Implementing artificial intelligence into your work process can lead to greater efficiencies and more power – provided you get it right.
Most development in a traditional systems environment follows the usual phases -plan, analyse, design, build, test, and deploy, but the AI environment is quite different.
In this event, we’ll be discussing what you need to know if considering implementing an AI solution, including:
- Minimising data bias
- Determining training datasets
- Managing data privacy
- Building from scratch versus adapting publicly available algorithms
This event is part of the program for both the Digital Innovation Festival and the AI Festival.
Venue partner - Zendesk
Ticket price includes drinks, light refreshments and a copy of the event report.
Jonathan Chang - Managing Director, Silverpond
Jonathan is the founder and managing director of Silverpond, a technology consulting company based in Melbourne. Founded in 2005, Silverpond has been working with startups and organisations such as 7-Eleven, Powercor and Australia Post, helping them navigate and deliver solutions across major technological trends such as web, mobile and now machine learning.
Machine learning will touch and transform every industry, and Silverpond is proud to help promote and develop the machine learning industry in Australia by running deep learning workshops, hosting events and conferences, and helping grow the local industry group, Melbourne AI.
Karin Verspoor - Professor, School of Computing & Informations Systems, University of Melbourne
Karin is a Professor in the School of Computing and Information Systems and Deputy Director of the Health and Biomedical Informatics Centre at the University of Melbourne. Trained as a computational linguist, Karin’s current research primarily focuses on extracting information from the biomedical literature and clinical texts using machine learning methods to enable biological discovery and clinical decision support. Karin held previous posts as the Scientific Director of Health and Life Sciences at NICTA Victoria Research Laboratory, at the University of Colorado School of Medicine, and Los Alamos National Laboratory. She spent 5 years in start-ups during the US Tech bubble, where she worked on the precursor to Google’s AdSense software, and helped design an early artificial intelligence system called Webmind.
Soon-Ee Cheah - Data Scientist, Zendesk
Soon-Ee is a Data Scientist with Zendesk and works on using machine learning and artificial intelligence to help businesses connect with their customers. Most recently, Soon-Ee worked on the research and development of Answer Bot, a deep-learning powered product that answers customer queries with relevant knowledge base articles. Prior to joining Zendesk, Soon-Ee was a researcher in microbial bioinformatics and pharmacometrics at the Monash Institute of Pharmaceutical Sciences.
Mark Moloney - GM Big Data Analytics, Telstra
Mark's current focus is on use of AI and machine learning to create commercial value. Projects include virtual agents, use of deep learning to support human agents, and operationalising big data systems to produce customer insights and features to drive AI applications.
Mark's background has been a mix of software engineering and management consulting; the last 5 years in combining software engineering, data science and big data.
He's drawn to hard-to-solve problems that challenge convention, while maintaining a commercial focus on delivery and value.