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) …
US President Donald Trump often tweets from his iPhone about pressuring China to address its $375bn trade surplus with the United States. But a closer look at the Apple smartphone reveals how the headline figure is distorted. The big trade imbalance - at the heart of a potential trade war, with Trump expected to impose tariffs on Chinese imports this week - exists in large part because of electrical goods and tech, the biggest US import item from China. Apple Inc's iPhone, however, illustrates how a big portion of that imbalance is due to imports of American-branded products - many of which use global suppliers for parts, but are put together in China and shipped around the world. Take a look at the iPhone X. IHS Markit estimates its components cost a total of $370.25.
As policymakers debate the government's role in developing artificial intelligence, a House bill aims to shed light on the emerging technology's role in strengthening national security. The National Security Commission on Artificial Intelligence Act would create an independent panel to explore recent advancements in artificial intelligence and assess the economic and national security impacts of the budding technology. Introduced Tuesday by Rep. Elise Stefanik, R-N.Y., who heads the House Armed Services Subcommittee on Emerging Threats and Capabilities, the legislation would provide direction for agencies looking to steer the growth of AI in the coming years. With some experts calling artificial intelligence "the biggest economic and technological revolution" of our lifetimes, maintaining an edge in the field could prove critical to America's position on the world stage. "Artificial intelligence is a constantly developing technology that will likely touch every aspect of our lives," Stefanik said in a statement.
The potential hit to their bottom lines has property-casualty insurers in an arms race to figure out how they can design policies and price the risk of the vehicles that technology firms, such as Uber and Alphabet Inc., GOOGL -0.16% are seeking to deploy in huge numbers, according to industry brokers, executives and trade groups. It isn't clear that the death this week in Arizona would be an example of how liability would shake out for the industry. A person familiar with Uber said the firm's test vehicles are insured through a commercial-insurance policy for a maximum of $5 million per accident. The insurer or insurers couldn't immediately be learned. The Uber accident highlights a likely broader trend to come in driverless cars.
Four ways to explore the use of voice technology for your business. At its introduction, Siri became a cultural touchstone, The iPhone-resident, voice-activated assistant gave Apple users a taste of a user interface that had previously not seen much usage beyond science fiction. Since then, though, Siri has attracted aggressive competition. The biggest surprise among these has been Alexa, which sprung forth from an unlikely source in Amazon.com This has led many to argue that Siri has fallen behind its competitors in the space that it pioneered, but Apple may not be running the same race as its competitors.
According to the Economist Intelligence Unit report, 75% of business executives surveyed said AI will be actively implemented in the next three years. Artificial intelligence is very popular; everyone is talking about it, everyone wants it, and very few understand how to use it in a long-term meaningful way. The first hurdle is to decide how and where to introduce it in an organization. This can be difficult because of the fear of job loss and that the technology will replace human skills. This can be expected; with every new technology there are challenges.
In my first blog post on the topic – Customer Experience and Machine Learning: Practical Applications – I discussed how machine learning techniques are being used today by financial services organizations to achieve business benefit. Insurers and retail banks are using machine learning to improve personalization by being able to better analyze and predict customer behavior, and deliver the optimal marketing offer, message, or price. But what is coming in the future? Based on the research we are doing – we are seeing a few capabilities come to forefront. These include augmented analytics, collaborative machine learning, and the introduction of decision trees and neural networks within deep learning.
Willis Towers Watson's The Global Future of Work Survey approached 909 companies worldwide, and found that they expect automation will account for 22% of the work being done in the next three years. That compares with the 12% of work companies say is being done using artificial intelligence (AI) and robotics today, and just 7% three years ago. The research suggested that HR is not currently fully prepared for potential organisational changes brought on by technology. Just 31% of organisations have taken steps to address talent deficits, only 32% have attempted to identify the emerging skills required for their business, while 29% say that they have tried to find appropriate talent for a digital workforce. While few employers have measures in place, respondents said they were planning to take action in the future through establishing which tasks can be automated (50%), and identifying ways to reskill talent whose work could be automated (48%).
The engineering research wing of the United States Defence Department DARPA wants to use machine learning to develop new technologies for use in combat. AIs can now be used not just to recognise objects that already exist but also to devise new ones. Machine learning is already used in some engineering and design contexts, and DARPA wants to expand that usage. AIs programmed to understand fundamental physics will be set engineering challenges, giving them free rein to supply out-of-the-box solutions that will help with innovative design. It is hoped that AI will greatly assist the US government in developing new machines and components for military purposes.