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Morning Coffee: The 3,000 people who can name their price in finance or in tech. Fund manager likes to hire 40 year-olds

If you're a specialist in artificial intelligence (AI), you'd might want to make the most of it while you can.

Following a disagreement last year over the extent of the AI talent shortage between Montreal-based Element AI Inc and Chinese internet giant Tencent Holdings, Bloomberg reports that Element AI has confirmed its methodology.

Element AI calculated last year that there are fewer than 10,000 people in the world capable of building contemporary AI systems, and said that only 3,000 of them are looking for jobs at any one time. Given the explosion in the use of AI systems across banking, hedge funds, and technology firms like Google, Facebook or Amazon, these 3,000 people would seem to personify the moniker of "most hireable people in the world." Tencent, however, thinks Element AI has underestimated their supply - it calculated in December that there are 200,000 to 300,000 AI "practitioners" available, thereby suggesting the shortage is far less acute

Who's right? Element AI's methodology certainly has some faults. The company said yesterday that it arrived at its number by scouring LinkedIn for people who'd earned PhDs since 2015 which included the words, "deep learning, artificial neural networks, computer vision, natural language processing or robotics." It then overlaid this with the requirement that they had coding skills like Python, TensorFlow or Theano. So far so good, but what if you're an AI expert who's not on LinkedIn? Element AI also looked at people who are actively publishing papers at academic conferences in the past seven years; it calculated that there are no more than 10,000 of these.

Tencent's methodology is not known, but would seem to encompass China as a potential source of hundreds of thousands of AI practitioners.

Irrespective of who's right, one truth does seem to hold: if you're a recent(ish) PhD with a specialism in artificial intelligence, you might want to monetize it as soon as possible. Element AI's chief executive notes that universities are busy training up thousands more AI experts, but that it will take three years for the new supply to reach the workforce.

Separately - and anti-ageism legislation be damned - Bloomberg has unearthed a fund manager who only hires people with experience of an "absolute disaster" in the markets, implying that they need 10 years' experience at least. The manager, Paul McNamara at GAM Asset Management in London, has a team of five people. The youngest is aged 39.


Deutsche Bank has now fallen 19.6% since the beginning of the year, by far the steepest drop in the Bloomberg 500 Europe Banks and Financial Services Index. Barclays Plc had the second-worst performance among big banks with a 5.1% decline. (Bloomberg) 

“I’ve lost $4 million, 3 years worth of work, and other people’s money.” (Marketwatch)

“Why would you think you could lose everything if you had made 4 percent a year for five years," fine, I will allow it. But if you tripled your money in a year, that was the tell. (Bloomberg) 

Winton’s funds were down 3% to 4% over Monday and Tuesday, their worst short-term performance in five years. (Financial Times) 

'Liquidity withdrawal and being short volatility are not natural bedfellows. The only practical way to reduce exposure is to short the S&P 500 index itself -- which leads to a doom spiral of everyone exiting at the same time. ' (Gadfly)

Berenberg wants to hire 50 people a year in London over the next two years through, "selective hiring." (Financial News) 

Former Morgan Stanley banking analyst Huw Van Steenis quit Schroders unexpectedly after less than two years. (Financial News) 

A Deutsche trader in Australia has been charged with creating millions of false trades. (Business Insider) 

Most annoying 18 year old (bitcoin trader) in the world. (Australian Financial Review) 

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AUTHORSarah Butcher Global Editor
  • kk
    11 February 2018

    It's not correct either. There are many PhD data scientist wannabes who really only know statistics and jumped on the bandwagon. Question them in-depth on neural network models and they can only tell you the basic architecture of propagation.

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