How artificial intelligence is transforming the world


Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it.1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations. Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance. In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values.2 Although there is no uniformly agreed upon definition, AI generally is thought to refer to "machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention."3 According to researchers Shubhendu and Vijay, these software systems "make decisions which normally require [a] human level of expertise" and help people anticipate problems or deal with issues as they come up.4 As such, they operate in an intentional, intelligent, and adaptive manner. Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.

The 25 Ways AI Can Revolutionize Transportation: From Driverless Trains to Smart Tracks


With massive breakthroughs in smart technologies being reported every month, it won't be long until our transport industries are dominated by AI. Here are just some of the ways artificial intelligence is changing the face of transport, and what we can expect in the near future. Autonomous cars have quickly moved from the realm of sci-fi into reality. Though still in the early stages, these AI-driven vehicles could drastically change how we get from A to B in the near future. From plowing snow to collecting garbage, self-driving trucks could soon be taking over a lot of our dirty work.

Intelligent to a Fault: When AI Screws Up, You Might Still Be to Blame


Artificial intelligence is already making significant inroads in taking over mundane, time-consuming tasks many humans would rather not do. The responsibilities and consequences of handing over work to AI vary greatly, though; some autonomous systems recommend music or movies; others recommend sentences in court. Even more advanced AI systems will increasingly control vehicles on crowded city streets, raising questions about safety--and about liability, when the inevitable accidents occur. But philosophical arguments over AI's existential threats to humanity are often far removed from the reality of actually building and using the technology in question. Deep learning, machine vision, natural language processing--despite all that has been written and discussed about these and other aspects of artificial intelligence, AI is still at a relatively early stage in its development.

Scaling the AI Ladder - THINK Blog


The first automobile was driven down the streets of Detroit in 1890. It would take another 30 years before Henry Ford streamlined production and made cars available to the mass market. The obvious lesson: sometimes technology has a long gestation period, before we can scale it for everyday use.

Revamping the Automotive Landscape with Technology


Abdallah Shanti, EVP & Group CIO of the Americas Region, Volkswagen AG [ETR:VOW3], Abdallah Shanti is Executive Vice President and Group Chief Information Officer for IT Region Americas. In this role, Shanti leads IT strategy, direct...

The road to AI leads through information architecture


Ford drove the first automobile down the streets of Detroit in 1890. It would take another 30 years before the company streamlined production and made cars available to the mass market. The obvious lesson: Sometimes technology has a long gestation period before we can scale it for everyday use. But, digging a bit deeper, there is a more profound lesson.

NVIDIA swings for the AI fences


CES showcases the tech trends that will shape the year ahead. See the most important products that will impact businesses and professionals. NVIDIA, as I've written about several times, is the company that started in gaming and graphics but which has rapidly transformed into an organization focused on AI. Nope, NVIDIA is swinging for the fences, leveraging its GPU technology, deep learning, its Volta architecture, its Cuda GPU programming platform and a dizzying array of partnerships to move beyond mere tech and become an industrial powerhouse. CEO and Founder Jensen Huang gave the Sunday night keynote at CES, an prized time slot once dominated by Microsoft.

Toward Adapting Cars to Their Drivers

AI Magazine

A more modern view is to envision drivers and passengers as actively interacting with a complex automated system. Such interactive activity leads us to consider intelligent and advanced ways of interaction leading to cars that can adapt to their drivers. In this article, we focus on the adaptive cruise control (ACC) technology that allows a vehicle to automatically adjust its speed to maintain a preset distance from the vehicle in front of it based on the driver's preferences. Although individual drivers have different driving styles and preferences, current systems do not distinguish among users. We introduce a method to combine machine-learning algorithms with demographic information and expert advice into existing automated assistive systems.

Future of AI revenue: Top 10 uses cases for next decade


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, and services related revenue should reach almost $150 billion. These functional areas are applicable to many use cases, industries, and generate benefits for both businesses and individuals. Here are the top ten use cases which will reap financial rewards for AI technology product and service companies, and a broad spectrum of benefits for everyone else. Sharing economy leaders Lyft and Uber, and new entrants can easily leverage autonomous cars to facilitate getting a vehicle from one car rental customer to another.