How China is winning in the Age of Artificial Intelligence

Alibaba Campus
Alibaba Campus

Currently, I’m on a 4-week China trip, visiting many cities. In Hangzhou, I met CEIBS peers who work for Alibaba. While the Alibaba campus is quite impressive, I got even more impressed by Alibaba’s leadership culture, which is encouraging its employees to innovate as intrapreneurs.

If you start your own project (a new mobile app, a patent, a scientific paper, etc.), you’re doing it in your own pace, you’re not being micro-managed and you’ll receive a bonus based on success. Intrapreneurship at Alibaba is just one of many examples where we (Europeans) can learn a lot from China!

Yue and me, Hangzhou West Lake

While traveling in China I was reading AI Superpowers: China Silicon Valley, and the New World Order by Kai-Fu Lee, a book that is a must-read to get an idea where China’s AI ambitions are heading to. What matters most for AI innovation these days, the author argues, is access to vast quantities of data—where China’s advantage is overwhelming.

AI Superpowers: China, Silicon Valley, and the New World Order
  • Kai-Fu Lee
  • Publisher: Houghton Mifflin Harcourt
  • Gebundene Ausgabe: 272 pages

A quite entertaining book focusing on the new mindset of China’s young generation is this one: Young China: How the Restless Generation Will Change Their Country and the World by Zak Dychtwald.

  • Publisher: MACMILLAN USA
  • Gebundene Ausgabe: 304 pages

[Update 2 May 2019]: Which other cities in China did I visit? Check out my Tableau Public viz:

Die 5 wichtigsten Bücher zu Data Science

Welche Bücher sollten Sie lesen um als Data Scientist erfolgreich zu sein? | Photo Credit: via Sebastian Sikora

Für den Einstieg und den Überblick zu Data Science:

The Data Science Handbook
  • Field Cady
  • Publisher: John Wiley and Sons Ltd
  • Gebundene Ausgabe: 416 pages

Die universelle Programmiersprache Python eignet sich hervorragend zur Lösung von Data-Science-Fragestellungen:

Eine Einführung zu Statistical Learning und Machine Learning (classification, clustering, supervised, unsupervised, …) mit R:

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
  • Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
  • Publisher: Springer
  • Edition no. 1201372017 (29.09.2017)
  • Gebundene Ausgabe: 426 pages

Bei großen Datenmengen führt an Hadoop kein Weg vorbei:

Hadoop: The Definitive Guide
  • Tom White
  • Publisher: O'Reilly and Associates
  • Edition no. 4 (30.04.2015)
  • Taschenbuch: 728 pages

Wie Data Science im Unternehmen Mehrwert schafft: