主宰代的兩大主題

1、10 January 2020GlobalEQUITIESMSCI China Massive shift towards technologyMSCI Chinas Index Weight as of 201940%What caught my eye? v.123Key points The 2020s are likely to be the key period in evolution of AI & blockchain. AI might end work, blockchain might end money; both will change politics. Progr

2、ess depends mostly on data & capital. China has both in abundance.Two themes will dominate 2020s35%30%25%20%15%10%5%TechnologyConsumersIndustrialsIncrease in Index WeightEnergy /MaterialsFinancials/RealEstateDecrease inAI & blockchain disrupting both real world & cloud of financeTelecommunication0%I

3、ndex Weight0%10%20%30%40%50%MSCI Chinas Index Weight as of 2009Source: Factset; MSCI; Macquarie Research, January 2020China Technology Basket Performance18017016015014013012011010090Dec-16 Feb-17 Apr -17 Jun-17 Aug -17 Oct-17 Dec-17 Feb-18 Apr -18 Jun-18 Aug -18 Oct-18 Dec-18 Feb-19 Apr -19 Jun-19 A

4、ug -19 Oct-19Dec-1980China tech nology baske t vs. MSCI ChinaChina tech nology baske t vs. MSCI Asia ex Jap anSource: Factset; MSCI; Macquarie Research, January 2020China Intangible Assets (% of GDP)RMB mnAs % of GDPTwo ideas are likely to dominate the next decade: (a) artificial intelligence (AI);

5、and, (b) blockchain. These will upend every human endeavour, from self-driving cars and robotics to central banks (CB), allowing some countries and companies to leapfrog others. Putin was right to argue that these technologies could allow some to gain the world dominance. On the other hand, instead

6、of centralizing and dominating, the same technologies might liberate and de-centralize. We view this outcome as less likely (at least for a while), but there is a promise of freedom, as technologies are politically agnostic and can be used for good as for evil.Although Kurzweils prediction that by 2

7、029, AI will achieve human-level of intelligence and pass Turing test, will prove to be optimistic, the pace of progress is accelerating beyond single input-output outcomes or constrained games. AI has already exceeded human capabilities in more complex tasks, including Go (the pinnacle of human gam

8、es) and poker. Recently Elon Musks AI venture beat human champions of Dota2 and won several war games that require complex strategies and co-operation. The same applies to language processing, where AI has already bypassed us. Super computers are now being miniaturised, requiring less power while de

9、livering human brain processing. There is also a possibility ofquantum computing taking-off by the end of the decade. While true flexibility and6,0 00,0005,0 00,0004,0 00,0003,000,0002,0 00,0001,0 00,000-199 5200 0200 8201 39.0%8.0%7.0%6.0%5.0%4.0%3.0%2.0%1.0%0.0%memory implants need to await the 20

10、30s-40s, the 2020s will witness major progress. AI does not need to be better than us, it just needs to be good enough.AI and blockchain technologies also have the capacity to disrupt the cloud of finance, just as AI, automation and 3D printing are disrupting the physical world. There are good reaso

11、ns why everyone from BIS, Fed and ECB to China and Russia, banks (e.g. JP Morgan) and tech giants (e.g. Facebook) are all exploring topics related to cryptocurrencies and blockchain technologies. It is as much of a threat as it is an opportunity. Blockchain can massively simplify transactions while

12、eroding banking fee pool. It could also potentially either strengthen CBs orInta gible InvestmentInta gible Investment as % of GDPSource: Wu, Hao; Macquarie research, January 2020InsideTOC o 1-1 h z u HYPERLINK l _TOC_250002 The decade that will remake the world2 HYPERLINK l _TOC_250001 China econom

13、y & market at the cutting edge13 HYPERLINK l _TOC_250000 Appendices19AnalystsMacquarie Capital LimitedViktor Shvets +852 3922 3883 HYPERLINK mailto:viktor.shvets viktor.shvetsPerry Yeung +852 3922 4769 HYPERLINK mailto:perry.yeung perry.yeungbypass them entirely. While in the short term, it is unlik

14、ely that authorities will permit rapid proliferation of currencies outside their control, it is unclear such powerful forces could be ultimately contained within national borders.China faces no limitations on data harvesting or capital allocationChina is razor focused on threats and opportunities ar

15、ising from these technologies. Digital RMB is already closer to fruition than most others while Chinas AI spending continues to lead the world. Although it relies on Western intellectual breakthroughs, the progress over the next decade is likely to be more dependent on availability of capital and da

16、ta, rather than new discoveries. Unlike the West, China has no limitations in harnessing these prerequisites. Chinese companies are already challenging all aspects of the new world from hardware to software, robotics to surveillance. While most EM and DM equity markets remain stuck in conventional b

17、usinesses (from banks, telcos, commodities to utilities), China is witnessing an explosion of leading-edge themes. Only the US has a similar vitality. We think investors will be better off buying into the future rather than fine- tuning stimuli, discount rates and valuations. This is not the time fo

18、r conventional.Please refer to page 26 for important disclosures and analyst certification, or on our website HYPERLINK /research/disclosures /research/disclosures.AI & blockchain will change the worldWhile singularity might arrive in 2029, the progress is likely to be considerable through2020sAI do

19、es not need to be better than us, it just needs to be goodenough andThe decade that will remake the worldThe development of AI raises colossal opportunities and threats that are difficult to predict nowthe one who becomes the leader in this sphere will be the ruler of the world, - Vladimir Putin, 20

20、17The year 2029 is the consistent date I have predicted, when an artificial intelligence will pass a valid Turing test achieving human level of intelligenceI have also set the date of 2045 for singularity which is when humans will multiply our effective intelligence a billion fold, by merging with t

21、he intelligence we have created, - Ray Kurzweil, 2018The economics of money is back in the limelight. Even five years ago, I cannot imagine that a lecture on money and the payment system could have been a subject for an event like todays Agustin Carstens, General Manager, Bank of International Settl

22、ements (BIS), Princeton University Lecture, Dec 5, 2019Ray Kurzweil, US academic, inventor and futurologist, has an enviable track record of predicting timing of various technological breakthroughs. In his books (The Age of Intelligent Machines, 1990, The Age of Spiritual Machines, 1999 and Singular

23、ity is near, 2005) he offered many predictions, from when machines will be able to beat human chess champions and when personal computers will appear in various shapes (including wearables), preferred method of internet proliferation (i.e. he suggested wireless will dominate) to when machines will p

24、ass the Turing test (i.e. becoming undistinguishable from humans). Remarkably, a reasonably large proportion of his predictions came true. Hence, one needs to take his predictions seriously.While it is not clear whether computers, machines or AI would ever exist, feel or love, in terms of computatio

25、nal power, patterns recognition and decision-making that is largely free of human inconsistencies and phobias, AI is already matching and often exceeding human capabilities.In 1990, Kurzweil predicted that by 2000 computers will beat humans in the game of chess. This was achieved by the IBMs Deep Bl

26、ue in 1997. In 2011, IBMs Watson used advanced language processing to win against all human opponents at Jeopardy, and while Google expected its AlphaGo computer to take decades to beat humans in the most complex game ever invented (i.e. Go), it was achieved in less than five years (2016). Even more

27、 impressively, Libratus (an AI bot) in 2017 defeated four of the worlds best poker players, a complex game requiring AI to guess others hands, while in 2019, Elon Musk-backed Open AI defeated top human team in one of the most lucrative and complex e-sport games (Dota2) as well as winning in a number

28、 of other war games that require strategy and co-operation. Bill Gates heralded the most recent wins as major breakthroughs, as they were no longer predicated on constrained and limited outcomes. At the same time, Watson AI is now communicating with more than one billion people, ranging from Quest D

29、iagnostic to OnStar. AI-based research has already predicted another missing link in human evolution while AI-assisted medical diagnosis and treatment is becoming routine and China has been building AI-based tools to assist its 100,000 plus judges.Does it mean that AI is now as smart as humans? The

30、answer is no.First, all of the above programs were written for single purpose games and applications. While machine learning techniques are massively improving, we still cannot convert an AlphaGo machine to perform radically different tasks. We can create a robot with sufficient dexterity to fold sh

31、irts, but this robot cannot yet perform multitude of functions required of a human butler. Second, one of the fastest of todays super computers at the Oak Ridge National Laboratory executes 1018 instructions per second (or a thousand trillion times faster than the first commercially available comput

32、ers launched in the 1950s) and its power is now in line with the theoretical maximum of human brain. But the big difference is the power consumption. Todays largest super computers use about a million times more power than the human brain. Given that Moores law is gradually running-out of steam, one

33、 possible answer (adopted by Google) is to create single purpose-driven machines, which use hundreds of times less power; alas, these computers are not sufficiently flexible.Quantum computing will be likely the long-term path, and it could become reality within 2020s, but both timing and how it will

34、 work remains highly uncertain.The key consideration, however, is not that AI needs to become much smarter than we are (although chances are that this will indeed happen sometime in the 2030s-40s), but that technology simply becomes good enough to perform a huge variety of tasks. Given AIs low incre

35、mental cost and massive scalability, good enough is going to be an unbeatable formula.chances are that it will be in ever wideningcirclesAI, automation & 3D printing will continue to remake real world, whileStarting with business processing and computer efficiency applications in the 1990s, technolo

36、gy has over the last 15 years progressed into variety of industries involving manipulation of digits (i.e. entertainment, music, news generation and gathering, check-out counters, social media, trading patterns on stock exchanges and global markets, and gradually moving into education and training).

37、 The next frontier involves manipulation of atoms. A powerful mix of AI, robotics, cloud computing and 3D printing is starting to revolutionize manufacturing, distribution and logistics. Fully autonomous cars and personal assistants (from secretaries to butlers) is the Trojan horse that will undoubt

38、edly unleash a dramatic change in how technologies are being used and how human environment will be structured. Manufacturing will eventually reside where consumption is located, with a gradual elimination and simplification of supply chains and closures of conventional factories. All of these are l

39、ikely to become the dominant themes through the 2020s.According to IFR, the installed industrial robotics capacity already exceeds 2.7m robots (vs 1.3m in 2013), and the total is expected to reach 4m by 2022. This is equivalent to 99 robots per 10,000 manufacturing employees, up from 48 robots in 20

40、10, and in China robotics density now exceeds 140 robots per 10,000 employees. Although global manufacturing recession has significantly slowed the pace of progression, nevertheless, the total installed in 2019 (421,000) was still broadly similar to 2018 vs. 304,000 in 2016. Apart from industrial ro

41、bots, another major growth area is in professional and service robots, from logistics and exoskeletons to unmanned aerial vehicles and cleaning, logistics to maintenance. In 2018, total shipments rose by 61% to 271,000 units and the industry has now expanded to almost US$10bn. IFR expects, shipments

42、 of service robots to exceed 1m per annum by 2022, when compared to virtually nothing in 2014-15.Fig 1 Supercomputer Power (FLOPS per second)Fig 2 Global Installed Industrial Robots Base (000) Grow th in Supercomputer Pow er, FLOPS (Floating-Point Operations per Second)Required f or human brain neur

43、al simulationRequired f or human brain f unctional simulationBlue Gene/LMDGrape 3-basedASCI PurpleASCI WhiteBlue Gene/P Columbia SX-8Earth SimulatorNum. Wind Tun.ASCI RedCP-PACS/2048 SR2201/1024CM-5/10241E+201E+191E+181E+171E+161E+151E+141E+131E+121E+111E+10199 0200 0201 0202 0203 04,5 004,0 003,5 0

44、03,0 002,5 002,0 001,5 001,0 00500-2013 2014 201 5 201 6 2017 2018 201 9 202 0 2021 2022Installe d Indu strial RobotsInstalle d Indu strial Robots per 10,000 emplo ye es120100806040200Source: Singularity, Macquarie Research, January 2020Source: IFR, Macquarie Research, January 2020Fig 3 Global Insta

45、lled Industrial Robots Base per 10,000 Manufacturing Employees - 201877433832721714099units 9008007006005004003002001000Kor eaGer ma nyJapanUSChinaGlo balFig 4 Global Professional Service Robot Shipments (000) installed base approaches 1m120 0100 08006004002000201 6201 7201 8201 9202 0202 1202 2Sour

46、ce: IFR, Macquarie Research, January 2020Source: IFR, Macquarie Research, January 2020including many areas that today cannot be automated andthis will have an ever- deeper impact on jobs,manufacturing, distribution andservicesWhether it is conventional manufacturing or services, global economy is ra

47、pidly moving to a much higher automation density. While in the past automation applied only to select few niches (such as automotive sector), today, robots are becoming far better in most of the typical human skills, including dexterity (such as textiles industry or folding shirts), identifying comm

48、on behavioural patterns (such as trading securities and streaming news) or surveillance.Hence, it is likely that the 2020s will witness an accelerated atrophy of jobs and occupations, or at the very least, a significant proportion of tasks will be automated. For example, McKinsey Consulting recently

49、 estimated that over the next decade, 60% of global occupations are likely to suffer at least 30% decline in functionality, even as few will go totally extinct. Although new jobs (or more appropriately, ways of spending time) will be invented, there is little doubt that the productive sphere for con

50、ventional labour will continue to narrow. This is already reflected in declining premiums for college education and slowing or negative pay rises for occupations with higher-than- average cognitive functions. There is a corresponding increase in compensation for occupations that currently cannot yet

51、 be replaced or at least partially automated (such as plumbers, truck drivers, construction workers, cooks etc). However, by the end of 2020s, proliferation of self- healing pipes and increasing sophistication and functionality of autonomous cars is bound to start eroding marginal pricing power of p

52、lumbers and truck drivers while dexterity and machine learning will start impacting cooks, butlers and personal assistants. Eventually by sometime in the 2030s, there will be an increasing pressure on the best computer coders and PhD students.Fig 5 Automated Futures Trading (% of Turnover) in most c

53、ases more than 50%, and some already in excess of 80%Fig 6 Probability of Loss of Job due to Automation (2013- 2033) 90%80%70%60%50%40%30%20%10%0%FX - G1 0 Equ itie s -FX - EM Equ itie s - Crude OilBaseGra in &100 %80%60%40%20%TelemarketersAccountantsRetail sale sTechnical writersReal Estate agen ts

54、Comme rci al p ilotsEconomistsActo rsFirefightersEditorsEng ineersAthletic CoachesClergy0%IntUSMetalsOilseed201 4 201 8Pro bability of loss of job du e to comp ute riza tion - 201 3-2033Source: CFTC, Macquarie Research, January 2020Source: Frey & Osborne, Macquarie Research, January 2020Fig 7 US Tru

55、ck Drivers Average Hourly wage increases (% YoY) rapid for nowFig 8 US Plumbers & Heating/Ventilation Average Hourly wage increase (% YoY) rapid for now 7.0%6.0%5.0%4.0%3.0%2.0%1.0%Jun-16Dec-16Mar-17Jun-17Dec-17Mar-18Jun-18Dec-18Mar-19Jun-190.0%5.0%4.5%4.0%3.5%3.0%2.5%2.0%1.5%1.0%0.5%Jun-16Sep -16De

56、c-16Mar-17Jun-17Sep -17Dec-17Mar-18Jun-18Sep -18Dec-18Mar-19Jun-19Sep -190.0%Sep -16Sep -17Sep -18Sep -19Truck transportationPlumbi ng and hvac contractor sSource: BLS, Macquarie Research, January 2020Source: BLS, Macquarie Research, January 2020Fig 9 US Computer Programming Services Average Hourly

57、wage increases (% YoY) imploding alreadyFig 10 US Architectural and Engineering Average Hourly wage increase (% YoY) imploding already 12.0%10.0%8.0%6.0%4.0%2.0%0.0%-2.0%-4.0%199 1-6.0%8.0%6.0%4.0%2.0%0.0%-2.0%199 1199 3199 5199 7199 9200 1200 3200 5200 7200 9201 1201 3201 5201 7201 9-4.0%199 3199 5

58、199 7199 9200 1200 3200 5200 7200 9201 1201 3201 5201 7201 9Custom comp ute r pr ogramming servi cesArchitectu ral a nd engine ering service sSource: BLS, Macquarie Research, January 2020Source: BLS, Macquarie Research, January 2020Fig 11 US Durable Manufacturing Average Hourly wage increases (% YoY

59、) easingFig 12 OECD College Premium (2010 vs 2015) decreasing everywhere 6.0%5.0%4.0%3.0%2.0%1.0%0.0%Durable Manufacturing190180170160150140130120110CzechPor tug alSlovakGer ma nyUKSwissAustriaKor eaSwede n100Jan-90 Apr -91 Jul-92 Oct-93 Jan-95 Apr -96 Jul-97 Oct-98 Jan-00 Apr -01 Jul-02 Oct-03 Jan-

60、05 Apr -06 Jul-07 Oct-08 Jan-10 Apr -11 Jul-12 Oct-13 Jan-15 Apr -16 Jul-17 Oct-18IrelandGre eceAustralia-1.0%201 0 201 5Source: BLS, Macquarie Research, January 2020Source: OECD, Macquarie Research, January 2020It will also continue to depress trade intensity whileAt the same time, we believe that