Venture Step

Dalton Anderson (00:00)
Welcome to VentureStep podcast where we discuss entrepreneurship, entry trends and the occasional book review. Today we're going to be taking some time to take a ride through the fascinating and sometimes chaotic story of autonomous vehicles. So no pun intended. Let's buckle up. But of course, before we dive in, I'm your host, Dalton Anderson. I've got a bit of a background in programming, data science, insurance.

Offline you can find me running building my side business or lost in a good book You can listen to this podcast and video and audio format on YouTube If audio is more your thing you can find the podcast on Apple podcasts Spotify or wherever else you get your podcasts Once again today, we're going to be discussing the journey sometimes bumpy but fascinating journey

of autonomous vehicles. And autonomous vehicles, feel like is one of the few mature industries that is still built on speculative value. Like I don't think there's that many companies that are providing a service to the public, either B2B or B2C.

where it's generating legitimate revenue to support all the resources going into the projects. I don't think that there is a company right now that is providing like a surplus. I know that there's people selling shovels. I mean, we know that story. It's not the people digging for gold is the people selling the shovels that make the money. And so you could see those things with the AI, with Nvidia selling the GPUs to, and these other AI specific chips

these AI companies and the videos holding the bag. Same thing could be for.

companies that provide hardware. know that Tesla used to get used their AI to run AI on Tesla. had and this camera setup is pretty odd. It's doing some construction in my room and the is kind of a sidebar but there's a construction in my room and I got another monitor on my desk and I haven't rearranged my mic setup and stuff. So I got you set up on an underwear box.

and I'm looking into the camera and it's like literally in my face. It's a bit odd. So trying my best. If you're watching on video, if not, then you won't know what I'm talking about. But anyways, back to it. Hardware, selling hardware, Tesla. That's what I talking about. Tesla used Nvidia for the longest until COVID happened. And then Tesla was rightfully so upset because

they couldn't produce some of their Teslas because they had all the Teslas built and ready to go. But they didn't have enough chips to provide to the Teslas. so Tesla was like, all right, well, I guess we'll just make our own chips, which is crazy because it's not that easy, but whatever it worked out. Similar thing could be said for Amazon during those peak shipping periods.

Amazon was heavily reliant on UPS and then UPS was missing some of their orders and are not, you know, not necessarily missing the order, but missing the shipping times for the order. And so Amazon's like, all right, fine. I'll just make my own logistics company. Can't be that hard. And so it's kind of an example is

At certain points, if you're not, I don't even know what I was going with that. was really going on a tangent with the Tesla thing and talking about how Nvidia is holding the bag basically and making all of these chips and the autonomous driving vehicle industry is built off of speculative value and it currently doesn't offer major services to the public at the moment. That could be changing.

with regulations and other things and improvements, but at the moment, no. And so I'm saying, okay, most of the money is going to people working on the projects and or companies providing hardware.

And maybe my point was, hey, if you're providing hardware but can't sustain it, some of these larger tech companies will just build it themselves. But for smaller ones, obviously, they

enough of that. Today's agenda is we're going to talk about the early days and that deals with the DARP challenges. Then we'll talk about how DARP kind of raises stakes a little bit. And then we'll talk about the next section of DARP. And then we'll talk about the, you know, the rise of self -driving cars and like which companies are which and blah, blah, blah. And where we're at today, which is pretty interesting.

Okay. That being said, so DARP, DARP is the Defense, what is it? Defense Advanced Research Projects Agency, for sure. And DARP had an initial challenge in 2004 where they requested a group of people, I would say like, you know, teams, group of teams to compete in this autonomous driving vehicle challenge in the Mojave Desert, 150.

Mojave. Oh man, I'm butchering that on the podcast. One take, one take, no edits. So anyways, so we're in the desert, 150 miles.

And no one finishes in 2004. And there's a couple of reasons why they didn't finish. Once, one, there were, you know, sensor limitations. There wasn't as advanced as today. Like the sensors weren't as advanced as they are today or, and you'll see later, pretty soon later, they get advanced. They had, you know, algorithm shortcomings.

Their algorithm was used like processing data were not sophisticated enough and they weren't consistent in maintaining control in complex environments like the desert and navigating at all. Mechanical and hardware issues. The heat caused issues with stuff being overheating. So these chips typically like if you have a computer at home or if a computer on or yeah, if you have a computer at your house.

so you may not, but a computer, a laptop, when you're running like a video movie for a long time or playing video games on it, you'll hear the fans start going and you'll hear the, you'll hear everything overheating, like not overheating, but you'll, you'll feel your computer getting hot. And at a certain point your computer was overheating shut down to avoid risk of like burning out the chips. So basically, you know, the, all the workload

what you're computing on the chips, it slowly heats up the system and your phone gets hot. Sometimes you're playing games for a long time. That's from, you know, just the computation of the chips working and energy is transferred via heat. And obviously it heats up your phone and there you are. Your phone is hot. Okay. So think about that, but think about a car, the computers it takes to run

car through the desert. It's hot and it's already doing a lot and and it's difficult and they probably didn't test it that well. So here we are. It's just overheating and just not working. Another thing that they had was they had communication challenges.

So they had basically like a control center you'd think of and now would send the instructions or so to the to the vehicle.

those instructions were only making it so far. And so after like 30 miles or something, it just disconnect. that's an issue too, because if you don't know where you're going, what to do, then well, you're lost. So one year later, like right after that challenge, everyone failed. And the government was like, hey,

We need to figure this out. We want people to finish. So what they did was they did the same exact challenge and they're like, if you win, I think if you finish the race, they are to the increase of difficulty and then if you finish the race, you got a million dollars. And so they'd fund your project or

Same thing, same kind of gig in the desert.

It's significantly more difficult race, but if you finish you get a million dollars.

That year they had sensor improvements. They started using LIDAR. They had better sensors and they had a year to kind of figure it out. LIDAR can be used for like low light or no. LIDAR can be used in low light situations and LIDAR stands for light detection and ranging.

So LIDAR works in a way that's different than other sensors for autonomous vehicles to where you can see at night. And that's basically what you need to know. They do some tests on it. You can see online where the car works, it can pitch black with no light. And without that, you can't see. But LIDAR has some caveats.

So it's good to have a balance, a mixture of a couple different sensors, and then you get the best of both worlds. It's like, if you buy a computer, not a computer, if you buy a camera at home, like for your outside, and your camera is only color, and then you try to do video at night, and you can't really see anything.

And so it's good to have a camera equipped with both color and night vision or, you know, black and white or something. And so that's kind of the same, same premise here. The team started incorporating machine learning into their algorithm. And so that, that improved kind of these simulations and things on the fly because the models they were using could only interpret the real data that it was receiving. So it wasn't able to do simulations as well.

So machine learning, can do this virtual learning via simulation and improve their model by training it in a virtual world instead of the real world. They did a whole bunch of collaboration. And so these other teams, they kind of all banded together and it was like, hey, like, what do you know? What are you doing? What am I doing? And so they all worked together with their collaboratively sharing their knowledge, which was great after the 2004 event of no one finishing.

I think they were just like, don't care who finishes. We just need someone to finish. Please. We, we can't be embarrassed like this again. We're supposed to be smart. So they applied all their lessons learned from the 2004 failures and they addressed their weaknesses and design and they led to, it led to five teams finishing, which is big. And so then the government was like, okay.

All right, so we got some promising candidates here. So they moved on to the desert. They moved on from the desert to the cities. And so the cities is a bit different of a challenge because obviously it's in the city. It was closed off, but it's in the city. You've got to obey traffic laws. so this, I wouldn't say punished, but this pushed the team to

apply these sophisticated algorithms and sensors

the real world. And so we're shifting to a real world complex problem. And it forces these cars to act in a controlled way in this controlled environment. So it moves it from this controlled environment, like the deserts, to a complex urban setting, which is different. You have

Abide by pedestrians, intersections, parking and other real world scenarios.

In the challenge, I'm pretty sure it's closed off. DARPA has these fake cities that they have built. So they just use those, I'm pretty sure. But I have to look that

But okay, so the challenge was in the city, right? Because you have to apply these real world problems. I mean, these real world, these real world situations to this already complex problem as is. And apply traffic laws, follow city streets challenge. Where, and I'm looking it up. Where is the location?

Urban Challenge.

So, okay, so this is 2007. I found one, but I guess they...

Okay, so in 2007 it was held at...

The George AFB. I don't know what that is. So I'm sure the internet knows. AFB. Okay, so George Air Base. my gosh. that's embarrassing. The George Air Force Base. Let's say you know, I don't know anything about the military. So if you don't know, AFB stands for Air Force Base. Got

So it was held, this urban challenge in the city was held at an air base. So it is kind of more of a controlled environment. Like I was saying, like there's, they're not going to like, okay, now try it in New York city. Like that'd be crazy.

Okay, so there's a couple issues with this. So you'd have increased autonomy of the vehicles. You would need advanced perception and decision making to navigate these urban environments. You need object detection, tracking, to know what these objects are. Like what does a human look like? What does a stop sign look like? If a light is red and

What does that mean? What if it's blinking red? What if it's red and you're in the right hand lane? I mean, there's just a lot of like, what ifs going on here. And if you're in the right hand lane, boy, you need to go to left hand all the way across the three lanes. Like how much space do you need to do that? What's a proper time to trigger your turn signal and then turn from or lane change like

like doing lane changes, navigating intersections. I mean, there's just a whole bunch of issues that come when you're applying all these.

real world requirements of autonomous vehicle driving. And a lot of those sometimes are conditionally made, but like how do you go about the image detection of like on the fly, looking at a video on a camera, detecting that there's a stop sign, how far away can you detect the stop sign? Is it a clear stop sign? Like I know the stop signs have like hanging trees over it, so maybe it's

Maybe it's 30 % of a stop sign, 40 % of a stop sign. How do you know that that's the stop sign that if that's a stop sign at all, I don't know. How do you not confuse the pedestrian stop signs on the sidewalks versus an actual stop sign? Is it the sizing or does it just recognize the color or what or where it is to the angle of the car? Would that determine it? I don't know. There's a lot of questions that they have to ask themselves and answer.

may or may not have had all that figured out by then, but they do need to figure it out if they're ever going to launch, which they have done that later. Public awareness. So I think people, people are less comfortable with this autonomous vehicle thing. They've seen all these sci -fi movies where the autonomous vehicles take over, people hack their car and drive them into a brick wall and off them. There's a whole bunch of movies like

where you just need to be walking around in

aluminum hat and protecting yourself against aliens, which I recommend by the way, if you ever leave the house without your aluminum hat, what are you doing? I've got one. I've got a hat that's lined, lined in aluminum custom made for me and I make sure I never leave the house without it. Anyways, hopefully you guys got to kick out of that one. Hopefully my mom is killing me right

to listen to this. He's like, what are you doing? Okay. So public awareness, people typically aren't very cool with autonomous vehicles. People don't like change. They're not necessarily going to embrace it. It's sketchy. I feel like it's way less sketchy than driving itself though. People can doze off. can, you know, get frustrated, distracted, whatever.

and cause mistakes and cause people to die.

So.

I think that if you were not driving and it was just an algorithm.

Who's at fault? Is it the company though? I don't know. I think it'd be difficult. I think it'd be difficult to prove that like a company acted in negligence. Like how can you say it might be at fault, but is it at fault or is the person in the car that wasn't paying attention at fault? Cause the person is still supposed to be monitoring

the system. I don't know, maybe if you're sitting in the, all the way in the back, like laying down and your autonomous vehicle just drives you wherever you

And I think then, how do you get a drink of water? I think then that you might have some level of, hey, we could blame it on this company, but I think it's just difficult. I think it's difficult thing to do.

Sidebar again, but public awareness. People are now aware of autonomous vehicles and they're kind of freaked out about

There's tech enthusiasts like yourself. You're listening to this podcast episode. You probably think autonomous vehicles are awesome. And then there's a lot of people, majority of people are not for it at all. But this race, the city one, inspired commercial applications where you can apply this autonomous vehicle technology to these real world situations, which I keep repeating.

And the development of the self -driving car industry has bloomed since then, or what they'll say to you. So the rise of self -driving cars. So there's been quite a few people that started

didn't finish and there's quite a few new players. But the one player that has been constant in this regard is Google's Waymo. Waymo started in the mid 2000s and I think Waymo has the strongest position right now and Waymo is right now offering

US.

Right now, Waymo is offering routes in the US. so they are, as of June 2004, Waymo is offering autonomous ride services, Waymo 1, in Los Angeles, in a 63 square mile from Santa Monica to downtown LA, Phoenix. So now it's saying Phoenix fleet.

expanded to include North Scottsdale and North Phoenix, Mesa.

San Francisco.

San Francisco has logged more than 3 .8 million miles while providing rides. Austin is testing, Waymo is testing their fully autonomous rides across 43 square miles of the city.

and they're also in DC and some other places. So I think Waymo has one of the best positions for that reason. It's like Waymo is just way more in front. I try to make a pun out of that, Waymo, way more in front. But Waymo.

Think is in the best position for these offerings. But Lyft has an offering, Uber has an offering, but they don't.

Originally they were pushing for autonomous vehicles and then I think that dropped off. drew, I think Uber, and this is kind of confusing because they'll say, well, we're not doing this anymore. And then they will not do it. And then they'll come back and they'll not do it. They'll think about shutting it down. They'll pull funding, they'll add funding back. So it's kind of difficult story to, to follow cause it's constantly changing and you never really know.

what the deal is. Okay. So Uber, Uber gave up their own proprietary Uber model or Uber autonomous vehicles, whatever you want to call it. And Uber is partnering with, guess who you know, Waymo. So Waymo and Uber partner as of May, 2023. I wonder

Yep. So Lyft is also partnered with Waymo to provide self -driving vehicles. Okay. So that really solved it. That really solved it. Everything just came together there where

Waymo is ahead. So there's Waymo and then there's Tesla, which I love Tesla, but I'm just really not sure about their full self -driving capabilities. I mean, it's been going on and on for years that they're talking about full self -driving, full self -driving. But is this full self -driving? I don't know. I don't know what level their self -driving is, but I don't think it's full.

self -driving.

Okay, so full self driving is rated two.

So basically the driver needs to stay ready and be attentive at all times to make sure. So it can handle like parking, traffic signs, other things. Right now I guess they're in beta for self -driving level five.

I'm not really sure how it's called full self -driving if it's not full self -driving though. So I'm kind of confused like why call it that? Just call it self -driving. Why are you calling it full self -driving? And then people that I don't know, people that don't know it's like any of these things like related to autonomous vehicles, they're gonna be so confused. They're gonna be like, wait, what? What's going on here? He said full self -driving. This isn't drive itself. It parks my car.

which a lot of companies can do. It's not a big deal. Okay. So there's Tesla, which is behind Waymo and Waymo should be in front to be fair. Like Waymo started pretty much first. Waymo has the backing of Google and they've been backing Waymo for a long time since like the mid 2000s. And they had a headstart. Google has massive resources in machine learning and deep learning.

the infrastructure to support these things. And I'm not saying infrastructure like company initiatives and capital. I'm talking about they've built up over 20 years, built up servers and these TPUs that they have and these other things to allow them to train data and run simulations and be at the top of their game when it comes to deep learning, machine learning and all these

type of algorithmic processes that require a lot of resources and compute. Google already has it all set up for them. And I would think that that gives them an advantage, because you're not starting from scratch on something that takes a long time to build yourself and is very resource intensive and time intensive to get that all put together and energy intensive. There's a whole bunch of things that makes that difficult.

So they should be in front. And if anyone asks you like, why should they be in front? You could just name off a couple of those items and be like, okay, that makes sense. Thank you. Thank you. Thank you for letting me know. And then you'd be like, Tesla's come a long way. I just don't think that they should call it full self -driving if it's not full self -driving. They're in beta for full self -driving, but they're currently only offering level

and it was crazy expensive before. And you would think that, so it was expensive, full self -driving, Tesla, it was expensive before they made it a subscription. It's $99 a month, which is a lot. But it used to be,

It says opens on Saturday, this is April, 2021, 2004. On Saturday, full self -driving is software's $8 ,000 from the previous price, $12 ,000. And that is only tied to the owner, not the car. So if you sell your Tesla to someone, that feature,

is tied to you as the owner, not to the car. But I don't think if you buy a new car that you get it for free. think that if I'm to ask that if you buy a new Tesla after you purchase.

Do you need to buy

license.

Ahem.

Okay, so that is nice. All right, so it's tied to the car, not the car, it's tied to the owner, but the owner's license isn't tied to the car, it's tied to the person. So maybe you can also, this would be pretty cool if you could inherit a full self -driving license. That'd be pretty cool too, where if I unfortunately were to die, I could give it to my friend and they would inherit it, or I'd give it to my mom, or whoever, or my nan.

that or my dad, that would be pretty cool.

But it's not tied to the car, it's tied to the owner. And if the owner buys a new Tesla, you don't have to be concerned with, I have to buy another one. You can just transfer it to your new vehicle. it says, customers who purchase a new vehicle may be eligible to transfer full self -driving capability from their current vehicle to the new one. Okay. Pretty cool.

That sounds very sticky. You know, once you drop $12 ,000 on your license that you have permanently and you buy, you're in the market to buy a new car and you're like, should I buy the car with full self -driving that I don't have to pay for? And I can just transfer my license to the new car or should I just buy a new car and potentially buy another license?

think it's an easy question to answer. Okay. So the challenges that we've had is there's been a couple of accidents. There's been people falling asleep at the wheel, potentially hurting others. And there's been a couple of people that have died.

And there's other issues, just people are just concerned about the whole thing. And I guess rightfully so, but I don't know. My personal opinion is like, people die a lot from car crashes, like a lot of people.

each year.

Okay, so 43 ,000 people have died.

her year. And I guess that was the last that was the last statistic as of 2024 43 ,000 and in 2002 34 ,000 people. I'm not trying to say that the people who died are not important. Like obviously I'm not advocating for anyone to die, but I do

that the progression of this technology if done correctly could save a lot more lives than just the couple that have lost during the process. mean, obviously I'm not, once again, I'm not advocating saying that's good, like they deserve it or anything like that. All I'm saying is accidents happen and I think

the technology improving at the rate it is. And if they do it correctly and in a safe manner, that years from now, we could potentially have this technology to allow elderly people that can't see very well or have anxiety related to driving with high traffic situations.

they have a way to get out of the house and experience the life and freedom that they used to experience when they were younger. And they could live better lives and be more connected with the community and allow more time with families when you're traveling instead of having someone drive. And you could play board games or do something as a family or watch a movie all cuddled up in the back. I don't know.

possibilities are endless or you get a company car and then you have to work during your company trip in their car anywhere you go on company hours and you're working not only when you're traveling and in the office, you're working in the car. You're on call in the car. I'm sure people love that. Imagine the productivity, Bob. What if, what if we just, we just got everyone company cars.

and we had them work in the car while the car's driving them to places. Like they need to run errands during work day, that's fine, as long as they stay in the car. And then we also give them an AI bot butler that could take the errands from them while they park their car and they'll stay parked in the car and the butler would go get the groceries. The butler would go get those things. And if they wanted to get a haircut or something like that that requires them to leave the car, then they have to schedule an appointment.

Yeah, I don't know. That could go down a dark path, but I think it's pretty funny to think about. Okay.

Crazy sidebar there. Crazy. We're having fun today, you know. It's crazy. Crazy where I go sometimes with these things. Okay, so there was other traditional automakers that kind of had their own little go at it. So GM had, I think Blue Cruise division. I'm not sure how active that is. Is.

A lot of these things are really shut down honestly. During COVID there was like the big crash. Cause these companies were just held, hold, still, they think, yeah. It self -filled that. Okay.

So Blue Cruise is...

for Ford and Lincoln's and that is, I just don't know who they're partnered with because they closed out their venture with Argo AI. So Ford acquired Argo AI. Argo AI was a startup that was also part owned by Volkswagen. So Ford and Volkswagen had a partnership with Argo and then GM had their own little thing called,

Cruz I think or Cruz something. They just made that themselves in Cruz.

LLC under General Motors. So this is was talking about. In 2003, they suspended operations for cruise. This is GM's subsidiary. And then in 2004, May,

put the cars back on the road to begin testing.

is because their operational permits were

Okay, so Blue Cruise, Argo AI is no longer part of Ford and Volkswagen Group. So after that, Ford was focusing more on like they said near term assistant driving features, which I don't necessarily agree with because I think that a lot of the big features that we have in life are from

like shooting for the stars and ending up in the moon. Like all the technology advancements that we had from trying to land on the moon that we still use today is like bonkers. And so when you're really pushing, pushing the boundaries of what can be to reality, try to push that into reality, what you're dreaming of, the side effects of, you know, these ideas flinging off the hammer.

come into the public, the public eye or just the public in general and greatly affect their lives in a positive manner. So I think they should always shoot for the moon or shoot for the stars and if you end up at the moon, yeah, so be it. I you're still far away. Well, what do I know? I've never ran an auto company before, so who knows? Just my thoughts.

So the Argo AI company shut down. Volkswagen is still pursuing the self -driving and they're partnered with a company called Mobileye. And then there is another company called Motional, which is Hyundai's joint venture. Motional is in development for level four and they also have partnerships with Lyft and VIA.

So some exits, Uber has notably had an exit in 2023. They shifted from that and they sold their stakes in the Thomas vehicle group. from there.

They are now just partnered with Waymo, which is fine. I'm Google fan, it's all good. More for it. So Argo AI is what was once a, know, this promising self -driving startup backed by Google and Volkswagen. However, both companies decided to shut down Argo in 2022.

citing challenges to achieve autonomous vehicles at scale, which is true. It's

There are some Chinese companies that I potentially will butcher, but there's a value pony and we ride. just bad, bad bay.

They have government support as they're kind of all merged into one area. Like if you're a big company in China, like you're pretty much a part of the government. So those companies have strong government, government support and they're able to kind of do it as they wish and really push the technology forward. And there's technology providers. Like I was talking about like Mobileye.

and Luminaire Technologies and so on. Those companies are the people selling the shovels and Mobileye is a big one. Mobileye really equips a lot of orcs for their vehicles and the stuff is not cheap. Some of that stuff is like couple hundred thousand dollars. The Mobileye kit for your car.

And the LIDAR stuff, I mean, it's all pricey. It's all pretty pricey. And Mobilize revenue at 2023 was 2 .8 billion. Not bad, not bad. There's not that many billion dollar revenue companies. So I hope that gave you a better idea of where we're at with autonomous vehicles. And there are some large,

scale companies and there are some smaller ones. There are some companies selling shovels. But once again, I think that it's super interesting because there isn't that many industries that have this much resources devoted to it that is completely speculative. know, AI companies have products that users are using at scale and these AI features, I'm sorry, features, these AI products

kind of like features where Apple or Google or Microsoft could add that feature that you were offering at a company and it basically just closes you down, closes you down. And so at a certain point, you gotta turn your feature into a viable product or else you're gonna die. But you have to do so before you get too big to where the company that you're trying to steal market share from just makes

a feature that they just added to their product. Because if you make things inconvenient for other people, they're just not going to do it. So that's the lesson is, man, the specular value of autonomous vehicles. I'm all over the place. This episode, it's crazy. I was asked at work today if I had a long weekend and,

I was like, that question towards me? Cause like a group of people in the meeting and they were like, yeah, yeah, it's to you. And I was like, yeah, I guess so. I was working on the closets all weekend when he has house and he's like, yeah, man, you look at it. Thank you so much. I really appreciate it. man. Okay. So there's quite a few companies.

At the level of autonomous level two, there's some at three, four, and there are some that are like partially there, fully autonomous. I think there's only Waymo and maybe some in China. But I would say majority are at two, some are at three, some are at four, and then very few at

There is.

testing at five, I'm pretty sure, where like no one's in the front seat and it just drives itself. But it's at, it's fully autonomous, but it's not fully autonomous to the point where people trust it to drive 80 miles an hour on the highway or 70, depending on whatever your speed limit is. People don't trust it to do those things. And so there was a company that was pretty interesting that closed down during COVID and I didn't really find another example. I mean, there's the Indy autonomous driving track.

race, India autonomous driving race, where they pitted top universities against each other and professors to make an autonomous driving vehicle.

racing against the track at speeds of like 150 or something. And so their thought process was, okay, if we could safely race cars at 150, we could drive cars at street level, street speeds, which makes sense. And then there was this other company that was like a Formula One for racing for autonomous vehicles, and it was called Robo Race. And Robo Race sounded pretty sick. It was this world's first autonomous vehicle racing series.

where teams that compete with self -driving cars and they basically like a computer science and engineering team, mechanical engineering team to build the cars and the algorithm to race. But one of the cool features was you could race the car yourself. So like on the track, you could be racing with the other AIs and you could basically be playing a video game while the event is going on.

racing against the AI and having this level of experience, like heightened experience that hasn't been seen before. So I feel like racing is a lot more like when you're doing it. I'm not a racer. I did like go -karts, like speed go -karts. go like 50 miles an hour. But I'll tell you that doing that is fun, right? I feel like some things you have to experience yourself.

If you're watching someone.

shoot a rifle, like you're like at a driving range, or not a driving range, that's golf. If you're at a shooting range and you're watching it on TV and like some person's like loading up a rifle and then shooting out the range, it's not the same thing as you going to the range and shooting the rifle. Like it's way different, it's a way different experience. And that can be said for a lot of things, but the excitement

like racing around, feel like would be way more when you're racing other AI drivers that are on the road racing in real life in real time. It sounded really cool, but it closed and folded obviously during COVID, as I said earlier, I hope that they make something like that again, but I just don't know like how viable is it for real race enthusiasts?

race enthusiasts want the personality of the driver or the personalities of the team. There's a, they can have a team in there, personality of the team, but are they as charismatic as a driver that's been doing, and passionate as a driver that's been doing this for, you know, 30 years or 20 years or, you know, all of their childhood was like training on the track and all these things. And they have all this pipped up emotions on race day. Those kinds of things you can't get from an algorithm that

are related to human connection

Maybe a Thomas vehicles will take away some things, but a lot of things that will get back like the ability to connect and communicate with your loved ones and your partner and your friends while a car is driving you, which sounds really cool. Or you could do your homework or work. You know, you also work. Don't forget that. So, but.

I hope that you enjoyed this, you know, like anymore. It's 15 minutes long. I hope you enjoyed this rambling episode of me talking about the history of Thomas vehicles. It's a wild ride. You never really know what's going to happen. The combies pull out, come back.

go away, fade away, emerge like the phoenix. So yeah, you never know. You're on the edge of your seat with this. And I think there's exciting developments years to come from now. And thank you for listening. Hope to hear you. I keep saying that. I said that last episode when Nana roasted me. I hope

Be in your ear next week. Whispering the show. Venture Step podcast. In your ear next week. Showing a little bit more personality on this episode. I'm exhausted, brain dead, and I have missed my upload time. So that's gonna be sad. Okay, see everyone. Wherever you are, have a good day, good night, good morning, good afternoon,

Have a great week and see you next week. Bye.