Alex Manea, chief security officer and founding member of BlackBerry’s security force explains how autonomous vehicles work and how you are striving to make a secure transition by connecting all these devices. He also addresses the evolution of the (Internet of Things) during the past 10 years to deliver real value by connecting your devices. He says CES has also transitioned as the perfect forum to bring all these solutions—smart home, personal wearables, smart kitchen, and cars—to the forefront. Here is part one of a two part “Look Who’s Talking” Interview discussion focusing on security, IoT, blockchain, and the future of emerging-disruptive innovation.

 

To hear this interview on The Peggy Smedley Show in its entirety, click here.

Peggy Smedley:
Let’s talk about what you’ve been seeing here at CES. You’ve been in this business a long time. You know both from a security perspective and a perspective. What’s your take on how we’ve been evolving? I think you see a lot of exciting things. When we were doing the panel, we talked about how the Internet of Things is evolving since you’ve been around. What excites you the most these days?

Alex Manea:
I think first and foremost, CES is a really cool place to see what’s evolving to see the latest and greatest technology. It’s been neat because I’ve been at CES for about the past 10 years or so. I’ve seen a lot of evolution in terms of the technologies here. What I love these days is that there’s so many innovative IoT technologies out there, right? So many different types of smart home appliances, personal wearables, smart kitchens, automotive stuff. There’s so much cool technology here. I really think that CES is showing the evolution of IoT and how IoT is really starting to mature and really starting to provide value to consumers.

Smedley:
In looking at that, BlackBerry has really evolved. You (BlackBerry) has been involved in the automotive space. You made the acquisition of QNX. That’s really shown what you guys have done. BlackBerry has done some really innovative things here, and I’m going to be candid. People have said that BlackBerry isn’t in this. But, BlackBerry has stepped up and said, ‘We understand from an underlying perspective what the industry and the Internet of Things is really all about.’

Manea:
Yeah. I think that’s what gives us a big advantage in this is if you think about it, even when we were a mobile phone company, we were first and foremost still a security company, right? We were making mobile phones that were the most secure in the world. What we’ve done over the past couple years is we’ve evolved from being a mobile device manufacturer to being a software and security company really helping to serve the enterprise of things. All of the different things connecting to the enterprise, whether that be desktops or laptops or mobile devices. Whether it’s IoS or or even IoT endpoints, so things like automotive, for instance. It’s been a really natural evolution for us, because we’ve always focused on security. We’ve taken all the things we’ve learned about security from the mobile space and really applied them to the IoT space.

Smedley:
Let’s talk about that. What do you think has been the biggest challenge for BlackBerry? It’s not only what BlackBerry’s doing, but you’ve done it really well with partnerships. I think that’s where you excel in a lot of ways. I think, and I don’t know if you consider this, but in some ways I think you’re agnostic with a lot of partners. You say we go to market and we partner with a lot of people. That’s what makes you somewhat unique.

Manea:
Yeah. I think that’s part of the evolution of BlackBerry, right? If you think about where BlackBerry was 10 years ago, we were making everything ourselves. We were making the device ourselves, the operating system ourselves, the control ourselves. These days, it’s all about ecosystems, right? In order to participate and be part of the ecosystem and be the platform for the ecosystem, we have to partner with others. Automotive is a great example where automotive is such a complex ecosystem. It’s not just a car manufacturers. You have all the tier one suppliers, all of the different parts of the ecosystem. What we’re doing is we’re just basically going around and becoming platform agnostic. We’re saying we want to help you secure your cars. We want to help you secure your enterprise, and we’re willing to partner with anyone who wants our help doing that.

Smedley:
Automotive has become a really tricky space right now. I think everybody wants in it, and I think it’s becoming so complex that we’re talking about autonomous vehicles. Where are we truly when we talk about autonomous cars? Are we there? What level are we? We say we’re going to have autonomous cars on the market. Where are we, and when are we really going to get there?

Manea:
I think the key thing to understand about autonomous cars is it’s not a binary thing, right? A lot of people still think about is my car self-driving or not. The reality is that almost every high-end car in the market has some level of autonomy or at least some level of driver assistance, right? If you think about it in many ways as consumers, we’re starting to get used to that. We’re starting to get used to the concept of hey, my car’s going to tell me when I’m driving too close to the car in front of me, or it’s going to help me keep my lanes or it’s going to help me park my car. A lot of people don’t realize that is in some ways a form of autonomy.

Now, in terms of when self-driving cars are really going to be on the road, it’s going to be a step-by-step process, right? There’s going to be first and foremost, we’re going to see cars become more self-driving in urban environments, in environments where we kind of know what to expect. But, if you think about level five autonomy, for instance, I wouldn’t expect that to be around for at least another 10, 20 years, because realistically, we’re going to have to put a lot more technology in the car for the car to be able to drive itself in a rural environment and be able to detect all the things it needs to detect.

Smedley:
You talk to Tesla and they go hey, we’re already there. You get in our cars, you can go from Palo Alto to the office and back, to the grocery store. How is that possible, then? Somebody hears that and they go those cars are already on the street. Is that really what’s happening, or you say they’re testing it out, but we’ve got so much before two cars can make decisions together on the road? Somebody watching this goes I’m so confused on what that really means.

Manea:
What we’re starting to see now is autonomous cars being on the road and interacting with human drivers, right? If you look at the long-term vision of autonomy it’s eventually going to get to the point where pretty much all the cars on the road are autonomous. At that point, that’s kind of really the cool long term vision, because then the cars can actually start communicating with each other. Imagine for instance that my autonomous vehicle is going down the road and all the sudden, traffic stops and it has to the brakes really quickly. At that point, there’s a new technology called vehicle-to-vehicle communication where it can actually beam out a signal to the other cars on the road, basically saying hey, you’re going to have to put on a hard break. Make sure you’re ready for this, right? Again, autonomy is not a binary thing. It’s going to continue evolving, but the long-term vision in my opinion is very exciting, because ultimately when everyone’s driving self-driving cars, that’s going to make traffic a lot more efficient, and that is going to make us a lot more productive.

Smedley:
What infrastructure has to be ready to make this happen: For the lights, the things around us, for us to really say we are ready?

Manea:
Yeah. That’s a great point, because a lot of people talk about vehicle-to-vehicle, but in my opinion vehicle-to-infrastructure becomes even more important there. Because if you think about how cars do self-driving these days, in many ways they’re trying to imitate how humans drive. For instance, I’m driving my car up to an intersection. The car basically sees that it’s a stoplight, but as humans we can instinctively say heuristically okay, that’s a red light. That’s a stop light. The car essentially has to do realtime image processing and has to basically detect that as a stoplight. That’s actually very data intensive and processing intensive for the car. Eventually, where we want to go to with V2I (vehicle-to-infrastructure) is where the stoplight is essentially beaming out a signal basically saying hey, I’m a stoplight. You need to stop. You need to stop. At that point, our vehicles become a lot more efficient and we have a lot safer roads because of the fact that the vehicles and the humans no longer have to make that judgment. They’re basically just listening to the infrastructure and the infrastructure’s telling them what to do.

Smedley:
Are we now talking about, not only sensors in the road, but video and sensors communicating together? Is this the kind of data that is required?

Manea:
Yes, absolutely. The other big question there as well is security and authentication, right?

Smedley:
That’s what I was going to get to next.

Manea:
If I’m a bad actor for instance, what stops me from pretending to be a stoplight, right, and essentially just creating gridlock across the road? Especially if the road is full of autonomous vehicles, that’s one area that we’re really focused on from a BlackBerry standpoint. Basically how do we create a hardware that is the root of trust within the chipset to really be able to authenticate all of those different commands, and to be able to say yes, this is really Peggy’s car and yes, this is really a stoplight authenticated by the city of Las Vegas to make sure that the two are communicating properly.

Smedley:
Are we at that point where we are talking that we need all digital embedded type things? Are we talking a combination of analog and digital to make all of this work? What are we talking about? Because in some of this, we’re talking about roads, which would be more analog versus video, which is more digital?

Manea:
Long term, it’s ultimately going to be all digital. But, when I say long term, I’m not talking 10, 20 years. I’m talking 30, 40 years.

Smedley:
Now we’re really moving out there in time.

Manea:
But, you have to think about the fact that there’s going to be a transition period.

Smedley:
What’s the transition?

Manea:
The transition isn’t going to happen overnight. It’s going to happen in certain places faster than others. If you think about a place like New York City, for instance, I would expect that to have the infrastructure in place faster than maybe rural Montana, right? In rural Montana we might not necessarily have to make the investments right away to put that infrastructure in place, which puts more onus on the car manufacturers to really be able to in many ways program the cars to imitate the way human drivers drive. Whereas, in a place like New York City if we have the right infrastructure, at that point we can code the cars to communicate directly with the infrastructure and be a lot more efficient than how human drivers work.

Smedley:
The challenge, though, is that you can’t have a car that says I’m going to drive from New York to Montana if the infrastructure isn’t capable of handling it. Those are the challenges that the manufacturers have to be thinking about, because that one car is going to drive from one city, one state to the other. It has to be able to do that.

Manea:
Yes. I liken it a lot to the evolution of how we’ve evolved chess playing computers, right? I grew up as a chess player, for instance, and when I was growing up, humans were better than computers. One of the big turning points was when Deep Blue written by IBM was able to beat Garry Kasparov, who is the best human player at the time. But, what was interesting was when we first coded computers, computers were basically brute forcing the problem. They were basically trying to go through every possible move combination and look at it in terms of the entire tree. Human chess players don’t do that. Human chess players use heuristics.

They intrinsically can look at a position and say okay, these are the five to 10 moves that I think are the best chances so I’m going to keep looking down there. When computers were able to start using those human style heuristics, they all of the sudden leapfrogged humans and now, all of a sudden computers can play chess way, way better than humans. I think that’s going to happen with self-driving vehicles. The more self-driving vehicles can start using these road heuristics similar to humans the more they can start communicating with infrastructure, they’re eventually going to become better drivers than humans.



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