CloudQuant participated in the Newsweek conference on Artificial Intelligence and Data Science (December 5th to 7th, 2017).
International Business Times
BY LEIGH CUEN ON 12/06/17 AT 6:44 PM
When it comes to the financial industry, crowdsourced mistakes can be costly as well as embarrassing. So machine learning experts are busy figuring out solutions for dynamic prediction markets. Many of them rely on machine learning to manage human participants at some stage or another.
“If you allow anybody and everybody to come make estimates, how do you make sure somebody isn’t trying to game the system, that ridiculous people don’t put in ridiculous estimates?” Leigh Drogen, cofounder of the crowdsourcing fintech platform Estimize, said at the Artificial Intelligence & Data Science conference in New York City. “What we do is run a series of machine learning models against a set of rules…those models deal with weighing the contributors in different ways.” …
… “Bring us your ideas and we will share the money with you,” agreed Morgan Slade, CEO of the crowdsourced algorithmic trading startup CloudQuant. “For us, engagement means breaking it down into a contractible problem.” …
Read the full article on International Business Times at http://www.ibtimes.com/crowdsourced-data-reliable-2624950
CloudQuant Thoughts: The question, Is Crowdsourced Data Reliable? – The answer is sometimes. Our crowd researchers examining the crowdsourced data are finding alpha signals that are reliable. Each researcher needs to look at the data with a critical eye. Not everyone tweeting has pure motives after all.
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