Combining our efforts in moving the field forward
In recent decades, researchers in Aotearoa New Zealand, particularly the universities, have been carrying out fundamental research in AI, including in both of the high-level research streams of symbolic AI and subsymbolic/computational AI.
All of this fundamental AI research is vitally important as it provides the theoretical and algorithmic base that underpins and powers AI applications.
Among many of these fundamental AI research areas and key applications, Aotearoa New Zealand has been playing an important leadership role in the world in at least the following aspects:
- ML tools such as Weka and R
- Evolutionary learning and optimisation
- Data stream learning/mining
- Image and vision computing applications to primary industry
- Automated design of deep neural network architectures and other deep models
- Feature selection/construction and dimensionality reduction
- Dynamic scheduling and combinatorial optimisation
- Indigenous data sovereignty
- Oversight of government uses of AI and algorithms
- Oversight of harmful content on social media
Examples of fundamental research areas
Subsymbolic AI (mainly machine learning)
Deep learning (a subdomain of machine learning)
Applications have been focused on primary industry such as agriculture, aquaculture and open ocean/blue economy, environmental/earth science, geology and disaster management, chemical and material science and engineering, biological and biomedical sciences, as well as marine biology and genomics, public health and medicine, neural science/psychology and drug discovery, cybersecurity, biosecurity, food and water resources, networking and the Internet of Things (IoT), tourism and knowledge travel, sustainable and renewable energy, finance and economics including GDP and CPI prediction, tax, banking, and insurance, and linguistics and languages including natural language processing of te reo Māori.