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At a recent United Nations conference in Shanghai I discussed critical topics on the Chinese AI ecosystem. This article clearly and elaborately outlines perspectives on the strengths and weaknesses of the Chinese AI ecosystem, based on my interviews and discussions with various Chinese NGOs, founders, and investors.
Back at the beginning of the year, I set out to get a feel for a city in the longitudinal center of the country, between two coastal tech hubs in San Francisco and NYC: Austin. I wanted to find out what made Austin an attractive AI and tech hub the way I had in Boston, Atlanta, Montreal, and Bangalore before it. It turns out the AI startup community in Austin is measurably different than those on the east and west coast, and it stood out to me in the way it was able to offer a quality of life that's rare for fresh-out-of-college talent on the coasts.
Over the last two years, we have witnessed a steady increase in our percent of readership in India. Sometime in 2017, Bangalore became one of our largest sources of job applicants, and our single biggest city in terms of readers - overtaking both London and NYC.
Last September I had the chance to do a series of AI-related speaking engagements in Atlanta (one of those presentations became one of our most popular articles on “enterprise AI adoption”), but unlike most trips, I spent very little time in the hotel.
With "machine learning" excitement in full swing, Boston is buzzing as always with it's own batch of startups, accelerators, and VCs, and I decided to do a deep dive into the local artificial intelligence ecosystem.
Artificial intelligence and machine learning adoption among different industries represents a new chapter in digital transformation. However, according our own research across industries, AI adoption in 2017 remains low with majority of major success stories coming only from the largest tech players in the industry (Google, Baidu, Apple, etc). McKinsey Global Institute estimates that in 2016, tech giants invested $20-30 billion into AI, while smaller companies altogether invested an estimated $6-9 billion.
In the last 12 months, Montreal has arrived on the world stage as an epicenter for machine learning and artificial intelligence. The city's extraordinarily high density of AI talent isn't new, but the demand for machine learning is, and the proverbial "tech spotlight" is now shining bright on this very French Canadian city.
In just the last few months:
Women in artificial intelligence (AI) and machine learning (ML), or the lack thereof, is not a new topic in media, just as gender equity and disparity in the workplace is not a new subject of research for academics and think tanks. But discussing these issues openly is no less important. While we address the potential reasons and implications of these issues toward the end of this article, our initial interest in this subject came from our desire to know the following: