Subaru isn't exactly known for developing emerging technologies for its vehicles, so we'll bet you'd never expect the automaker to equip the 2019 Forester with facial recognition technology. But that's exactly what it did -- Subaru has announced at the ongoing New York International Auto Show that it developed a feature for the vehicle that uses facial recognition to detect driver fatigue and distraction. "DriverFocus" comes as a standard feature for the most expensive Touring version of the vehicle, though it's unclear if you can pay extra to have it installed on another model. The feature runs on top of Subaru's new driver assist system called EyeSight, which (unlike DriverFocus) will come pre-installed on all Forester models. It's not a hands-free driving technology, but it covers basic driver assist offerings, such as adaptive cruise control, lane departure warning and lane assist, as well as pre-collision braking.
Two weeks ago, the e-commerce retailer Amazon opened its first offline convenience store, Amazon Go – without a cashier. On January 22, the first visitors of the Seattle store were tracked in the shop using image recognition and machine learning algorithms. The technology finds out what the visitors have bought and charges it automatically to their account. After the customer has scanned their smartphone to enter the store, cameras throughout the store track them as a 3D object without facial recognition. The biggest challenge for image recognition is to differentiate between similar-looking products and customers hands, which often cover the products and their labels. For the retail industry, this is a revolution and is likely to be a major step in linking the online and offline worlds.
Key Points: – AI already impacts many aspects of our daily lives at work and at home – Over the next decade, AI enterprise software revenue will grow from $644 million to nearly $39 billion – Here are the top 10 ways that we predict AI will impact business over the next decade including vehicular object detection, predictive maintenance and intelligent recruitment. Artificial intelligence already impacts many aspects of our daily lives at work, at home and as we move about. Over the next decade, analyst firm Tractica predicts that annual Global AI enterprise software revenue will grow from $644 million in 2016 to nearly $39 billion by 2025. Services-related revenue should reach almost $150 billion. These functional areas are applicable to many use cases, industries, and generate benefits to both businesses and individuals.
"Connected to other part," my iPhone says to me as I stand somewhere in London's Soho, trying to decipher the letter on the top of a bus stop. "Hello?" says an American woman, reminding me of Scarlett Johansson's disembodied artificially intelligent character from the sci-fi film Her. "Hey, er … can you give me a hand by reading the letter on the bus stop?" "Sure … can you move your phone a bit more up, and to the left … Ya! I thank her, end the session, pull up Citymapper and navigate my way onto the 453 going to New Cross. I have a little bit of vision, but only enough to see motion and movement.
The combination will generate immediate results for both Caruma and RoadBotics' customers in the fast-growing and emerging connected vehicle market. Caruma's artificial intelligence-based connected-vehicle platform will incorporate RoadBotics' algorithms, data collection engine, and the processing to deliver advanced information on road surfaces, features, object detection and analysis. "Our growing ecosystem of vision-based connected-vehicle integrations leverages the power of Caruma's open platform to drive innovation, and RoadBotics is a great example of that," said Chris Carson, Chief Executive Officer at Caruma Technologies, Inc. "We're excited to work with this outstanding team and truly believe that their inclusion into our ecosystem will be a significant step towards improving infrastructure management, traffic management, and roadway maintenance." RoadBotics, a computer vision company spun out of Carnegie Mellon's Robotics Institute last year, utilizes an advanced cascade approach with multiple, specialized algorithms chained together to achieve a complex understanding of the world. The technology identifies, characterizes and assesses various real-world roadway conditions that gives roadway managers, vehicles, and others a variety of roadway and signage maintenance recommendations.
It's no surprise that a future with self-driving cars and passengers as co-drivers is fast approaching. Yet while automakers race to be the first to bring a fully autonomous vehicle to the market, there is also a growing focus on the driver. Cars that are 100 percent autonomous (and affordable) are still decades away from hitting the road. In the meantime, semi-autonomous cars must learn to better understand the driver. This can be facilitated using machine learning and computer vision inside the car.
The '90s were the era of the PC, and 2006 ushered in the era of the smartphone. Today, we are at the beginning of the third era in end-user devices: the connected car. In some ways, this shift could be even more significant than the previous ones because it combines the digital and physical world in a way we haven't seen before. As cars evolve into computers on wheels, the biggest business opportunities will be less about "metal and rubber" and more about services. McKinsey estimates that the value of connected car data could be worth $1.5 trillion a year by 2030.
"Although this Statement focuses on the enormous safety potential of these new technologies, they offer an even wider range of possible benefits. Vehicle control systems that automatically accelerate and brake with the flow of traffic can conserve fuel more efficiently than the average driver. By eliminating a large number of vehicle crashes, highly effective crash avoidance technologies can reduce fuel consumption by also eliminating the traffic congestion that crashes cause every day on our roads. Reductions in fuel consumption, of course, yield corresponding reductions in greenhouse gas emissions. To the extent vehicles can communicate with each other and with the highway infrastructure, the potential for safer and more efficient driving will be increased even more.
Toyota Motor Corp. has long tried to pitch its vehicles as "irreplaceable companions." But in this age of artificial intelligence, the company is taking the man-machine relationship to a new level. Enter Toyota's newest companion: the palm-sized Kirobo Mini robot. The 4-inch-tall black-and-white talking cherub, complete with cutesy yellow eyes, red boots and a Toyota logo emblazoned on its chest, takes its name from the Japanese words for "hope" and "robot." Toyota plans to start selling the robot through dealerships in Japan next year for 39,800 ( 390).
Maintaining the highest level of user safety will be non-negotiable when it comes to the deployment of autonomous vehicles whether they are used for personal or mass transport, or logistics in industrial environments. However, for reasons of sheer volume, it will be road vehicles where the biggest changes will be felt. Vehicle efficiency and road safety will be improved and congestion will come down and the technology and legislation is in development to make it a reality. It is generally agreed that the transition to autonomous driving will be gradual. In the US, the National Highway Traffic Safety Administration (NHTSA) has defined five levels of automation, from 0 to 4, which it refers to as the automation continuum.