AI News, How Autonomous Vehicles Will Transform Cities and Suburbs by ... artificial intelligence
The WIRED Guide to Self-Driving Cars
In the past five years, autonomous driving has gone from “maybe possible” to “definitely possible” to “inevitable” to “how did anyone ever think this wasn’t inevitable?” to "now commercially available."
The details of the program—it's available only to a few hundred vetted riders, and human safety operators will remain behind the wheel—may be underwhelming but don't erase its significance.
Countless hungry startups have materialized to fill niches in a burgeoning ecosystem, focusing on laser sensors, compressing mapping data, setting up service centers, and more.
This cycle has restarted, and the term “driverless car” will soon seem as anachronistic as “horseless carriage.” We don’t know how cars that don’t need human chauffeurs will mold society, but we can be sure a similar gear shift is on the way.
Just over a decade ago, the idea of being chauffeured around by a string of zeros and ones was ludicrous to pretty much everybody who wasn’t at an abandoned Air Force base outside Los Angeles, watching a dozen driverless cars glide through real traffic.
So, Darpa figured, maybe someone else—someone outside the DOD’s standard roster of contractors, someone not tied to a list of detailed requirements but striving for a slightly crazy goal—could put it all together.
Each team grabbed some combination of the sensors and computers available at the time, wrote their own code, and welded their own hardware, looking for the right recipe that would take their vehicle across 142 miles of sand and dirt of the Mojave.
But the race created a community of people—geeks, dreamers, and lots of students not yet jaded by commercial enterprise—who believed the robot drivers people had been craving for nearly forever were possible, and who were suddenly driven to make them real.
Within 18 months, they had built a system that could handle some of California’s toughest roads (including the famously winding block of San Francisco’s Lombard Street) with minimal human involvement.
And the proliferation of ride-hailing services like Uber and Lyft weakened the link between being in a car and owning that car, helping set the stage for a day when actually driving that car falls away too.
The tech giants followed, as did an armada of startups: Hundreds of small companies are now rushing to offer improved radars, cameras, lidars, maps, data management systems, and more to the big fish.
The key tool for doing that perception work—seeing the difference between a stray shopping cart and a person using a wheelchair, for example—is machine learning, which requires not just serious artificial intelligence chops but also gobs upon gobs of real-world examples to train the system.
That’s why Ford invested a billion dollars into artificial intelligence outfit Argo AI, why General Motors bought a startup called Cruise, why Waymo has driven 10 million autonomous miles on public roads (and billions more in simulation).
In November 2018, Tesla debuted a feature called Navigate on Autopilot, which gives its cars (including those already on the road, thanks to an over-the-air software update) the ability to change lanes to get around slower drivers or to leave the highway when it reaches its exit.
At least two Tesla drivers in the US have died using the system (one hit a truck in 2016, another hit a highway barrier this year), and the National Transportation Safety Board has criticized Tesla for making a system that's too easy to abuse.
The huge automakers that build millions of cars a year rely on the complex, precise interaction of dozens or hundreds of companies, the folks who provide all the bits and bobs that go into a car, and the services to keep them running.
Instead, expect to see these robocars either debut as highway-bound trucks or in taxi-like fleets, operating in limited conditions and areas, so their operators can avoid particularly tricky intersections and make sure everything is mapped in excruciating detail.
You know how fiercely Uber and Lyft fight for market share today, tracking drivers, trying to undercut each other, and piling up promotions to bring in riders?
It’s easy to conjure up a dystopia, a world where robocars encourage sprawl, everyone lives 100 miles from their job, and sends their self-driving servants to do their errands and clog our streets.
The optimists imagine a new kind of utopian city, where this technology not only eliminates crashes but integrates with existing public transit and remains affordable for all users.
25 tech trends that will spearhead digital transformation in 2019 and beyond
If the past years have taught us anything, it’s that enterprises that don’t keep pace with the exponential changes in tech will struggle to survive.
The solution can be found in carefully observing trends and collecting data to gain insight into which tech best speeds up your digital transformation – which doesn’t happen overnight, mind you.
And the rapid rate of technological advancement has initiated exciting tech trends that can reinvent entire industries, delivering a slew of cutting-edge technologies.
Also, a blockchain-powered land registry system that uses smart contracts to record land sales is already being tested in India, while the government in Dubai plans to run several public services on distributed ledger technology.
Businesses can rely on blockchain to raise money using an Initial Coin Offering (ICO) – a crypto-version of going public, where investors get crypto tokens instead of shares.
Machine learning (ML), a subset of artificial intelligence, is credited with delivering many of those benefits, training machines to continuously learn and make decisions by discovering insights and patterns in data with minimal human intervention.
Artificial intelligence platforms are also expected to have a big impact on big data analytics as they can efficiently process data and deliver actionable business intelligence.
In addition to this, companies are advised to pay attention to dark data – unused digital information – and analyse it to derive additional insights.
And for those interested in exploring the universe, SpaceVR is developing “the world’s first virtual reality camera satellite” to give people a chance to experience the vastness of space.
This software shows “where, when and how building spaces are used at any given point in time”, enabling managers to better manage the use of space and make their workplace more efficient.
Instead of sending data across long distances to clouds or other storage centres and potentially experiencing latency, edge computing speeds things up and processes some of that data closer to where it originated.
This means that the user’s computer, a connected device, or edge servers are expected to do more of the computing through a “mesh network of micro data centers” instead of relying on clouds that are “no longer sufficient to instantaneously process” the data we generate.
And edge computing will become even more critical, with more than 75 billion IoT devices expected to be in use worldwide by 2025, generating ever-increasing amounts of data.
Instead, network behaviour analytics based on deep learning technology is seen as a potential solution as it enables fast detection and the prevention of suspicious activities.
Finally, the growing popularity of the cloud means that this sector, too, will have to deploy strong cyber-security protection through virtualised firewalls, virtualised intrusion detection, or other tools.
One of the well-known issues is, for instance, the trolley problem – an ethical dilemma in which the subject (in this case, a train, but in a modern-day setting it could be a self-driving vehicle) is forced to choose between staying its course and colliding with five people, or sverwing to save those, killing ‘only one’ in the process.
David Cearley, vice president of research firm Gartner, says that companies should move beyond asking “are we compliant” to “are we doing the right thing”.
Unlike classical computers that rely on bits to process information (in the form of 1s and 0s), quantum computers use qubits that can store more information and perform more complex calculations at much greater speed.
With the power of artificial intelligence you can easily scan images of someone and create realistic footage of people saying or doing something they never did or said.
For instance, the tech company Proximie is developing AR-based solutions to improve medical training, and the California Institute of Technology released an AR app to help people with visual impairment to identify objects and obstacles in their surroundings.
Earlier this year, they bought 1,000 drones from well-known drone manufacturer DJI, which they use to scan construction sites, identify materials, and map (potential) building areas.
What makes drones so appealing is that they can safely and efficiently reach disaster areas and help rescue teams to locate victims and deliver food and medical supplies.
This car manufacturer developed an autonomous vehicle dubbed EZ-PRO to help reduce traffic congestion and pollution, which are common issues in last-mile deliveries.
Autonomous vehicle startup Nuro is also working hard at improving last-mile deliveries with the development of autonomous electric vehicles that will deliver packages, groceries, and food to customers both in urban and suburban areas.
For instance, Climeworks, a tech company from Switzerland, developed a technology that can “collect carbon dioxide (CO2) from ambient air and pair it with renewably made hydrogen (H2) to make methane fuel that would add little or no CO2 to the atmosphere”.
Although Russia didn’t seem to be very fond of cryptocurrencies at first, it clearly changed its mind, as it’s been reported that the Russian government is planning to develop its own cryptocurrency called cryptoruble.
Self-checkout machines making cashiers obsolete, robots replacing factory floor workers, and driverless trucks putting drivers out of work is by most accounts the future we’re heading towards.
The consequences of the tech revolution aren’t just more efficient companies and new products, but also jobless people in dire need of some form of social safety net.
One way to tackle these challenges is by introducing an universal basic income or UBI, a regular sum of money given by the state that enables citizens to meet their basic needs.
Industries such as manufacturing and healthcare are set to be especially strong growth factors as, for instance, the number of connected devices in manufacturing will double between 2017 and 2020.
Meanwhile, online fashion retailers such as Yoox have developed AI tools that analyse social media content, customer feedback, online magazines, and the company’s own sales data to recommend potentially popular and lucrative clothing designs.
The Indian e-commerce site Myntra took a similar approach, witnessing the sales of shirts with AI-generated designs “growing at 100 per cent”, the company’s CEO, Ananth Narayanan, says.
For instance, chatbots are already an important element of customer service, while AI-powered analytics and ad-delivery systems will enable companies to reach and engage customers more efficiently than ever before.
By creating a digital twin of a physical object and dynamically modifying it using real-time data collected by IoT sensors, engineers are now able to better track and analyse the performance of a number of objects, such as cars, buildings, or even jet engines.
Leading global investment banking, securities and investment management firm Goldman Sachs also acknowledged the value of digital twin tech by including it in its series “The Outsiders” as a trend that’s “on the edge of today’s investable universe”.
Efforts to reduce pollution aren’t happening fast enough, and we’re unlikely to keep the global temperature rise below 2 degrees Celsius as proposed by the Paris Agreement.
The Environmental Defense Fund, an NGO, is planning to launch a satellite to measure levels of methane released into the atmosphere by the oil and gas industry, which is one of the leading human-made emission sources of this greenhouse gas.
Google Maps Street View cars will soon be equipped with Aclima’s air quality sensors that’ll measure and map carbon dioxide, carbon monoxide, and nitrogen dioxide in selected cities.
Companies such as the Iceland-based Carbon Recycling International (CRI) have even found a way to turn carbon dioxide into methanol, which is then sold on the European fuel market, and Volkswagen plans to spend over €40 billion on electrification and e-mobility.
These projects paint a picture of the global economy turning to environmental tech to protect the planet, and this trend is expected to grow way beyond 2019.
IV / Industrial
Millennials are helping to drive the shared economy, while the convergence of shared and autonomous vehicles (e.g., robo taxis) is a significant development with positive implications for urbanization and the environment.
In the shared and autonomous world, manufacturers will no longer compete on volume and brand, while consumers will buy journeys and miles/kms.
APTV has positioned itself as a key supplier for electrical architecture, autonomous driving and connectivity, and is one of the first to show returns on its autonomous vehicle investment.
Traffic jam detroit
Business Internet and Technology Innovation Rush hour in Singapore, a crowded island city of nearly 6 million people, is much like rush hour in almost every major city in the world: a living hell of clogged highways and stressed-out drivers.
They have in mind a solution that is radical and all-encompassing: to replace car ownership with ride-sharing.The key ingredient in this plan is the emerging technology of autonomous vehicles (AVs)—cars and shuttle buses that, through the miracle of artificial intelligence, can drive themselves with no human at the wheel.
- On 19. juni 2021
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