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Data Science is Where to Find the Most AI Jobs and Highest Salaries - AI Trends

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Jobs in data science grew nearly 46% in 2020, with salaries in the range of $100,000 to $130,000 annually, according to a recent account in TechRepublic based on information from LinkedIn and LHH, formerly Lee Hecht Harrison, a global provider of talent and leadership development. Related job titles include data science specialist and data management analyst. Novacoast, which helps organizations build a cybersecurity posture through engineering, development, and managed services. Founded in 1996 in Santa Barbara, the company has many remote employees and a presence in the UK, Canada, Mexico, and Guatemala. The company offers a security operations center (SOC) cloud offering called novaSOC, that analyzes emerging challenges.


Future of distracted driving technology makes Edmonton pitch CBC News

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An Australian-based technology firm that uses artificial intelligence to catch distracted drivers made a pitch to an Edmonton conference on Friday. Acusensus presented its automatic camera enforcement technology at the International Conference on Urban Traffic Safety. Founded in early 2018, the company made international headlines with a pilot program in Australia earlier this year. The Acusensus camera system is mounted on the side or above the road, like photo radar. But unlike photo radar, the system takes high-resolution pictures of every passing car.


Differentially Private Contextual Linear Bandits

Neural Information Processing Systems

We study the contextual linear bandit problem, a version of the standard stochastic multi-armed bandit (MAB) problem where a learner sequentially selects actions to maximize a reward which depends also on a user provided per-round context. Though the context is chosen arbitrarily or adversarially, the reward is assumed to be a stochastic function of a feature vector that encodes the context and selected action. Our goal is to devise private learners for the contextual linear bandit problem. We first show that using the standard definition of differential privacy results in linear regret. So instead, we adopt the notion of joint differential privacy, where we assume that the action chosen on day t is only revealed to user t and thus needn't be kept private that day, only on following days. We give a general scheme converting the classic linear-UCB algorithm into a joint differentially private algorithm using the tree-based algorithm. We then apply either Gaussian noise or Wishart noise to achieve joint-differentially private algorithms and bound the resulting algorithms' regrets. In addition, we give the first lower bound on the additional regret any private algorithms for the MAB problem must incur.


Small investments can leverage big data for construction sector - constructconnect.com - Journal Of Commerce

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If there's one thing Rory Armes wants audiences at Buildex Calgary to understand, it's the idea that even a small investment in big data and predictive artificial intelligence (AI) can provide actionable insights and pay solid dividends. Armes is CEO of Eight Solutions Inc., a company built on the idea that any business, large or small, can benefit from big data analytics and predictive AI. Its proprietary solution is Cumul8, a cloud-based Internet of Things platform that accepts a wide range of data from any type of monitoring device, then teases valuable conclusions from that data. "People are sometimes left with the notion that they either go all-in on costly predictive AI systems, or stay out of it altogether," says Armes. "Those unrealistic polar choices leaves them comatose." He aims to demystify the concepts around big data in a construction context, explain predictive AI and show how it can quickly demonstrate value.


Sign of the times: Another powerhouse FI partners with UAlberta scientists

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From artificial intelligence (AI) to data science to mathematical finance, ATB Financial has its eyes on the future for its clients, Albertans and the tech sector. Following a red hot 2017, with multiple announcements of collaborations and partnerships, University of Alberta scientists have just received another green stamp of approval from the financial sector with the announcement of a new collaboration with ATB Financial. In a four-year partnership that will see an infusion of nearly a million dollars ($940,000) into various research projects and student internships, ATB's data scientists are working with University of Alberta scientists, collaborating to create customer-centric experiences that redefine the value a financial institution can deliver. Three initial projects are underway. They are focused on real-time fraud detection, predictive analytics--to identify key moments in customer or business journey--that are focused on customer support and a tailored recommendation system similar to those ubiquitous with Amazon.


Data governance in the digital age: Canada's great big data map

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Big data is usually associated with Facebook, not farming. But as Ian MacGregor writes, harnessing data from agriculture, mining, forestry and other primary industries could be the next big economic opportunity in Canada -- if we do it right. This is part of a series of excerpts from essays commissioned by the Centre for International Governance Innovation. He used the data he collected to create what he called the "great map"-- and in the process unlocked the commercial potential of North America. Big data is as important to Canada in the 21st century as Thompson's topographical data was in the 19th century.


Non-Intrusive Signature Extraction for Major Residential Loads

arXiv.org Artificial Intelligence

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.


Another Fortune 500 Company to Conduct Pilot Evaluation of OneSoft--s Machine Learning Platform

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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.


Qualities of a Well-Built ETL Tool

@machinelearnbot

Hayden has written content for some of the biggest logos in the Silicon Slopes (Utah) and works exclusively as a freelance writer . A graduate of the University of Utah, Hayden spends his free time enjoying every winter sport the Rocky Mountains have to offer! So you've determined that your use case doesn't merit the time and energy required to create a customSQL solution, and you're ready to pick an ETL tool to help you get what you need out of your data. The problem is, you're not sure how to tell if you've found a tool that will meet your needs. That's where this list comes in.