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Responsible AI in Practice: Openness, Transparency and...Paint Stripping (ETIG Event)

  • Date: Fri, 16 Aug 2019, 2:00 pm - 4:00 pm
  • Location: Eleanor Harrald Building, Lecture Theatre, Frome Road, Adelaide

As part of our AI Emerging Technology Interest Group, the Australian Institute for Machine Learning is delighted to be bringing data specialist, speaker and author, Ellen Broad, to Adelaide.

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Ethics of Artificial Intelligence

  • Date: Thu, 15 Aug 2019, 5:30 pm - 8:00 pm
  • Location: Lot Fourteen, Eleanor Harrald Building, Frome Road, Adelaide

AI is one of the most important topics of today. Developments in AI will disrupt the economy and the world in ways not seen since the industrial revolution. As AI continues to permeate every aspect of our lives, we must ask ourselves:

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Analysing MRI brain images - current and future methodology

  • Date: Thu, 15 Aug 2019, 1:30 pm - 2:30 pm
  • Location: Barr Smith South 2051

The Australian Institute for Machine Learning (AIML) invites you to hear from special guest visiting Professor Mark Jenkinson, Head of the Structural Modelling and Analysis at the , and Professor of Neuroimaging with the 成人大片 and SAHMRI.  

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Farming of the future: revolutionising agriculture through AI

  • Date: Wed, 14 Aug 2019, 5:30 pm - 6:30 pm
  • Location: Adelaide City Library, Rundle Place, 77-91 Rundle Mall

Australia has a rich agricultural industry. To continue to be competitive on a global-scale while also meeting the needs of a growing global population (effectively putting the sector under pressure), farmers are looking to AI. 

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Machine Learning and the Challenge of Innovating with Australian Businesses

  • Date: Thu, 1 Aug 2019, 6:00 pm - 8:00 pm
  • Location: The Precinct, Startup Stadium Level 2, 315 Brunswick St 路 Fortitude Valley

This month at Queensland AI it is our pleasure to welcome Dr. Paul Dalby from The Australian Institute for Machine Learning at the 成人大片.

Paul will explore the challenges of working with Australian companies to innovate, and will present his ideas on how they could structure themselves to be more responsive to the opportunities offered by machine learning technologies.

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