Artificial intelligence takes on Wall St

Artificial intelligence takes on Wall St

Artificial intelligence takes on Wall St

Babak Hodjat believes humans are too emotional for the stock market. So he's started one of the first hedge funds run completely by artificial intelligence.

"Humans have bias and sensitivities, conscious and unconscious," says Hodjat, a computer scientist who helped lay the groundwork for Apple's Siri. "It's well documented we humans make mistakes. For me, it's scarier to be relying on those human-based intuitions and justifications than relying on purely what the data and statistics are telling you."

Hodjat, with 21 patents to his name, is co-founder and top scientist of Sentient Technologies Inc., a startup that has spent nearly a decade-largely in secret-training an AI system that can scour billions of pieces of data, spot trends, adapt as it learns and make money trading stocks.

The team of technology-industry vets is betting that software responsible for teaching computers to drive cars, beat the world's best poker players and translate languages will give their hedge fund an edge on Wall Street pros.

Read Also:
Healthcare Big Data Silos Prevent Delivery of Coordinated Care

The walls of Sentient's San Francisco office are dotted with posters for robots-come-alive movies such as "Terminator." Inside a small windowless trading room, the only light emanates from computer screens and a virtual fire on a big-screen TV. Two guys are quietly monitoring the machine's trades-just in case the system needs to be shut down.

"If all hell breaks loose," Hodjat says, "there is a red button."

Sentient won't disclose its performance or many details about the technology, and the jury is out on the wisdom of handing off trading to a machine. While traditional hedge funds including Bridgewater Associates, Point72 and Renaissance Technologies have poured money into advanced technology, many use artificial intelligence to generate ideas-not to control their entire trading operations.

All the same, Sentient, which currently trades only its own money, is being closely watched by the finance and AI communities. The venture capital firm owned by Hong Kong's richest man, Li Ka-shing, and India's biggest conglomerate, Tata Group, are among backers who have given the company $143 million (NZ$199m). (Beyond trading, Sentient's AI system is being applied to a separate e-commerce product.)

Read Also:
5 architectural principles for building big data systems on AWS

Trading is "one of the top 10 places that AI can make a difference," says Nello Cristianini, a professor of artificial intelligence at the University of Bristol who has been advising Sentient. "A trading algorithm can look at the data, make a decision, act and repeat-you can have full autonomy."

Sentient's team includes veterans of Amazon, Apple, Google, Microsoft and other technology companies. They're part of a small group in Silicon Valley using expertise in data science and the field of artificial intelligence known as machine learning to try and disrupt financial markets.

AI scientists typically have no interest in working for a hedge fund, says Richard Craib, who started the AI hedge fund Numerai. "But they may want to mess around with data sets." Numerai's system makes trades by aggregating trading algorithms submitted by anonymous contributors who participate in a weekly tournament where prizes are awarded in Bitcoin.

It recently raised US$6m from investors including Howard Morgan, the co-founder of the quant investment management firm Renaissance Technologies. "It's entirely a data science problem," Craib says.

Read Also:
How to avoid pitfalls with data analytics projects

Another company, called Emma, started a hedge fund last year based on an artificial intelligence system that can write news articles.

Hodjat of Sentient spent much of his career focused on the language-detection technology behind smartphone digital assistants. Several employees from his previous company, Dejima, went on to create Apple's Siri. Rather than join, he chose to focus on advances in artificial intelligence. His career goals didn't include finance, but he sees markets as one of the most promising applications for the technology.



Read Also:
Why being a data scientist 'feels like being a magician'
Read Also:
Why being a data scientist 'feels like being a magician'
Read Also:
Architecting and Structuring a Big Data Ecosystem
Read Also:
3 Ways IT Can Benefit from Self-Service Analytics

Leave a Reply

Your email address will not be published. Required fields are marked *