to release this,
and you have Elon time on thosedeadlines.
It's insane.

Doug (08:24):
By the end of the year or something, he said, we'll be
able to do unsupervised in ourown cars, but probably just in
these areas where they've madeRobotax available.
Now, the interesting thingabout that is we've seen these
cars with verificationtechnology or something on
there, and basically some otherTesla vehicle with a mast on top
that appears to have camerasand some kind of LIDAR, maybe

(08:49):
they seem to be doing that as aprecursor to expanding the area.
And I have had friends inCalifornia tell me that, oh,
we've seen these in the Bay Areaas well, going on Page Mill
Road, which is right nearTesla's technology headquarters
in Palo Alto.
I'm not exactly sure what thoseare because they say they don't
do HD maps, but I get the sensethat what they're doing is

(09:09):
scanning in the environment fortheir simulation.
And then they train off thesimulation because then they can
create the kind of scenariosthat could be fatal in a real
test, what they think might beedge cases and try to train in
that way.
And right.
Yeah, at least as Elon hasdescribed it.
I guess that's what they'redoing.
My understanding also that theyplan to soon expand to the San

(09:31):
Francisco Bay Area, which Iguess would include Palo Alto,
those sort of areas.
But there they don't have theactual permits to do a robo taxi
type thing.
So what they're gonna do isthis safety monitor will
actually just be in the driver'sseat.
Sure.
So that's gonna be like theUbers that are already there
because you have a bunch of Uberdrivers that will drive Teslas
and they just do FSD the wholetime and they're just sitting

(09:53):
there ready to take over.
Basically, you have a licenseto do an Uber type service, but
not a robotaxi type service.

Louis (10:01):
You mentioned them basically mapping areas, and
your assumption is forsimulation and to expand their
coverage areas.
There was some drama aroundtheir expansion map for Austin
with Robotaxi.
I guess we don't have a pictureof that to show, but we can
talk about it.
It's Elon, right?

Doug (10:21):
Classic Elon.
It feels like his emotionalmaturity is that of a
13-year-old or something.
I mean, I don't I don't mean tobe too critical, but the way he
is vindictive and also what hethinks is funny.
It's like, come on, we'llexpand it and we'll elongate it.
So he had the shape, it looksphallic.
But Waymo has correspondinglymade their service area larger

(10:43):
as well.
And yeah, great, compete onthat.
But again, you have thoselimitations, you need more
vehicles because if you expandthe service area, then you don't
want your customers waitingbecause you don't have enough
vehicles.
I mean, on that note, so inAustin, for you to get a Waymo,
you're using Wayne.

Louis (10:58):
You have to use Uber, correct?
You don't use the Waymo app.

Doug (11:01):
Right.
So there was some news recentlyof Uber using Lucid Gravity.
I think so, yeah.
Lucid already has some tech onit, it has cameras already, but
they're also adding, as saidwould say, some hickey d'os from
Nuro.
And Nuro has been around for awhile.
I feel like they started withlarger ambitions and they scaled

(11:22):
down to just food delivery typething.
So not transporting people, buthave these things that
transport goods or food orsomething.
But they've taken thattechnology, put that on the
Lucid Gravity, and then thatwill be a robo taxi, assuming
Tesla doesn't own that term, arobo taxi type vehicle that Uber
will use in addition to theseWaymo's.
I don't know what Uber'sendgame is there.

(11:44):
Originally was trying to dothis stuff themselves, and it
made perfect sense, right?
Because once they can getdrivers out, then they can make
a lot more money.
The ROI is much higher.
Sure.
Of course, their program, whichwas run by Lewandowski, I think
his name is.
Yeah.
He's been around.
He went from Google and Uber.
He does an autonomousconstruction company or

(12:05):
something like that now, right?
He worked for Tesla too for awhile, but then when he left
Tesla, I think they sued him.

Louis (12:11):
Anthony Lewandowski.

Doug (12:13):
Yeah.
He co-founded Waymo.
He was working on self-drivingsemi-trucks because he thought
that was a good spot.
And then Uber, I think, scoopedhim up from that.
There's a big lawsuit over ittrying to claim that he stole
intellectual property.
I think both Google and Teslawere suing him at some point.
But yeah, Uber had their ownself-driving effort.

(12:33):
They had test cars with aobserver in the driver's seat,
but there's actually video.
That person was playing withtheir phone, they weren't paying
attention.
Somebody was jaywalking, andreally they just came out of
nowhere in the darkness and thecar hit them.
I think even if the personresponsible was paying
attention, probably thepedestrian or uh I think they
might have been walking abicycle, but that person got
killed, and that probably stillwould have happened, but it was

(12:56):
such a thing that they quittheir efforts.
So I don't know what's theirend game here.
That makes sense for Lucidbecause they need money, they
need to be able to sell cars andshow people their vehicles.
Like the gravity is a nice car,right?
So that actually will be aluxury type experience.
Uber has their differentlevels.

Louis (13:12):
Oh, like the black versus the Uber Black, maybe or
whatever.

Doug (13:15):
Or XL and all that.
So that might be a nicerexperience.
Seems expensive.
Those Lucids are expensive, andthen that extra hardware.
You have any insight?
Like what is there end-gamethere?

Louis (13:26):
I think, like you said, at the time early on, like most
hyped things, self-driving withAI was so hyped 10 to 15 years
ago, all these people were like,Oh, yeah, it's only a couple
years away.
Oh, within a few years, we'llhave it.
Not just Elon.
I would say people that weren'tworking on the problem.
So engineers and scientiststhat were working on the problem
knew how hard it was.

(13:46):
Yeah.
And all the business folks andmarketing folks were like super
hyped.
Hey, this is gonna be only acouple years away.
Yeah, I'm sure some of that wasdriven by Elon.
So, yeah.

Doug (13:54):
So, like you said, the people I know at Stanford that
started a lot of stuff, right?
They won the DARPA GrandChallenge.
They were like back in 2016when Elon was like next year,
and they're like, we're thinkingmore like 15 years.

Louis (14:05):
Right, exactly.
The insiders that work on thestuff kind of knew that there's
no way, you know, as engineersoften do.
Executives, marketing,investors, they were all pushing
it.
So Uber was in the space tryingto do it themselves.
They divested out of it, andnow they're partnering, which I
think makes a lot more sensebecause it's way cheaper, you
know, make these partnershipdeals.
I still think is a smartbusiness decision on their side.

(14:27):
If you look at their revenue,they're gonna make money through
all the other things they do.
The licensing that they'repaying, say for the software or
the access to the cars, isprobably less than they're
paying a driver, the amount ofdriving that they're doing.
Uh, but even if it wascomparable, like they still make
a lot of money on top of it.
So I think it makes sense.
I think if eventually thetechnology matures enough, Uber

(14:48):
might end up buying something tobring it in-house or making
some kind of tight partnershipwith somebody.
But yeah, until that nut's beencracked, there's not much point
in them trying to do itin-house.
They kind of gave up on that.
I think that was a smartdecision.

Doug (15:00):
Yeah, but when that point happens, when Robotax actually
work, like does Uber's brand,does it have enough cachet that
why wouldn't Waymo, which italready does in San Francisco,
just be their own app or Tesla,obviously, and even Lucid.
You know, if they have some ofthis tech and they're working
with Neuro, Uber doesn't ownthis tech.

Louis (15:18):
Right.
Why would they profit sharewith Uber?
Basically, it's a marketplace,right?
One of the main things thatUber has going for itself is not
just taxiing, it's actuallyUber Eats, the food delivery
service.
So they're integrated into thepoint of sale systems for
thousands and hundreds ofthousands of restaurants all
over the place and the menuintegration, all that kind of
stuff.
So those types of things arereally hard to build out for a

(15:42):
new company to come along and dothat.
It makes a lot more sense tojust partner.
So I don't see like Waymo fullybeing able to compete with Uber
at that kind of scale.
The other thing is they do havename recognition, they have way
more users and they're in waymore locations.
So Waymo could start a war withthem and try to like battle and
take over markets.
But I feel like a lot of thosecompanies that have the

(16:02):
technology will very likelymerge, get purchased, or just
have partnership deals withother companies to do it,
especially as you want to gointo more and more markets.
But time will tell.
Personally, I think it makes alot of sense.
Uber is going to be able tolicense it.
I also think they have enoughmoney that they'll be able to
buy something if they need to.
If the technology getsrestricted to just one company
that has it, nobody else is evenclose, then you know that's a

(16:23):
different kind of conversation.
But what I'm expecting is it'sgoing to be multiple competing
companies having comparabletechnology because they're all
slowly creeping towards it.
So we'll have to see whathappens.
I mean, I think even Elon hassaid like they plan on being
able to license the technologyto non-Teslas, right?
They want to be able to sellthat technology to another

(16:43):
company.
If it worked really well, I'msure an Uber would just license
it.
They'd be perfectly happy to dothat.

Doug (16:49):
So I've always been a little bit skeptical about that,
just because we've seen how theCybertruck is still kind of
limited with their FSD, and thatis only a slightly different
configuration in terms of theplacement of the cameras and
whatnot.
So, how well Tesla's system canmap onto other vehicles and
other vehicles can just adopttheir system is a little bit

(17:10):
unclear to me.

Louis (17:12):
I completely agree.
I feel like the problem rightnow is the technology companies
are struggling to get thetechnology to work at all.
They're struggling to even justcrack self-driving, working in
all the various education thingsthat happen, that they haven't
even moved on yet to like how doI generalize its functioning
and abstract it away so that Ican put it on any kind of car

(17:32):
and model with different cameraconfigurations, it still works
just as well.
So I think in time that'llhappen, right?
That's we've talked about it inthe past and earlier episodes
around things like yeah, you'remapping all the camera signals
into this virtual spacerepresentation of the
environment, which then themodels will go against.
So there are ways to get there,but we're definitely far away

(17:53):
from that.
There are systems like Kama AI,for example, that work on a lot
of different cars.
Now, granted, they're you knowa 2.5 kind of system similar to
what Tesla is, and they can workwith different kinds of
configurations.
So it's interesting to see.
I'm looking forward to itexpanding more in Austin.
I'm looking forward to Teslasworking through their stuff.
I hope that they really getsome progress.

Doug (18:15):
To me, the real test is in the coming months.
Right now it's summertime, theweather's mostly clear.
We've already seen the cardeciding to quit because it
rained and it actually kicked apassenger out, and then when it
stopped raining, they got to getback in.

Louis (18:31):
And we will point out that Austin is a university
town, so traffic is a lotlighter in summer compared to
the rest of the year.

Doug (18:39):
And we already see how it fails with railroad crossings.
The other thing that we haveyet to see it work correctly on
is the school bus stoppingproperly for a school bus.
It may see that stop sign andthen just treat it as a stop
sign, like I can stop and then Ican just continue.
Kids aren't in school yet.
So in September that may comeup.
And then, yeah, when theweather changes, not just rain

(19:01):
but snow.
I guess that's not an Austinthing and maybe not a Bay Area
thing, but the days will getshorter.
Currently, their system worksat night, but it stops at a
certain time.
You wonder how much of that isrelated to daylight.
I'm also still skeptical ofcameras only.
I think you can get a lot ofthe way there with cameras, and
cameras are doing most of thejob, but I really do think,
especially as these sensors getcheaper, you gotta have the

(19:22):
backups.
Like I think LiDAR wouldproperly identify the railroad
crossing bar coming down andknow not to try to go through
that.
Sure.
We'll see how it goes.
You know, the other thing isthe hardware I mentioned earlier
that there are reports thatTesla's only working on hardware
four right now, or at leastthey'll be the first ones that
get unsupervised.
Hardware or AI 5, as they'recalling it, is delayed.

(19:45):
That was one of the things thatElon said next year or
something.
Where I think originally we'reexpecting it by the end of this
year.

Louis (19:51):
It's supposed to be this year, but now it's likely next
year.

Doug (19:54):
He made some comments about it in the earnings call,
basically talking about howamazing it is.
In fact, they'd have to nerf itoverseas because it's so good.
It would violate exportcontrols on compute.
Okay, maybe, but that sounded alittle bit like juicing it up,
spreading a little thick abouthow amazing it is.
But you and I, as hardwarethree, people are still waiting
for our updates.

(20:14):
The question is, will this evenbe solved on hardware four, as
we've talked about before?
Will this hardware five benecessary?
He've mentioned that they'regonna expand hardware four
10xing the parameters.

Louis (20:26):
Right.

Doug (20:27):
Can you give us an idea of what that means?
Sure.
I'm not really a CS type guy oreven a neural network type guy,
but the basic cartoon is youhave different layers, right?
And then you have so many nodesper layer.
Correct.
To 10x the parameter, does thatmean more nodes?
Does it mean more layers?
What does it mean?

Louis (20:43):
Usually it means more nodes.
While you can have more layers,most of the time when people
are talking about how manyparameters, they're usually
talking about how wide it is, sohow many parameters are passing
through.
But yes, it could be they'readding layers as well.
But the direct mapping or likewhy they need more hardware for

(21:05):
that is basically each parameteris more calculations that need
to be done and more RAM to keeptrack of it.
So you need more memory and youneed to do more calculations as
you pass data through.
More dot products.
So, yeah, exactly.
More dot products, more linearalgebra.
As they're dealing with thistype of problem, they're scaling

(21:27):
it up.
Generally speaking, with neuralnets, how it seems to work for
the most part, and this is howit relates directly to like
ChatGPT and LLMs and things likethat, is more parameters with
more data equals betterperformance in a wider range of
things.
That just seems to just keephappening.
We increase the parametercount, we add more data, it gets
there.

(21:47):
Now, there's definitelydiminishing returns to some
degree, although that mostlycomes out of quality of data and
things like that.
As you get higher quality datawith more parameters, things
tend to work well.
That also gets to why the powerrequirements go up and the
hardware requirements go up andthe number of GPUs you need go
up and costs keep increasing.
If we look at how big cloudinfrastructure with models work.

(22:11):
So, for example, if you look athow ChatGPT, Gemini, or those
types of tools, anthropics, clawstuff, they actually have
something called multi-modelwhere they have different models
that specialize in differentareas.
And so when you give it arequest, it's not just one big
massive neural net that has allthe parameters doing everything.
They tend to filter it out tosome models of varying sizes

(22:32):
that do different things.
What I expect is in the future,once this problem is cracked,
that will be the secrets tomaking self-driving not a giant
monster and need infinitecompute and GPUs and everything
else.
Is they will probably dosomething along the lines where
it'll recognize I'm in this typeof environment.

(22:52):
I'm low light, I'm at night,I'm in US versus Canada versus
Europe versus whatever.
There'll be different modelsthat specialize in certain
driving environments.
There's be like a baseline andthen more fine-tuning around
these other things.
Anyway, that's what myexpectation is in the future.
So more parameters basicallymeans hardware four is probably

(23:12):
not going to pull it off.
And if they decide they needthose parameters to be able to
solve these problems, they needmore hardware.
They need more compute, theyneed more RAM.
Well, he said this 10x was inhardware four.
Still was in the range of whathardware four can technically
do.
Yes.
The question is, is that 10xgoing to be enough?
Yeah.
The problem is you don'tactually know until you get
there.
So it may not be enough.

(23:33):
And they're going to need to doanother 10x and another 10x,
right?
Only time will tell.
Hopefully, as you get to acertain baseline, again, because
of potentially diminishingreturns, you could get it to
where it's good enough, and thenyou could make it a little bit
better and you need a lot morecompute, but not everybody needs
that amount of compute, right?
There could be differences, andthat's that whole argument they
made in the past.
You know, Tesla was like, Yeah,we have models for hardware

(23:56):
four, and then we kind of scalethem down for hardware three.
You can do some optimizationand things where you can scale
things down a bit too, and it'llrun on lesser hardware, but
still give you comparableperformance.
That might be the plan, right?
Maybe if they keep scaling itup, they get better, better
hardware and they eventuallyscale it back.
But at this point, I'm of theopinion that hardware three is
likely never going to actuallywork for FSD.

(24:17):
And that's Elon's opinion, too,at this point.
So Elon finally agrees, whichis good.
I'm also of the opinion thathardware four may never actually
get to FSD.
It's hard to know because Idon't think we're as close as
enthusiasts like to think weare, and certainly not as close
as Elon likes to say they are.
When we originally predictedthis, similar to like you said,
you had insiders back atStanford that in 2015, 2016

(24:41):
said, Oh, we're probably 15years out.

Doug (24:43):
Yeah.

Louis (24:43):
I still don't expect it to come before 2030.
I think 2030 is probably theearliest we would likely see it.
So it's very likely we'll behardware six, hardware seven by
then.
But who knows?
What I'm hoping is that withhardware five, they might be
doing a form factor that's morecompatible with hardware four.
I could be completely off basethere, but maybe it's closer.

(25:04):
What we had was like hardwaretwo, 2.5, and 3 could all be
swapped in with some effort.
And so the problem was hardwarethree to four, there's no way
to retrofit.
They may come out with aspecial thing, but I'm assuming
they probably won't.
They're gonna drag their feetuntil there's almost no hardware
three cars on the road, or theymight come out with one
eventually.
Hardware four to five,hopefully, is upgradable.

(25:25):
My expectation is as theyrealize they have to keep
transitioning these hardware,they're gonna try to do a better
job of making to where theycould more easily upgrade older
cars if they had to withinreason.
If they decide they needadditional cam replacements or
they need LiDAR or some otherkinds of sensors, who knows if
they'll ever do that?
You can't just slap that inthere.
Um, but it would be nice if youcould upgrade the compute or

(25:46):
something along those lines.
We'll see.
I'm glad that progress is beingmade.
I definitely feel like Teslawill hopefully learn a lot more
quickly now that they're tryingto do robotaxi.
As you said, it's a trial byfire.
They have not much choice towork through those things, but
that doesn't mean that they cansolve it.
That doesn't mean that they'lldo it quickly.
It's a very difficult problem.

(26:07):
Technically, no one has done itin a non-geofenced all
environment, all weather, alltime of day.
Like there's a ton ofrestrictions on the folks out
there doing it.
I still think Waymo's in thelead from what I've seen.
I think technology-wise, theyare the most advanced of
self-driving vehicles, but alsothey're geofenced and they have
a ton of restrictions.
Teslas don't have all thoserestrictions.

(26:29):
Teslas technically work in moreenvironments, they just don't
work as reliably in the sameenvironments that Waymo works
extremely reliably in.

Doug (26:37):
So well, Waymo certainly took their time with it, years
of trials, but Tesla has moredata.

Louis (26:43):
Yeah, Tesla has more data, Waymo has more hardware
and sensors, and years ofengineering on it.

Doug (26:48):
And also risk aversion, true, positive or negative, but
I don't think people should diein testing this, so and we've
had at least in autopilot andFSD, some dozen or dozens of
people have died.
It is what it is,unfortunately.
So another thing that came upbriefly in the earnings call was
someone asked about Teslainvesting in XAI.

(27:12):
Elon made a big point about nottalking about it, though there
has been some news, and hesuggested that's something the
shareholders might think ofbringing up, which seems like a
hint as to what he wants peopleto do.
What's going on with XAI?
I mean, I hear that they'reraising a lot of money.
Yep.
SpaceX is investing, whichdoesn't make a whole lot of
sense to me.
SpaceX investing two billioninto it.

Louis (27:33):
Honestly, it's classic Elon.
Elon has historically done alot of games around multiple
companies, gets one to invest inanother one and then merge and
then absorb and do that kind ofstuff.
He also knows a lot aboutraising money.
Yes, Tesla's a public company,but we all can agree their
valuation and their market capis not connected to

(27:53):
fundamentals.
It's purely speculative andit's based on a lot of hype.
So, what is the biggest hypething in the world right now?
AI.
Yes.
We didn't even have to planthat.
We both could just know AI isthe insane hype.
Over 90% of all investmentdollars go into AI-based
projects.
Not to spend too much time onit, but AI is without question a

(28:17):
bubble.
At least that's my opinion andthe opinion of many others.
You may disagree.
If you look at market cap rightnow, there's six or seven
companies which make up 35% ofthe United States stock market.
So the entire stock exchangevalue is like six companies.
All of those companies areinvesting hundreds of billions
of dollars into AI.

(28:38):
All that money gets funneledinto NVIDIA.
So NVIDIA makes the chips thateverybody's using.
Okay, to be pedantic, theydon't make the chips, they
design the chips, and TSMC makesthe chips, but whatever, that's
just because I used to work insemiconductor.

Doug (28:50):
NVIDIA makes the money.

Louis (28:51):
NVIDIA makes the money, but yes, all that money's
funneling into NVIDIA, and it'sessentially a big arms race.
Everyone's of the opinion thatas soon as I get AGI, as soon as
I have this super intelligentAI, I'm gonna conquer the world.
That's everybody's assumption.
Now, I don't agree with that,and I won't get in all the
reasons why I disagree.

Doug (29:09):
It does feel like a race for power, though, doesn't it?

Louis (29:12):
It's really a race for power, but the power that
they're racing for is not asgood as people think it is.
And what I mean by that isright now, AI seems great and
it's improving quickly, andthere's all this cool stuff
happening with it, as many of usgot to experience using tools
ChatGPT, Gemini, O'Claude,Anthropic, that kind of stuff,

(29:34):
cursor, whatever, depending onthe flavor of AI that you like
to use.
AI is going to eat the world,it's using lots of things, it's
in and everything, it's goingeverywhere.
Here's the thing that mostpeople don't think about or know
about AI.
AI is majorly subsidized byinvestor dollars.
So in the last two years,there's been $580 billion spent

(29:55):
by these top six or sevencompanies on AI.
That's capital.
Expenditures of buying videocards mostly, getting power for
those video cards, things likethat.
The revenue generated by all oftheir AI stuff, and this is
very generous, is about $30billion.
So they've spent more than 10times what they've gotten back.

(30:18):
And what's interesting is ifyou look at the rate of
expenditure and the rate ofgrowth of revenue, the gap is
not closing.
The gap is widening.
Now, most people think of AIfrom like the ChatGPG days.
Those of us like myself thathave worked in the AI space,
this is goes back to the earlyto mid-2000s.
AI at Google and those types ofcompanies have been going back

(30:41):
almost 20 years now.
In research and academia, itgoes back to the 50s, like it's
been around forever.
So if you look at it, it's likewhere's the ROI on the current
AI hype?
It's currently spend, andhopefully in the future we'll
make money.
How do they make any moneyright now?
It's like subscription fees.
Subscriptions.
Yeah, basically, all of theseproducts that are using AI are
all built on top of thesesubscriptions.

(31:02):
But again, the subscriptionsare majorly subsidized by
investor dollars.
So investors have effectivelyburned over $550 billion, just
gone.
That money is disappeared outof their pockets, gone to buy
GPUs, and those GPUs arebasically running these models.
At some point, you have to makethat money back.

(31:23):
At this current rate, if theydidn't have to buy any more
GPUs, it would take them over adecade to make their money back.
But that's not how it works.
There's always a bigger model,a better thing, a new shinier
toy, and bigger, better GPUs.
So every year they're spendingeven more and even more.
And after a couple of years,the old GPUs go away.
So GPUs you buy now aren'tgonna be here in 10 years,

(31:45):
they're gonna be in a garbagedump somewhere.
Anyway, the point is AI is abubble because they aren't
making a return on what they'respending.
And even if you could get thecost way down on, say, GPUs,
they don't have to buy them asmuch, the models are more
efficient.
You still have the energy cost.
That's the other thing.
Right now, to run these models,it's more expensive than hiring

(32:06):
a person.
So there's all this drama likeAI is going to replace
everybody.
There is no remote close chanceof that happening just from an
energy cost.
A human brain runs on 25 wattsa day.
A GPU cluster used to run yourAI model to be not as good as a
person right now runs on many,many megawatts.

(32:26):
It's not even remotely in thesame realm of things.
All is to say, as part of thisarms race, it's a hype race in a
bubble.
And if you look at previous ARMraces, like between the United
States and the Soviet Union, itwas an arms race of trying to
spend, which essentially causedthe losers to collapse and go
bankrupt, right?
They basically ran out ofmoney, ran out of steam of

(32:47):
trying to produce.
So the hope is that somebody'sgoing to win and everybody else
is going to lose.
That's their shtick.
You've got all these companiesspending lots of money hoping to
not be the loser.
Who's in that race?
Technically, Tesla is in thatrace.
And if you look at Elon,Twitter was purchased by XAI.
What happened there?
Basically, all this money,hundreds of billions of dollars,

(33:09):
feeding into AI companies.
Hype, hype, hype, hype, hypeinflates the valuations.
You don't need to make money aslong as you have the potential
to make a lot of money in thefuture with AI.
XAI within a few months ofbeing founded, very small
company, very few people workingon it, is suddenly worth more
than Twitter.
Because even though Twitter is$44 billion whenever when Elon

(33:31):
bought it, there's no super hypecurve anymore.
That's a already existingbusiness.
It has revenue, it's losingmoney.
They don't go, ooh, that'svalued a lot more than it should
be.
But XAI is like, ooh, it's aninfant.
It could be worth a lot.
You don't know.
There's so much potentialthere.
So the investors hype it up.
It becomes worth a significantamount of money.
Elon gets to play the shellgame where XAI now gets to buy

(33:54):
Twitter or X for paper money,basically not real money.
He gets to use stock and thisfake valuated money.
Now that becomes one company.
So XAI is basically Twitter,but like with an emphasis on
Grok, their one product, and ontrying to build AI to get to
AGI.
What's happening with all thosecompanies, though?
They all have billions ofdollars and they're buying

(34:15):
billions of dollars of videocards every year.
So they need more money.
They need more money.
They need to buy more videocards.

Doug (34:22):
In that earnings call, someone asked, Would Tesla buy
XAI with a merge?
And Elon said something like, Idon't think that would be
appropriate.
Or basically, he shot down thatidea.
And I feel like that might haveto do with Tesla being public
and XAI not being public.
So just having Tesla invest init allows him to transfer money.

(34:43):
Correct.
Because Tesla is the piggybank.
Use some of that Tesla money inthe thing that he owns more of,
which is XAI, without having togive up control any control to
Tesla since he only owns about13% of Tesla.
Absolutely.

Louis (34:57):
If XAI was able to become a bigger company than Tesla,
which it can't right now, itcould in the future, who knows,
on the AGI arms race, but rightnow it can't.
Elon would absolutely let XAIbuy Tesla because that would
give him a lot more control.
He would love to do thatbecause he controls so much of
XAI.

Doug (35:16):
He said that he would like to have 25% control of Tesla.
Yeah.
And the reasoning he's given isbecause of AI type stuff, and I
guess Optimus and robots, andhe thinks that's a big thing in
the future.
It's potentially dangerous, andhe wants to be sure that he has
a level of control.
Sure.
I'm not sure how much I trusthim in that control necessarily.

(35:39):
Yes.
Because, you know, certainsigns from him as an aside, I'm
not really sure how to put that,but like his emotional maturity
doesn't seem quite high.
But then also he has a kind ofutilitarian view of people.
That seems to be like a not toouncommon trait among the CEO
class.
You know, some people call itpsychopathy.

(36:00):
But for example, Bill Gates,right?
In the early 2000s, Bill Gatescame to Stanford to give a talk,
and I was there.
And it was really about hisphilanthropy and doing things
like helping cure malaria orhelp stop the spread in Africa,
for example.
Somewhere circa around thattime, he gave a TED talk where
he released a bunch ofmosquitoes so people could

(36:21):
experience that, but hopefullythose mosquitoes weren't
carrying malaria.
But at this talk in Stanford,he said he used to think that
since we're worrying aboutglobal warming and
overpopulation, that maybe theyshouldn't solve these problems
in Africa because we have toomany people.
So that this is helping controlthe population.
And he said thismatter-of-factly, it's you know,

(36:42):
maybe it's okay to let thesepeople die.
Uh, but then he said he foundout when we raise their standard
of living, particularly women,they end up having fewer
children.
Rick.

Louis (36:52):
So he thought, okay, maybe that's a it's a more
ethical way to accomplish thesame thing.

Doug (36:55):
I he didn't say ethical, he just like maybe that's a
better way to go about it.
He didn't seem to be making ajoke at all that he could make
that switch and be like, oh,okay, whatever.
Okay, I'll do it that wayinstead.
Which kind of struck me asscary.
Now, of course, Elon, I I getsimilar vibes from him, uh, but
he's on the other end of wantingpeople to have many more kids.
He wants more kids.
But I feel like from him, ithas to be the right people

(37:17):
having more kids, though, notjust anybody, particularly him.
Yeah.
There's 14 kids that we knowof.

Louis (37:22):
There are billionaires that have kids in the hundreds.
Yeah.
Is a thing.
Eugenics was popularized by theultra wealthy back 100 years
ago.
But yes, there is somethingabout it when you have that much
money and power and influencethat you start thinking about
things in a different way.
And that different way is itgenerally involves less empathy
than what you would hope forsomebody that has a lot of money

(37:44):
and power.
Scary.
Back to this whole thing.
I think XAI needs more money.
Elon likes to play the shellgame of move money around his
companies, also get moreinvestment dollars.
And he said he expects toachieve super intelligence
within the next couple years.
I would still argue, first ofall, you have no way to know if
we can or how to get there orwhat's going to happen.

(38:05):
But even if you could, how areyou going to make the money
back?
That's the other argument is atsome point it needs to make a
return.
You have to have a product orservice that generates enough
money to do it.
And outside of I'm going tocrack Bitcoin and get all the
Bitcoin, which now suddenly theywouldn't be worth anything.
If somebody could crack it,they would all become worthless.
Yeah.
What's the secret way in whichthis super intelligent thing is

(38:27):
going to collect all moneywithout stealing it?

Doug (38:29):
Controlling everything, inventing new physics.

Louis (38:32):
Yeah.
Anyway.

Doug (38:34):
Another aside, yeah, I listened to a number of
podcasts, mostly news andscience-y ones, but I was
considering because I'd see themon X all the time.
Let me check out this all-inpodcast, see what's going on.
It's run by Jason Calicanus anda bunch of Elon either admirers
or cronies.
Like Jason Kalicanus was Elon'sneighbor or something.
And I think the guest wasTravis Kalnik, the guy that Uber

(38:57):
founded Uber, yeah.
Yeah.
And I'm listening to thisthing, and I wasn't quite sure
who was talking, but I guess itwas Travis.
And they're talking about howI've been using these LLMs, and
I'm just asking questions aboutphysics.
And I'm testing the limits ofphysics.
And I feel like I'm just closeto discovering some new physics.
And I'm like, what the heck areyou talking about, dude?
You know, it's an LLM, right?
And maybe it trained on somereal theories.

(39:19):
It's just going to startputting stuff together in a way
that if you're not a theoreticalphysicist, might sound really
intriguing.
Like, wow, this is reallypushing things to the edge.
And just hearing them all talkabout it.
Are you guys nuts?
I mean, I mean, I'm not atheoretical physicist myself,
but that's sort of what got meinterested in physics, but I
went more the experimentalroute.
But it just seems so naive.

(39:40):
And what do you call theDunning Kruger effect or
whatever?

Louis (39:43):
It's the Gellman amnesia effect.
It's parallel to that.
It's you read a newspaper asthe original, right?
And you go, hey, this is sointeresting, all these things.
Oh, I'm learning all thisstuff.
It's so factually correct.
And then you get to the thingthat you're an expert in, and
you go, Oh, this is completelyflawed.
Look at all the mistakes inhere.
But you assumed everything elsewas correct that you aren't an
expert.
So that's absolutely the sameeffect, in my opinion.

(40:05):
Yeah.

Doug (40:06):
Especially with theoretical physics, existing
theoretical physics right now,or people that are working on
grand unified theories to try toling quantum mechanics with
general relativity.
And look, general relativityand quantum have been flawless
in terms of every time you do anexperiment to test it to even
more nines or whatever.
It's so good, those theories.
And they predict things thatthe people that wrote those

(40:28):
theories didn't even expect.
Einstein didn't expect blackholes, for example.
But they work in certainregimes, and there's a regime
where one works and the regimeswhere the other doesn't quite
work.
And so people have been workingon that for a while.
String theory has gotten a lotof time, and there are a bunch
of other kind of theories peopleare working on.
The problem is pretty much noneof them you can actually test.
So you're just making math.

(40:50):
Right.
And math can be a model ofreality, but it isn't reality.
It isn't necessarily reality.
So yeah, you can come up withtheories and test them
mathematically to at least seeif they are self-consistent.
And a lot of them aren't.
But whatever Chat GPT orwhoever's spewing about this
stuff, it's gonna be nonsense.
Now, I do see places where itcould be useful where there is a

(41:12):
ton of literature on a certaintopic, and maybe it could point
to areas where there's gaps inknowledge by comparing things
that other people have said,maybe, and suggest some grad
student might want to go work onthis, give suggestions for
where you could do furtherexperimentation, maybe.
Or it could find parallelsbetween different fields.

(41:32):
And this happens in mathematicsa lot, actually, that you have
totally different fields, butyou're able to, with some
insight, find an isomorphismbetween these two fields.
Oh, actually, this field isreally the same as this field,
but it's like a differentmapping, different
representation, like having amatrix representation of
something or a graphicalrepresentation of something, and
it might take a while to figureout that oh, these are the same
thing.
Ed Whiton, it's string theory.

(41:54):
There used to be dozens ofstring theories, and he managed
to unify them, show them, oh,actually, these are all just
aspects of the same theory.

Louis (42:00):
Or in computer science, lambda calculus and Turing
machines.
So Alonzo Church's work andAlan Turing's work ended up
being isomorphic.
But at the start, they werecompeting computational models
for how computers could work,anyway.

Doug (42:13):
So there are places, but dude, it's not you're not
pushing the envelope, it's notreaching the edge of physics,
you're not doing anything.
You're not finding new physics,at least not theoretical
physics.

Louis (42:23):
It's mental masturbation.

Doug (42:25):
That's what it is.

Louis (42:26):
He's gonna bleep me out in the podcast there.

Doug (42:29):
So yeah, anyway, that just irked me.
And these people that do thispodcast, these are the investor
class, right?
Correct.
So they're so bought into thishype, and it's something that I
can see that oh, wait, this isnuts, right?
And you guys maybe can't tellthat it's nuts, but it's nuts.
Someone needs to tell you thatthat's nuts.
So yeah, it makes it feel morelike a bubble.

Louis (42:50):
It is absolutely yeah.
And I work in AI, I developmodels, I do all that work, I've
been doing it for a number ofyears now, but I also use the
tools daily for work and not forwork.
And so they're very powerful,useful tools that are not
actually self-aware or notartificial intelligence and are
not better at doing my jobwithout me versus with, you

(43:12):
know, it's a tool.
Yeah, anyway, back to thetopic.
So XAI raising all this money,they're buying video cards.
Are they gonna do anything withit?
Who knows?
Elon said he doesn't want Teslato buy XAI outright.
Part of me wonders if thebubble was to pop.
Say it starts to go down if hethen uses it at that moment to
buy, because right now XAI isgrowing and riding that bubble

(43:33):
wave up, and it's gonna growfaster than what Tesla likely
could, just due to the sizedifference, right?
It's easier for a small thingto grow bigger than a big thing.
I'm curious if things turn, ifsuddenly it's like, oh, investor
dollars are drying up andpeople are less interested, and
video cards stop being able tobe produced at a rate that they
need or whatever.
If suddenly he sees the writingon the wall and goes, Hey,

(43:55):
now's a good time for us to buyXAI just to leverage it into
having more controlling sharesof Tesla.
But yeah, I don't know.
What's funny to me is a lessonthat Elon didn't seem to learn
that many other tech companyexecutives learned.
You know, if you look at Googleor you look at Meta, Facebook,
the founders of those companiesonly have a small percentage
share, right?
Surrey and Larry combined don'thave as much ownership of

(44:17):
Google as Elon has of Tesla.
Elon actually has more Teslapercentage-wise, which gives you
value that gives you dollars,your bank account.
But they have 51% controllingshares because they have
multiple classes of shares.
So I think their class B islike 10 to 1 voting power versus
value.
And a normal person can't buythose shares, only the founders

(44:37):
have them.
So basically, Elon didn'tstructure the company in that
way for Tesla.
I don't know if he didn't knowthat he could, or if he just
never did, and now it's too hardto do.
It might go back to Martin andMark.
Right.
It might be he never couldbecause he wasn't actually one
of the co-founders of thecompany.
But it's one of those thingswhere Elon probably wishes he
had some other class of shareswhere he could do that.

(44:59):
Uh, but yeah, Zuckerberg, hedoesn't own 50% of the meta,
Facebook, but he does have a lotof controlling stake because of
it.
Elon is much wealthier than allthose folks because he has a
higher ownership stake at thiscompany, but because he doesn't
have the voting shares, it'sriskier for him.
Granted, he has pretty goodcontrol over his board and the
majority of the investors rightnow, but things could change.

(45:22):
We'll see how it goes.
I agree with you.
I'm shocked SpaceX is going tobe investing.
I don't see what SpaceXbenefits at all.
I worked for an AI startupcompany that was doing quite
well, had a lot of investmentmoney and IBM Watson people, all
this other nonsense.
And we had a project for NASAthat we spoke with them about
it, and it was so ridiculousbecause it's like AI needs to
run on a cluster of machines, ithas to run on a big cluster.

(45:45):
You don't have that in space,and you can't usually deal with
the latency delays depending onthe type of thing you're working
on.
So space greatly changes howmuch AI you can have.
Oh, having that HAL, yoursci-fi stuff, we're very far
away from having that.

Doug (46:02):
There are companies talking about putting these data
clusters in space, right?
Sure.
You'll have unlimited solarpower, and then also you can
deal with your thermal issuestoo.

Louis (46:10):
You're gonna need all that shielding for cosmic rays,
right?
Depends where in space you'reputting it, I guess.
You're gonna have to deal withbit flips and error rates and
all that.
Yeah, but you can errorcorrection, you can decrease
those and then but errorcorrection usually comes through
additional hardware, so you'rerunning less throughput of what
you have, or you're running onmuch older technologies, you're

(46:32):
not running like four nanometerin space, you're using 28
nanometer or bigger becauseyou're less prone to those types
of interference.
It's one of those things thatif you want bleeding edge video
cards and you want to juiceeverything you can out of there,
yes, space is an option, butit's gonna be difficult.
And then it's the bandwidthtransferring data back and
forth.
But anyway, SpaceX, I'm notsure what they're gonna benefit

(46:52):
from this.
I think it might just be anElon control SpaceX.

Doug (46:55):
I would think SpaceX needs that money given how they're
behind with the Starship andwhatnot.

Louis (47:00):
Yeah, that's a few more rockets they could be blowing up
to test things.
Two billion bucks.

Doug (47:04):
But SpaceX is private, and Elon probably has majority
controls so he can make thathappen.
He can do whatever he wants.
Tesla makes a little moresense, though.
Yes.
That hasn't happened in my caryet.
But putting grok in the car, doI even want that?

Louis (47:18):
I do not want grok in my car.
There's an argument to be madethat the improvements or the
advancements that XAA does couldbe leveraged by Tesla for
self-driving.
The newer architecture thatAndre Carpathy, what he did
before he left being director ofdata science and machine
learning stuff at Tesla was theyswitched over to a
transformer-based model, right?

(47:38):
Transformer architecture iswhat LLMs use.
It is possible for improvementsto be made at XAI that do help
Tesla, but you don't need togive them billions of dollars
for those improvements.
That's not helping Tesla.
So that's that.
That's on the XAI stuff.
We'll see what happens.
It's gonna be shareholdervotes, I'm sure, whenever they
get to that point.
So one of the other things wewant to talk about model y

(48:00):
variants.
So there have been new Model Yvariants seen, and I'm gonna
pass it to you because you knowway more about it than I do.
I just know there's asix-seater in China.
Is it Model L or something likethat?

Doug (48:11):
This is Tesla trying to be more competitive in China, I
feel.
BYD has been doing game bustersthere.
Overall, if Tesla sales aredown, revenues down, they're
losing certain things like theEV tax credits, the 7500 federal
tax credit, and then also thezero emission vehicle credits
that they're able to sell thosecredits to other companies.

(48:32):
Basically, the Trumpadministration has zeroed all
that stuff out.
The 7500 that goes away Q4.
So Tesla has for competition inChina, they have this L variant
that's basically a six-seater,it's seven inches longer.
People want people movers.
I think that's reasonable.
My disappointment of it isstill has that sort of fastback.
I'd rather they just squared itoff like the Rivian and made it

(48:55):
more of a proper people moverbecause I think even with the
longer someone like me sittingin those back seats are going to
be cramped without the ceilingheight.
So it ends up being just likeseats for kids, maybe slightly
bigger kids.
There was already a six-seatervariant of the Model Y, or I
guess maybe even seven-seaterbecause they just had the
standard bench, but that waskind of ridiculous.
So this makes some sense.

(49:16):
It feels a little too little,too late in China.
China has some amazing, verycool sort of luxury vehicles
there.
But I expect that this variantwill probably make its way to
the US.
You know, the Model Y is theirmoneymaker.
And then the other thing isduring the call, there's some
talk about this lower costTesla.
And they've talked about in thepast, but it wasn't gonna be

(49:39):
what some people had called theModel 2, like the lower cost
vehicle.
The question was asked, Well,what is it gonna look like?
And one of the other executiveswere like, Well, we can't
really talk what it looks like.
That'll be like anannouncement.
And Elon just cuts and says, Itlooks like a Model Y, letting
the cat out of the bag.
Yep.
So basically, it's gonna besome Model Y variant.
We had a list of things aboutit because there was some leak.

(50:01):
They're just trying to make itcheaper.
So get rid of the glass roof.
It still has the front cameraand the bumper, it seems to
still have all the FSD-relatedstuff, but not that light bar.
That's to me the main coolfeature of the newer Model Y is
the signature feature.
Yeah, it's not gonna have thatreflective light in the rear
that glows down on the roadbehind it.

(50:22):
Instead, it's gonna be apainted body panel back there.
Maybe no light front bar.
And then for the interior,there's talk about maybe it
would have cloth seats.
They got rid of the littlecubby in the front, which some
people might like, kind of likethe pass-through back in the old
Model S days where those kindof open.
No cover on the cup holders.
I'm not really sure what that'ssupposed to say, but no real

(50:43):
screen, that should actuallysave some money, and it would
still have that single stock forthe turn signal.
But they want a lower costvehicle.
Earlier, they were talkingabout it being available in Q3
or something.
Probably they're gonna wait toQ4 because that's when the
discount goes away.
So they're gonna try to keepselling their more expensive
vehicles before that vehiclebecomes available, right?

(51:05):
But these changes that I don'tsee them saving that much money,
but I guess they could eat intotheir margin more, and then it
can also act as that productladder.
In a way, it just takes away alot of the things that were
added in the new Model Y.
So I don't see it being thatdifferent than someone driving a
2024 Model Y.

(51:26):
Sure.
The sound system might be astep down to try to make it
cheaper, or really just toincentivize people to go ahead
and spend that more money andget the better Model Y.
It's funny how everything isModel Y, because that's the
thing that's been making all themoney.
Though I have heard reportsthat that newer Model Y isn't
selling as well.
And like we've talked about,these cyber trucks filling up
parking lots all over thecountry.

(51:47):
I've also seen Model Y'sfilling up this space because
overall test of sales have beendown.
And we'll see if this helps.

But two main things (51:56):
one is a bit of a stale product line.
They could have come up with anewer car, but they spent all
that time on the cyber truckwhen they could have made a
proper pickup truck that morepeople would like or a newer,
lower cost vehicle.
Because these little refreshes,that's okay, but it doesn't
feel exciting.
It's not something that peopleare really clamoring out to get.

(52:18):
Right.
And then the other thing isjust the brand reputation
because of Elon.
There are other choices now,and a lot of people don't feel
like supporting Elon anymore.
And sadly, a lot of thosepeople were existing Tesla
customers.
And he doesn't seem toacknowledge that.
So I'm not sure how they reallymove forward as a company
there.
Sure.
And certainly the stock priceis tied to Elon.

(52:40):
The people that are buying upthe stock and speculate about
the future, they're reallybought into the Elon vision.
And for the most part, I amtoo, in terms of the basic
vision of where the technologyis going, what's interesting,
and what things are exciting.
But for Elon, that doesn'treally seem to be cars.
I would like Tesla to rememberits bread and butter and
actually be more of a carmanufacturer than you know,

(53:03):
Optimus and whatever, howevermany years from now.
They moved on.
Cars were old news.
Yeah, I really wish that wasn'tthe case.
I mean, if you want to spin offand do these other things, I
don't know.
Any opinions?

Louis (53:16):
I agree with that.
I wish they would stick withcars.
He already has how many othercompanies that he started at
different times.
If you want to do somethingdifferent, do a different
company that's focused on thatother thing.
But yeah.

Doug (53:28):
As a good segue, the next thing they've done is that Tesla
has opened this Tesla Diner.
A diner in LA.

Louis (53:35):
What?
Because that's a businessthat's got future written all
over it.

Doug (53:39):
Yeah, it's cool.
They've been talking about thisthing for a while, at least
since 2018 or something.
He wanted like a really cooldestination or whatever.
Actually, we mentioned it lastepisode when we were talking
about Elon stealing all thesci-fi names.
And there was talk aboutcalling this thing Milliways

(53:59):
from the restaurant at the endof the universe.
Milliways was a restaurantliterally at the end of the
universe.
Back in those days, the theoryof the big crunch was a bit
bigger.
So you had the big bang, whichis expansion, and then there
would be an end.
And so that's what DouglasAdams was sort of talking about.
And you could, I don't know,somehow travel through time and
end up being there.
And there's something abouttrying not to run into yourself

(54:20):
when you go again or something.
I don't know.
You know, Douglas Adams, hissci-fi was actually more comedy,
and the sci-fi wasn't that wellthought out.
But anyway, it doesn't seemlike they called it Milloways.
All the branding is TeslaDiner.
My guess is that there isprobably a rights issue calling
it that.
Right.
Uh, the other thing wementioned was the super cluster

(54:41):
that XAI has built, and theycall that Colossus.
And that's to me, is a directreference to Colossus, the
Forebend Project.
But Colossus as a name is veryold, and no one's going to own
that name.
You can't own it, right?
Yeah.
There are poems named Colossus,some ancient mythology.
You have an X-Men characternamed Colossus.
No one can just own that.
So I could see them using thatpretty easily.

(55:02):
But Millowes is prettyspecific.

Louis (55:04):
So can you give us a little bit of an update on
what's novel about the TeslaDiner or like what would we see
or learn about it now that itopens?

Doug (55:12):
It's got an interesting menu of supposedly pretty good
food.
I've seen people's reviews ofit.
They have these roller skatepeople that will deliver it.
It's trying to thinkretrofuturistic.

Louis (55:22):
That's what I think of the future roller skates.

Doug (55:25):
Well, it's retrofuturistic, right?
I know.
Yeah.
You can order food from yourcar and they can bring it.
But that idea goes back to the50s or whatever.

Louis (55:35):
The 1950s.
Yep.

Doug (55:36):
And then it also is kind of a drive-in movie theater.
They have these huge LED wallscreens.
They're showing stuff like StarTrek episodes, Twilight Zone,
2001, a Space Odyssey.
Supposedly they can't play fullmovies later into the evening.
I feel kind of bad for thepeople that live near this
thing.
Yep.
There's a condo where they lookat their window and they're

(55:59):
looking at the back of thesescreens.
And then you think about thepeople that now their windows
are being inundated by thebright LEDs of the screen.
That's the opposite problem.
But adjacent to it is this 80spot supercharger station.
So there's a lot of parkingthere.
Obviously, it's crazy right nowbecause everybody's trying to
check it out.
Because it's new.
Yeah, because it's new.
I'm not sure how sustainable itwill be.

(56:20):
We know the restaurant businessis very hard to make money
unless you're selling.

Louis (56:24):
Remember when cyber trucks were crazy and everyone
wanted one?

Doug (56:28):
We'll see how this pans out over time.
I've led to check it out.
I mean, this stuff's overpricedas anything else is in LA.
Yeah.
Seems neat, but in the middleof this neighborhood, the kind
of traffic it's gonna generate,and then also the time it takes
for you to get your food andconsume it, right?
To me is gonna be longer thanthe time it takes for you to
charge.
So then what happens?

Louis (56:49):
It's not an efficient use of space for charging.

Doug (56:51):
Probably you'll have people unplugging so they don't
get congestion charged, but thenthey're still occupying the
spot.
So supercharging isn't really adestination type charging
thing.
Right.
Supercharging needs to be onjust off the highways, you know.
In route.
Here it's the middle of thecity.
So I kind of feel for theseneighbors and just from the Bay
Area where there are people thatfeel like they need to
supercharge.

(57:12):
You have these long lines ofpeople waiting in this queue.
Actually, it'll be fun if theywere set up for a queue and then
people could take their orderswhile they're in the queue,
right?
And someone delivered it toyou, kind of like the drive-thru
at Chick-fil-A or whatever.
Right, right.
So they've talked aboutexpanding it, having one in
Starbase, which again would beinteresting, but they'd really

(57:32):
have to do the traffic controlbecause Starbase, you have a
pretty small highway going downthere.
And imagine if you have carstrying to line up to get in
there.

Louis (57:42):
Not a lot of infrastructure for this type of
thing, yeah.

Doug (57:45):
So another cool thing about it, I should mention, is
that they had Optimus theredistributing popcorn like you
might at a movie theater.
But clearly, given the way itwas moving, it was being
teleoperated.
So I don't know how long that'sgonna last.
But I did want to talk aboutOptimus a little bit.
Sure.
Optimus came up in the earningscall.
Elon has expressed the opinionthat Optimus is even bigger than

(58:05):
Robotaxi.
Honestly, I've been a littlemore impressed with other
companies instead of what I'veseen with Optimus.
Of course, the hand thatOptimus has is very interesting.
They've spent a lot of time onthe hands, but there are a lot
of tabs that don't necessarilyneed careful hands.
To me, the most interestingstuff I've seen is out of
Unitree.
For one thing, you can actuallyget one, and so you see
research people with theseunits, and they have a new

(58:26):
version out that looks more likean athlete, looks like it has
better balance and stuff.
So, you know, if you look forit, there are also some videos
of the unit tree going nuts.
Yep, I saw that.
Have you seen this?
I did see that video, yes.

Louis (58:38):
It's like it's ready to kill somebody.
Yeah, it was getting alltangled up, but there was like a
harness or something that I'veseen two different versions of
it going nuts.

Doug (58:46):
Sure.
It looks like it wants to justkill anybody around it with the
arms flailing around.
Destroy all humans.
Yeah, that's what it lookedlike.
You know, I'm nuts and I wantto kill somebody.
They're self-aware.
Yeah, but I think what happenedin both instances, because it's
on this harness, it's beingheld up, and so its feet aren't
touching the ground, and it'sbeen given some command, but it

(59:06):
has a sense of balance.
So it's trying to balanceitself, but its feet aren't on
the ground, so it thinks it'sfalling, and so it's doing all
this stuff to try to counteractthe falling, just like you might
do.
You might move your arms aroundto produce a torque to try to
keep yourself from rotating tothe ground.
So it's trying to do that andit's not getting the right
feedback from its legs becauseit thinks its legs are swept out

(59:27):
from under and it's just notstopping and it's just going
nuts.
So it's because it's on thatharness that is flailing around,
but that does not look safe,right?
You don't want to be anywherenear that thing.
Yeah, yeah.
I don't know how much mass itsarms have, but it needs to have
some mass for it to be able toactually help to have a
corrective use as it's trying toflail around.
So if you're in the way ofthat, man, you might end up with

(59:51):
a broken neck.

Louis (59:54):
Yeah, I remember seeing at one of the research labs
where I worked, they had thesesleeves they would put on.
Robotic arms that they theywere developing where they
basically project outelectromagnetic fields and it
could detect something comingclose.
So if anything was in range, itwould stop or slow way down
because it would be like, oh no,something's close to me, I'm
about to hit it.
But yeah, it's one of thosegeneral purpose problems of when

(01:00:16):
you have freely moving humanoidrobot in a chaotic environment.
How do you make it actuallyprotect to not move too fast and
hit something or a person orfall on someone or whatever?
There's so many dangers togetting that to be safe.
I think that's a lot of thehurdles that still need to be
solved before we will have themin our homes.
Yeah.
Right.

(01:00:36):
Even if you could have anOptimus and even if it could
walk around freely and dosomething to do it safely is a
whole nother question.

Doug (01:00:43):
There's a company called One X.
They do the software in the BayArea, and some of the work
happens in Norway.
But their philosophy is yeah,about the safety.
So if you look at their robot,it looks very soft.
It has a kind of a textilepadded cover on everything so
that you know it's pliable.
Like when you hug a person, forexample, you're squishing fat

(01:01:04):
and muscle.
You're not hitting bonesdirectly.
Not hitting the bones directly.
So that's the idea that thebody is compliant, sure, such
that it has some give when youtouch it, so that you're not
instantly gonna get injured byinteracting with the thing if
you happen to bump into it or ithappens to bump into you.
So at least there are peoplethinking about those kind of
things.
Yes.

(01:01:24):
As far as Optimus, though, uh,I feel like that's had some
delay also because Elon has beentalking about, oh, we're gonna
sell a Legion.
But the update he's given isthat, well, we could have done a
thousand of Optimus 2, but wehave an Optimus III coming down
the line, and we'd ratherinstead of going to production
with Optimus 2, we'll go toOptimus III.

(01:01:44):
So it looks like they'redelayed a year or so compared to
what they were talking aboutbefore.
Because they were talking aboutsome deliveries, yep, but it
looks like that's been pushedout a bit.
I guess the first time I wasrunning a program, he left, he's
gone.
And actually, Tesla's hadseveral key people leave.
Yeah, executives leave andsuch.
Head of sales, head of sales ofNorth America.

(01:02:06):
It's like, well, we're notreally selling much, so get out.
You gone.
I don't think it's that guy'sfault.
Of course not.

Louis (01:02:15):
Yeah, yeah.

Doug (01:02:15):
We had a comment that we'll pay attention to.
Drew Z said, if they bring backfree supercharging for the life
of the Cybertruck, I'm gettingone.
That probably is a pretty gooddeal.
Not for me, it's not.
If you like driving, if youlike going on trips or whatever.

Louis (01:02:31):
I've still never needed to supercharge my car in three
years or whatever.

Doug (01:02:35):
So I was hoping to go on a road trip myself, but I have
some international travel comingup and I didn't have time to
fit in that road trip.
And I'm annoyed because thesupercharger miles that I have.
I have like a thousand freesupercharger miles.
Are they expiring?
They're gonna expire.
It's like, why?
Why do they need to expire?

Louis (01:02:53):
Like your credit card points, your frequent flyer
miles.
Most of them don't expireanymore, but they did for a long
time.
Come on, man.
They don't like carrying theliability on the books.
I guess they like to be able towrite it off.
Yeah, it's too bad.
Well, that's unfortunate.
I never had pre-superchargingmiles, and I probably never
will.
I just charge it home.

(01:03:14):
Cool.
As always, thank you all forlistening and hanging out with
us.
Mike will be back, hopefully,on the next one.
As always, you can become asupporting member on Tesla
Motorsclub.com.
You can post on there, find allkinds of great info.
All right, well, have a goodone, and we'll catch you next
time.
Later.

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Q2 Earnings Call, Robotaxi Trials, & Tesla Diner | Tesla Motors Club Podcast #75

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.css-14f5ked{margin:0;word-break:break-word;display:-webkit-box;-webkit-box-orient:vertical;box-orient:vertical;-webkit-line-clamp:2;overflow:hidden;}Q2 Earnings Call, Robotaxi Trials, & Tesla Diner | Tesla Motors Club Podcast #75