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4 Ways IBM Watson's Artificial Intelligence Is Changing Healthcare


Some say that artificial intelligence (AI) will radically change healthcare in the future. But that prediction overlooks an important detail: AI is already significantly changing healthcare. IBM (NYSE:IBM) Watson Health general manager Deborah DiSanzo spoke at the annual J. P. Morgan Healthcare Conference on Wednesday. She provided an update on the progress that IBM Watson, the AI system famous for beating Jeopardy! DiSanzo highlighted four areas where AI is making a big difference today.

Can Machine Learning Turn Big Data into No Big Deal?


With technology moving so fast, new ways to automate, and connected machines, how can managers and engineers simplify the complexity of that ecosystem? Is machine learning (ML) or artificial intelligence (AI) the key? This article will define some buzzwords, what they mean, and if they might help simplify these complex technologies so that you can move back into production. New technologies, such as Big Data and the Industrial Internet of Things, are gaining more traction. While security is a concern, some companies push ahead because the benefits are too great.

Leverage AI to revolutionize and advance healthcare


What is Intel doing in the area of artificial intelligence/machine learning? Artificial intelligence is causing a technological revolution. Intel recognizes the power AI has to transform society and industries. We are committed to democratizing AI and machine-learning innovations so that everyone has the opportunity to benefit. To that end, we've been doing a number of things: This group focuses on solutions that make it easy to incorporate custom AI solutions into existing infrastructure.

AI could have 'immense' benefits for NHS, says tech committee chair


The chairman of the Commons Science and Technology Committee has thrown his weight behind recommendations for the widespread introduction of artificial intelligence (AI) to the NHS. Norman Lamb said the rewards could be "immense" in terms of cost savings and diagnosing patients more quickly. But he warned people's privacy must be protected and that the health service should get a "fair deal" from technology companies implementing the systems. The report, by the Reform think tank, said AI could be used to target treatment by predicting which individuals or groups might be at risk of illness, to send patients to the most appropriate services or to enable them to "self-care". The technology can also be used to improve diagnoses, Reform said, including for breast cancer – 30 times faster and more accurately than humans, the group claimed.

Artificial intelligence proves major time savings for federal employees


The phrase "artificial intelligence" can stir up a lot of panic at some federal agencies, and can give rise to the idea of intelligent machines putting some employees out of work. However, some federal agencies are embracing the idea of artificial intelligence, and in those test cases, adopting machine learning comes down to a few key strategies like starting small and managing expectations. While AI isn't a panacea for every big-data problem in government, agency leaders say they see value in using machine learning to handle the most tedious aspects of handling data, which frees up human operators to address more mission-critical issues. Insight by Red Hat: Agency experts examine the DevSecOps mindset in government. "Artificial intelligence is an imperative.

How AI is transforming the future of fintech


WIRED Money takes place in Studio Spaces, London on May 18, 2017. For more details and to purchase your ticket visit "Breaking: Two Explosions in the White House and Barack Obama is injured." At the time of the tweet, AP's account had around two million followers. The post was favourited, retweeted, and spread. At 13:13, AP confirmed the tweet was fake.

Can AI win the war against fake news?


It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us. One algorithm meant to shine a light in the darkness is,

The Great AI Paradox

MIT Technology Review

You've probably heard versions of each of the following ideas. With computers becoming remarkably adept at driving, understanding speech, and other tasks, more jobs could soon be automated than society is prepared to handle. This "superintelligence" will largely make human labor unnecessary. In fact, we'd better hope that machines don't eliminate us altogether, either accidentally or on purpose. Even though the first scenario is already under way, it won't necessarily lead to the second one.

Drones Invasion Of Pop Culture: Fact or Fiction?

Forbes Europe

Maybe you've read the statistics on how many drones are filling our skies: The FAA anticipates 7 million by 2020. Perhaps you've heard about how drones are revolutionizing commercial operations. It's possible you know someone who has a drone of their own, or seen a quadcopter hovering over your local park. The reality is there's no shortage of drones filling our homes, stores, skies, and seas. It should come as no surprise that the technology is steadily making its way into our media.

How to use machine learning and AI in cyber security


Cyber criminals are constantly seeking new ways to perpetrate a breach but thanks to artificial intelligence (AI) and its subset machine learning, it's becoming possible to fight off these attacks automatically. The secret is in machine learning's ability to monitor network traffic and learn what's normal within a system, using this information to flag up any suspicious activity. As the technology's name suggests, it's able to use the vast amounts of security data collected by businesses every day to become more effective over time. At the moment, when the machine spots an anomaly, it sends an alert to a human – usually a security analyst – to decide if an action needs to be taken. But some machine learning systems are already able to respond themselves, by restricting access for certain users, for example.