BRIAN SANTO: I’m Brian Santo, EE Times Editor in Chief, and you’re listening to EE Times on Air. This is day three of our special series of podcasts reporting live from the Consumer Electronics Show in the Mojave Desert. In the past couple of years, the automotive industry has dominated CES, and this year it’s happening again.

In today’s episode:

Qualcomm made some headline news, announcing it is burrowing deeper into the automotive market. We’ve got an interview with the Qualcomm vice president in charge of the company’s automotive operations.

…did we mention that Qualcomm is getting deeper into the automotive market? One of our colleagues has test-driven a new Qualcomm-powered autonomous vehicle. We’ll report on that.

…also, live interviews with executives from Infineon and with Texas Instruments about adding autonomous functions to cars equipped with driver assist capabilities, also referred to as ADAS.

…an analysis of a novel approach for autonomous vehicles from Intel’s MobilEye unit…

…and finally, Toyota surprised show-goers expecting the company to talk about cars. The company skipped right past that subject and on to planning entire smart cities.

Some of the biggest news in automotive at this year’s CES was Qualcomm’s formal announcement of its “Snapdragon Ride Platform.” The new platform got instant credibility with the announcement that GM is Qualcomm’s new partner on assisted driving technology.

Qualcomm long ago established itself as a supplier for connectivity and infotainment systems in the automotive sector. The market for vehicle automation seemed like an obvious next step, and investors have been wondering if the company was going to take that step.

Qualcomm put an end to that question by rolling out the new Ride Platform, which it described as “scalable.” By mentioning that GM is now working with Qualcomm on ADAS, Qualcomm is also hoping to let the world that the world’s largest mobile chip company has a foot in the door in the ADAS market.

Junko caught up with Nakul Duggal, Qualcomm’s Senior Vice President & Head of Automotive Product & Program Management, right after the company’s press conference in Las Vegas. She asked him to break down what exactly the Snapdragon Ride Platform entails, what Qualcomm means by “scalability,” and whether the relationship with GM will have any impact on GM’s partnership with Cruise, which has a focus on fully autonomous driving.

NAKUL DUGGAL: We look at the automotive business in four ways. That is the telematics business and the CD direct business, which we’ve been in for a long time. That is a business that we understand quite well. We started the Snapdragon digital cockpit business about five years ago. And that is doing exceptionally well. Between the telematics and the digital cockpit business, we now have over $7 billion in our design pipeline. We have over 19 automakers. We are leading in many of these areas. So that business is going really well.

We announced two new areas to our portfolio today. The first one was the Snapdragon Ride platform, which is an autonomous driving– an ADAS– platform. It includes an SOC, an accelerator and the autonomy stack. And this is an area we’ve been working for a number of years, and we announced it finally. What is going to differentiate us in this space compared to competitors is the scalability. So we will address everything from Level 1 to Level 5. The efficiency of the platform that we are building from a power perspective, so these are much more efficient compared to competing solutions. And then the stack is a reference stack. You can use our stack, you can use components of the stack, or you can bring your own stack. If you don’t want to use ours, our platforms on the SOC and X-ray are completely open. So this scalability approach, to us, is a big differentiator. We saw a lot of success when we did the digital cockpit business with scalability. And General Motors has announced a partnership with us across all three of these domains: across telematics, infotainment and ADAS. We are very proud to see that relationship move forward.

And then finally, we announced a new service called cloud to cloud, which is essentially designed to be able to manage the vehicle from an automaker’s perspective often it has been deployed. So managing in terms of being able to make updates to the car, being able to unlock new capabilities, make flexible configurations so you don’t have to change the hardware. The only way that you change it is actually through the updates in software.

So these four areas I think put us in a very compelling position to have a very highly differentiated portfolio for our automaker and Tier One customers.

JUNKO YOSHIDA: All right. You know, keeping this conversation high level, what I’m gathering from various players in the automotive chip market is that, in the past, or even at present, a lot of car companies have been making what they call “band-aid” solutions. The new features coming in, they do a chip solution from one chip company and then another new feature comes in, Okay, we’re going to switch to another company or another Tier 1 who can provide us some new solutions. So this has been very fraught with so many variabilities. How do you think that your Snapdragon Ride platform can answer that question?

NAKUL DUGGAL: One thing that we have always done different is that, when we engage with customers, we don’t engage transitionally for one generation. We look at the requirements for the business that we are getting in across the board, for every Tier, and then we design our portfolio accordingly. With the Ride platform, very similar to the cockpit platform or the telematics platform. We understood the requirements all the way from the entry to the most advanced systems. And we have built the portfolio to be very scalable. We start from 30 tops that could address Level 1 requirements, all the way up to 700 tops for Level 5 and even beyond, if you need to get there. So that we understand that there is no reason for the automaker to fragment their partner base, their supply chain base, to different suppliers for different Tiers. And the reason so far automakers have had to deal with this is because they don’t find scalable platforms that address the needs at the right cost point, at the right power efficiency point, and really in terms of being able to deliver that scalability. These are very difficult solutions to deliver through any one supplier across the board. At Qualcomm, our strategy has been to be scalable always, and that I think is what is going to get away from what you define as the “band-aids” that have been so far implemented.

JUNKO YOSHIDA: All right. Well, let me ask you this: You did mention your new relationship with GM. I mean, you’ve always had a relationship with GM, but you are now expanding the relationship all the way to ADAS. How does that fare with the GM strategy to work with… You know, they’ve been working with Cruise on the autonomous vehicles, and if indeed the Snapdragon Ride platform can address all the way to 4+, Level 4+ or 5, what’s going to happen?

NAKUL DUGGAL: So let me make sure that we explain this quite clearly. The partnership that we announced at GM, we’ve had a partnership on telematics for a long period of time. We announced a partnership on the digital cockpit SOCs, and now also on the ADAS SOCs. The stack that are introducing for the Ride platform, that is a Level 2 stack. Level 2, Level 2+. And the GM partnership is really around making sure that we have the ability to work with a partner like GM across domains like telematics, but now also new domains like infotainment, as well as ADAS, to essentially get around some of the challenges that you were mentioning earlier, where you have to keep switching from one generation to another. Here our relationship is based upon the fact that we have scalable platforms. We deliver a level of capability and service to our customers, and as they have seen that we are a supplier that can be trusted, that they can rely on, that is meeting their commercial, their technical, their power requirements, they’re looking at our platform, and it’s something that makes sense. I cannot comment on the other programs that GM is obviously working on.

JUNKO YOSHIDA: All right. As a Qualcomm, when do you make Level 3, Level 4 stacks available to your potential customers?

NAKUL DUGGAL: So we have the Level 2+ stack available now, actually. And we are going to be continuously making updates to these Level 2 stacks, which will, in our belief, evolve to more capable stacks. We get asked the question, Do you support sensors like lidar, etc? We can support all sensors. The stack is capable of supporting all sensors.

We also keep in mind very carefully the cost of these sensors. So as the sensors get to a cost point where they become broadly available, we are happy to add any sensors. As far as when we get to the next level of stack capability, I think it will be a progression. We believe that the stack that we are delivering today is very compelling, and automakers the Tier Ones who were interested in it and start to work on it, and we will work with them to evolve the capability along with their own teams.

JUNKO YOSHIDA: Does your platform actually include some of the network capabilities? In-vehicle network, we’re talking about bringing in more data inside a vehicle. We’re talking about whole car, software upgrades, so on and so forth. You probably need a PCIE, all the gigabit ethernet kind of stuff. What sort of network processors are part of your Snapdragon Ride Platform?

NAKUL DUGGAL: So we support ethernet. We support PCIE on the Snapdragon Ride. We support all of the updates for all of these platforms. So really anything that is needed to run the platform on the automotive bus for local internet working, all of that is available. And then of course on top of that, any software that is needed, any drivers that are needed, any update solutions, any auto solutions, all of those are included as part of the platform.

JUNKO YOSHIDA: Okay. Very good. Thank you so much.

NAKUL DUGGAL: Thank you.

BRIAN SANTO: As if working with GM isn’t enough, Qualcomm burnished its ADAS bona fides by bringing its highly autonomous vehicle to Vegas. Jim McGregor, our friend at Tirias Research, got a chance to ride on it. And this is what Jim told us:

He said, “The ride was on a highway in Vegas. The car did well at merging, navigation and even avoiding an aggressive Camaro that cut us off and almost spun out. Overall, it was a comfortable ride, and the system appeared to operate very well,” he said.

Of course, other chip giants in the autonomous vehicle segment – such as Nvidia and Intel/MobilEye – had already been there and done that. The market is getting crowded.

Leading up to CES 2020, veteran automotive chip suppliers such as NXP Semiconductors and Texas Instruments also announced new chips. Both claim their respective product families will help OEMs and Tier Ones to modernize the current vehicle architecture. The goal is to enable car companies to do over-the-air upgrades, for example, to become software-upgradeable vehicles a la Tesla.

NXP calls its chip the Vehicle Network Processor. TI also announced a similar gateway processor and ADAS processor. Both companies are known for their grounded views on highly autonomous vehicles.

Junko sat down with TI on the first day of the official opening of the CES show floor. She asked TI what it takes to be a trusted chip supplier to the automotive industry.

The first voice from TI you hear will be Sameer Wasson, vice president and general manager of TI’s processor business unit. The other voice belongs to Curt Moore, general manager and product line manager for the company’s Jacinto processors.

JUNKO YOSHIDA: What are the basic, unique requirements to be in the automotive market as a chip company?

SAMEER WASSON: You’ve got to understand the need from a safety, reliability, longevity perspective. Bringing that together, expressing that in semiconductors, understanding the system, getting to those unique corner cases, those problems, that makes automotive very unique. And transferring some technology from a different market over here without the correct part, without the correct architecture, without the correct time over target and R&D, often leads to bad results.

JUNKO YOSHIDA: Let me inject myself. Talk about bad results! I mean, when we… Sameer you and I were talking about… you talked about this industry, meaning automotive industry, has a long memory. Tell us a little bit about that.

SAMEER WASSON: It has a long memory because this technology stays in vehicles for a very long time.

JUNKO YOSHIDA: “A long time” like 15 years?

SAMEER WASSON: Easy. Things will change. Some components change faster, some components will change slower. But there is technology in cars which stays there for a very long time. So when you’re thinking of it, a mistake done in one step can impact you for multiple years. And that mistake doesn’t necessarily have to be catastrophic. It could be a poor systems choice. It could be a sub-optimized system where the cost is not really where it needs to be, and that prevents it from scaling to where it needs to go and be accessible for everyone. So our mission in life is to make sure that when you’re making this technology, it does something which is scalable, accessible and no make any of these sub-optimum decisions which prevent us from getting to that mission.

JUNKO YOSHIDA: And they are unforgiven. Once you make a mistake, can you crawl back into the same OEM?

SAMEER WASSON: It’s not easy.

JUNKO YOSHIDA: Not easy.

SAMEER WASSON: It’s not easy.

CURT MOORE: And I think, as we’re looking… as the automotive market is changing, as now processors are moving into more and more mission-critical applications inside the car, this is becoming more and more important to really be thinking about the system and how you implement the safety for these mission-difficult systems and not retrofitting something.

JUNKO YOSHIDA: Not retrofitting it. You know, one of the things… I think Sameer, you were the one who mentioned that there are two schools of thought. Getting into this autonomy business. I mean, we’re talking about the Level 2 cars to the Level 4+ or Level 5 cars. There are two schools of thoughts. One is sort of a top-down approach from a bottom-up approach. Tell us the difference and where TI sits in that spectrum.

SAMEER WASSON: We definitely… The difference is, you can take a leap of faith and go build a general purpose computer and say, Let me just brute force and get to a high level of autonomy. We are not doing that. We are taking a more nuanced approach, using a heterogeneous architecture. So that we are using different components of processing to go solve specific problems. So if you need general purpose compute, we have general purpose compute. If you need specific vision accelerators, because they give you the lowest power, we’ve invested in that. If you want to do machine learning and signal processing, we’ve invested in that. So we definitely believe in a more bottom-up approach of building that technology and then letting it scale to as high as you want.

Bottom line is, safety is paramount. To make safety happen, you’ve got to have the technology accessible for the masses. And our technology enables you to do that because we don’t need fancy cooling, for example. We don’t need anything which requires you to then go say, How do I architect this differently because my machine is just bigger. We scale from really small to really big. But really big is important. But being able to scale is more important.

JUNKO YOSHIDA: Let me be a devil’s advocate. Some people talk about really there’s a beauty to the top-down approach because you, as you mentioned, the OEMs always want the next shiny object. So this year this might be focused on certain things, next year they’ll focus on something different, whether it’s a heads-up display or the audio thing or whatever. So the chip companies are put in a position to provide one solution at a time, which automotive companies want, but at the same time, that could end up (according to the top-down advocate) is that it’s going to be a band-aid solution. Band-aid after band-aid. So you eventually get a really unwieldy platform that you can’t really… The decision you made this year, five years from now could have been the wrong decision. What do you say to that?

CURT MOORE: I think the key thing that we’re really looking at is, How do we deploy ADAS to the masses? Deploying ADAS to the masses has a huge element of cost associated with it, a huge cost component to it. If you just start from the high end down, you’re not going to be able to go hit those costs points or enable those system cost points to allow car OEs to really deploy these ADAS features to their entire fleet. And that’s really where we can go impact safety, is by getting these ADAS features into lower-cost cars. Because when you think about it, those are going to be the largest number of cars often driven by people with less experience. You know, younger drivers, etc. And that ADAS functionality can really have a big safety impact. So by attacking those low-cost systems and getting that ADAS functionality and worry about it from a cost point of view is going to make the road safer.

SAMEER WASSON: To your point, top-down has its advantages if you’re looking at scaling to the top end of that market. Absolutely. What our strategy is, we want to get all of the market. And scaling up sometimes is easier than scaling down. Scaling up means you’re putting two of our solutions, and they’re software-compatible and the scale.

JUNKO YOSHIDA: I see.

SAMEER WASSON: Scaling down, once you have that infrastructure built into the chip, scaling down comes at the cost of either cost or power. Simple. It’s physics, right? So we have taken the approach of saying, Let’s take a level block approach to this and build it up.

The other thing is, no two OEMs are the same.

JUNKO YOSHIDA: Ah! That’s a good…

SAMEER WASSON: No two car lines in the OEM is the same. So there could be… Think of a very high end OEM. They make really, really good cars. But they have some scale. They go from your economy car to the highest end car. Your economy car may only have one SOC. And that is your front camera, that is your centralized compute sensor fusion, that is your automated parking. How do you get it to do that in that price point? It’s a very different price point.  Secondly, that power. They don’t have the budget to port fully. The same OEM may actually have that very, very high end vehicle. Now anyone catering to them, whether it is us or whether it is a Tier One, that software investment is the most expensive one. So now, we’ve got to come up… and that’s what, quite frankly, makes our job fun. How do you tackle this puzzle? And our strategy is, let’s go build level blocks. Let’s go build level blocks that, when put together, can get you the highest level of performance which the OEM needs. But make sure you’re catering to each of those segments in a thoughtful manner.

CURT MOORE: And the ones that are going to be most cost sensitive are going to be the lower-end vehicles. So there’s where we want to make sure that we optimize system bom, because that’s the one that’s going to be critical.

JUNKO YOSHIDA: Very good. Thank you so much.

BRIAN SANTO: In yesterday’s podcast, Junko interviewed NXP’s CTO Lars Reger about Ultra-Wide Band technology. She also asked him how NXP would compete with new entrants to the autonomous vehicle market. Reger’s response was, “We think we can completely complement each other.”

Recall, too, that Qualcomm was once planning to acquire NXP in hopes of expanding its business into the automotive market. The deal did not get consummated, but Reger said, “NXP can work with a number of other chip companies such as Nvidia, Karlay or Qualcomm. Their primary focus is on AI. We,” Reger said, “we’ve got the rest of the solutions ranging from vehicle networks to security/safety.”

Next, Junko sat down with Peter Schiefer, Infineon’s division president responsible for automotive. The various ways to implement autonomy in vehicles actually occupies a spectrum. If robotaxis are at one end of the spectrum, Schiefer sees a growing trend that carmakers will be bringing down “some use cases” of Level 3 and Level 4 cars into what used to be more run-of-the-mill ADAS vehicles.

JUNKO YOSHIDA: All right. I’m here with Peter at the Infineon booth, and we were just talking about how this whole autonomous vehicle market we’ve been hearing every year at the CES. And CES 2020 we see the air has changed. I mean, thank goodness all the full-fledged hype of autonomous vehicles has kind of subsided, right? And we’re talking about two different approaches for the autonomy. Explain how you see the different industry players approaching autonomy differently.

PETER SCHIEFER: Yeah, basically what I see is that the market is building up in two approaches, where one approach is more for the fully automized kind of Level 5 cars which will be starting from my perspective mainly in the commercial use case, where you can, for example, replace drivers. And with that you can also justify the technology which is needed in order to enable such a function. However, this number of cars will be limited to that commercial use cases. Then on the other hand side, what I see now with the complexity and complication about approvals of a Level 3 car, I see a lot of companies now taking single uses cases out of Level 3, Level 4 car and pull them into a Level 2 car. There is then an incremental technology… technology which is needed incrementally to add to the function, delivers a benefit to the car owner.

JUNKO YOSHIDA: Okay. Give me some specific examples of use cases of a Level 3 and Level 4.

PETER SCHIEFER: That use case could be, for example, a parking support. So if you want to park the car, then this parking function can be one. The second one could be a highway pilot.

JUNKO YOSHIDA: Oh, okay. So it’s totally autonomous driving.

PETER SCHIEFER: Yes. For a certain situation, for a certain period of time.

JUNKO YOSHIDA: Okay. And these did not used to be considered as part of Level 2, right?

PETER SCHIEFER: Right. In the classical definition, this was not considered. And I see it changing now, and you may even call it a Level 2+ when you add these kinds of use cases. And here it’s a lot about the sensors and also the dependable compute power to enable these functions.

JUNKO YOSHDA: All right. We’re talking about the general trend in the automotive industry. Where does Infineon sit? How do you enable it?

PETER SCHIEFER: Basically, in the autonomous car you are replacing the eyes, the ears and the brain of the human driver. And that’s why the semiconductor technologies are enabling that. And it’s all about very precise sensing. And we are a leader in the 77 gigahertz routing system. It’s about dependable compute power. And this is all about our functional safe microcontrollers. And as these cars are connected to the outside world, it’s also about cyber security. There is no safety without cyber security and defining hardware incas for protection against cyber security key. And this is a key at Infineon.

JUNKO YOSHIDA: Tell me a little about dependable compute power. What’s the downside? And how do you mitigate it?

PETER SCHIEFER: On the one hand, most people when they talk about autonomous cars, are talking about the big number cruncher. But there’s more than that. You need to have a fully fail operational and failsafe system. That’s why you need to have a functional safe microcontroller next to the number cruncher. And this is what Infineon provides. But it’s more than that. The whole system needs to be dependable. So for example, if you are driving very fast on a highway and the power supply gets disconnected, then the computer cannot calculate. So therefore, a very reliable and dependable power supply is key for that overall safety and security of the system.

JUNKO YOSHIDA: All right. Very good. Thank you so much.

BRIAN SANTO: Of course, for many of us covering the automotive sector at every CES, we don’t feel complete if we don’t attend MobilEye’s press conference. It’s traditionally a one-hour lecture on the latest technology advancements from Professor Amno Shashua, president and CEO of Mobileye, which is now an Intel company.

At a time when most automotive companies have been striving to achieve “redundancy” by fusing data from a variety of sensors – vision, radar, lidar and others – Mobileye this year discussed a way to create redundancy by using only photographic cameras, but running the incoming data through different types of neural networks.

Junko got help from Phil Magney, founder and principal at VSI Labs, to break down Mobileye’s new proposal.

JUNKO YOSHIDA: We just came out of Mobileye’s press conference, and Phil and I were talking about, it’s almost like having been in a classroom for one hour! So what was your biggest takeaway, Phil?

PHIL MAGNEY: Well, it’s hard to come out of a press event like that and not feel impressed. And I feel like it’s very authentic, and I feel like there’s a lot of science, a lot of very pragmatic information presented in this announcement, in this release.

JUNKO YOSHIDA: That’s true. It was less fluff, less marketing one-liners, but it’s more about substance. Okay, let’s break it down because there are a few things that surprised us, right? One thing was Professor Sashua talking about the use of cameras can actually go a long way in terms of driving towards autonomy. Tell me a little bit about what you saw in terms of their heavy use of cameras. How it has been involving.

PHIL MAGNEY: Yeah. I completely agree with you. Obviously, it’s a very camera-centric approach. It uses many cameras. But what I like about it is, we’re starting to see a diversification of AI algorithms used to go after a problem in multiple different ways. And that’s how you’re able to create a little bit of redundancy through the camera solution. So it was pretty impressive that even though they are still using cameras, through a couple of different neural networks they’re able to really kind of simulate what you could do with lidar.

JUNKO YOSHIDA: Yeah, some of the pictures they showed were interesting. So one stream they use a heavy use of cameras. But there is a separate stream if the companies choose to do so, they can bring in radar and lidar, and that could also provide the redundancy. Is that what they said?

PHIL MAGNEY: Yeah. I think basically it’s going to be up the customer, really. What’s the customer going to be comfortable with? I think the fact of the matter is, I think that you can do a terrific job of creating Level 2+ automation with a camera-centric solution. I think the proof is there that it can be done. Obviously another company that’s very successful with that is Tesla. But honestly, not every OEM is going to be 100% with that, and so they’re going to still probably want to use certainly radar and possibly even lidar as well if the prices come down.

JUNKO YOSHIDA: Let’s talk a little bit about a very impressive YouTube video he shared with the audience today. He was talking about driving in Jerusalem is Boston Plus, which sounds pretty deadly to me. But tell me, What did we see in that YouTube? What was so impressive about it?

PHIL MAGNEY: Well, I think basically they were showing that the ability to be agile when they are faced with a lot of situations… Like in that video, it’s showing a tandem bus, which is very, very big. So it occludes a lot. So you have to take that into consideration. And they’re showing how it’s coping with the pedestrian. But it’s also showing a little bit of assertiveness as far as its ability to be agile, because this is on the fact that if you are overly cautious with your AV stack, you’re going to be painfully slow. And that’s going to be bad for everyone.

JUNKO YOSHIDA: Who would pay for a robotaxi when it’s too slow to get there, right?

PHIL MAGNEY: Exactly. Exactly. Time is money and valuable, rather.

JUNKO YOSHIDA: So what was the timeline that Mobileye talked about today? He was talking about that we won’t get to the consumer AV until we nail down the robotaxi, right?

PHIL MAGNEY: One thing he made perfectly clear is that the robotaxi is really going to be coming in as a transportation, as a service, rather than any kind of consumer Level 4 or 4+ vehicles. It’s going to be led by a handful of companies that are going to deploy it as a commercial business, which has always kind of been my expectation as well. Again, I can’t recall the name off the top of my head, but they’re working with several companies on that and some new ones. Neil in China. Exactly. I think they’re making great progress.

And then of course the other segment is the evolution of ADAS into Level 2+, and they seem to have a very solid plan for that and a lot of customers lined up and programs in place for that, too.

JUNKO YOSHIDA: All right. Very good. Thank you so much.

BRIAN SANTO: During the briefing, Shashua talked about the importance of executing on the robotaxi business. He claimed that a fully autonomous “commercial” robotaxi today could cost between $10,000 to $15,000. But with enough experience and insights gained from the robotaxi business and Mobileye’s own development of new hardware, a “consumer” Automated Vehicle might be possible at less than– get this– $5,000 by 2025, he said.

Toyota traditionally has a splashy presentation every year at CES, and it traditionally talks about cars. But things change. Frequent EE Times contributor David Benjamin – Benji – attended the presentation.

So, Benji, you walked into a press conference expecting to hear all about cars and a smart cities press conference broke out. Is that right?

DAVID BENJAMIN: Yeah. It was the Toyota press conference. Akio Toyota, the chairman of Toyota, was the speaker. And in the last few years, of course, Toyota presented concept cars and talked about automated driving. And usually featured Gil Pratt, which is one of the really smart guys talking about autonomous driving. And one of the few who warned that it’s going to be a longer haul to get to the Level 5 family car than the industry really wants. But instead, Toyota San talked about building a woven city, which would be a smart city that interweaves all the elements of artificial intelligence from scratch in the area around Mt. Fuji in Japan, close to where my wife’s family lives. And I’m encouraging them to buy up real estate.

BRIAN SANTO: Good advice. So did he present this as a concept community? Or is Toyota actually building it?

DAVID BENJAMIN: That’s a good question. He introduced Bjarke Ingels, who’s head of the Bjarke Ingels Group, BIG, from Copenhagen, who is the architect who has drawn up these spectacular artist’s renderings of the place. I think that, in some respect or another, Toyota must have control over the turf, because they were presenting it as a future reality. But they also said that they’re going to build the whole thing virtually before they build it physically. And they were inviting investors and innovators and anyone inspired by living a better life in the future to contribute to the project. So I think that it’s not necessarily going to come around in the next six months or so.

BRIAN SANTO: So this isn’t exactly a complete and utter departure from vehicle technology and electronic vehicle technology. So they’re going to be talking about a smart city with all that entails– parking meters and home management and that sort of thing– but they’re also talking about some of the infrastructure about delivering things– delivering groceries, delivering people. So it looks like there is a vehicle component to this smart city. Tell us what Toyota discussed about that.

DAVID BENJAMIN: One of the things that Gil Pratt was talking about the last couple of years was the real immediate future for autonomous vehicles. It will be things like delivery vehicles and shuttles and trams that follow a fixed route, that essentially go in a loop from Point A to Point B, back to Point A again. And deliver things, move people around, pick up nannies, drop them off, things like that. And my impression of this woven city is that virtually all the vehicles on the streets where vehicles will be allowed will be these sorts of autonomous, loop-driven vehicles delivering things. I don’t think there will be any parking meters. And I think people’s private cars– assuming they have them– will be parked beneath or around these George Jetson condos that are going to go up. And if you’re commuting someplace else, going to Tokyo or Jigasaki or Yokohama, you’re going to be picking up your car in a garage and leaving a woven city and driving on regular roads. And probably not using an autonomous car.

BRIAN SANTO: We should mention first that this is the initial concept. “City” might be too grand a word to describe it, right?

DAVID BENJAMIN: Well, the initial population is going to be 2,000. So we’re talking about a smart village. Who knows how big it could get? Again, I talked about the fact that it’s close to Mt. Fuji, and if it gets big enough, they’ll probably have to tear down Mt. Fuji and build suburbs.

BRIAN SANTO: Or drill into it, one or the other, right?

DAVID BENJAMIN: Well, if you could get rid of those tourists who go up and down the mountain all the time, it wouldn’t necessarily be a bad thing.

BRIAN SANTO: Thanks, Benji.

And so we conclude our third day of coverage of the 2020 Consumer Electronics Show. This is our final podcast live from CES. We invite you to listen to our first two as well.

Our regularly scheduled podcast is our Weekly Briefing, which we usually present every Friday. Well, not this Friday. We’ll resume our regular schedule the Friday after next.

This podcast is Produced by AspenCore Studio. It was Engineered by Taylor Marvin and Greg McRae at Coupe Studios. The Segment Producer was Kaitie Huss. The transcript of this podcast can be found on EETimes.com. Find our podcasts on iTunes, Spotify, Stitcher, Blubrry or the EE Times web site. Signing off from CES in Las Vegas, I’m Brian Santo.