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.

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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).

Great idea, big potential, but few applications so far and a lot to learn. This sums up the outlook for how public services could make use of artificial intelligence (AI), the technology that is stirring up hopes and fears, and is already surrounded by an aura of inevitability. There is some debate about its definition, but it is generally seen as a stream of computing developed to carry out tasks usually requiring human intelligence, and to learn from what it takes in. It came in for a new round of attention last week when the Government's chief scientific adviser, Sir Mark Walport, delivered a Turing Institute lecture on the potential. It was notable for emphasising the overall significance rather than much precision on how AI could be used: Walport spoke of applications in justice, welfare, education and medicine, but largely in broad terms.

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