AI/Machine Learning Take Over ... event wrap up

A great opportunity to learn more about machine learning and artificial intelligence from the Research and Technical Services team at Callaghan Innovation at Tuesday evenings event sponsored by Waikato Innovation Park and supported by CultivateIT.

We were live streaming the event and you can find the video on the Waikato Innovation Park Facebook page.

Callaghan Innovation Business Development Manager Jin Rong Zhang kicked off the evening highlighting that the Research and Technology Services team has about 200 scientists based in Christchurch, Wellington and Auckland with expertise across data, IoT, biotechnology, advanced materials and advanced manufacturing, extending an invitation for audience members to connect with her and her colleagues to find out more about the expertise that Callaghan Innovation has to offer.

Jin Rong Zhang then introduced Donal Krouse, Senior Research Scientist – IoT and Data Solutions Group, who has studied pure mathematics and theoretical computational science, and who as data scientist focuses on efficient inference and value optimisation for businesses. Some of the highlights from work he has been involved with include estimating the number of 5 cent coins in circulation, a review of defence spending, sports analytics, and prostate cancer diagnostics.

Donald provided a high-level overview of artificial intelligence and applications of the technology covering a diverse range of needs and opportunities in NZ. Y started off with a picture of an eighteenth-century chess playing machine as an example of “fake intelligence’, as there was apparently a good chess player hidden amongst the cogs, and moved into defining artificial intelligence covering the various levels and providing relevant examples.

The audience heard about futuristic concepts such as artificial super intelligence and artificial general intelligence and then, where we are working at present, the artificial narrow intelligence level where we can make machines do various tasks with an error rate that is better than humans. Donald mentioned that it is important to not only consider the complexity of the task but also efficiency as we work toward artificial general and artificial super intelligence.

Audience members were then asked whether they were familiar with the terms machine learning and deep learning and if there was anyone working on projects applying these concepts. Donald then took us through how machine learning works as a form of data driven programming and the process of “training” where applications are fed data and trained before they operate in a live scenario. Terms such as supervised learning, unsupervised learning and reinforcement learning were defined, and Donald explained that for now many are operating in a supervised learning context.

The need for an enormous amount of data in most cases was reinforced and several applications of machine learning were then discussed including photo tagging, loan approvals, targeting online advertising, speech recognition and language translation, the use of sensors for preventive maintenance and self-driving cars.

Other examples where large amounts of data are not required were then presented including Xero’s first exercise with machine learning, and another initiative Callaghan Innovation was involved with where a neural net was used to accurately enabled efficient inventory management of consumables.

Donald then mentioned Callaghan Innovations publication “Artificial Intelligence – Technology Landscape in NZ” and also referred to the NZ Tech AI Forum’s recent report “Artificial Intelligence – Shaping a Future New Zealand“ as useful reading material when considering where to get started in terms of machine learning and artificial intelligence and the application of these and other emerging technologies.

Google, AWS and IBM Watson and the concept of Artificial Intelligence as a service (AIaaS) were mentioned in terms of approaches to the application of machine learning and artificial intelligence, with Donald pointing out that amongst the keys to a successful artificial intelligence and machine learning projects is taking the time to think about what you are trying to achieve, focusing on the value proposition and to be specific about requirements and constraints.

The concluding Q&A focused on whether data science was in fact an emerging field, as some consider it to be, and the actual history of concepts such as machine learning, deep learning and artificial intelligence, as well as the importance of considering and adjusting for data bias, where we are at on the scale of possible applications of the technology, the likely impact of the Internet of Things, and also where people interested in being involved with initiatives in the areas of machine learning and artificial intelligence can get started.

Kin Lung (KL) Chan, Business Development Manager – IoT and Data Solutions Group, pointed out the importance of staying in the loop around what is happening with emerging technology highlighting the role of forum’s and knowledge sharing initiatives. In the Waikato we have the regular IoT Waikato Future Tech Meetup supported by Waikato Innovation Park and CultivateIT. The July IoT Waikato Future Tech Meetup included Ben Reid of the AI Forum, Shaun Belcher from The Nem.io Foundation talking about Blockchain, Karen Saunders and John Kinghorn presenting the Smart Hamilton strategy as a response to smart cities, and Jesse Armstrong of Vaka Interactiv discussing digital storytelling and AR/VR.

To close out the evening, Novel Gopal, Business Growth Advisor at Waikato Innovation Park, presented the audience with an overview of some of the services available to support small businesses with technology innovation and business growth in the Waikato including accessing funding as well as opportunities to engage students and relevant expertise.

Audience members then enjoyed a bite to eat and drinks whilst networking with the team from Callaghan Innovation and Waikato Innovation Park.

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