All right, so now we're moving from a well established very huge industry like cybersecurity into something a little more exciting and to a lot of people a lot more futuristic as well, which is the self driving cars. Now, according to the SAE International, they have broken things up into a number of different sort of levels that classify how a car is, you know, self driving or self assisted or the many different levels as you can see here. Now, for most people, they generally agree that levels four or five around there are self driving or autonomous or fully self driving or fully autonomous. There's lots of different names for it. That all essentially means the same thing which is obviously the car and the computer inside, driving the car on its own without any human interaction. The main distinguishing points between levels four and five seem to be that level four, you can sit in the car and you can, you know, generally do whatever you want, you can hop in the backseat, if you want that's perfectly legal, the car will be legal to fully drive itself and handle all situations.

Level five takes it to a whole other level where sometimes they totally get rid of the actual steering wheel and the pedals and it's literally just like a room that you're sitting in that is driving you around kind of like a pod or something like that. So those are the main two differences between level four and five if you've been wondering, but in both scenarios, you're still looking at a car that will essentially fully drive itself. So currently, this industry is not quite in its infancy but it's obviously still very big in terms of research and development. No one has that absolute final end product, fully self driving car that you know, I can go out and buy for 20,000 or whatever it might be out there. Everyone's still doing research and development, everyone's still testing their cars. And well, it's not stuck in the lab or anything really far off in the future like that.

It still is, for the most part speaking, you know, relegated to particular tech companies or particular car companies going around and, you know, testing their vehicles and testing their systems. And even though it's in this early stage of development, it still is a multibillion dollar sort of industry. There is this huge sort of arms race going on where all these companies are desperately trying to get their product, you know, certified and legal and out the door and, you know, basically get to the moon First, if you would. This is sort of had some quite profound effects. You've had companies like mobile AR, which is a Israeli or used to be Israeli company, was bought out by Intel for over $15 billion absolutely huge amount of money and As you can imagine, there's also a recent lawsuit that went on between Wei mo and Uber. It's particularly over self driving cars and their patents and all that sort of stuff.

They ended up settling out of court for I think about 240 odd million dollars. So there is a lot of money involved. This is a huge industry is the first company to you know, really crack that self driving car and get that product out, whether it's Google, whether it's, you know, way mo or Uber or Tesla or whoever it might be, is obviously gonna make a lot of money. So they're putting a lot of resources behind it. And it's certainly a very big industry, even though it's just sort of getting started and underway. And there's not just the sort of typical tech companies out there like your Uber and like your, you know, Google who was basically represented by Weimer.

There's also the traditional car companies out there as well like GM and Ford, also trying to develop their own self driving car system. So you've got multiple multibillion dollar companies from multiple industries, all together, trying to essentially race each other to the finish line to make this amazing new product. So as you can imagine, it is an absolutely huge, huge industry at the moment. If I had to, you know, try and envisage and pick a winner, or whoever is, you know, closest to the finish line of developing that product. To me personally, that would be Weimer the company. Other analysts have done, you know, their work and chosen other companies.

But in most of the scenarios, waymo very often ranks quite high, if not the number one, to me, though they seem to be actually delivering on the product a lot sooner than what other companies are doing. So if you're not familiar with them, YMO is actually the company that got spun out from Google. Way back in 2009. Google actually started development on self driving cars. It was part of the you know, x projects or they moonshot projects. Their idea obviously was to build a self driving car.

And as that progressed and progressed, it finally graduated out of this sort of moonshot x love oratories, as they call it, and graduated into becoming a spin off company that's now part of the bigger alphabet sort of umbrella company out there. So way Mo, while it sounds like a completely different company, it is in effect, alphabet or Google. And it comes with all that legacy development and technology that they did all the way back since 2009. So that they working on this for a very, very long time. They've got their own, you know, personalized areas and car parks and driving areas that they do all these special tests on them. They've also got their cars, the minivans that they've been driving around in Phoenix for a good while now.

They've just recently actually announced that they are running these four The public so as a public person living in Phoenix, you can, you know, subscribe to this service and already right now physically hop into one of these vans that will drive you around fully autonomously. Now. It's a very important step that I took just recently. And that was to actually remove the technician or the person that was monitoring the car. Usually, when companies are running self driving cars, the cars themselves are driving by themselves. There's always you know, an engineer or technician or someone monitoring the system sitting in the steering wheel ready to take over at a moment's notice.

And this is true of virtually all the other tech companies or car companies out there doing their work, what YMO has actually done as the confident enough in their own systems that they've been able to take that technician out of the front seat and I believe they have them sitting in the backseat, just sort of still monitoring what's going on, as I said still, you know, early stages for this technology, but the There is literally no one in the front two seats. If you hop into one of these cars, or one of these vans, they will drive you around with no one in the front seat doing it all by themselves. And this is something that's already been going on for a number of months. And they even also announced just recently a, what would you call it a partnership with Jaguar, where they'll be rolling out upwards of 20,000 eyepieces, which is a new premium sort of sedan SUV crossover type thing that will be fitted out with this way mo technology and will be able to self drive essentially.

So over the next few years, they'll hopefully be rolling out anywhere upwards of that 20,000 number. And these of course, will be available to their customers as well to hop into a you know, super fancy Jaguar car and have it drive them around, you know, maybe they're a little, you know, higher up. Maybe they're an executive or something like that. I'm one of more premium fancy cars opposed to just your mom and kids. wanting to go to sport or something, which is what a lot of people use the vans for. By the way, though, to me, waymo seems to be the furthest along in their development.

They take their safety extremely seriously, like a lot of other companies do. But they seem to have an excellent track record. They're very open and transparent about the, you know, results and all that sort of stuff. And they seem to be, you know, close to market. They've got real people from the public already in their cars in their vans, that already driving them around in real life. It's not some, you know, he's a development car, a prototype car or anything like that, which a lot of other companies are still working on.

They're actually there with a delivered product already. That being said, although they are furthest along right now, doesn't necessarily mean they will be the winners. It's a space that both you and I will have to watch and you know, see as different companies progress and how they roll things out. Perhaps way mo will, you know, have a huge accident like Uber had just recently where they actually killed a pedestrian that was walking across the road. I don't know. But those sorts of things can drastically affect the timelines for each company.

And you know, it's very difficult to tell. So at the moment, it's best to just sort of keep an eye on it. Most of these systems that are being developed, obviously use machine learning and AI and what is called neural nets, or deep neural nets, or deep learning. And basically, they combine this computer technology with a number of sensors that all are in the cars, everything from radar to, you know, traditional cameras and ultrasonic sensors all the way up to the very fancy LIDAR systems, which is essentially a laser based radar. So I think that's spinning around or pushing out laser light in a particular direction, and the laser hits something comes back and it can measure the distance to that object and see where it is. You know, measure speed and all that sort of stuff.

So these sorts of systems are quite technical, obviously, as you can imagine, they usually have them dotted all over the actual cars. And if you want to get a better idea in terms of what a self driving car actually sees, you can sort of get a good idea from this video here, which I really would recommend everyone going and watching in full. It's made by way Mo, just to sort of show you what the actual smart cars and these are fully self driving cars actually see because most people think that it's just like a normal everyday car, maybe with some cameras on it, and it can only see you know, what a human person can see, which is, you know, visual spectrum and what's in front of your person walking here. But with LIDAR and radar and many other of the senses, they can actually see much, much further they can see through things they can see, you know, 200 300 feet in the distance and Sort of select at and map every single object that is there or moving and predict where these objects are going all in real time, all at the same time.

So they can be much, much more advanced than humans. And that's expected because they have these more advanced abilities, that, you know, there will be a higher expectation of them. One particular famous company that isn't actually using LIDAR, however, is Tesla. Now, they, for whatever reason, believes that all the actual self driving, you know, fully self driving actual car technology can be built and deployed, just by using things like ultrasonics radar, and mainly speaking the actual camera systems that they have. So they have, I believe, about eight cameras all around the entire car nicely all the directions. And that paired together with their fleet learning and the you know, very advanced neural net.

They believe that they can get to full autonomous you know, self driving cars. Just simply with those cameras and radar systems that they don't need the LIDAR systems, for the most part in the industry. Everyone else except Tesla believes that LIDAR is you know, a necessity and they have them on their car, perhaps they have three or four of them on their car. One downside of LIDAR is that it originally was incredibly, incredibly expensive talking like, you know, 1020 $50,000 per LIDAR system are also extremely bulky and large. If you sort of go back and look at some videos from 2009, when Google was doing its original testing, you saw these huge LIDAR things on top of their car. Nowadays, they're more sort of, I guess, park or you know, coffee cup sized or something like that.

But even that's, you know, not the finished product yet. They're getting even smaller and even cheaper every day. So it's expected that hourly costs, you know, maybe 510 to $50 or something like that, once the technology really gets properly developed. Or perhaps in a few years, Tesla might take that on board, they seem to be pretty adamant that they can get to full autonomy with that technology. But again, it's something that we'll just have to sort of wait and see and watch with bated breath. So in the end, we have Tesla with their particular approach that doesn't want to use Lada they seem to be more relying on a huge amount of Fleet learning with all their actual Tesla vehicles out on track and their Model S and x and now their model three, which is you know, being bought in the hundreds of thousands.

So if they can have a slightly less, you know, technical system without LIDAR on it, and but hundreds of thousands of people driving millions and billions of kilometers, collecting a lot of data for them. That could very well be enough to have them master that technology before someone like Weimer, who's more relying on less kilometers driven but you know, better quality data with higher near resolution LIDAR and radar technology. To record better data, so it's a bit of a race between all the companies, you know, it's very difficult to tell which one will particularly win. But what I will try and do in the next section is sort of peer into the future a bit and just sort of see what might happen when this technology actually comes online. So I'll have a chat with you in the next pop thing.