Some things I learned this week: 10/6/18

As I continue reading reports on China’s bold investments in the future, I read the Mercator Institute for China Studies’ report on the Made in China 2025 initiative. Lots of takeaways below:

  • “Made in China 2025” refers to its industrial masterplan to ‘challenge the economic primacy of the current leading economies and international corporations’, through the promotion and dissemination of smart manufacturing technology. Given China’s history of labor-intensive industries, this is a strategic move to avoid the “middle-income trap” and move upstream in the value chain.
    • This plan hinges upon three abilities: developing innovative products, creating internationally well-known brands and building modern, industrial production facilities. This will not only require incredible funding and organization to develop Chinese capabilities, but will also look for foreign investment opportunities that may be (at least informally and partially) guided by the state.
  • While increased innovation capacity could be a boon for it’s global economic partners, China’s leadership is predicted to seek the replacement of foreign technology with home-grown enterprises and promote Chinese companies in international markets.
  • Self-sufficiency sits at the core of this strategy, and the 2025 plan calls for a large uptick in domestic market share of the production of mobile phone chips, industrial robots and renewable energy equipment.
    • Chinese enterprise will be backed by billions of state-financing, in addition to various provincial-level financing vehicles
    • On the other hand, foreign competitors will meet information technology obstacles, exclusion from local subsidies, and possibly future discriminatory practices.
  • The plan will target the following technologies: new generation information technology, high-end computerized machines and robots, space and aviation, maritime equipment and high-tech ships, advanced railway transportation equipment, new energy and energy-saving vehicles, energy equipment, agricultural machines, new materials, biopharma and high-tech medical devices.


I also took a look at the Council on Foreign Relations article, “Why Does Everyone Hate Made in China 2025?”. Quick summary:

  • In light of the continuing American tariff threats to China, the U.S. released a 200-page report attacking China for unfair trade practices, and cited the ‘Made in China 2025’ plan 116 times.
  • Evidently, some of the very quotas that China outlines for self-sufficiency (although not officially in its 2025 plan) violate WTO rules.
  • The U.S. and other developed economies are extremely wary of China’s push towards foreign acquisitions, forced technology transfer agreements, and commercial cyber espionage in order to catch up in high-tech industries.


Lastly, I read a global equity research report by J.P. Morgan on AI. Here’s what I found interesting:

  • How artificial intelligence is different from traditional predictive software (simplified): AI discovers patterns and logic in data and adjusts its behavior accordingly, whereas traditional software is limited to pre-defined logic (i.e. the programmers have to write if/then statements for the set of conceivable use cases, whereas AI can form these independently of human programming, given sufficient data inputs).
  • Why businesses are going crazy: the scope and scale of AI application is boundless.
    • Customer experience can benefit from better recommendation systems, virtual assistants (imagine Siri for medical patients)
    • Company operations can predict and reduce the impact of equipment failure (see GE’s Predix software), enhance quality control and generate prescriptive responses for people and machines
    • IDC forecasts a surge in AI-focused spending at 50% 2017-2021 CAGR
    • Why now? Access. Increasingly available, large datasets and cheap computing power, reinforced by positive feedback loops.
  • Artificial intelligence is not a winner-take-all market; while Google/Microsoft/Facebook will dominate, traditional companies can maintain strong positioning by digitizing their information assets (on customers, processes, supply chain, etc.)
  • “Suppliers” of AI
    • Internet companies: think Google, Facebook, Baidu, Tencent… they’ve amassed massive troves of data and use AI for analysis/prediction
    • Platform-as-a-Service providers: Amazon, Microsoft, IBM, Oracle, Alibaba… they offer AI capabilities (data, cloud computing power, AI/ML processing kits)
    • Enterprise software vendors: SAP, Salesforce, Adobe… they help companies with digital transformation
    • Specialist AI functions: companies focused on computer vision, natural language processing, chatbots, geolocation, pattern recognition, predictive maintenance…
    • IT services: Accenture, Capgemini, Cognizant… for the design, implementation and integration of digital capabilities
  • Case studies: Netflix says that its predictive algorithm drives 80% of its users’ viewing activity and has over $1B of annual impact on its business. The Associated Press, partnering with AI firm Automated Insights, freed up 20% of its journalists’ time otherwise spent reviewing earnings data while resulting in no job losses. Google uses AI from its 2004 acquisition of DeepMind to manage power usage in its data centers (composing significant portions of data center operating costs), reducing overall power consumption by 15% (plausibly hundreds of millions of dollars).

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