San Francisco – Michigan announced an initiative to explore the development of a more than 40-mile (64-kilometer) stretch of road dedicated to connected and autonomous vehicles between the cities of Ann Arbor and Detroit. The project will be led by Cavnue, a subsidiary of Sidewalk Infrastructure Partners, and will be supported by an advisory committee that includes General Motors Co., Ford Motor Co. and Toyota Motor Corp., as well as autonomous driving startups Argo AI and Alphabet Inc.'s Waymo. "We are taking the initial steps to build the infrastructure to help us test and deploy the cars of the future," Michigan Governor Gretchen Whitmer said in a statement. Michigan said the dedicated autonomous vehicle (AV) corridor is the first of its kind and eventually will improve safety and transit access for communities along the road. The first two years of the project will focus on testing technology and exploring the viability of a highway dedicated to vehicles that drive themselves.
Harro has over 20 years of experience in management consulting and early stage investments in disruptive products, processes and services. In many of the conversations with our (potential) customers, we discuss the power of artificial intelligence. In many publications the usage of AI is almost promoted as "the land of milk and honey" -- but those with a bit of experience will be able to tell you that using AI is not always the answer, and it's not as easy to implement as many try to make you believe. But with the right use-cases defined, it can help your company -- or you as a person -- make life easier or create specific added value. I'd like to tell you about how AI improved my personal life in five examples.
Arranging transportation to the airport, lugging bags, waiting on security lines, and putting up with delays are just some of the headaches travelers suffer when flying from one city to the next. Airlines and technology companies are developing artificial intelligence to ease the journey. Here, The Wall Street Journal outlines one vision of the future of air travel, based on interviews with a major aircraft manufacturer, airlines, technology developers and travel consultants.
Verizon on Thursday released details around its initiative to enhance the GPS accuracy of the phones, drones, and IoT devices that run on its network. The company said it's been building and deploying Real Time Kinematics (RTK) reference stations to its network that are meant to provide hyper-precise location information for connected devices. Verizon said RTK's pinpoint-level location data is a building block to bring to scale emerging technologies like driverless cars, drone delivery, and IoT. As part of its efforts, Verizon is also working with mapping provider HERE Technologies and automated mobility specialist Renovo on scaling autonomous vehicle technology that can address future autonomy needs and pedestrian safety issues. On the mapping side, the companies are pairing HERE's HD Map and HD Positioning technologies with intelligent RTK algorithms, and making that scalable.
Over the past few decades, software has been the engine of innovation for countless applications. From PCs to mobile phones, well-defined hardware platforms and instruction set architectures (ISA) have enabled many important advancements across vertical markets. The emergence of abundant-data computing is changing the software-hardware balance in a dramatic way. Diverse AI applications in facial recognition, virtual assistance, autonomous vehicles and more are sharing a common feature: They rely on hardware as the core enabler of innovation. Since 2017, the AI hardware market has grown 60-70% annually, and is projected to reach $65 billion by 2025.
Germany's Ibeo Automotive Systems, which specializes in lidar systems for autonomous driving, has signed a contract to provide China's Great Wall Motor Company (GWM) with its latest solid-state design. Ibeo said that it has commissioned key partner ZF Friedrichschafen – which in 2016 acquired a major stake in Ibeo – to produce the sensors and control unit for the "Level 3" system, which will provide partial autonomy. GWM has contracted one of its own subsidiaries to develop the system, which will be based around vertical cavity surface-emitting lasers (VCSELs) produced by Austria's AMS. Ibeo points out that, after signing a letter of intent in 2019, it has already been in pre-development with GWM for a year. Officially, the project started with the signing of an additional contract by the two parties last month.
On April 14, 1906, the Miles brothers left their studio on San Francisco's Market Street, boarded a cable car, and began filming what would become an iconic short movie. Called A Trip Down Market Street, it's a fascinating documentation of life at the time: As the cable car rolls slowly along, the brothers aim their camera straight ahead, capturing women in outrageous frilly Victorian hats as they hurry across the tracks. Early automobiles swerve in front of the cable car, some of them convertibles, so we can see their drivers bouncing inside. After nearly a dozen minutes, the filmmakers arrive at the turntable in front of the Ferry Building, whose towering clock stopped at 5:12 am just four days later when a massive earthquake and consequent fire virtually obliterated San Francisco. Well over a century later, an artificial intelligence geek named Denis Shiryaev has transformed A Trip Down Market Street into something even more magical.
Data annotation consists, text annotation, image annotation, and video annotation using the various techniques as per the project requirements and machine learning algorithms compatibility. Data annotation is done to create the training data sets for AI and ML while image annotation is a very important type of image annotation. A task of marking and outlining objects and entities on an image and offering various keywords to classify it which is readable for machines. Presently, Image annotation is growing very fast as image annotation is a very important task as this data helps to create accurate datasets that help computer vision models work in a real-world scenario and get effective results. We annotate & tag images with respective labels & keywords for easy and accurate categorization & help you in creating your customized image annotation services.
Most of the buzz around artificial intelligence (AI) centers on autonomous vehicles, chatbots, digital-twin technology, robotics, and the use of AI-based'smart' systems to extract business insight out of large data sets. But AI and machine learning (ML) will one day play an important role down among the server racks in the guts of the enterprise data center. AI's potential to boost data-center efficiency – and by extension improve the business – falls into four main categories: Put it all together and the vision is that AI can help enterprises create highly automated, secure, self-healing data centers that require little human intervention and run at high levels of efficiency and resiliency. "AI automation can scale to interpret data at levels beyond human capacity, gleaning imperative insights needed for optimizing energy use, distributing workloads and maximizing efficiency to achieve higher data-center asset utilization," explains Said Tabet, distinguished engineer in the global CTO office at Dell Technologies. Of course, much like the promise of self-driving cars, the self-driving data center isn't here yet.
Self-driving cars often use a combination of normal two-dimensional cameras and depth-sensing'LiDAR' units to recognize the world around them. However, others make use of visible light cameras that capture imagery of the roads and streets. They are trained with a wealth of information and vast databases of hundreds of thousands of clips which are processed using artificial intelligence to accurately identify people, signs and hazards. In LiDAR (light detection and ranging) scanning - which is used by Waymo - one or more lasers send out short pulses, which bounce back when they hit an obstacle. These sensors constantly scan the surrounding areas looking for information, acting as the'eyes' of the car.