A Future Powered by Artificial Intelligence
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A FUTURE POWERED BY ARTIFICIAL INTELLIGENCE Lawrence Burns, Investment Manager. First Quarter 2017 THIS PAPER IS INTENDED SOLELY FOR THE USE OF PROFESSIONAL INVESTORS AND UK INTERMEDIARIES AND SHOULD NOT BE RELIED UPON BY ANY OTHER PERSON. IT IS NOT INTENDED FOR USE BY RETAIL CLIENTS. – A Future Powered by Artificial Intelligence Baillie Gifford IMPORTANT INFORMATION AND RISK FACTORS The views expressed in this article are those of Important Information Hong Kong Lawrence Burns and should not be considered as advice or a recommendation to buy, sell or hold a particular Baillie Gifford Asia (Hong Kong) Limited investment. 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Important Information South Africa Baillie Gifford Overseas Limited is registered as a Foreign Financial Services Provider with the Financial Services Board in South Africa. Cover Image: AlphaGo press conference, South Korea, March 2016. Calton Square, 1 Greenside Row, Edinburgh EH1 3AN © Getty Images AsiaPac. Telephone +44 (0)131 275 2000 www.bailliegifford.com A Future Powered by AI 25629 0317.indd Copyright © Baillie Gifford & Co 2015. Ref: 25629 INS AR 0323 First Quarter 2017 Important Information North America Baillie Gifford International LLC is wholly owned by LAWRENCE BURNS Baillie Gifford Overseas Limited; it was formed in Delaware in 2005. It is the legal entity through which Investment Manager Baillie Gifford Overseas Limited provides client service and marketing functions in America as well as some marketing functions in Canada. Baillie Gifford Overseas Limited is registered as an Investment Adviser with the Lawrence graduated BA in Geography Securities & Exchange Commission in the United States from the University of Cambridge in of America. 2009. He joined Baillie Gifford the same year and has spent time working Potential for Profit and Loss in both the Emerging Markets and All investment strategies have the potential for profit and UK Equity Departments. Lawrence loss. Past performance is not a guide to future returns. is a co-manager of the International Concentrated Growth strategy as Stock Examples well as a member of the EAFE Alpha Portfolio Construction Group. He is Any stock examples and images used in this article are involved in both listed and unlisted not intended to represent recommendations to buy or sell, investing and travels extensively neither is it implied that they will prove profitable in the researching his particular interest in future. It is not known whether they will feature in any how pervasive technology and China future portfolio produced by us. Any individual examples are changing our world. will represent only a small part of the overall portfolio and are inserted purely to help illustrate our investment style. This article contains information on investments which does not constitute independent research. Accordingly, it is not subject to the protections afforded to independent research and Baillie Gifford and its staff may have dealt in the investments concerned. All information is sourced from Baillie Gifford & Co and is current unless otherwise stated. The images used in this article are for illustrative purposes only. 3 – A Future Powered by Artificial Intelligence A FUTURE POWERED BY ARTIFICIAL INTELLIGENCE BY LAWRENCE BURNS Andrew Ng, Baidu’s Chief Scientist*, plays a game with his friends. The object of the game is to come up with industries that you think won’t be transformed by Artificial Intelligence (AI). He admits he isn’t very good at this game, struggling to get much beyond the answer of his hairdresser. For him, AI is the new electricity and just like electricity it has the potential to transform industries from agriculture to healthcare. This is not the distant future, but an outlook for the next ten years. For Robin Li, Baidu’s CEO, this means the age of mobile internet is coming to an end. Next will come the age of AI. His view also echoes that of Google’s CEO, Sundar Pichai: that we will move from a “mobile first to an AI first world”. Indeed, there appears to be a growing consensus that the internet and computing could be about to enter a distinct new phase. 4 * Andrew Ng has left Baidu subsequent to the initial publication of this article. First Quarter 2017 data. Rather than trying to examine because they specialise in doing a samples of information with preset large number of simple calculations rules, computers are now powerful in parallel. Overall, computational enough to examine complete data sets performance in deep learning has WHY NOW? and observe whatever patterns might improved a staggering fiftyfold in exist within them. With the advent of just three years. unsupervised learning, this data does not even need to be labelled to allow The proliferation of the internet, the computer to make sense of it. particularly on mobile devices, has led AI has been in development for Deep learning is enabling remarkable to an explosion in the data necessary to over sixty years. During this time, improvements in machine translation, feed deep learning algorithms. In 2016, it has gone through several periods natural language recognition and it was observed that more data was of excitement. In the past, there was computer vision. created in the previous two years than considerable focus on looking at how in the whole of human history. This human experts behaved and then Moore’s law suggests that processing matters because today’s artificial mind codifying those practices as rules power doubles every two years, but is still rather dull. A human brain needs into a computer. In contrast, progress other improvements in computing only a dozen images of dogs and cats today is being driven by a subset of have actually enabled far greater to begin to distinguish between them. machine learning called deep learning. progress. Cloud computing lowered An artificial mind requires thousands Deep learning involves feeding data the cost, while a shift from using of examples. If AlphaGo had only to neural networks crudely modelled computer processing units (CPUs) been able to practice as much as Lee on how we think the human brain to graphics processing units (GPUs) Sedol, Sedol would have annihilated might work and using algorithms to has sped up deep learning by 10-20x. his artificial opponent. More data is 5 have the computer learn from that GPUs are well suited to deep learning creating smarter machines. – A Future Powered by Artificial Intelligence NATURAL LANGUAGE RECOGNITION The most relevant near-term application of deep learning is natural language recognition. This has the potential to change how we interact with the internet and therefore how By 2019 half of all Baidu every internet company interacts with its users. search queries will come Li believes this represents the third era of the internet. The first was the through speech and desktop era, with keyboards as the input device. The second was the image search. mobile internet with touch screen input. Li believes the mobile internet era is now coming to an end, replaced by the AI era with natural language recognition as the input device. The application of deep learning to natural language recognition has fuelled significant progress. Error rates have fallen from over 15% in early 2015 to below 4% today. Moreover, a Stanford study using Baidu’s Deep Speech 2 recently demonstrated that speech recognition was 3x faster in English and 2.8x faster in Mandarin than using a touch screen.