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[ M A R K E T R E V I E W I n 2015, David Siegel, the co-founder of quantitative hedge fund giant Two Sigma, told a conference that there would come a time “when no human investment manager will be able to beat the computer.” What sounded like science fiction is gradually becoming reality as computers move into the investment world. Artificial intelligence (AI) has already beaten humans at many other games—chess, Go and poker to name but a few—but its use in investing has been slower to mate- rialise. This, however, looks set to change. Machine learning is a catch-all 42 TheTrade Summer 2017 | M A C H I N E L E A R N I N G ] name for a range of algorithms that can identify repeatable patterns and relationships within observed data. The development of machine of its actively managed funds into algorithmic funds with a focus on AI and quant-based investing. The move has seen seven of 53 stock “Our algos are biologically inspired.” JEFF HOLMAN, CHIEF INVESTMENT OFFICER, SENTIENT learning is being driven by the computing and data revolutions of the past decade. Computing power has broadly doubled every two years since the 1970s making it easier for new entrants to tap into the computing power needed to develop AI technologies. Mean- while, it is estimated that 90% of data in existence today was created in the last two years. A company like AHL, the quantitative invest- ment arm of hedge fund manager Man, for example, receives around 1.5 billion data ticks every day. Harnessing and storing data has become easier—in 1981 a gigabyte of storage cost $300,000, the price is below 10 cents today. And asset managers are sitting up and taking notice. In March BlackRock - the largest fund manager in the world - an- nounced it was moving a number pickers stepping down, and will impact some $30 billion of the company’s equity funds. It could mark a watershed in the progress of fund management as more follow its lead into machine-based investment. Sentient, founded in San Francis- co in 2008 by scientists and engi- neers, has spent six years building out the different components to capture data for investment pur- poses. Using dark cycle technology to tap into hundreds of thousands of unused computers from 4000 facilities in the world it claims to have one of the largest compute facilities in the world dedicated to AI. Its machine learning algorithm uses evolutionary processing —a branch of AI inspired by bio-natu- ral selection—from which it has de- veloped AI techniques and applied them to stock pattern prediction. “Our algos are biologically inspired,” says Jeff Holman, chief investment officer at Sentient. “They are evolutionary algos used to develop strategies via natural selection. They undergo mutations and combine or breed with each other. The compute power means you can test billions of strategies in