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The Master of Machine Learning is enticing technologists to invest | Technology and Business

The Master of Machine Learning is enticing technologists to invest | Technology and Business
The Master of Machine Learning is enticing technologists to invest 

Machine Learning maestro is tempting technologists to finance

Li Deng has been working with artificial intelligence and machine learning for nearly three decades.  He spent 17 years at Microsoft and founded the tech company's Deep Learning Center in Redmond, Washington.  But for the past five years, Deng has worked in finance, and now he's on a mission to persuade other technologists to get into the field as well.

"In finance, the data is huge. In many cases, it's much bigger than the data you're dealing with in technology," Deng tells us.  "Therefore, we need people who are very good at dealing with large datasets and who understand the essence of advanced learning models like Deep Neural Networks."

Deng spent 3.5 years at hedge fund Citadel, where he was Head of Machine Learning until November 2020.  In May 2022 he joined Vatic Investments, an automated liquidity provider founded by James Chiu of Jump Trading.  At Vatic, he is slowly building a team with people from not just financial backgrounds.  "You don't need to know about finance to apply machine learning techniques to finance data sets," says Deng. "Raw smarts are the most important character trait I'm looking for.  If people have a financial background, that's good.  But if not, it is relatively easy to train people to apply AI techniques to financial problems."

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Deng says his network of AI contacts is substantial, and he is still in touch with the 100 or more interns who went through his program at Microsoft.  “I interviewed three people last week and I am interviewing four PhDs in the Seattle area tomorrow,” he says.  “I have been involved in the Seattle tech scene for some time and I know a lot of good engineers and researchers here. Good people often contact me when they are available. They know I can give them challenging jobs."

At Vatic, the challenging task means using machine learning to generate automated buy and sell signals based on learning from as much data as possible, even when the dataset is noisy.  Most of the people Deng and Chiu interview have PhDs, but a handful only have bachelor's degrees.  "We hired exceptionally strong graduates without PhDs, but typically we try to identify the top 1%," Deng says.  Chiu says PhDs are preferred because they demonstrate that people have used tools, "in a deeper way that can be applied to our problems. The training of a PhD allows you to define a problem and use tools."  Helps in understanding how to solve a problem by using it.

Although machine learning is excellent for trading buy and sell signals, Deng says that human traders can still benefit: "Human traders can sometimes react rapidly and provide insights very quickly."  By comparison, he says that machines can make the false assumption that the past will repeat itself in the near future and this does not always hold, although techniques such as smart temporal regularization can be applied to reduce this error.

Source: efinancialcareers.com, directnews99.site