Tag Archives: control

#432331 $10 million XPRIZE Aims for Robot ...

Posted on March 19, 2018 by Android

Ever wished you could be in two places at the same time? The XPRIZE Foundation wants to make that a reality with a $10 million competition to build robot avatars that can be controlled from at least 100 kilometers away.

The competition was announced by XPRIZE founder Peter Diamandis at the SXSW conference in Austin last week, with an ambitious timeline of awarding the grand prize by October 2021. Teams have until October 31st to sign up, and they need to submit detailed plans to a panel of judges by the end of next January.

The prize, sponsored by Japanese airline ANA, has given contestants little guidance on how they expect them to solve the challenge other than saying their solutions need to let users see, hear, feel, and interact with the robot’s environment as well as the people in it.

XPRIZE has also not revealed details of what kind of tasks the robots will be expected to complete, though they’ve said tasks will range from “simple” to “complex,” and it should be possible for an untrained operator to use them.

That’s a hugely ambitious goal that’s likely to require teams to combine multiple emerging technologies, from humanoid robotics to virtual reality high-bandwidth communications and high-resolution haptics.

If any of the teams succeed, the technology could have myriad applications, from letting emergency responders enter areas too hazardous for humans to helping people care for relatives who live far away or even just allowing tourists to visit other parts of the world without the jet lag.

“Our ability to physically experience another geographic location, or to provide on-the-ground assistance where needed, is limited by cost and the simple availability of time,” Diamandis said in a statement.

“The ANA Avatar XPRIZE can enable creation of an audacious alternative that could bypass these limitations, allowing us to more rapidly and efficiently distribute skill and hands-on expertise to distant geographic locations where they are needed, bridging the gap between distance, time, and cultures,” he added.

Interestingly, the technology may help bypass an enduring hand break on the widespread use of robotics: autonomy. By having a human in the loop, you don’t need nearly as much artificial intelligence analyzing sensory input and making decisions.

Robotics software is doing a lot more than just high-level planning and strategizing, though. While a human moves their limbs instinctively without consciously thinking about which muscles to activate, controlling and coordinating a robot’s components requires sophisticated algorithms.

The DARPA Robotics Challenge demonstrated just how hard it was to get human-shaped robots to do tasks humans would find simple, such as opening doors, climbing steps, and even just walking. These robots were supposedly semi-autonomous, but on many tasks they were essentially tele-operated, and the results suggested autonomy isn’t the only problem.

There’s also the issue of powering these devices. You may have noticed that in a lot of the slick web videos of humanoid robots doing cool things, the machine is attached to the roof by a large cable. That’s because they suck up huge amounts of power.

Possibly the most advanced humanoid robot—Boston Dynamics’ Atlas—has a battery, but it can only run for about an hour. That might be fine for some applications, but you don’t want it running out of juice halfway through rescuing someone from a mine shaft.

When it comes to the link between the robot and its human user, some of the technology is probably not that much of a stretch. Virtual reality headsets can create immersive audio-visual environments, and a number of companies are working on advanced haptic suits that will let people “feel” virtual environments.

Motion tracking technology may be more complicated. While even consumer-grade devices can track peoples’ movements with high accuracy, you will probably need to don something more like an exoskeleton that can both pick up motion and provide mechanical resistance, so that when the robot bumps into an immovable object, the user stops dead too.

How hard all of this will be is also dependent on how the competition ultimately defines subjective terms like “feel” and “interact.” Will the user need to be able to feel a gentle breeze on the robot’s cheek or be able to paint a watercolor? Or will simply having the ability to distinguish a hard object from a soft one or shake someone’s hand be enough?

Whatever the fidelity they decide on, the approach will require huge amounts of sensory and control data to be transmitted over large distances, most likely wirelessly, in a way that’s fast and reliable enough that there’s no lag or interruptions. Fortunately 5G is launching this year, with a speed of 10 gigabits per second and very low latency, so this problem should be solved by 2021.

And it’s worth remembering there have already been some tentative attempts at building robotic avatars. Telepresence robots have solved the seeing, hearing, and some of the interacting problems, and MIT has already used virtual reality to control robots to carry out complex manipulation tasks.

South Korean company Hankook Mirae Technology has also unveiled a 13-foot-tall robotic suit straight out of a sci-fi movie that appears to have made some headway with the motion tracking problem, albeit with a human inside the robot. Toyota’s T-HR3 does the same, but with the human controlling the robot from a “Master Maneuvering System” that marries motion tracking with VR.

Combining all of these capabilities into a single machine will certainly prove challenging. But if one of the teams pulls it off, you may be able to tick off trips to the Seven Wonders of the World without ever leaving your house.

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#432303 What If the AI Revolution Is Neither ...

Posted on March 14, 2018 by Android

Why does everyone assume that the AI revolution will either lead to a fiery apocalypse or a glorious utopia, and not something in between? Of course, part of this is down to the fact that you get more attention by saying “The end is nigh!” or “Utopia is coming!”

But part of it is down to how humans think about change, especially unprecedented change. Millenarianism doesn’t have anything to do with being a “millennial,” being born in the 90s and remembering Buffy the Vampire Slayer. It is a way of thinking about the future that involves a deeply ingrained sense of destiny. A definition might be: “Millenarianism is the expectation that the world as it is will be destroyed and replaced with a perfect world, that a redeemer will come to cast down the evil and raise up the righteous.”

Millenarian beliefs, then, intimately link together the ideas of destruction and creation. They involve the idea of a huge, apocalyptic, seismic shift that will destroy the fabric of the old world and create something entirely new. Similar belief systems exist in many of the world’s major religions, and also the unspoken religion of some atheists and agnostics, which is a belief in technology.

Look at some futurist beliefs around the technological Singularity. In Ray Kurzweil’s vision, the Singularity is the establishment of paradise. Everyone is rendered immortal by biotechnology that can cure our ills; our brains can be uploaded to the cloud; inequality and suffering wash away under the wave of these technologies. The “destruction of the world” is replaced by a Silicon Valley buzzword favorite: disruption. And, as with many millenarian beliefs, your mileage varies on whether this destruction paves the way for a new utopia—or simply ends the world.

There are good reasons to be skeptical and interrogative towards this way of thinking. The most compelling reason is probably that millenarian beliefs seem to be a default mode of how humans think about change; just look at how many variants of this belief have cropped up all over the world.

These beliefs are present in aspects of Christian theology, although they only really became mainstream in their modern form in the 19th and 20th centuries. Ideas like the Tribulations—many years of hardship and suffering—before the Rapture, when the righteous will be raised up and the evil punished. After this destruction, the world will be made anew, or humans will ascend to paradise.

Despite being dogmatically atheist, Marxism has many of the same beliefs. It is all about a deterministic view of history that builds to a crescendo. In the same way as Rapture-believers look for signs that prophecies are beginning to be fulfilled, so Marxists look for evidence that we’re in the late stages of capitalism. They believe that, inevitably, society will degrade and degenerate to a breaking point—just as some millenarian Christians do.

In Marxism, this is when the exploitation of the working class by the rich becomes unsustainable, and the working class bands together and overthrows the oppressors. The “tribulation” is replaced by a “revolution.” Sometimes revolutionary figures, like Lenin, or Marx himself, are heralded as messiahs who accelerate the onset of the Millennium; and their rhetoric involves utterly smashing the old system such that a new world can be built. Of course, there is judgment, when the righteous workers take what’s theirs and the evil bourgeoisie are destroyed.

Even Norse mythology has an element of this, as James Hughes points out in his essay in Nick Bostrom’s book Global Catastrophic Risks. Ragnarok involves men and gods being defeated in a final, apocalyptic battle—but because that was a little bleak, they add in the idea that a new earth will arise where the survivors will live in harmony.

Judgement day is a cultural trope, too. Take the ancient Egyptians and their beliefs around the afterlife; the Lord of the underworld, Osiris, weighs the mortal’s heart against a feather. “Should the heart of the deceased prove to be heavy with wrongdoing, it would be eaten by a demon, and the hope of an afterlife vanished.”

Perhaps in the Singularity, something similar goes on. As our technology and hence our power improve, a final reckoning approaches: our hearts, as humans, will be weighed against a feather. If they prove too heavy with wrongdoing—with misguided stupidity, with arrogance and hubris, with evil—then we will fail the test, and we will destroy ourselves. But if we pass, and emerge from the Singularity and all of its threats and promises unscathed, then we will have paradise. And, like the other belief systems, there’s no room for non-believers; all of society is going to be radically altered, whether you want it to be or not, whether it benefits you or leaves you behind. A technological rapture.

It almost seems like every major development provokes this response. Nuclear weapons did, too. Either this would prove the final straw and we’d destroy ourselves, or the nuclear energy could be harnessed to build a better world. People talked at the dawn of the nuclear age about electricity that was “too cheap to meter.” The scientists who worked on the bomb often thought that with such destructive power in human hands, we’d be forced to cooperate and work together as a species.

When we see the same response over and over again to different circumstances, cropping up in different areas, whether it’s science, religion, or politics, we need to consider human biases. We like millenarian beliefs; and so when the idea of artificial intelligence outstripping human intelligence emerges, these beliefs spring up around it.

We don’t love facts. We don’t love information. We aren’t as rational as we’d like to think. We are creatures of narrative. Physicists observe the world and we weave our observations into narrative theories, stories about little billiard balls whizzing around and hitting each other, or space and time that bend and curve and expand. Historians try to make sense of an endless stream of events. We rely on stories: stories that make sense of the past, justify the present, and prepare us for the future.

And as stories go, the millenarian narrative is a brilliant and compelling one. It can lead you towards social change, as in the case of the Communists, or the Buddhist uprisings in China. It can justify your present-day suffering, if you’re in the tribulation. It gives you hope that your life is important and has meaning. It gives you a sense that things are evolving in a specific direction, according to rules—not just randomly sprawling outwards in a chaotic way. It promises that the righteous will be saved and the wrongdoers will be punished, even if there is suffering along the way. And, ultimately, a lot of the time, the millenarian narrative promises paradise.

We need to be wary of the millenarian narrative when we’re considering technological developments and the Singularity and existential risks in general. Maybe this time is different, but we’ve cried wolf many times before. There is a more likely, less appealing story. Something along the lines of: there are many possibilities, none of them are inevitable, and lots of the outcomes are less extreme than you might think—or they might take far longer than you think to arrive. On the surface, it’s not satisfying. It’s so much easier to think of things as either signaling the end of the world or the dawn of a utopia—or possibly both at once. It’s a narrative we can get behind, a good story, and maybe, a nice dream.

But dig a little below the surface, and you’ll find that the millenarian beliefs aren’t always the most promising ones, because they remove human agency from the equation. If you think that, say, the malicious use of algorithms, or the control of superintelligent AI, are serious and urgent problems that are worth solving, you can’t be wedded to a belief system that insists utopia or dystopia are inevitable. You have to believe in the shades of grey—and in your own ability to influence where we might end up. As we move into an uncertain technological future, we need to be aware of the power—and the limitations—of dreams.

Image Credit: Photobank gallery / Shutterstock.com

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#432193 Are ‘You’ Just Inside Your Skin or ...

Posted on March 2, 2018 by Android

In November 2017, a gunman entered a church in Sutherland Springs in Texas, where he killed 26 people and wounded 20 others. He escaped in his car, with police and residents in hot pursuit, before losing control of the vehicle and flipping it into a ditch. When the police got to the car, he was dead. The episode is horrifying enough without its unsettling epilogue. In the course of their investigations, the FBI reportedly pressed the gunman’s finger to the fingerprint-recognition feature on his iPhone in an attempt to unlock it. Regardless of who’s affected, it’s disquieting to think of the police using a corpse to break into someone’s digital afterlife.

Most democratic constitutions shield us from unwanted intrusions into our brains and bodies. They also enshrine our entitlement to freedom of thought and mental privacy. That’s why neurochemical drugs that interfere with cognitive functioning can’t be administered against a person’s will unless there’s a clear medical justification. Similarly, according to scholarly opinion, law-enforcement officials can’t compel someone to take a lie-detector test, because that would be an invasion of privacy and a violation of the right to remain silent.

But in the present era of ubiquitous technology, philosophers are beginning to ask whether biological anatomy really captures the entirety of who we are. Given the role they play in our lives, do our devices deserve the same protections as our brains and bodies?

After all, your smartphone is much more than just a phone. It can tell a more intimate story about you than your best friend. No other piece of hardware in history, not even your brain, contains the quality or quantity of information held on your phone: it ‘knows’ whom you speak to, when you speak to them, what you said, where you have been, your purchases, photos, biometric data, even your notes to yourself—and all this dating back years.

In 2014, the United States Supreme Court used this observation to justify the decision that police must obtain a warrant before rummaging through our smartphones. These devices “are now such a pervasive and insistent part of daily life that the proverbial visitor from Mars might conclude they were an important feature of human anatomy,” as Chief Justice John Roberts observed in his written opinion.

The Chief Justice probably wasn’t making a metaphysical point—but the philosophers Andy Clark and David Chalmers were when they argued in “The Extended Mind” (1998) that technology is actually part of us. According to traditional cognitive science, “thinking” is a process of symbol manipulation or neural computation, which gets carried out by the brain. Clark and Chalmers broadly accept this computational theory of mind, but claim that tools can become seamlessly integrated into how we think. Objects such as smartphones or notepads are often just as functionally essential to our cognition as the synapses firing in our heads. They augment and extend our minds by increasing our cognitive power and freeing up internal resources.

If accepted, the extended mind thesis threatens widespread cultural assumptions about the inviolate nature of thought, which sits at the heart of most legal and social norms. As the US Supreme Court declared in 1942: “freedom to think is absolute of its own nature; the most tyrannical government is powerless to control the inward workings of the mind.” This view has its origins in thinkers such as John Locke and René Descartes, who argued that the human soul is locked in a physical body, but that our thoughts exist in an immaterial world, inaccessible to other people. One’s inner life thus needs protecting only when it is externalized, such as through speech. Many researchers in cognitive science still cling to this Cartesian conception—only, now, the private realm of thought coincides with activity in the brain.

But today’s legal institutions are straining against this narrow concept of the mind. They are trying to come to grips with how technology is changing what it means to be human, and to devise new normative boundaries to cope with this reality. Justice Roberts might not have known about the idea of the extended mind, but it supports his wry observation that smartphones have become part of our body. If our minds now encompass our phones, we are essentially cyborgs: part-biology, part-technology. Given how our smartphones have taken over what were once functions of our brains—remembering dates, phone numbers, addresses—perhaps the data they contain should be treated on a par with the information we hold in our heads. So if the law aims to protect mental privacy, its boundaries would need to be pushed outwards to give our cyborg anatomy the same protections as our brains.

This line of reasoning leads to some potentially radical conclusions. Some philosophers have argued that when we die, our digital devices should be handled as remains: if your smartphone is a part of who you are, then perhaps it should be treated more like your corpse than your couch. Similarly, one might argue that trashing someone’s smartphone should be seen as a form of “extended” assault, equivalent to a blow to the head, rather than just destruction of property. If your memories are erased because someone attacks you with a club, a court would have no trouble characterizing the episode as a violent incident. So if someone breaks your smartphone and wipes its contents, perhaps the perpetrator should be punished as they would be if they had caused a head trauma.

The extended mind thesis also challenges the law’s role in protecting both the content and the means of thought—that is, shielding what and how we think from undue influence. Regulation bars non-consensual interference in our neurochemistry (for example, through drugs), because that meddles with the contents of our mind. But if cognition encompasses devices, then arguably they should be subject to the same prohibitions. Perhaps some of the techniques that advertisers use to hijack our attention online, to nudge our decision-making or manipulate search results, should count as intrusions on our cognitive process. Similarly, in areas where the law protects the means of thought, it might need to guarantee access to tools such as smartphones—in the same way that freedom of expression protects people’s right not only to write or speak, but also to use computers and disseminate speech over the internet.

The courts are still some way from arriving at such decisions. Besides the headline-making cases of mass shooters, there are thousands of instances each year in which police authorities try to get access to encrypted devices. Although the Fifth Amendment to the US Constitution protects individuals’ right to remain silent (and therefore not give up a passcode), judges in several states have ruled that police can forcibly use fingerprints to unlock a user’s phone. (With the new facial-recognition feature on the iPhone X, police might only need to get an unwitting user to look at her phone.) These decisions reflect the traditional concept that the rights and freedoms of an individual end at the skin.

But the concept of personal rights and freedoms that guides our legal institutions is outdated. It is built on a model of a free individual who enjoys an untouchable inner life. Now, though, our thoughts can be invaded before they have even been developed—and in a way, perhaps this is nothing new. The Nobel Prize-winning physicist Richard Feynman used to say that he thought with his notebook. Without a pen and pencil, a great deal of complex reflection and analysis would never have been possible. If the extended mind view is right, then even simple technologies such as these would merit recognition and protection as a part of the essential toolkit of the mind.This article was originally published at Aeon and has been republished under Creative Commons.

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#432181 Putting AI in Your Pocket: MIT Chip Cuts ...

Posted on February 27, 2018 by Android

Neural networks are powerful things, but they need a lot of juice. Engineers at MIT have now developed a new chip that cuts neural nets’ power consumption by up to 95 percent, potentially allowing them to run on battery-powered mobile devices.

Smartphones these days are getting truly smart, with ever more AI-powered services like digital assistants and real-time translation. But typically the neural nets crunching the data for these services are in the cloud, with data from smartphones ferried back and forth.

That’s not ideal, as it requires a lot of communication bandwidth and means potentially sensitive data is being transmitted and stored on servers outside the user’s control. But the huge amounts of energy needed to power the GPUs neural networks run on make it impractical to implement them in devices that run on limited battery power.

Engineers at MIT have now designed a chip that cuts that power consumption by up to 95 percent by dramatically reducing the need to shuttle data back and forth between a chip’s memory and processors.

Neural nets consist of thousands of interconnected artificial neurons arranged in layers. Each neuron receives input from multiple neurons in the layer below it, and if the combined input passes a certain threshold it then transmits an output to multiple neurons above it. The strength of the connection between neurons is governed by a weight, which is set during training.

This means that for every neuron, the chip has to retrieve the input data for a particular connection and the connection weight from memory, multiply them, store the result, and then repeat the process for every input. That requires a lot of data to be moved around, expending a lot of energy.

The new MIT chip does away with that, instead computing all the inputs in parallel within the memory using analog circuits. That significantly reduces the amount of data that needs to be shoved around and results in major energy savings.

The approach requires the weights of the connections to be binary rather than a range of values, but previous theoretical work had suggested this wouldn’t dramatically impact accuracy, and the researchers found the chip’s results were generally within two to three percent of the conventional non-binary neural net running on a standard computer.

This isn’t the first time researchers have created chips that carry out processing in memory to reduce the power consumption of neural nets, but it’s the first time the approach has been used to run powerful convolutional neural networks popular for image-based AI applications.

“The results show impressive specifications for the energy-efficient implementation of convolution operations with memory arrays,” Dario Gil, vice president of artificial intelligence at IBM, said in a statement.

“It certainly will open the possibility to employ more complex convolutional neural networks for image and video classifications in IoT [the internet of things] in the future.”

It’s not just research groups working on this, though. The desire to get AI smarts into devices like smartphones, household appliances, and all kinds of IoT devices is driving the who’s who of Silicon Valley to pile into low-power AI chips.

Apple has already integrated its Neural Engine into the iPhone X to power things like its facial recognition technology, and Amazon is rumored to be developing its own custom AI chips for the next generation of its Echo digital assistant.

The big chip companies are also increasingly pivoting towards supporting advanced capabilities like machine learning, which has forced them to make their devices ever more energy-efficient. Earlier this year ARM unveiled two new chips: the Arm Machine Learning processor, aimed at general AI tasks from translation to facial recognition, and the Arm Object Detection processor for detecting things like faces in images.

Qualcomm’s latest mobile chip, the Snapdragon 845, features a GPU and is heavily focused on AI. The company has also released the Snapdragon 820E, which is aimed at drones, robots, and industrial devices.

Going a step further, IBM and Intel are developing neuromorphic chips whose architectures are inspired by the human brain and its incredible energy efficiency. That could theoretically allow IBM’s TrueNorth and Intel’s Loihi to run powerful machine learning on a fraction of the power of conventional chips, though they are both still highly experimental at this stage.

Getting these chips to run neural nets as powerful as those found in cloud services without burning through batteries too quickly will be a big challenge. But at the current pace of innovation, it doesn’t look like it will be too long before you’ll be packing some serious AI power in your pocket.

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#432165 Silicon Valley Is Winning the Race to ...

Posted on February 24, 2018 by Android

Henry Ford didn’t invent the motor car. The late 1800s saw a flurry of innovation by hundreds of companies battling to deliver on the promise of fast, efficient and reasonably-priced mechanical transportation. Ford later came to dominate the industry thanks to the development of the moving assembly line.

Today, the sector is poised for another breakthrough with the advent of cars that drive themselves. But unlike the original wave of automobile innovation, the race for supremacy in autonomous vehicles is concentrated among a few corporate giants. So who is set to dominate this time?

I’ve analyzed six companies we think are leading the race to build the first truly driverless car. Three of these—General Motors, Ford, and Volkswagen—come from the existing car industry and need to integrate self-driving technology into their existing fleet of mass-produced vehicles. The other three—Tesla, Uber, and Waymo (owned by the same company as Google)—are newcomers from the digital technology world of Silicon Valley and have to build a mass manufacturing capability.

While it’s impossible to know all the developments at any given time, we have tracked investments, strategic partnerships, and official press releases to learn more about what’s happening behind the scenes. The car industry typically rates self-driving technology on a scale from Level 0 (no automation) to Level 5 (full automation). We’ve assessed where each company is now and estimated how far they are from reaching the top level. Here’s how we think each player is performing.

Volkswagen
Volkswagen has invested in taxi-hailing app Gett and partnered with chip-maker Nvidia to develop an artificial intelligence co-pilot for its cars. In 2018, the VW Group is set to release the Audi A8, the first production vehicle that reaches Level 3 on the scale, “conditional driving automation.” This means the car’s computer will handle all driving functions, but a human has to be ready to take over if necessary.

Ford
Ford already sells cars with a Level 2 autopilot, “partial driving automation.” This means one or more aspects of driving are controlled by a computer based on information about the environment, for example combined cruise control and lane centering. Alongside other investments, the company has put $1 billion into Argo AI, an artificial intelligence company for self-driving vehicles. Following a trial to test pizza delivery using autonomous vehicles, Ford is now testing Level 4 cars on public roads. These feature “high automation,” where the car can drive entirely on its own but not in certain conditions such as when the road surface is poor or the weather is bad.

General Motors
GM also sells vehicles with Level 2 automation but, after buying Silicon Valley startup Cruise Automation in 2016, now plans to launch the first mass-production-ready Level 5 autonomy vehicle that drives completely on its own by 2019. The Cruise AV will have no steering wheel or pedals to allow a human to take over and be part of a large fleet of driverless taxis the company plans to operate in big cities. But crucially the company hasn’t yet secured permission to test the car on public roads.

Waymo (Google)

Waymo Level 5 testing. Image Credit: Waymo

Founded as a special project in 2009, Waymo separated from Google (though they’re both owned by the same parent firm, Alphabet) in 2016. Though it has never made, sold, or operated a car on a commercial basis, Waymo has created test vehicles that have clocked more than 4 million miles without human drivers as of November 2017. Waymo tested its Level 5 car, “Firefly,” between 2015 and 2017 but then decided to focus on hardware that could be installed in other manufacturers’ vehicles, starting with the Chrysler Pacifica.

Uber
The taxi-hailing app maker Uber has been testing autonomous cars on the streets of Pittsburgh since 2016, always with an employee behind the wheel ready to take over in case of a malfunction. After buying the self-driving truck company Otto in 2016 for a reported $680 million, Uber is now expanding its AI capabilities and plans to test NVIDIA’s latest chips in Otto’s vehicles. It has also partnered with Volvo to create a self-driving fleet of cars and with Toyota to co-create a ride-sharing autonomous vehicle.

Tesla
The first major car manufacturer to come from Silicon Valley, Tesla was also the first to introduce Level 2 autopilot back in 2015. The following year, it announced that all new Teslas would have the hardware for full autonomy, meaning once the software is finished it can be deployed on existing cars with an instant upgrade. Some experts have challenged this approach, arguing that the company has merely added surround cameras to its production cars that aren’t as capable as the laser-based sensing systems that most other carmakers are using.

But the company has collected data from hundreds of thousands of cars, driving millions of miles across all terrains. So, we shouldn’t dismiss the firm’s founder, Elon Musk, when he claims a Level 4 Tesla will drive from LA to New York without any human interference within the first half of 2018.

Winners

Who’s leading the race? Image Credit: IMD

At the moment, the disruptors like Tesla, Waymo, and Uber seem to have the upper hand. While the traditional automakers are focusing on bringing Level 3 and 4 partial automation to market, the new companies are leapfrogging them by moving more directly towards Level 5 full automation. Waymo may have the least experience of dealing with consumers in this sector, but it has already clocked up a huge amount of time testing some of the most advanced technology on public roads.

The incumbent carmakers are also focused on the difficult process of integrating new technology and business models into their existing manufacturing operations by buying up small companies. The challengers, on the other hand, are easily partnering with other big players including manufacturers to get the scale and expertise they need more quickly.

Tesla is building its own manufacturing capability but also collecting vast amounts of critical data that will enable it to more easily upgrade its cars when ready for full automation. In particular, Waymo’s experience, technology capability, and ability to secure solid partnerships puts it at the head of the pack.

This article was originally published on The Conversation. Read the original article.

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