***** The date of the AGM has been changed to Tuesday January 29 *****
The 2019 Annual General Meeting (AGM) for the IEEE Winnipeg Section will be held on Tuesday January 29 from 6-9 pm at the Best Western Plus Airport Hotel. All local IEEE members are invited and encouraged to attend this event and a buffet dinner will be provided. Section highlights from 2018 will be shared and the 2019 Executive Committee will be elected. The minutes from last year’s AGM and the agenda for the business portion of the meeting are available below.
The evening’s keynote presentation will be delivered by Dr. Mark Alexiuk, CTO of Sightline Innovation Inc:
Title: Applied Machine Learning – A Prairie Perspective
Bio: Mark Alexiuk is a graduate of the Electrical and Computer Engineering Program (BSc, MSc, PhD) at the University of Manitoba.
Throughout his career he has worked with Manitoban companies, including those in the fields of medical devices (IMRIS) and identity/information services (IMT).
Currently, as CTO of Sightline Innovation, he leads a 24 person developer team to provide a data trust environment and enterprise applied machine learning solutions for challenging problems in manufacturing, healthcare and agriculture. His research interests include exploratory data analysis, pattern recognition and applied machine learning.
Abstract: Artificial intelligence (AI) has matured over many decades. Early technologies included rule-based systems and perceptrons. Significant effort is currently being invested in reinforcement learning, deep learning and generative adversarial networks. Superhuman mastery has been obtained in selected areas (checkers, chess, Jeopardy, Shogi), practical applications have been deployed to the mass market (machine translation) while artificial general intelligence (AGI) remains elusive. Software scalability, distributed but connected devices, inexpensive storage and computation together amplify into a seemingly imminent and immense power of AI that excites the imagination (universal prosperity and social good!) while simultaneously engendering fear (loss of control; loss of livelihood through automation!). Tempering these thoughts are observations: AI is yet brittle and can be fooled; technical systems have residual complexity; goal setting has its own challenges; emergence can be observed but not necessarily planned. This talk explores selected opportunities to apply technology and frankly discusses challenges in data acquisition, annotation, optimization and robustness, for applications in manufacturing, healthcare, and agriculture.
Please follow and like us:
