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) …
Microsoft (NASDAQ: MSFT) is in the middle of a massive transition right now, but you may not have noticed. That's because the company is moving effortlessly into the burgeoning artificial intelligence (AI) market -- and it's bringing its legacy products and services along with it. Over the past few years, Microsoft has successfully been building new features into its Office products and launching new AI-powered tools through its Azure cloud-computing service as the company looks beyond its Windows products to the fast-growing AI market. Microsoft CEO Satya Nadella said recently that AI is the "defining technology of our times," and he's probably right. AI has the capability to alter how we drive our cars, it will help automate our factories, it will both create and kill jobs, it can be used in warfare, and it's already being used to help improve our healthcare.
Cloud Robotics is a term that was popularized by James Kuffner after he brought together researchers from different relevant fields (robotics, machine learning, and computer vision) to assist in coming up with the initial Cloud Robotics concept. Cloud robotics, as the name suggests is bringing together cloud computing and robotics. In essence, taking all the benefits of cloud computing and finding ways to apply them to robot software and robotics. The past couple of years have established cloud computing as the technology of now and the future. In 2017, spending on cloud services was $153.5bn, and this is expected to rise by 21.1% in 2018 to $184.4bn.
Successful companies aren't waiting to embrace and adopt new technologies such as AI and machine learning, IoT, chatbots, and blockchain. According to Gartner, one of the differentiating practices of a high-performing business is focusing investments on moving the technology core forward and testing emerging technologies. Here, find the latest trends around these disruptive new technologies, and learn how your organization can harness their powerful capabilities to grow your business, gain a competitive edge, and achieve real business value. Three Ways to Disrupt IoT for Real Results How can we rethink IoT initiatives so that they actually create value for companies? How Robots and AI Can Improve Shared Services Centers Five strategies can help organizations adopt robotic process automation and artificial intelligence with successful results.
Big Data has already made fundamental changes to the way businesses operate. There are huge advantages for companies who can derive value from their data, but these opportunities come with challenges, too. For some, this is the challenge of acquiring data from new sources. For others, it is the task of building a scalable infrastructure that can manage the data in aggregate. For a brave few, it means extracting value from the data by implementing advanced analytic techniques and tools.
In this chapter of our thought leadership series, AI Business caught up with Kari Ann Briski, the Director of Deep Learning Software Product at NVIDIA. Based in San Francisco, Kari works together with researchers and enterprise customers to bring the benefits of deep learning to their applications. Deep learning is being applied to solve many big data problems from computer vision, image recognition, speech recognition, and autonomous vehicles. With deep learning, there is enormous potential to cure disease, construct smart cities and revolutionize analytics. Today more than 19,000 companies are currently using deep learning to transform their capabilities.
NVIDIA and Baidu announced a broad partnership to bring the world's leading artificial intelligence technology j cloud computing, self-driving vehicles and AI home assistants. Speaking in the keynote at Baidu's AI developer conference in Beijing, Baidu president and COO Qi Lu described his company's plans to work with NVIDIA to bring next-generation NVIDIA Volta GPUs to Baidu Cloud, providing cloud customers with the world's leading deep learning platform. This partnership will adopt NVIDIA's DRIVE PX platform for Baidu's self-driving car initiative, and develop self-driving cars with major Chinese carmakers. Optimize Baidu's PaddlePaddle open source deep learning framework for NVIDIA Volta GPUs and make it widely available to academics and researchers. "NVIDIA and Baidu have pioneered significant advances in deep learning and AI," said Ian Buck, NVIDIA vice president and general manager of accelerated computing.
With the Internet of Things (IoT), vehicles are evolving from self-contained commodities focused on transportation to sophisticated, Internet-connected endpoints often capable of two-way communication. The new data streams generated by modern connected vehicles drive innovative business models such as usage-based insurance, enable new in-vehicle experiences and build the foundation for advances such as autonomous driving and vehicle-to-vehicle (V2V) communication. Through all this, we here at Google Cloud are excited to help make this world a reality. We recently published a solution guide that describes how various Google Cloud Platform (GCP) services fit into the picture. Vehicles can produce upwards of 560 GB data per vehicle, per day.
Machine learning is a form of artificial intelligence that allows computers to learn by providing them with lots of examples. Once this phase ends, the program can answer questions about data it has never seen before. In the past, "machine learning" was the domain of specialized research groups, but now it has risen greatly in popularity as shown by this Google Trends chart on searches over the last five years. Employers are looking to hire data scientists. Forbes reports that the demand for data scientists and advanced analysts will increase 28% by the year 2020.
Over the past decade, big data analysis and applications have revolutionized practices in business and science. They enabled new businesses (e.g., Facebook, Netflix), to disrupt existing industries (e.g., Airbnb, Uber), and accelerated scientific discovery (genomics, astronomy, biology). Today, we are seeing glimpses of the next revolution in data and computation, driven by three trends. First, there is a rapidly growing segment of the economy (e.g., Apple, Facebook, GE) that collects vast amounts of consumer and industrial information and uses this information to provide new services. This trend is spreading widely via the increasing ubiquity of networked sensors in devices like cell phones, thermostats and cars.