AI is expected to be the next revolution in computing with broad commercial applications.

This has resulted in a significant amount of private investment flowing into the industry with funding in ANZ growing by 70% CAGR to reach $48mn.

For many years, the term ‘artificial intelligence’ (AI) conjured up something out of science fiction; but in recent years, powerful advances in computing technology have unleashed a transformative wave of new technical capabilities and consequently, a large number of valuable commercial applications. Many experts see AI as a revolution similar in impact to the shift from manual labour to machine automation, and the rise of software, with AI being the next logical extension – from programmed, rule-based software which dramatically lowered the cost of replicating and automating processes, to intelligent algorithms which self-teach and self-improve to surpass human capabilities in a range of domains. 

Contents

Key takeaways

Background

• VHA-TPG merger announcement
• ACCC statement of issues for proposed TPG-VHA merger
• TPG ceases mobile network deployment
• ACCC Opposition and VHA Federal Court Proceedings

Key takeaways

Why focus on AI?

The Australia-New Zealand AI Investment Landscape

• Australia and New Zealand have some strong AI fundamentals – but face ongoing challenges around talent affordability, access to data and investment
• Funding to local AI startups has increased dramatically over the last five years
• Local AI startup funding has been concentrated in the early stages
• AI startup funding has been concentrated in verticals like Internet of Things, Industrials, Life Sciences & Healthtech
• The largest local raises are relatively small by international standards – and dominated by a small set of investors

ANZ’s top 10: The coolest local AI startups

• Company profiles
  • Hyper Anna
  • Black.ai
  • Soul Machines
  • Flurosat
  • Akin
  • Baraja
  • Curious Things
  • Gameface.ai
  • Presagen
  • Seemode

Deep dive: AI policy

• International public policy
• Industry-led policy
• New Zealand
• Australia

Appendix A: What is AI?

• The history of AI
• Narrow AI versus general AI
• AI: Sorting the hype from the reality
• AI Glossary

Appendix B: Deep dive on US-China competition for AI leadership

• United States
• China

Appendix C: Australia’s Innovation Strategy

Appendix D: Country-level approaches to AI policy

List of charts/tables

Figure 1. Annual VC funding of US startups, AI versus total, 1995-2017

Figure 2. Comparative number of research papers published on deep learning, by country

Figure 3. Number of accepted & submitted papers by affiliated country, 2018 AAAI conference

Figure 4. Top 10 regions by NIPS 2017 Publication Index

Figure 5. New Zealand AI ecosystem map

Figure 6. Total funds raised by self-identified AI startups, Australia and New Zealand, 2014-18

Figure 7. Funds raised by ANZ AI Startups, by stage, 2014-18

Figure 8. Total funds raised by stage for ANZ AI startups, 2014-18

Figure 9. Number of investments in AI ANZ startups, 2014-19, by investor type

Figure 10. Verticals coinciding with AIML in ANZ startups, 2014-19

Figure 11. Total funds raised by ANZ AI startups with last round type, 2014-19

Figure 12. Most active investors, by number of investments in AI ANZ companies, 2014-19 (showing only 2+ investments)

Figure 13. Total value raised in disclosed funding rounds, by company, 2014-2019

Figure 14. Sector focus and applications: profiled startups

Figure 15. Overview of national AI strategy announcement dates

Figure 16. Key developments by jurisdiction in AI policy, 2014-19

Figure 17. Timeline of AI reaching human-equivalent performance across narrow tasks

Figure 18. Annual AI-related papers published per year globally

Figure 19. Performance of best-in-class AI systems against humans

Figure 20. AI expert predictions on timeline for matching human performance

Figure 21. Gartner Hype Cycle, August 2018

Figure 22. Industrial applications of AI

Figure 23. CB Insights’ AI 100 (outstanding AI startups, 2019)

Figure 24. AI gains by country through to 2030

Figure 25. AI-related patent publications, China vs. US, 2013-17

Figure 26. Field-weighted citation impact of AI authors by region, 1998-2016

Figure 27. Number of active US-based startups developing AI systems

Figure 28. Annual VC investment in US-based AI startups, across all stages