The field of artificial intelligence is red hot thanks in part to big companies like [f500link]Google[/f500link], [f500link]Facebook[/f500link], and [f500link]Microsoft[/f500link] using AI-related techniques to train computers to recognize objects in photos and understand human language.
But these companies were only able to train their computers to perform these difficult feats because they have the enormous quantities of data that’s required. Companies that want to use artificial intelligence techniques like machine learning algorithms to improve their businesses will need to either have or acquire copious amounts of data, which will only become more valuable as the field of AI advances.
That’s one of the takeaways from a panel on artificial intelligence Monday in Aspen, Colo. during Fortune’s annual Brainstorm Tech conference.
“Data is the new oil,” Shivon Zilis, a partner with the venture capital firm Bloomberg Beta, said about data’s increasing value.
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Although companies like Google (GOOG), Facebook (FB), and [f500link]Amazon[/f500link] (AMZN) have open sourced their own artificial intelligence software so any programmer can access the code and use it to build their own apps, they are not making the necessary data available, Zilis explained. These companies are releasing these AI software toolkits for free so they can recruit more engineers to their companies, she said.
When it comes to competition, it’s the data these companies posses that’s more important than the actual AI software tools they use and release to the public.
David Kenny, the general manager of IBM’s (IBM) Watson data crunching service, agreed with Zilis and said “the value of data goes up every day AI advances.”
“Data will become a currency,” Kenny said. He also explained that only 20% of the world’s information is stored on the Internet, with the other 80% being privately held within companies and organizations.
Additionally, Zilis discussed the history of so-called “AI winters” in which the hype of AI failed to meet the general public’s expectations, and led to periods of years of declining research into AI during the mid-1970’s and the late 1980’s to early 1990’s.
Today, however, the rise of the cloud and the ability to access tremendous amounts of computing power to analyze huge amounts of data has the potential to strengthen the existing AI-related algorithms and lead to new more powerful algorithms. Because of these technological developments, Zilis does not believe companies will lose interest in AI.
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“Are we going to hit a winter?” asked Zilis. “Absolutely not.”