China, Unicorns and the Battle for Global AI

Guest Post by Angelina Cheok Back in 2015, China’s economy appeared to be at a crossroads. Its slowing growth seemed to herald a death knell for the country’s start-up boom, while the outlook for its tech sectors look equally grim. Think tanks, academics and journalists like the Harvard Business Review and Foreign Policy published scathing critiques of China’s inability to…

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Gender Bias in Venture Capital: Bad Business

Venture capitalists are being called out for gender bias. A recent Fortune article reported that female founders received only 2% of venture capital dollars in 2016. Some high profile VCs, and VC-backed startups, are facing a litany of sexual harassment charges. An interesting study of VC decision making even found (unintentionally) how male and female founders were treated differently in subtle ways.…

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Innovation in Australia: A Yank’s Perspective

As an American venture capitalist who recently moved to Australia, it’s been fun to notice differences in how the US and Australia innovate. I’ll be the first to admit I’m no expert on Australia. For what it’s worth, however, I thought I’d share some novice observations in the hope that it’s somehow helpful to other cross-border innovators pondering these same…

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Some Ideas Are Better Than Others (and I don’t mind saying so)

Some ideas are better than others. This is a challenge for business strategists, who are voracious consumers of ideas (books, seminars, case studies, articles, blogs, biographies, etc.), but who aren’t typically trained to judge an idea’s quality. This leaves strategists vulnerable to bias, persuasion, poor heuristics and psychophysiological reactions (called ‘intuition’). Everyone from the doorman to the chairman has an…

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Venture Capital and Statistics: Art Meets Science

Venture capitalists usually try to avoid statistics, arguing that picking startups is more art than science. When asked why they don’t use statistical decision tools, most VCs say there either isn’t enough data to build reliable models, or picking startups is simply too intangible and complex to be reduced to math. There’s some truth to both arguments… but they’re getting…

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Will robots kill jobs, or create them?

A lot of people are worried about losing their jobs to either a robot or a line of code. This anxiety is fair – just ask Encyclopedia Britannica.  Some say 6% of all US jobs will be lost to robots by 2021, others say 38% of US jobs will be automated by 2030, and even in Australia the government estimates…

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Global race in data science decision-making

On your mark, get set, go 2017! While most folks in the US intuitively understand the pull from abroad, it might surprise them to hear this: I'm finding many overseas companies way ahead of their US counterparts when using data science to improve decision making. It’s real. It’s noticeable. Speaking as an American, it’s even a bit scary. I’ve been guilty…

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