Edmonton
Google's AI powerhouse DeepMind is opening its first international lab in Canada
Although it was bought by Google in 2014, AI firm DeepMind has always been true to its British roots -- expanding its offices in London, working closely with UK institutions like the NHS, and even teaching in the country's universities. Now, though, the company is opening its "first ever international AI office" -- in Edmonton, Canada. It's a natural fit for DeepMind, which has close links with the AI research community in Edmonton's University of Alberta. The company says nearly a dozen Alberta grads have joined its ranks, and the firm has sponsored the university's machine learning lab for a number of years. Richard Sutton, professor of computing science at Alberta, was also DeepMind's first outside advisor, and will head up the company's new base along with colleagues Michael Bowling and Patrick Pilarski.
Non-Intrusive Signature Extraction for Major Residential Loads
Dong, M., Meira, P. C. M., Xu, W., Chung, C. Y.
The data collected by smart meters contain a lot of useful information. One potential use of the data is to track the energy consumptions and operating statuses of major home appliances.The results will enable homeowners to make sound decisions on how to save energy and how to participate in demand response programs. This paper presents a new method to breakdown the total power demand measured by a smart meter to those used by individual appliances. A unique feature of the proposed method is that it utilizes diverse signatures associated with the entire operating window of an appliance for identification. As a result, appliances with complicated middle process can be tracked. A novel appliance registration device and scheme is also proposed to automate the creation of appliance signature database and to eliminate the need of massive training before identification. The software and system have been developed and deployed to real houses in order to verify the proposed method.
Research Challenges of Digital Misinformation: Toward a Trustworthy Web
Ciampaglia, Giovanni Luca (Indiana University) | Mantzarlis, Alexios (Poynter Institute) | Maus, Gregory (Indiana University) | Menczer, Filippo (Indiana University)
The deluge of online and offline misinformation is overloading the exchange of ideas upon which democracies depend. Fake news, conspiracy theories, and deceptive social bots proliferate, facilitating the manipulation of public opinion. Countering misinformation while protecting freedom of speech will require collaboration across industry, journalism, and academia. The Workshop on Digital Misinformation — held in May 2017 in conjunction with the International Conference on Web and Social Media in Montréal, Québec, Canada — was intended to foster these efforts. The meeting brought together more than 100 stakeholders from academia, media, and tech companies to discuss the research challenges implicit in building a trustworthy Web. Below we outline the main findings from the discussion.
AAAI News
Recently, AAAI coordinated and The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) cosigned a statement with CRA, and the Thirty-First Conference on Innovative Applications of Artificial expressing concern about the proposed Intelligence (IAAI-19), will be held in Honolulu, Hawaii, USA, January tax bill and its ramifications for graduate 27 - February 1, 2019. The technical conference will continue its student stipends. Other organizational 3.5-day schedule, preceded by the workshop and tutorial programs.
Reactive Reinforcement Learning in Asynchronous Environments
Travnik, Jaden B., Mathewson, Kory W., Sutton, Richard S., Pilarski, Patrick M.
The relationship between a reinforcement learning (RL) agent and an asynchronous environment is often ignored. Frequently used models of the interaction between an agent and its environment, such as Markov Decision Processes (MDP) or Semi-Markov Decision Processes (SMDP), do not capture the fact that, in an asynchronous environment, the state of the environment may change during computation performed by the agent. In an asynchronous environment, minimizing reaction time---the time it takes for an agent to react to an observation---also minimizes the time in which the state of the environment may change following observation. In many environments, the reaction time of an agent directly impacts task performance by permitting the environment to transition into either an undesirable terminal state or a state where performing the chosen action is inappropriate. We propose a class of reactive reinforcement learning algorithms that address this problem of asynchronous environments by immediately acting after observing new state information. We compare a reactive SARSA learning algorithm with the conventional SARSA learning algorithm on two asynchronous robotic tasks (emergency stopping and impact prevention), and show that the reactive RL algorithm reduces the reaction time of the agent by approximately the duration of the algorithm's learning update. This new class of reactive algorithms may facilitate safer control and faster decision making without any change to standard learning guarantees.
Another Fortune 500 Company to Conduct Pilot Evaluation of OneSoft--s Machine Learning Platform
Edmonton, Alberta, Feb. 07, 2018 (GLOBE NEWSWIRE) -- OneSoft Solutions Inc. (the --Company-- or --OneSoft--) (TSX-V:OSS, OTC:OSSIF)--is pleased to announce that its wholly owned subsidiary, OneBridge Solutions, Inc. (--OneBridge--), has entered into a Pilot Program agreement with another U.S.-based, Fortune 500 natural gas, oil and petrochemical company (the --Client--). The Client, whose operations include natural gas gathering, treating, processing, transportation and storage, primarily in the United States, will evaluate OneBridge--s Cognitive Integrity ManagementTM (--CIM--) SaaS solution.
Robot judges? Edmonton research crafting artificial intelligence for courts
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 predicts schizophrenia with 74% accuracy - HEALTH & SCIENCE - Jerusalem Post
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.
AI Arrives in Canada: Will Prosperity Follow? EE Times
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."