The Truth About Artificial Intelligence
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This document summarizes key findings from the 2018 AI Index Annual Report on the state of artificial intelligence. It finds that AI startups and funding have increased significantly in recent years. For example, active AI startups increased 113% from 2015 to 2018 while VC funding for US AI startups increased 350% from 2013 to 2017. It also discusses growing interest in AI courses and the adoption of AI across different industries. However, it notes challenges like the need for more diversity in AI and ensuring technologies are developed and applied responsibly.
The Truth About Artificial Intelligence
- 1. The truth about Artificial Intelligence @Jon_Whittle@ MONASH INFORMATION TECHNOLOGY PROFESSOR JON WHITTLE | Dean
- 2. From January 2015 to January 2018, active AI startups increased 113%, while all active startups increased 28%. VC funding for U.S. AI startups increased 350% from 2013 to 2017 Meanwhile, VC funding for all active startups increased 100%. MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 3. South Korea and Taiwan have experienced the most growth, 5x growth since 2004 MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 4. From 2015 to 2017 the number of job openings requiring Deep Learning increased 34x MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 5. UC Berkeley's 2017 introductory ML course has 6.8x as many students as it had in 2012 MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 6. Combined AI + ML 2017 course enrollment at Tsinghua University was 16x that of 2010 MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 7. “We found widespread adoption of different AI technologies across sectors, functions, and geographies around the world; about half of all companies had embedded AI into a corporate business process. However, most had not yet adopted the complementary practices necessary to capture value from AI at scale.” Michael Chui, McKinsey & Company and the McKinsey Global Institute Taken from: AI Index Annual Report 2018
- 8. MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 9. MONASH INFORMATION TECHNOLOGY Taken from: AI Index Annual Report 2018
- 10. “Organizations tend to incorporate AI capabilities in functions that provide the most value within their industry. For example, Financial services has heavily incorporated AI in Risk, while Automotive has done so in Manufacturing, and Retail has done so in Marketing / sales.” AI Index Annual Report 2018
- 11. 0 1 2 3 4 5 6 Australia Canada Germany France Singapore South Korea UK $Bn (AUD) AI Investment over next 5 years Alibaba: $15Bn Softbank: up to $100Bn Amazon: $16Bn Alphabet: $13Bn The Chinese government is creating a $22Bn AI market in China to ensure that China leads the world in AI by 2030. US DARPA announces $3Bn+ investment plan to overcome limitations on AI technology. Source: various
- 12. A brief history of AI’s ups and downs Source: https://towardsdatascience.com/history-of-the-first-ai- winter-6f8c2186f80b
- 13. Deep learning Big data Computing power “We really need to temper our expectations and stop hyping deep learning capabilities. If we don’t, we may find ourselves in another AI Winter.” Thomas Nield, https://hackernoon.com/is-another-ai-winter-coming-ac552669e58c
- 14. “The best thing you can do is be specific about the problem you are trying to solve and understand its nature. If you want to categorize text messages, you probably want to use Naive Bayes. If you are trying to optimize your transportation network, you likely should use Discrete Optimization.” Thomas Nield, https://hackernoon.com/is-another-ai-winter-coming- ac552669e58
- 15. What is AI anyway?
- 17. Examples vs rule-based approach See Cassie Kokyrnov’s blog https://hackernoon.com/why-ai-is-here-to-stay- 9c75b1868b9b?utm_source=The+Crunch&utm_campaign=2db03e5079- THE_CRUNCH_55_COPY_01&utm_medium=email&utm_term=0_aa18ea5b4e-2db03e5079- 233747585
- 18. Source: Joelle Pineau ICSE 2019 keynote, https://2019.icse-conferences.org/details/icse-2019-Plenary-Sessions/20/Building-Reproducible-Reusable-and-Robust-Machine-Learning-Software
- 20. AI in Law Enforcement Smart farming https://static.independent.co.uk/s3fs- public/thumbnails/image/2017/06/25/18/minority-report.jpg?w968https://tr4.cbsistatic.com/hub/i/r/2018/02/12/e0a1a532-03d1-4932-aebb- ead6d88caae5/resize/1200x/b88a9dad26a46f674125d8d8816d0e8d/istock-913641932.jpg
- 21. AI in Healthcare Smart farming https://media.apnarm.net.au/media/images/2019/02/24/b881821867z1_20190224085842_000g5i1earro2-0- cfa3lk6nbues9touur2_ct1880x930.jpg
- 22. AI in sustainable development Smart farming https://cdn.vox-cdn.com/thumbor/Twe13cA0ZjVEJHTC- RwU2vSnfcA=/0x243:2500x2118/1220x813/filters:focal(0x243:2500x2118):format(webp)/cdn.vox- cdn.com/uploads/chorus_image/image/46679984/shutterstock_150559442.0.0.jpg
- 23. AI in transport Smart farming emotiv.com
- 24. Caveats
- 26. Smart farming https://automatedsmarthome.files.wordpress.com/2015/11/image.jpg?w=1024 Diversity AI Index Annual Report 2018 80% of AI professors are male On average, 80% of professors from UC Berkeley, Stanford, UIUC, CMU, UC London, Oxford, and ETH Zurich are male
- 28. Smart farming Responsible AI functionality, cost, safety, security, privacy Inclusion, diversity, responsibility, transparency, well-being IT now Responsible IT
- 30. “AI promises to be the most disruptive class of technologies during the next 10 years One of the biggest aggregate sources for AI- enhanced products and services acquired by enterprises between 2017 and 2022 will be niche solutions that address one need very well. Business executives will drive investment in these products, sourced from thousands of narrowly focused, specialist suppliers with specific AI- enhanced applications.” John-David Lovelock, Gartner research vice president
- 31. Top tips • AI is good at specific tasks not general ones • AI is good when 100% accuracy isn’t necessary • Know what problem you are trying to solve • Do you have the right data? • Do you know which AI technique to apply? • Be responsible in your application of AI • Automation vs AI • Applying AI requires expertise