Tuomas Sandholm and Noam Brown spent the past year building an AI that plays Texas Hold'Em. The two Carnegie Melon researchers call their creation Libratus, and they believe it can top the world's best players at no-limit Hold'Em, a version of the classic poker game that allows any bet at any time. No machine has ever reached such heights with this unusually complex game of cards. Although AI systems have topped the best players at checkers, chess, Othello, and even Go, no-limit Hold'Em creates a different obstacle. In contrast to those other games of intellect, a poker player can know only part of what's happening during each hand.

Join Entrepreneur's The Goal Standard Challenge and make 2017 yours. From creating personalized shopping experiences to offering virtual buying assistants -- AI is improving the online shopping experience for consumers and retailers. Shoppers will be able to easily find the best price for an item and communicate with chatbots for quick customer service. For retailers, they'll be able to better analyze consumer data to predict future buying patterns, create autonomous replenishing systems and also save money and time on customer service by utilizing chatbots. Related: Has Artificial Intelligence Arrived At The Sales Function Yet?

The outcomes of the future are pretty uncertain eventualities. But yet, we as humans strive to predict future outcomes and scenarios in a variety of ways. For example the complete guesswork of choosing your lottery numbers, to the more logical science & technology based efforts of meteorologists predicting future weather patterns. Needless to say, human beings have an innate desire to analyze patterns and contemplate the unknown. When it comes to the future of the mobile marketing industry, things are a little more certain than next week's big numbers.

There are seven key megatrends driving the future of enterprise IT. You can remember them all with the helpful mnemonic acronym CAMBRIC, which stands for Cloud Computing, Artificial Intelligence, Mobility, Big Data, Robotics, Internet of Things, CyberSecurity. In this post we dive deeper into Artificial Intelligence. Artificial Intelligence is the discipline of thinking machines.

Something that reminds me of this is the framework of generative adversarial networks. The generator is updated to try to trick the discriminator (by gradient descent to minimize its accuracy), which is then updated again to deal with the new samples. This framework has been very popular in the past few years, but is very tricky to use in practice, and there's a lot of ongoing research (e.g. this paper from earlier this year and this one just published two days ago) in getting them to work more reliably. You could imagine, maybe, having human annotators do some kind of label smoothing for the discriminator: true data set samples get the label 1, terrible samples get label -1, okay ones get -.75, great ones get 0, maybe the best ones get labeled as .5 or even 1. I haven't thought through the consequences of this too much, but it might help.

Meet Jill Watson, a first-time teaching assistant at Georgia Tech assigned to moderate an online forum for a computer science class. Jill was 1 of 9 TAs assigned to help answer questions about coursework and projects from the 300 students enrolled in the advanced course. During the first few weeks in January, Jill really struggled. This was Knowledge-Based Artificial Intelligence, after all, a course with the goal to "build AI agents capable of human-level intelligence and gain insights into human cognition." It was also a requirement for graduate students to earn their master's degree.

Nvidia (NASDAQ:NVDA) and Mercedes-Benz parent Daimler AG (OTCPK:DDAIF) (OTCPK:DDAIY) announced a partnership for AI powered Mercedes cars. These cars, which are expected to be available within the next year, will feature self-driving capability as well as an active driver assistance function called "Co-Pilot." Co-Pilot may well be the most intelligent human-machine interface ever devised. The announcement at CES of the Nvidia/Daimler partnership came only a day after Nvidia CEO Jen-Hsun Huang gave his keynote at CES. Since the announcement of the Nvidia/Tesla (NASDAQ:TSLA) partnership last year, the automobile industry has been waking up to the fact that the race to build the first commercially available self-driving car is all but won.

Despite spending more money on security than ever, organisations struggling with a widespread cybersecurity skills gap are often told how technologies like big data, analytics, machine learning, and artificial intelligence can aid them in protecting their data or critical infrastructure from attackers. Organisations ranging from startups to established large corporations are investing in the building of AI systems to bolster defences by analysing vast amounts of data and helping cybersecurity professionals identify far more threats than would be possible if they were left to do it manually. But the same technologies that improve corporate defences could also be used to attack them. It's the simplest method of cyberattack available -- and there are schemes on the dark web which put all the tools required to go phishing into anyone's hands. It's simply a case of taking an email address, scraping some publicly available personal data to make the phishing email seem convincing, then sending it to the victim and waiting for them to bite.

In billiards, you must call your shot ahead of time. You don't get any points for luck. With that in mind, here are my on-the-record predictions for 2017. Self-driving cars, previously existing only in the world of science fiction, are becoming a reality. Today taxis are driving themselves in Singapore.