If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This is the Udacity's Self-Driving Car Engineer Nanodegree Program final project for the 1st Term. To write a software pipeline to identify vehicles in a video from a front-facing camera on a car. In my implementation, I used a Deep Learning approach to image recognition. Specifically, I leveraged the extraordinary power of Convolutional Neural Networks (CNNs) to recognize images. However, the task at hand is not just to detect a vehicle's presence, but rather to point to its location.
Artificial intelligence (AI) can obtain unbelievably accurate insights into a neighborhood's inhabitants – from their income and level of education to their ethnic background and political beliefs – just by looking at images from Google Street View. If, for example, you wanted to see whether an area voted Republican or Democrat, the AI algorithm would be able to correctly tell you with over 80 percent accuracy, namely based on the types of vehicles riding on the road. The deep-learning algorithm was developed by a team of computer scientists based at Stanford University. Their study was published in the Proceedings of the National Academy of Sciences. Throughout this process, it used an object recognition algorithm to clock tens of millions of houses, landscape features like shrubberies, and – most importantly – vehicles.
"The Computer Society's predictions, based on a deep-dive analysis by a team of leading technology experts, identify top-trending technologies that hold extensive disruptive potential for 2018," said Jean-Luc Gaudiot, IEEE Computer Society President. "The vast computing community depends on the Computer Society as the provider for relevant technology news and information, and our predictions directly align with our commitment to keeping our community well-informed and prepared for the changing technological landscape of the future." Dejan Milojicic, Hewlett Packard Enterprise Distinguished Technologist and IEEE Computer Society past president, said, "The following year we will witness some of the most intriguing dilemmas in the future of technology. Will deep learning and AI indeed expand deployment domains or remain within the realms of neural networks? Will cryptocurrency technologies keep their extraordinary evolution or experience a bubble burst?
Whether they drive themselves or improve the safety of their driver, tomorrow's vehicles will be defined by software. However, it won't be written by developers but by processing data. To prepare for that future, the transportation industry is integrating AI car computers into cars, trucks and shuttles and training them using deep learning in the data center. A benefit of such a software-defined system is that it's capable of handling a wide range of automated driving -- from Level 2 to Level 5. Speaking in Tokyo at the last stop on NVIDIA's seven-city GPU Technology Conference world tour, NVIDIA founder and CEO Jensen Huang demonstrated how the NVIDIA DRIVE platform provides this scalable architecture for autonomous driving. "The future is surely a software defined car," said Huang.
Deep learning, an advanced machine-learning technique, uses layered (hence "deep") neural networks (neural nets) that are loosely modelled on the human brain. Machine learning itself is a subset of Artificial Intelligence (AI), and is broadly about teaching a computer how to spot patterns and use mountains of data to make connections without any programming to accomplish the specific task--a recommendation engine being a good example. Neural nets, on their part, enable image recognition, speech recognition, self-driving cars and smarthome automation devices, among other things. However, the success of deep learning is primarily dependent on the availability of huge data sets on which these neural nets can be trained, coupled with a lot of computing power, memory and energy to function. To address this issue, says a 14 November press release, researchers at the University of Waterloo, Canada, took a cue from nature to make this process more efficient, thus making deep-learning software compact enough to fit on mobile computer chips for use in everything from smartphones to industrial robots.
Governor Andrew Cuomo of the State of New York declared last month that New York City will join 13 other states in testing self-driving cars: "Autonomous vehicles have the potential to save time and save lives, and we are proud to be working with GM and Cruise on the future of this exciting new technology." For General Motors, this represents a major milestone in the development of its Cruise software, since the the knowledge gained on Manhattan's busy streets will be invaluable in accelerating its deep learning technology. In the spirit of one-upmanship, Waymo went one step further by declaring this week that it will be the first car company in the world to ferry passengers completely autonomously (without human engineers safeguarding the wheel). As unmanned systems are speeding ahead toward consumer adoption, one challenge that Cruise, Waymo and others may counter within the busy canyons of urban centers is the loss of Global Positioning System (GPS) satellite data. Robots require a complex suite of coordinating data systems that bounce between orbiting satellites to provide positioning and communication links to accurately navigate our world.
In March 2016, Google's Alphago artificial intelligence (AI) program stunned the world by beating the human world champion Go player in front of 200 million spectators. This was living proof of the potential in AI technology and the level of maturity reached by neural network and deep learning technologies. Those astounded by the success included quite a few engineers and managers who have been leading the AI revolution in the world in recent years. One of these was Intel VP Naveen Rao, general manager of the company's Artificial Intelligence Products Group, which was founded last year. "When I studied at college in the 1990s, we regarded artificial intelligence as'creative work'," Rao relates.
Recent Gartner estimations lead us to believe that up to 20 billion connected things will be in use by 2020. Data is the oil of our century -- but should we be concerned with a "data spill hazard"? Will artificial intelligence curb this threatening phenomenon, or rather, will it reveal the full potential of IoT data value? If my calculations are correct, when artificial intelligence hits the Internet of Things... you're gonna see some serious sh*t." The question is no longer whether companies should embrace big data analytics technologies.
AT THE Consumer Electronics Show in Las Vegas two years ago a leading car maker unveiled a machine that it said was a vision of the future. It certainly looked the part, with a sleek silver body shell, a steering wheel that retracted into the dashboard and four lounge-style chairs that could rotate to face one other. The most startling feature, though, was its self-driving ability. It was filmed navigating through San Francisco shortly before its futuristic doors swung open to journalists. We stepped onto the car's wooden floor and looked at a calming forest projected onto the windows as the car drove itself along the runway of a nearby airbase.
As governments and tech giants alike target AI advances, one facial recognition start-up has secured a huge amount of funding in China. The Dubai police force is welcoming AI into its operation with open, robotic arms. Apple is reportedly testing a new 3D facial-scanning feature that will unlock your iPhone instead of using a fingerprint. Facebook is powering ahead with its augmented reality camera trials, taking in Meitu (and its 1.bn users) in its latest project. The money it's attracting is massive, too.