This morning - as someone pointed out in another thread - Mobileye's executives did their Q3 conference call with various analysts. The full transcript is here on Seeking Alpha. And I've cut and pasted some of the best parts relevant to Tesla specifically beneath the link:
Mobileye's (MBLY) CEO Ziv Aviram on Q3 2015 Results - Earnings Call Transcript | Seeking Alpha
Insights from the call:
1 - Mobileye strongly implies that the next suite of hardware - 8 cameras on EyeQ3 - coming within months will be all that is needed for autonomous driving - and after that it's all software development.
"...the next phase is going to be eight cameras, so the infrastructure that they will introduce the vehicle. We will take the same infrastructure up to fully autonomous vehicle. Well, the hardware will not going to be changed. There is going to be only updates of software, once they introduce the full set of eight cameras around the vehicle.
2 - There is neural network "deep learning" going on in the current implementation of Autopilot - regardless of the need for additional cameras in the future:
"Recently, we launched our first deep learning functions on Tesla auto pilot feature. These capabilities include semantic free-space which uses every pixel in the scene to help us understand where are the curves, barriers, [indiscernible] drills, moving objects and anything that is not part of the driving path. Once we know the free-space, the big challenge is where to locate the vehicle in this free-space. We saw this with the holistic path prediction, which uses the context of the road to determine exactly where the car should go at all the time."
3 - There are two SEPARATE groups of "deep learning" fleet learning going on - Tesla's own properietary data set and Mobileye's data set. They are not one and the same, and Tesla is not sharing their own fleet learning with Mobileye.
This, to me, is an indication that Tesla's race to get Autopilot on the road is in fact a way to build a moat - a distinct competitive advantage - by building a superior self driving experience earlier than other automakers will be able to do.The discussion on the call implies that many auto makers are relying on outside companies and Mobileye's own fleet data to implement their self driving system. But Tesla is doing their own fleet learning and not sharing the data.
"we’re not part of the self-learning that Tesla is doing. (bold emphasis mine) This is their project. We continue developing our system based on growing huge database that is part of a database that’s created with the help of our customers, so it’s much, much bigger information that we can collect and we build on a wider scope of scenes and scenarios and different geographical roads in order to improve the system. And we are supporting Tesla with whatever necessary information they need for their own study, but we are not part of it."
And then an analyst asks about deep learning that Mobileye itself is doing with all its customers - or a "database" - the question and the answer were not entirely clear but they seem to imply that Mobileye has some much larger data set being collected from ALL its OEM customers to improve the system long term:
"Andrea James - Dougherty & CompanyThe second part of the question was about maintaining the ownership as you grow on more and more vehicles. You maintained the ownership of the database.
Ziv Aviram - Co-Founder, President and CEO
The database is collected through the validation process with our customers, so it’s analyzing together with our customers the different scenarios and improving the performances. It’s a constant process, it’s never end and actually the data is used only for our system because it was taken and recoded through our system. And only our system can use this kind of data. Even if you give it to somebody else, it’s useless for them. And this is a benefit or interest of all the industry to have as much as bigger database in order to have the most robust and the most cost-effective system that everybody can share."
4 - Deep learning requires a HUGE data set which can only be acquired by having a fleet on the roads doing the learning.By the time other manufacturers actually launch real hands-off autopilot systems Tesla will have raced ahead and have an informational advantage in building a reliable self driving car in real world conditions.
Self driving isn't yet a simple bolt-on which can be purchased from a company like Mobileye. There is real value to be had with an in-house software development team and a linked network of real-world customers driving your cars improving the system.
"For example, we saw with a deep learning the free space. We saw with the deep learning the holistic path prediction but we still use a huge amount of code that we have done in the last 16 years and this is kind of additional layer of technology on top of what we have today. It’s not one algorithm that suddenly can do slightly better than free space and to the system. In order to have a system, it’s a lot of elements that you have to orchestrate in order to make it work in the level of robustness that we presented today to the market.So on one hand, it is a very encouraging that it’s difficult, because, one, it’s difficult, it’s difficult also to our competitors. I believe that we have one of the strongest team and maybe the biggest team in the world that works on this specific application today, but it’s difficult to us. I believe it’s also difficult to others. And I would not expect so quickly somebody would show results on the level that we’re presenting today."
5 - Mobileye's CEO very subtly criticized Elon Musk for referring to a single camera EyeQ3 setup as "autopilot" rather than simply "Lane Keeping Assist"
"So, currently, we are very happy with the introduction of Tesla with what we call Lane Keeping Assist, which is the best in class Lane Keeping Assist today. And we hear a lot of great feedbacks on this system. And but we also hear some feedback of people that abuse the system and drove much higher speed than what was recommended by Tesla.And once you abuse the system is definitely there is a risk of failure and we might face some of the drivers that getting in trouble if that kind of system that not used according to what it was presented.
What we presented is Lane Keeping Assist system rather than auto pilot system. Auto pilot system is going to be presented next year, where is going to be 360 degrees coverage around the vehicle and is going to be multiple cameras with additional sensors. What we have today is just a mono camera looking forward. So it’s a very limited input that we have on the road.
But importance of this launch is, Tesla is willing to push the envelope faster and more aggressively than any other OEM, and definitely this is a very important in step forward to introduce the beginning of semi-autonomous application that will start being launched next year."
Mobileye's (MBLY) CEO Ziv Aviram on Q3 2015 Results - Earnings Call Transcript | Seeking Alpha
Insights from the call:
1 - Mobileye strongly implies that the next suite of hardware - 8 cameras on EyeQ3 - coming within months will be all that is needed for autonomous driving - and after that it's all software development.
"...the next phase is going to be eight cameras, so the infrastructure that they will introduce the vehicle. We will take the same infrastructure up to fully autonomous vehicle. Well, the hardware will not going to be changed. There is going to be only updates of software, once they introduce the full set of eight cameras around the vehicle.
2 - There is neural network "deep learning" going on in the current implementation of Autopilot - regardless of the need for additional cameras in the future:
"Recently, we launched our first deep learning functions on Tesla auto pilot feature. These capabilities include semantic free-space which uses every pixel in the scene to help us understand where are the curves, barriers, [indiscernible] drills, moving objects and anything that is not part of the driving path. Once we know the free-space, the big challenge is where to locate the vehicle in this free-space. We saw this with the holistic path prediction, which uses the context of the road to determine exactly where the car should go at all the time."
3 - There are two SEPARATE groups of "deep learning" fleet learning going on - Tesla's own properietary data set and Mobileye's data set. They are not one and the same, and Tesla is not sharing their own fleet learning with Mobileye.
This, to me, is an indication that Tesla's race to get Autopilot on the road is in fact a way to build a moat - a distinct competitive advantage - by building a superior self driving experience earlier than other automakers will be able to do.The discussion on the call implies that many auto makers are relying on outside companies and Mobileye's own fleet data to implement their self driving system. But Tesla is doing their own fleet learning and not sharing the data.
"we’re not part of the self-learning that Tesla is doing. (bold emphasis mine) This is their project. We continue developing our system based on growing huge database that is part of a database that’s created with the help of our customers, so it’s much, much bigger information that we can collect and we build on a wider scope of scenes and scenarios and different geographical roads in order to improve the system. And we are supporting Tesla with whatever necessary information they need for their own study, but we are not part of it."
And then an analyst asks about deep learning that Mobileye itself is doing with all its customers - or a "database" - the question and the answer were not entirely clear but they seem to imply that Mobileye has some much larger data set being collected from ALL its OEM customers to improve the system long term:
"Andrea James - Dougherty & CompanyThe second part of the question was about maintaining the ownership as you grow on more and more vehicles. You maintained the ownership of the database.
Ziv Aviram - Co-Founder, President and CEO
The database is collected through the validation process with our customers, so it’s analyzing together with our customers the different scenarios and improving the performances. It’s a constant process, it’s never end and actually the data is used only for our system because it was taken and recoded through our system. And only our system can use this kind of data. Even if you give it to somebody else, it’s useless for them. And this is a benefit or interest of all the industry to have as much as bigger database in order to have the most robust and the most cost-effective system that everybody can share."
4 - Deep learning requires a HUGE data set which can only be acquired by having a fleet on the roads doing the learning.By the time other manufacturers actually launch real hands-off autopilot systems Tesla will have raced ahead and have an informational advantage in building a reliable self driving car in real world conditions.
Self driving isn't yet a simple bolt-on which can be purchased from a company like Mobileye. There is real value to be had with an in-house software development team and a linked network of real-world customers driving your cars improving the system.
"For example, we saw with a deep learning the free space. We saw with the deep learning the holistic path prediction but we still use a huge amount of code that we have done in the last 16 years and this is kind of additional layer of technology on top of what we have today. It’s not one algorithm that suddenly can do slightly better than free space and to the system. In order to have a system, it’s a lot of elements that you have to orchestrate in order to make it work in the level of robustness that we presented today to the market.So on one hand, it is a very encouraging that it’s difficult, because, one, it’s difficult, it’s difficult also to our competitors. I believe that we have one of the strongest team and maybe the biggest team in the world that works on this specific application today, but it’s difficult to us. I believe it’s also difficult to others. And I would not expect so quickly somebody would show results on the level that we’re presenting today."
5 - Mobileye's CEO very subtly criticized Elon Musk for referring to a single camera EyeQ3 setup as "autopilot" rather than simply "Lane Keeping Assist"
"So, currently, we are very happy with the introduction of Tesla with what we call Lane Keeping Assist, which is the best in class Lane Keeping Assist today. And we hear a lot of great feedbacks on this system. And but we also hear some feedback of people that abuse the system and drove much higher speed than what was recommended by Tesla.And once you abuse the system is definitely there is a risk of failure and we might face some of the drivers that getting in trouble if that kind of system that not used according to what it was presented.
What we presented is Lane Keeping Assist system rather than auto pilot system. Auto pilot system is going to be presented next year, where is going to be 360 degrees coverage around the vehicle and is going to be multiple cameras with additional sensors. What we have today is just a mono camera looking forward. So it’s a very limited input that we have on the road.
But importance of this launch is, Tesla is willing to push the envelope faster and more aggressively than any other OEM, and definitely this is a very important in step forward to introduce the beginning of semi-autonomous application that will start being launched next year."
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