As Apple enters the artificial intelligence realm with iOS 10, leveling with its users about how it plans to collect their data -- and act transparently -- will be key. And that's exactly what the company attempted to do at its developer conference earlier this month. The Cupertino company quietly unfurled its plans to collect data from its users to improve the AI features embedded within Siri in the newest version of its mobile operating system. With the data, Apple hopes to improve its software's abilities to better predict its owners' needs. As privacy concerns grow with consumers, the company will employ "differential privacy," an algorithmic method that seeks to minimize the chances of identifying the data's origin while still allowing Apple to draw key inferences to improve its AI products.

Walk in to any major grocery store and shoppers will no doubt find an unmanned terminal subbing in for a cashier, allowing customers to scan their own groceries before paying their bill. So it's little wonder a June report from Ryerson University's Brookfield Institute for Innovation Entrepreneurship (BIIE) cautions service-oriented workers like cashiers and retail salespeople are at a 92% to 97% risk of being affected by advances in automation and artificial intelligence (AI) within 20 years. Davyde Wachell, CEO of Vancouver's Responsive Capital Management, even envisions artificial intelligence going so far as to shake up the job market in the financial sector. "Wealth management businesses that don't use AI and don't use machine learning are going to get left in the dust," he said. Already, robo-advisers are using automated tools to manage portfolios – a system known as passive portfolio management that relies on price averages to match market returns. Wachell, who studied AI and machine learning at Stanford University in the early 2000s "before it became a craze," told Business in Vancouver that it's only natural for AI to make a play for the robo-adviser market.

The diameter (or geodesic) or a network is defined as the longest shortest path in the network. We can see there are many paths of length six in the network. We can use the shortestPath function in Cypher to find the shortest path between any two characters in the graph.

NEW YORK: According to some prominent voices in the tech world, artificial intelligence presents a looming existential threat to humanity: Warnings by luminaries like Elon Musk and Nick Bostrom about "the singularity" -- when machines become smarter than humans -- have attracted millions of dollars and spawned a multitude of conferences. But this hand-wringing is a distraction from the very real problems with artificial intelligence today, which may already be exacerbating inequality in the workplace, at home and in our legal and judicial systems. Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many "intelligent" systems that shape how we are categorised and advertised to. Take a small example from last year: Users discovered that Google's photo app, which applies automatic labels to pictures in digital photo albums, was classifying images of black people as gorillas. Google apologized; it was unintentional.

Monday's edition of the Federal Register contains new property disclosure requirements for mining companies and a review of artificial intelligence. Artificial intelligence: The Obama administration is looking into artificial intelligence. The White House's Office of Science and Technology Policy announced Friday a request for information as it considers the challenges and opportunities presented by artificial intelligence. "Like any transformative technology, however, AI carries risks and presents complex policy challenges along a number of different fronts," it added. Finance: The Securities and Exchange Commission (SEC) is proposing new property disclosure requirements for mining companies.

Machine learning is a loose term, it covers many activities. From a software engineering aspect it could be seen as an activity evolved from pattern recognition. It can be even more narrowly viewed as the assignment of a label to a given input value.

With business applications of artificial intelligence ranging from customer service, to hiring, to marketing, it's clear that AI is a tool that is critical for companies to embrace. But using AI has consequences for business structures, hierarchies, and budgets. Why Dick's Sporting Goods decided to play its own game in e commerce Dick's Sporting Goods has long partnered with eBay Enterprise on its e -commerce platform. Learn the benefits and risks of this multi -million dollar IT bet. To understand how this new technology will disrupt traditional business models, and to help prepare businesses integrate AI in their plans, TechRepublic spoke with Dave O'Flanagan, CEO and co-founder of Boxever, a data science company based in Ireland.

After abandoning its own GPU for supercomputers, machine learning, and video games in 2009, Intel has returned to the market with a new 72-core Xeon Phi, to compete with NVIDIA's growing portfolio of GPUs. The Xeon Phi'Knights Landing' chip, announced at the International Supercomputing Conference in Frankfurt, Germany last week, is Intel's most powerful and expensive chip to date and is aimed at machine learning and supercomputers, two areas where Nvidia's GPUs have flourished. Inside the chip there is 72-cores running at 1.5GHz, alongside 16GB of integrated stacked memory. The chip supports up to 384GB of DDR4 memory, making it immensely scalable for machine learning programs. At the conference, Intel mentioned some of the issues with GPUs for complex machine learning programs.

Breakthrough technologies, including "socially aware" artificial intelligence and new generation solar panels, could soon tackle the world's most pressing challenges.

We're at the cusp of a sharp rise in devices that have no screen but do have conversational voice controls, such as the Amazon Echo. Smart home and Internet-of-things (IoT) objects that respond to users' voices will improve and become more intuitive with further iterations and wider adoption. Already they can, for example, dim the lights in a room and play a favorite song. With practice, and, by the virtues of machine learning, these user experiences will become ever more intuitive, capable, and innate. Beyond the IoT, brands are seeing bots as a new type of media – one that can be harnessed to expand a company's reach to new customers and networks.