The Paul Allen artificial-intelligence venture is preparing to take the technology it is working on, Aristo, to the eighth-grade level of science knowledge and understanding.
Artificial intelligence is getting bigger and smarter right here in Seattle.
The Allen Institute for Artificial Intelligence, a sister company to Paul Allen’s Institute for Brain Science, plans to hire 25 people in the next year as it prepares to take its Aristo technology to the eighth grade, moving on from teaching it fourth-grade science.
The company plans to take over about 6,000 additional square feet of space in its headquarters on North Northlake Way near Gas Works Park and grow its employee ranks, said CEO Oren Etzioni.
Etzioni leads the small team of 50 with Chief Operating Officer James Allard, and the executives are preparing for a hiring binge.
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Artificial intelligence has been all over the news lately, and this time not solely over fears that machines may eliminate people’s jobs. AlphaGo, an AI program developed by DeepMind, a Google company, beat one of the world’s foremost Go champions in March.
The machine’s victory over Lee Sedol at the numerically broad game shocked many people who believed AI was years away from such a feat.
But it didn’t happen overnight. The program may be fairly new, but the underlying research has been developing for decades.
“AlphaGo’s overnight success was kind of 50 years in the making,” Etzioni said.
In Seattle, Etzioni believes the team at Allen’s AI2 is attempting a much bigger challenge by teaching a computer to be a mastermind in all disciplines of science.
AlphaGo can train by playing the board game 24 hours a day, seven days a week. AI2’s Aristo cannot. There are only a finite number of scientific test questions in existence, and the AI2’s Aristo technology must learn using them.
The machine also learns from researchers across the world. AI2 recently wrapped up a global competition in which teams ran their own programs through an eighth-grade science test to see which could get the top score.
The Allen Institute awarded the $50,000 grand prize to Chaim Linhart, a senior researcher at TaKaDu, an environmental-services company in Israel.
Next year, the stakes will be much higher. AI2 plans to offer a $1 million prize if any team can beat a certain threshold — the exact percentage has not yet been determined — followed by smaller monetary prizes for runners-up.
“It helps to raise awareness and focus on important problems,” Etzioni said. “To win, teams have to publish their code.”
Eventually, AI2 wants to have a smart enough system that it can act as an assistant in different fields of science. For example, it could scan hundreds of thousands of medical-journal articles in an instant to give doctors immediate answers to their questions.
Early versions of that project, called Semantic Scholar, have launched for computer science and it is expected to launch for neuroscience this year.
Etzioni’s hope is that in about 20 years, the machine will be able to go even further, gaining the ability to form its own hypotheses from reading scholarly journals. He calls it a “scientists’ apprentice.”
AI2 is one of the leaders of the field of artificial intelligence in the region, but it certainly isn’t the only company developing machine-learning technology in Seattle.
Nearly all of them make applications for businesses that are not nearly as sexy as AlphaGo or IBM’s “Jeopardy!”-playing Watson.
“People who are running businesses, for the mundane but nonetheless insurmountable problems presented by big data, are turning to machine learning to make sense of this world of noise,” said Matt Bencke, CEO of Seattle tech startup Spare5. “…The incredible headline-gathering events are in some ways getting us distracted from the more mundane reality of how AI and machine learning are impacting our every day lives already.”
The company is in the business of a specific type of machine learning — mainly helping other companies clean up their own systems.
Spare5 combines machine-learning technology and actual humans to comb through data, pick out mistakes and ensure that machine-learning programs are performing accurately and identifying errors.
“We call it the right human in the right loop to provide the right training data,” said Andy Ganse, principal data scientist at Spare5.
Ganse and Etzioni both have held posts at the University of Washington, considered a top school from which to recruit AI engineers.
AI2 is looking there, and everywhere, to find experienced engineers and researchers, and ones who can be trained on the ins and outs of AI. Etzioni doesn’t see the hiring forecast as a goal. It is a set plan.
“Paul Allen is an inspiration,” he said. “He also has big expectations.”