With the shift to a value-based reimbursement model, hospitals and clinicians are looking for ways to increase efficiencies and improve patient outcomes. Artificial intelligence can help to streamline diagnoses and treatments by culling through volumes of data and pinpointing specific disease types or other patient data. Patients who need to be seen are seen quicker because a doctor or nurse wasn't spending time looking through reams of reports, which in turn increases satisfaction all around. The goal of cognitive computing is to make knowledge workers more effective, not to replace them, says Hal Andrews, president of healthcare at software company Digital Reasoning. "Any workflow that requires humans to read or skim or scan vast amounts of data, technology can make that more efficient," Andrews tells Healthcare Dive.

An artificial intelligence firm founded in Waterloo is being acquired by tech giant Microsoft. Maluuba's 50-employee team, including co-founders and former University of Waterloo students Sam Pasupalak and Kaheer Suleman, will become part of Microsoft's Artificial Intelligence and Research organization. Terms of the agreement, which was announced Friday, are not being disclosed. Maluuba has offices in Waterloo and Montreal. In a post announcing the agreement on the official Microsoft blog, Harry Shum, executive vice-president of the Artificial Intelligence and Research Group, said the Maluuba team will be consolidated in Montreal this year.

Essentially good hypotheses lead decision-makers like you to new and better ways to achieve your business goals. When you need to make decisions such as how much you should spend on advertising or what effect a price increase will have your customer base, it's easy to make wild assumptions or get lost in analysis paralysis. A business hypothesis solves this problem, because, at the start, it's based on some foundational information. In all of science, hypotheses are grounded in theory. Theory tells you what you can generally expect from a certain line of inquiry.

Rapid7 is a leading provider of security data and analytics solutions that enable organizations to implement an active, analytics-driven approach to cyber security. We combine our extensive experience in security data and analytics and deep insight into attacker behaviors and techniques to make sense of the wealth of data available to organizations about their IT environments and users. Our solutions empower organizations to prevent attacks by providing visibility into vulnerabilities and to rapidly detect compromises, respond to breaches, and correct the underlying causes of attacks. Rapid7 is trusted by more than 4,150 organizations across 90 countries, including 34% of the Fortune 1000. To learn more about Rapid7 or get involved in our threat research, visit www.rapid7.com .

Carnegie Mellon's No-Limit Texas Hold'em software made short work of four of the world's best professional poker players in Pittsburgh at the grueling "Brains vs. Artificial Intelligence" poker tournament. Poker now joins chess, Jeopardy, go, and many other games at which programs outplay people. But poker is different from all the others in one big way: players have to guess based on partial, or "imperfect" information. "Chess and Go are games of perfect information," explains Libratus co-creator Noam Brown, a Ph.D. candidate at Carnegie Mellon. "All the information in the game is available for both sides to see. Poker is a game of imperfect information, since neither player can see their opponent's cards," he writes in an email to The Christian Science Monitor.

Carnegie Mellon's No-Limit Texas Hold'em software made short work of four of the world's best professional poker players in Pittsburgh at the grueling "Brains vs. Artificial Intelligence" poker tournament. Poker now joins chess, Jeopardy, go, and many other games at which programs outplay people. But poker is different from all the others in one big way: players have to guess based on partial, or "imperfect" information. One of the most annoying things about Android has long been the custom skins that manufacturers would slap on top of the operating system. Things have gotten better in recent years, but plenty of users would be happier using Android as Google intended.

In January, Libratus, an AI agent, won $1.77 million in a Texas Hold'Em tournament against four professional poker players. Conducted by the computer science department at Carnegie Mellon University, the contest proved machine mastery of game theory. Prior to this experiment, no computer had demonstrated an ability to win in a strategic game with imperfect information. According to The Washington Post, researchers believe that the AI test will have implications across many sectors of our economy. Ultimately, it could be used in a number of situations including, business negotiations, cybersecurity attacks and military operations.

People generally appreciate how the new wave of artificial intelligence-powered chatbots from Web giants can perform basic online tasks on our behalf. Who doesn't like having the ability to order a large pepperoni pizza by speaking five words into a smartphone? But security experts warn there's not much to stop cybercriminals from using AI technology to take social engineering hacks and identity theft to scary new levels. A dire warning about the increasing use of AI technology by cybercriminal was issued by Intel (NASDAQ: INTC) last month. Eric Peterson, a Director of Threat Research at Intel Security, warned that machine learning is starting to crop up in sophisticated scams that have already netted $3 billion for the bad guys.

In a world that operates on billions of digits every day, humans are too slow and inattentive. To adapt, we must automate the processing of millions of complex transactions on a daily basis, at speeds fast enough to satisfy impatient digital users. This adaptation requires a massive level of digital transformation that can support operations, business processes and decision-making speeds faster than is humanly possible. Historically, digital technologies get faster, cheaper, more powerful and smaller every couple of years. We operate in human time, a biological cadence influenced by the physical environment, our well-documented physical, mental and emotional limitations, and the universe that we live in.

For generations, computers that have the ability to think for themselves have been the stuff of science fiction. Neural networks could provide computers with the ability to identify objects and solve problems. However, scientists can't figure out why the computer reaches the conclusion it does. How can we make computers explain themselves? While computers are currently not self-aware, there are programs and algorithms that enable computers to learn and behave in a similar manner to the human brain. Neural networks are used to teach computers how to identify objects, recognize patterns, and even solve problems by feeding in stimuli, recording the output, and then feeding back a result (whether correct or not).