AI computing needs high levels of data processing and conventional AI systems function by transmitting data to a cloud server to be processed. Insights about the data and the decisions to be taken by the system are then transmitted back to connected devices. This approach works fine but for the rapidly increasing number of IoT devices, this is not ideal. There are issues both with the processing power, cloud connectivity and battery capacities in the mobile devices. While connected devices are not ideal to support large data crunching, sometimes they are designed for purposes that need insights in real-time, such as in self-driving cars or in anomaly detection systems.
Should Elon Musk's robot-surgeon start inserting electrodes into human brains to connect humans and computers via a high-bandwidth brain-machine? What exactly are the implications for medical insurance? Should a self-driving flying taxi crash and kill civilians? These are the questions our CEO, Lizé Lambrechts, is asking. The insurance industry is developing new ways to assess and underwrite risk as artificial intelligence (AI) and automation advance.
Many airports hope to start using biometric scanners in lieu of passports to identify travelers. Buzz60's Tony Spitz has the details. The next time you go to the airport you might notice something different as part of the security process: A machine scanning your face to verify your identity. U.S. Customs and Border Protection (CBP) has been working with airlines to implement biometric face scanners in domestic airports to better streamline security. But how does the process work?
Machine learning and artificial intelligence (AI) systems are rapidly being adopted across the economy and society. These AI algorithms, many of which process fast-growing datasets, are increasingly used to deliver personalised, interactive, 'smart' goods and services that affect everything from how banks provide advice to how chairs and buildings are designed. There is no doubt that AI has a huge potential to facilitate and enhance a large number of human activities and that it will provide new and exciting insights into human behaviour and cognition. The further development of AI will boost the rise of new and innovative enterprises, will result in promising new services and products in – for instance – transportation, health care, education and the home environment. They may transform, and even disrupt, the way public and private organisations currently work and the way our everyday social interactions take place.
Nvidia CEO Jensen Huang proudly proclaimed on an analyst earnings call this week that artificial intelligence is the "single most powerful force of our time." Nvidia reported Q2 earnings and revenues that beat analysts' expectations as demand for graphics and artificial intelligence chips picked up. After the earnings call, I interviewed Huang about the company's progress. During the analyst call, he said there are more than 4,000 AI startups working with the company -- as compared to 2,000 AI startups in April 2017. In our interview, Huang said the actual number of AI startups Nvidia is tracking is closer to 4,500.
The automotive industry isn't just being driven by people -- it's also driven by data, particularly as automobile manufacturers move toward autonomous, self-driving vehicles. Last year, Waymo cars drove 1.2 million miles in California. Meanwhile, Tesla, with its Autopilot program, is actively collecting data from hundreds of thousands of vehicles to predict how its cars might perform autonomously. So far the company has collected hundreds of millions of miles worth of data. What are these autonomous vehicle manufacturers doing with all of that data?
Optimus Ride has already deployed its autonomous transportation systems in the Seaport area of Boston, in a mixed-use development in South Weymouth, Massachusetts, and in the Brooklyn Navy Yard, a 300-acre industrial park. Some of the biggest companies in the world are spending billions in the race to develop self-driving vehicles that can go anywhere. Meanwhile, Optimus Ride, a startup out of MIT, is already helping people get around by taking a different approach. The company's autonomous vehicles only drive in areas it comprehensively maps, or geofences. Self-driving vehicles can safely move through these areas at about 25 miles per hour with today's technology.
Nvidia CEO Jensen Huang said AI would drive long-term demand because it is the "single most powerful force of our time." Nvidia reported earnings and revenues that beat analysts' expectations as demand for graphics and artificial intelligence chips picked up in the second fiscal quarter. Huang also said his company's near-term growth will come from gaming and a couple of variants of the company's artificial intelligence chip business: inferencing and AI at the edge. During a conference call with analysts, Huang said artificial intelligence is the "single most powerful force of our time" and that there are more than 4,000 AI startups working with the company -- as compared to 2,000 AI startups in April 2017. In an interview with VentureBeat, Huang said the actual number of AI startups Nvidia is tracking is closer to 4,500.
As one of the world's busiest airports, (ranked No. 3 in 2018 according to Airports Council International's world traffic report), Dubai International Airport is also a leader in using artificial intelligence (AI). In fact, the United Arab Emirates (UAE) leads the Arab world with its adoption of artificial intelligence in other sectors and areas of life and has a government that prioritizes artificial intelligence including an AI strategy and Ministry of Artificial Intelligence with a mandate to invest in technologies and AI tools. The Emirates Ministry of the Interior said that by 2020, immigration officers would no longer be needed in the UAE. They will be replaced by artificial intelligence. The plan is to have people just walk through an AI-powered security system to be scanned without taking off shoes or belts or emptying pockets.
Object detection is a computer vision technique whose aim is to detect objects such as cars, buildings, and human beings, just to mention a few. The objects can generally be identified from either pictures or video feeds. Object detection has been applied widely in video surveillance, self-driving cars, and object/people tracking. In this piece, we'll look at the basics of object detection and review some of the most commonly-used algorithms and a few brand new approaches, as well. Object detection locates the presence of an object in an image and draws a bounding box around that object.