Below is a selection of original thought pieces written by SHFFT members on autonomous vehicle technology and the future of mobility.

The biggest threat facing connected autonomous vehicles is cybersecurity

By Rob Toews
Harvard JD/MBA 2018
August 25, 2016

Note: this article was originally published in TechCrunch.

Connected, autonomous vehicles are around the corner. Many of the most innovative and deep-pocketed companies in the world are racing to bring them to market — and for good reason: the economic and social gains they will generate will be tremendous.

But any transformative technology creates new challenges and risks in addition to benefits. This is no exception.

One of the biggest threats that society will face as transportation transforms in the coming years is vehicle cybersecurity. It is a topic about which much is still unknown, even among those working at the cutting edge of the industry; vehicle connectivity is a new phenomenon and the technology continues to evolve rapidly.

Thankfully, a major malicious cyberattack on a vehicle has yet to take place. But the potential danger was illustrated dramatically last year when two white-hat hackers remotely took control of a Jeep Cherokee and cut its transmission on the highway as part of a research initiative. The well-publicized incident prompted Chrysler to recall 1.4 million vehicles.

One of the central challenges in vehicle cybersecurity is that the various electrical components in a car (known as electronic control units, or ECUs) are connected via an internal network. Thus, if hackers manage to gain access to a vulnerable, peripheral ECU — for instance, a car’s Bluetooth or infotainment system — from there they may be able to take control of safety critical ECUs like its brakes or engine and wreak havoc.

Cars today have up to 100 ECUs and more than 100 million lines of code — a massive attack surface. Further complicating matters, auto manufacturers source ECUs from many different suppliers, meaning that no one player is in control of, or even familiar with, all of a vehicle’s source code.

The threat of automotive cyberattacks will only loom larger as society transitions toautonomous vehicles. But even before autonomous vehicles become widespread, car hacking is already a very real danger: In 2014, more than half of the vehicles sold in the United States were connected, meaning that they are vulnerable to cyberattacks.

Key players in the auto industry have begun to pay attention.

“A cyber incident is a problem for every automaker in the world,” General Motors CEO Mary Barra said in a recent speech. “It is a matter of public safety.”

Given the stakes, it is no surprise that this area has attracted a flurry of recent startup and investment activity. Argus Cyber Security, the largest and most established of these startups, raised $26 million in Series B funding last fall. Earlier this year, Harman acquired cybersecurity startup TowerSec for $72.5 million. In April, Israel-based Karamba Security raised $2.5 million in seed funding.

How auto cybersecurity works

We spoke with Argus executive Yoni Heilbronn about the details and challenges of auto cybersecurity.

“The best mental model for understanding how automotive cybersecurity solutions work is to envision them as having several layers of defense,” Heilbronn said. “Multiple solutions focused on different parts of the connected car ecosystem must be integrated in order to provide comprehensive, end-to-end protection; a single product alone is not adequate.”

Starting at the foundation, defensive software solutions can be housed locally on individual ECUs — for instance, a car’s brakes — to reinforce these ECUs against attacks. Moving up a level, software can protect the vehicle’s internal network as a whole by examining all network communications, flagging any changes in standard in-vehicle network behavior and stopping attacks from advancing in the network.

Next, solutions exist to defend the particular electronic units in a vehicle that areconnected to the outside world — for instance, infotainment units. This is a critical layer in the overall cybersecurity defense system, because it represents the border between the vehicle’s internal network and the external world.

Finally, cloud security services can detect and correct threats before they reach the vehicle. They also can send the vehicle over-the-air updates and intelligence in real time.

In addition to these layers of protection directly relating to a vehicle’s connectivity, supply chain risk management is a critical element of the overall cybersecurity effort. Compromised physical components can jeopardize the integrity of a car’s security architecture, making it imperative that OEMs only source parts from trusted suppliers.

The government’s role

Given the public safety implications, this topic has begun to receive much attention from U.S. lawmakers. In July 2015, Senators Markey (D-Mass.) and Blumenthal (D-Conn.) proposed legislation to establish mandatory federal standards for autocybersecurity.

“Drivers shouldn’t have to choose between being connected and being protected,” said Markey. “We need clear rules of the road that protect cars from hackers.”

Not everyone on Capitol Hill agrees, however. Senator Gary Peters (D-Mich.) has argued that regulators should adopt a more hands-off stance and allow private industry to take the lead in formulating solutions and setting standards.

Arguing that there is “a knowledge gap” among lawmakers on auto cybersecurity, Peters stated, “The way to prevent Congress from [imposing more regulation] is for the industry to step up. The technology is moving so fast that the problem will be the regulators not being able to keep up.”

Many observers believe that private industry has so far not taken the threat seriously or invested enough to proactively address it. This may, however, be changing.

A number of OEMs, including TeslaFiat Chrysler and GM, have recently established “bug bounty” programs to reward individuals that find and report security flaws in their cars’ software, an effort to further fortify their systems against vulnerabilities.

More significantly, the Auto-ISAC, an industry group of major auto manufacturers and suppliers, recently released a comprehensive set of best practices for automotive cybersecurity. The automakers plan for these guidelines to serve as the foundation for industry-wide cybersecurity standards; they likely also hope that taking the lead here will dissuade policymakers from intervening with stringent regulatory requirements.

The road ahead

There are more unknowns than knowns when it comes to the imminence and severity of automotive cyberattacks. Because a major malicious attack has yet to take place, it is hard to know exactly who is most likely to perpetrate such an attack, how it might happen and how much damage it might cause.

Society is often reactive rather than proactive with security issues, adopting serious preventive measures only after a major incident has occurred. Hopefully that pattern will not be repeated here. The good news is that automakers, startups and government regulators are all beginning to focus on the issue and take action to address it.

“A major auto cybersecurity event could happen tomorrow,” Argus executive Heilbronn said. “We all collectively need to come to grips with this. The hacking capabilities are out there right now. The vulnerabilities are out there right now. I do think that attacks will begin to take place unless we take this threat more seriously.”

Investment opportunities in the autonomous vehicle space

By Rob Toews
Harvard JD/MBA 2018
June 11, 2016


Note: this article was originally published in TechCrunch.

As companies race to bring autonomous vehicles (AVs) to market, investment activity in the space is heating up.

General Motors made headlines in March when it paid over $1 billion for Cruise Automation. A few weeks later leading venture capital firm Andreessen Horowitz entered the space, announcing investments in two early-stage autonomous startups, and Dispatch.

Most recently, secretive AV startup Zoox raised a massive $200 million funding round, making it Silicon Valley’s newest unicorn. These and other recent deals point to a growing investment frenzy as AVs get closer to mainstream commercialization.

The AV investment landscape is complex. It includes both hardware and software players and features competitors ranging from early-stage startups to large publicly traded corporations. This article will provide a primer for those interested in the rapidly evolving AV space.



The first and most obvious layer of the AV ecosystem is the vehicle itself. The capital investment and manufacturing expertise required to produce vehicles at scale largely preclude early-stage entrants from being active here. Even large, deep-pocketed technology companies investing heavily in an autonomous future — e.g. Google and Uber — seem unwilling and unlikely to become car manufacturers themselves.

The most probable outcome therefore seems to be that traditional car manufacturers will continue to mass-produce vehicles in the autonomous age. It is unclear whether this manufacturing role will continue to be as profitable for these companies as it has in the past. As value creation in transportation shifts toward high-tech components and software, manufacturers of the cars themselves may become an increasingly commoditized, low-margin business.

Virtually every traditional car manufacturer has by now begun to invest in autonomous vehicle capabilities. Those with particularly interesting autonomous programs include GM, Volvo and Mercedes-Benz. (While Tesla manufactures cars, it is more appropriately considered a technology company.)

Lidar sensors

Lidar is one of several types of specialized sensors that allow AVs to interpret their environment. Lidar sensors give the vehicle a precise three-dimensional awareness of its surroundings by projecting lasers in all directions and measuring the time they take to rebound, a process analogous to radar (the word Lidar is a portmanteau of “light” and “radar”).

Given how critical these components are for overall AV functionality, the market for Lidar sensors will be enormous. A handful of startups have recently emerged that specialize in their production.

Two key dimensions of these sensors are their size and their cost; the company that can harness Moore’s Law to drive both of these down the fastest will have a huge advantage. The Lidar sensors that Google used for its initial AV prototypes reportedly cost $80,000, an impracticable price point for the mass market.

The current market leader in Lidar production, Velodynepriced its most recent sensor at $500. Velodyne, a privately held company based in California, has yet to take any venture funding.

Another California-based Lidar startup that has attracted positive attention recently is Quanergy. Quanergy has announced that its sensors will cost only $250 and have no moving parts. The company has established relationships with a handful of large OEMs but has yet to bring a product to market.


Like Lidar sensors, cameras help AVs understand their environment and maneuver accordingly. Though less precise than Lidar, cameras offer the significant advantage of being able to detect color—important when, for instance, identifying traffic lights and signs.

The dominant player in AV camera production is a publicly traded Israeli company named Mobileye. Mobileye has high-profile supplier contracts with a number of auto manufacturers including Tesla.

Computer chips

Perhaps the most important piece of AV hardware is the computer chip that serves as the vehicle’s “brains.” These chips take inputs from the vehicle’s various sensors and, based on complex software algorithms (discussed further below), enable the vehicle to operate autonomously. As with microprocessors in personal computers, these components sit at the very center of the overall system’s functionality.

Given the enormous computing power demanded, AVs will require state-of-the-art microprocessors. The established chipmakers that have long dominated the microprocessor market — Nvidia, Qualcomm and Intel — seem poised to leverage their existing expertise to succeed with AV chips. All three companies have signaled that autonomous technology will be a strategic priority moving forward.

Of the three, Nvidia is arguably taking this opportunity seriously and investing most heavily in it. Investors have taken notice, with the company’s stock trading near an all-time high.


While the hardware described above is essential, AVs are able to act intelligently, or autonomously, because of their software. There are several different key types of AV software to be aware of.

It is worth noting that the divide between hardware and software companies, while helpful as a framework, is not entirely clean. Some hardware companies — e.g. Mobileye — also provide software to analyze their sensor data. Likewise, some companies classified below as software players also offer hardware as part of an end-to-end autonomous solution.

Mapping and localization

The first category of software critical to AVs is mapping and localization.

In order to effectively navigate, an AV must have a detailed and up-to-date map of its surroundings and must know where on that map it is located. Creating and continually updating such a map database is a massively challenging exercise.

The two biggest players specializing in digital worldwide map database creation are HERE and TomTom. Each of these companies has attracted significant investment attention — no surprise, given that maps will be a key strategic asset for the AV industry.

A coalition of German automakers including Audi, BMW and Daimler recently acquired HERE for around $3 billion (outbidding Uber, among others).

TomTom, a publicly traded company based in Amsterdam, has faced acquisition rumors for years by suitors including Apple; to date the company remains independent. Apple, Uber and Bosch all have partnerships to use TomTom’s data.

Meanwhile, other AV players — notably Google and Uber — are seeking to build mapping capabilities themselves, while a handful of smaller startups are also tackling this challenge.


As vehicles become increasingly connected to the Internet, other vehicles and surrounding infrastructure, cybersecurity will become an increasingly prominent concern. In an important warning of the potential dangers of connected vehicles, white-hat hackers last year remotely took control of a Jeep Cherokee and cut its transmission.

Entrepreneurs and investors are becoming active in AV cybersecurity. As examples, Tel Aviv-based Argus Cyber Security raised $26 million in Series B funding last year, auto electronics maker Harman paid $72.5 million for cybersecurity startup TowerSec in March, and newcomer Karamba Security raised $2.5 million in seed funding in April. More competitors will no doubt emerge soon.

Fleet operations and management

As the autonomous age dawns, many predict that private car ownership will become obsolete, replaced by shared AV fleets that individuals summon only when needed. The task of managing these fleets and optimizing their routes will be an immense challenge requiring complex software solutions.

Startups already beginning to tackle this challenge include RideCell, which in early April raised $11.7 million from BMW and Khosla Ventures. Given its strategic positioning and its commitment to autonomous technology, it seems safe to assume that Uber will invest and compete vigorously here.

AV artificial intelligence / machine learning

The central technological breakthrough at the core of the entire AV concept is the vehicle’s ability to conduct advanced and adaptive decision-making itself based on all the data at its disposal. Artificial intelligence software enabling vehicles to “think” in this way is the most important and technically demanding AV technology category of all. A handful of companies are seeking to build such solutions.

Some of these companies focus solely on software; to go to market, they will look to partner with, or be acquired by, hardware manufacturers. One prominent example is nuTonomy, which recently announced a partnership with the Singapore government to deploy driverless taxis there by 2018. nuTonomy, an MIT spinout, raised $16 million in Series A funding in May.

Other companies are building machine-learning software integrated with hardware in order to offer a comprehensive autonomous system. Included in this group are auto manufacturers such as Tesla but also many promising startups. Cruise Automation, recently acquired by GM, is one well-known example.

Another noteworthy startup is George Hotz’s is building aftermarket “kits” consisting of sensors, computers and software that allow customers to convert existing cars into AVs. The company aims to bring these kits to market for under $1,000 by the end of 2016.

Other startups tackling this ambitious challenge include Zoox, Peloton (focused specifically on long-haul trucking fleets) and Nauto, among many others currently in “stealth mode.”


The landscape of AV companies in these early days of the technology is fluid and fast-changing. Established auto manufacturers, large technology companies and scrappy start-ups are all fiercely competing to win in the AV ecosystem.

A wave of M&A activity, partnerships and consolidation seems likely as AVs move toward commercial availability. One thing is certain: There will be massive opportunity for profit as the autonomous vehicle market takes off in the coming years.

In the words of angel investor Tikhon Bernstam, one of Cruise’s earliest backers: “You’d be hard-pressed to lose money investing in this space right now because there is going to be tens or even hundreds of billions in M&A and IPOs going forward. Cruise at $1 billion may look very cheap one day.”

the luddite prophecy

By Adam Aliano
Harvard Law School 2017
May 30, 2016

Concern surrounding the negative economic effects associated with technological progress is hardly confined to contemporary discourse. There is evidence dating back to the writings of Aristotle of trepidation over technological progress and the concurrent loss of labor opportunities. Aristotle warned that, “[i]f every instrument could accomplish its own work, obeying or anticipating the will of others…chief workmen would not want [human laborers].” Going forward, the First Industrial Revolution featured the rise of the “Luddites,” a group of manual laborers staunchly opposed to the proliferation of the electrically powered machines that would replace them in the workplace. The Luddites focused on the destruction of these machines while society, writ large, dismissed their platform as socially and economically regressive. Thus, their prominence was short-lived.

As technology has advanced since the 1800s, some economists have derided concern over technological effects on the marketplace as a reprise of the “Luddite Fallacy”—the irrational fear of technological development. They cite that markets have always righted themselves after temporary technologically driven disruptions. Further, they posit that even with minor market disturbances, the broad-based societal benefit derived from innovation far outweigh the negatives. For example, saddle makers lost the bulk of their work with the advent of automobiles. But what would we, as a society, prefer: keeping saddle makers employed and preventing the proliferation of the automobile or permitting cuts to the saddle making market and reaping the benefits of automobiles? Clearly, the answer is to foster advancement and allow saddle makers to seek employment elsewhere.

With the advent of paradigm-shifting automated technology (particularly, automated vehicles or “AVs”) closely upon us, there is a colorable argument to be made that this revolution may be different than those past. Policymakers and the general public should be made aware of approaching market perturbations in order to better plan to mitigate potential fallout.

The introduction of “level 4” AVs—those utilizing sensors, GPS, and specialized controls to completely remove human input into the driving process—to the marketplace is fast approaching.  With the vast majority of car manufacturers (e.g., Ford, Nissan, and Toyota) and several technology companies making a concerted push for development, experts from the Institute of Electrical and Electronic Engineers (IEEE) estimate that “up to 75% of all vehicles will be fully automated by 2040.” Cementing the reality of AV development, President Obama and Transportation Secretary Foxx established a ten-year, $3.9 billion plan to “encourage faster innovation in [the industry] and develop a framework for…implementation.” Thus, the dawn of AVs is closer than most think and the potential negative effects should be widely acknowledged.

What makes the innovations in automated technology—specifically in AVs—different from past developments is the “skills gap” that will likely widen in the labor market. The distinction between the types of jobs that will be lost and those that will be created distinguishes this “revolution” from those prior. MIT Professor David Autor suggests that automation will cut into “manual non-routine” jobs (e.g., taxi drivers, truck drivers, and associated manufacturing jobs). These jobs are generally considered “low skilled” in nature (i.e., not requiring advanced training or degrees). The U.S. Bureau of Labor Statistics offers that there are nearly 6 million professionally employed drivers in the U.S. in addition to the 915,000 people employed in manufacturing support jobs. It is quite possible that the vast majority of these jobs will be eliminated with the introduction of AVs. Unlike past tech revolutions—where the saddle maker can easily transition to assembly line— this iteration will create new jobs that demand a relatively higher skill set (e.g., engineers, highly trained technicians and software developers).  Thus, the “skills gap” will feature a robust supply of displaced “low skilled” workers and unable to meet market demand for newly created “high skilled” jobs. A premium will be placed on those with advanced degrees and skills while displaced workers may be forced into lower paying, “manual routine” jobs in various industries.

The backdrop in which this development may occur is similarly important. Professors Goldin and Katz posit that since 1972, the bottom fifth of U.S. society hasn’t realized any annual income growth while the top fifth’s income crows at 1.6% per year and the top 5% grows at 2%. They largely attribute the rising wage inequality to the difference between the wages of the highly educated and less educated.  Since 1970, the growth of college graduates in the U.S. has slowed, thus the supply of “skilled” workers has similarly halted. Building off of these notions, if the premium for “skilled labor” is increased with new tech, and the pool of available workers is primarily “ low skilled,” inequality will worsen as workers may be forced to accept lower paying employment if they are employed at all.

So what can be done to mitigate this gap?

Some instructive recommendations emerge from the recent Trans Pacific Partnership agreement. A government-run—and private sector supported—job-retraining effort would help develop the necessary skills for displaced workers commensurate with industry demand. Furthermore, a concentrated revamping of primary, secondary, and vocational education curricula geared toward market-favored skills is needed. The increasingly popular idea of free community college would provide a valuable opportunity for individuals to garner new skills and thus soften the “job-skill polarization” problem.

A more unlikely proposition that is gaining traction in certain political and economic circles is the Universal Basic Income (UBI). In short, this policy (which can be implemented in various forms) would provide a lump sum of unconditional money to individuals on a regular basis. If the supply of available jobs is decreased by automation, and those jobs that are available can’t be filled due to a “skills gap,” unemployment rates have the potential to increase significantly. A UBI would serve as a baseline security blanket for the public and they will be encouraged to find additional income to add to the lump sum. Though there is some historic appeal from both sides of the aisle regarding the UBI, it is politically the least likely option to be enacted. Conservatives are skeptical of adding a significant amount of federal funding even if it were to reduce the red tape and number of programs already in place. Underlying this concern, policymakers of both parties tend to believe that a UBI would disincentivize work and create a rash of “free riders” within the economy.

In sum, automated innovation should not be impeded in any sense. The tangible benefits are too significant and outweigh the concerns cited above. It is important however, that we, as a citizenry, understand the potential drawbacks associated with these developments and that policymakers take a proactive stance to explore avenues to mitigate negative economic effects. 

what will a driverless future actually look like?

Rob Toews
Harvard JD/MBA 2018
March 19, 2016

Note: this article was originally published in TechCrunch.

There is a growing consensus that autonomous vehicles (AVs) will soon be a reality. The debate today centers not on whether, but how soon, AVs will be commonplace on our roads. But for all the buzz surrounding AVs, many details about what a driverless future will look like remain unclear.

Which business models will work best for the commercialization of AVs? Which AV usage models will be most appealing for consumers? Which companies are best positioned to win in this new market?

These are big questions, and no certain answers can be given at this stage. Nonetheless, it is valuable to reflect, in a concrete way, on how this transformative technology might develop. This article will present some conjectures.

The end of private car ownership?

At a high level, two possible paradigms seem most likely for how society will use AVs. The first is private AV ownership. Under this model, individuals or families would continue to own their own vehicles and use them to get around. As the cars would be self-driving, exciting new possibilities exist for their use.

Individuals could be more productive while in transit. Children, the handicapped, the elderly and others not previously able to drive themselves could commute alone. People could earn supplemental income by sending their cars, when otherwise not in use, to transport other people or goods (a future version of on-demand services like Uber or Instacart).

This option would, in a way, be the closest thing to a continuation of the current status quo. Little would have to change about carmakers’ core business models: individual consumers would still make purchasing decisions and would own and operate their own vehicles.

The second paradigm for AV use represents a more radical reconceptualization of how people get around in society. Under this model, a shared fleet of autonomous vehicles would exist that individuals could summon on demand to get from Point A to Point B. After dropping off one passenger, the vehicle could then pick up and transport the next passenger. Individuals would have no need to own their own cars; rather, they would receive mobility “as a service.”

There are many details about a “mobility as a service” model that are intriguing to consider. The most straightforward version of this model is one in which individuals summon AVs on a one-off basis when they need to get somewhere, paying per ride or per mile — effectively, a driverless version of how Uber or Lyft work today.

It is also possible, however, to imagine the development of more sophisticated subscription models. Under a subscription model, individuals would pay a flat fee on a monthly or annual basis for unlimited access to a given fleet of vehicles, to be used whenever they need a ride — loosely analogous to a SaaS model.

One interesting question is the amount of segmentation that would develop among subscription offerings. It seems likely that, as with most other consumer products, a wide range of AV subscription types would become available that offer different benefits and features depending on price. These differently priced subscription offerings could vary in terms of the types of vehicles in the fleet, the average required wait time for a ride, the electronics and other features available inside the vehicles and so forth.

The issue of segmentation closely ties to the equally important question of which player or players would own and operate these AV fleets. One possibility is that auto manufacturers — at least those that choose to enter the AV market — could offer subscriptions to fleets consisting entirely of their vehicles. Thus, as an example, one could choose to subscribe to Ford’s AV fleet in a given city for a certain rate, or alternatively to pay more to subscribe to Mercedes’ fleet.

Alternatively, these shared AV fleets might be operated not by the carmakers themselves but rather by fleet providers that aggregate various makes of vehicles. To create a profitable role for themselves in the market, these providers would have to add value to the experience in some way beyond vehicle manufacture (e.g. sophisticated mapping or passenger-matching algorithms). One could speculate that Uber, which recently has invested heavily in autonomous technology, envisions itself playing a role along these lines.

One last issue worth contemplating regarding future AV use is the optimal size and capacity of vehicles. The majority of drives in the U.S. today are solo trips, meaning that vehicle space is significantly underutilized and fuel usage is needlessly high. It is statistically rare that all five seats in a standard sedan (much less all eight seats in an SUV) are in use.

Given this, it is plausible to imagine single-occupancy pods making up a significant portion of future AV fleets — thus increasing fuel efficiency, economizing on materials costs and taking up less space on roads. Perhaps vehicles with a wide range of different capacities (from single-occupancy pods all the way to small buses that can fit 20 or 30 people) will all exist on the road, in proportion to their demand, and customers can indicate their desired vehicle size when summoning a car.

Winner take all?

In speculating about these possible AV business and usage models, it is important to keep in mind that this market will not necessarily be “winner take all.” It is altogether possible that more than one of these models — and others that have not yet even been imagined — will all coexist profitably in the market.

One need look no further than the current transportation market for an instructive analogy. Today, people get around in their daily lives in many different ways. Some people own their own cars. Some people rent cars when they need them (either through traditional car rental companies or newer models like Zipcar). Some people get everywhere through ride-sharing services like Uber or Lyft. Some people use public transportation or simply walk. People commonly switch from one of these solutions to another over the course of their lives depending on life’s changing circumstances.

The same will likely be true in the driverless future of tomorrow. For instance, shared fleet models may become prevalent, rendering the concept of private car ownership obsolete for many. At the same time, those who prefer may continue to own and operate their own AVs. Personal transportation is and will continue to be a massive market. There is room for many different models and companies to thrive, and it is unlikely that any one approach will win outright.

On a similar but broader note, many different types of companies will succeed in and add value to the autonomous vehicle space in different ways. It is highly unlikely that any one company will own the entire end-to-end AV experience (though if any company were to try, a plausible candidate would be Apple and its mysterious Project Titan). Instead, the AV experience is likely to be modularized across many different players.

For instance, profitable businesses will be built around producing: LIDAR sensors and other physical components for the vehicles; cybersecurity software to keep connected cars safe; high-performance computing chips to power the cars’ decision-making processes; consumer electronics for the cars’ interiors; mapping and geolocation software to enable the car to navigate; and much more. In this sense, AVs should be thought of not as a single new product but rather as an entirely new ecosystem in the economy.

Time will tell

The possibilities laid out above are, of course, speculative. As AVs continue to develop in the coming years, there will be many technology, product and business model advances that surprise us all. One way or another, autonomous vehicles’ impact on the way we live will be nothing short of transformative. It will be an exciting ride.

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