If Edmonton researcher Randy Goebel has his way, artificially intelligent judges and attorneys will become players in the courtrooms of the future. A professor in computing science at the University of Alberta, Goebel has partnered with scientists in Japan to develop artificial intelligence programs designed for the legal world. His team has already designed an algorithm capable of passing the Japanese bar exam. Now the computer scientists are taking their research one step further. The latest project is new artificial intelligence software that could weigh contradicting legal evidence, rule on cases and predict the outcomes of future trials.

Artificial intelligence and machine-learning algorithms are a useful predictor of schizophrenia with 74% accuracy, according to research at IBM and the University of Alberta in Edmonton, Canada. The retrospective study, which just appeared in Schizophrenia – published by the journal Nature – shows that the technology is capable of predicting the severity of certain symptoms in schizophrenia.

There's no question that AI is redefining processes across a whole spectrum of businesses. There is, however, a question of what that means for the overall economy. Canada is now investing in AI research with the expectation that it will benefit the country in general. DeepMind, the London-based leader in artificial intelligence owned by Google's parent-company Alphabet, is now reaching across the pond to Canada. On July 5, Demis Hassabis, co-founder and CEO, DeepMind announced "the opening of DeepMind's first ever international AI research office in Edmonton, Canada, in close collaboration with the University of Alberta."

Consumers have been paying their bills online and managing their finances for a couple of decades now, but big banks still remain laggards when it comes to adopting AI solutions that can improve their service to customers, a group of panelists who spoke about fintech at MB 2017 said. "Banks have a giant base of customers, and it's hard to move them all. Many people still prefer to go a bank branch to do their banking," said Dion Lisle, VP of fintech at Capgemini. "I hate to say this, but I think we're seeing a lot of'innovation theater.'" Some banks are moving faster than others, but even the laggards will feel pressure to adopt more AI features soon enough.

Artificial intelligence (A.I.) could become a game-changer for multiple industries. Powerful algorithms may soon be able to quickly sift through reams of data and information, delivering quantifiable insights for tasks such as enhancing guidance systems for self-driving cars, assisting physicians in diagnosing patients, or helping farmers implement plans that simplify the management and protection of their crops. Technology giants in the U.S. like IBM and Microsoft are exploring business opportunities where A.I. could have the most impact, but an ecosystem for this type of R&D is already thriving in Canada. Our neighbor to the north has produced several pioneers in A.I. Prominent computer scientists like Geoffrey Hinton, Ph.D., and Yoshua Bengio, Ph.D., started their careers in Toronto laying the groundwork for various A.I. oriented fields. Hinton, an engineering fellow at Google and professor emeritus of computer science at the University of Toronto, is considered a pioneer in training neural networks with multiple layers, a computing technique that provides A.I. with greater recognition capabilities.

Google's DeepMind artificial intelligence team has been based in the UK ever since it was acquired in 2014. However, it's finally ready to branch out -- just not to the US. DeepMind has announced that its first international research lab is coming to the Canadian prairie city of Edmonton, Alberta later in July. A trio of University of Alberta computer science professors (Richard Sutton, Michael Bowling and Patrick Pilarski) will lead the group, which includes seven more AI veterans. As Recode observes, you can chalk it up to a combination of familiarity and political considerations.

Google's high-profile artificial intelligence unit has a new Canadian outpost. DeepMind, which Google bought in 2014 for roughly $650 million, said Wednesday that it would open a research center in Edmonton, Canada. The new research center, which will work closely with the University of Alberta, is the United Kingdom-based DeepMind's first international AI research lab. DeepMind, now a subsidiary of Google parent company Alphabet (goog), recruited three University of Alberta professors from to lead the new research lab. The professors--Rich Sutton, Michael Bowling, and Patrick Pilarski--will maintain their positions at the university while working at the new research office.

The Order of Canada marks its 50th anniversary this year with 99 new appointments on its Canada Day honours list, including renowned figures from the fields of law, government, entertainment and sport, as well as Canadians whose contributions are less widely known. The list includes soccer star Christine Sinclair, television host Alex Trebek, actor Catherine O'Hara and Globe and Mail editorial cartoonist Brian Gable. Three people were named to the highest rank, Companion of the Order of Canada: former Supreme Court Justice Marshall Rothstein, National Arts Centre president Peter Herrndorf and The Prince of Wales. Nineeteen people were named Officers of the Order of Canada, including former spymaster Richard Fadden, hockey player Mark Messier and actor Michael Myers. There were 77 people named as members of the Order, including opera singer Tracy Dahl, historian Bill Waiser, public health nurse Cathy Crowe and Indigenous leader Terrance Paul.

Diverse action costs are an essential feature of many real-world planning applications. Some recent studies have shown that diversity of action costs makes planning more difficult, and that searching using unit action costs can outperform searching the same domain with diverse action costs. In this paper, we provide experimental evidence and theoretical analysis showing that search can also benefit from action cost diversity. We show that on several IPC problems cost diversity has a positive effect (reduces search effort). We then present a theoretical analysis establishing that these positive cases are not accidental. Our main result is a "No Free Lunch" theorem showing that any negative effects of cost diversity are always perfectly counterbalanced by positive effects. Our theoretical analysis also shows that it is advantageous to have a strongly concentrated distribution of solution costs. In many domains, unit costs will give rise to a more concentrated distribution than diverse costs, but we give an example typifying domains in which the opposite is the case.

Modeling causal dependencies often demands cycles at a coarse-grained temporal scale. If Bayesian networks are to be used for modeling uncertainties, cycles are eliminated with dynamic Bayesian networks, spreading indirect dependencies over time and enforcing an infinitesimal resolution of time. Without a ``causal design,'' i.e., without anticipating indirect influences appropriately in time, we argue that such networks return spurious results. By identifying activator random variables, we propose activator dynamic Bayesian networks (ADBNs) which are able to rapidly adapt to contexts under a causal use of time, anticipating indirect influences on a solid mathematical basis using familiar Bayesian network semantics. ADBNs are well-defined dynamic probabilistic graphical models allowing one to model cyclic dependencies from local and causal perspectives while preserving a classical, familiar calculus and classically known algorithms, without introducing any overhead in modeling or inference.