SEATTLE — Paul Allen has been waiting for the emergence of intelligent machines for a very long time. As a young boy, Allen spent much of his time in the library reading science-fiction novels in which robots manage our homes, perform surgery and fly around saving lives like superheroes. In his imagination, these beings would live among us, serving as our advisers, companions and friends.
Now 62 and worth an estimated $17.7 billion, the Microsoft co-founder is using his wealth to back two philanthropic research efforts at the intersection of neuroscience and artificial intelligence that he hopes will hasten that future.
The first project is to build an artificial brain from scratch that can pass a high school science test. It sounds simple enough, but trying to teach a machine not only to respond but also to reason is one of the hardest software-engineering endeavors attempted — far more complex than building the breakthrough Windows operating system, said to have 50 million lines of code.
The second project aims to understand intelligence by coming at it from the opposite direction — by starting with nature and deconstructing and analyzing the pieces. It’s an attempt to reverse-engineer the human brain by slicing it up — literally — modeling it and running simulations.
Allen persuaded University of Washington AI researcher Oren Etzioni to lead the brain-building team and Caltech neuroscientist Christof Koch to lead the brain-deconstruction team. For them, the quest to understand the brain and human intelligence has parallels in the early 1900s, when people first began to ponder how to build a machine that could fly.
There were those who believed the best way would be to simulate birds, while there were others, like the Wright brothers, who were building machines that looked very different from species that could fly in nature.
Whether they create something reflected in nature or invent something entirely novel, the mission is the same: conquering the final frontier of the human body — the brain.
“We are starting with biology. But first you have to figure out how you represent that knowledge in a software database,” Allen said in an interview. “I wish I could say our understanding of the brain could inform that, but we’re probably a decade away from that. Our understanding of the brain is so elemental at this point that we don’t know how language works in the brain.”
At its most basic level, artificial intelligence is an area of computer science in which coders design programs to enable machines to act intelligently, in the ways that humans do. Today’s AI programs can adjust the temperature in your home or your driving route to work based on your patterns and traffic conditions.
In medicine, AI algorithms are being used to do things such as predicting manic episodes in those suffering mental disease and finding connections between things such as weather, traffic and your health.
But when it comes to general knowledge, scientists have struggled to create a tech that can do as well as a 4-year-old human on a standard IQ test.
That will almost certainly change in the coming years as billions of dollars in Silicon Valley investments lead to the development of more sophisticated algorithms and upgrades in memory storage and processing power.
The most exciting — and disconcerting — developments in the field may be in predictive analytics, which aims to make an informed guess about the future. Although it’s mostly being used in retail to figure out who is more likely to buy, say, a certain sweater, there are also test programs that attempt to figure out who might be more likely to get a certain disease or even commit a crime.
Google, which acquired AI company DeepMind in 2014 for an estimated $400 million, has been secretive about its plans in the field, but the company has said its goal is to “solve intelligence.” One of its first real-world applications could be to help self-driving cars become better aware of their environments. Facebook chief executive Mark Zuckerberg says his social network, which has opened three AI labs, plans to build machines “that are better than humans at our primary senses: vision, listening, etc.”
All of this may one day be possible. But is it a good idea?
Allen and Etzioni say that they also have thought a lot about how AI might change the world and that they respectfully disagree with the doomsayers.
“There are people who say, ‘I don’t care about the ethics of it all. I’m a technologist.’ We are the opposite of that. We think about the impact of this kind of technology on society all the time,” said Etzioni, who is chief executive of the Allen Institute for Artificial Intelligence, “and what we see is a very positive impact.”
Koch is more hesitant.
“Runaway machine intelligence is something we need to think about more,” Koch, president and chief science officer of the Allen Institute for Brain Science, said. “Clearly, we can’t say let’s not develop any more AI. That’s never going to happen. But we need to figure out what are the imagined dangers and what are the real ones and how to minimize them.”
Allen’s vision is creating an AI machine that would be like a smart assistant, rather than an independent being. He admits he has wondered whether it will one day be possible for that assistant to evolve into something more.
“But that is a long, long ways away,” Allen said.
Building on the work that Allen accelerated through his philanthropy, governments around the world have launched their own brain initiatives in recent years.
The European Commission’s Human Brain Project, which began in 2013 with about $61 million in initial funding, aims to create an artificial model of the human brain within a decade. President Barack Obama announced the Brain Research through Advancing Innovative Neurotechnologies in 2014, comparing it to the Human Genome Project. BRAIN was launched with initial funding of $110 million.
Allen’s own interest in the brain began with his love of tinkering.
But it wasn’t until his mother, Faye, a former elementary school teacher, became ill with Alzheimer’s that Allen’s brain philanthropy took shape.
He founded the Allen Institute for Brain Science and seeded it with $100 million. But he didn’t want to just replicate what was being done at university and government labs.
“He wanted to do a different brand of science, tackle bigger questions,” said Allan Jones, who was involved in the founding of the institute and is now its chief executive. Allen’s marching orders were simple: Figure out “how information is coded in the brain.”
Allen, who has committed a total of nearly $500 million to the institute since then, thought that gathering great minds under one roof, all focused on the same goal, could accelerate the process of discovery.
Allen’s “big science” strategy has attracted and significantly increased the salaries of some of the world’s top talent — including a number of tenured professors at the peak of their careers, such as R. Clay Reid, a neurobiologist who left Harvard Medical School in 2012 to continue his work on how vision works in the brain.
The Allen Institute also has pioneered other approaches uncommon in biology research.
First, the brain institute started with data, not a hypothesis. Not just ordinary big data but exabytes of it — billions of gigabytes, the scale of global Internet traffic in a month — detailing the growth, white matter and connections of every gene expressed in the brain. Researchers spent their first few years painstakingly slicing donor brains into thousands of microthin anatomical cross sections that were then analyzed and mapped.
Then, it made all of its data publicly available, inviting anyone to scrutinize and build upon it.
By 2006, the institute’s scientists had created the most comprehensive three-dimensional map of how the mouse brain is wired and released that atlas to the public. By 2010, they had mapped the human brain.
Now many of the institute’s 265 employees are turning to more tangible problems, studying autism, schizophrenia, traumatic brain injury and glioblastoma, a rare but particularly aggressive type of brain tumor, as well as projects to understand the nature of vision.
All along, Allen has been backing parallel projects in artificial brains.
He wondered whether it might be possible to encode books — especially textbooks — into a computer brain to create a foundation upon which a machine could be a digital Aristotle, using a higher level of knowledge to interact with humans.
That idea grew into the Allen Institute for Artificial Intelligence (or AI2 as it is called by its employees), which opened Jan. 1, 2014, and has 43 employees. Etzioni said Allen’s investment is in the tens of millions of dollars and is growing.
In the past year, Etzioni and his team have created Aristo. The institute’s first digital entity now is being trained to pass the New York State Regents high school biology exam.
Not only do the engineers have to figure out how to represent memory, but they have to give this entity the ability to parse natural language and make complex inferences.
It’s not as easy as it sounds.
“It’s paradoxical that things that are hard for people are easy for the computer, and things that are hard for the computer any child can understand,” Etzioni said. For example, he said, computers have a difficult time understanding simple sentences such as “People breathe air.” A computer might wonder: Does this apply to dead people? What about people holding their breath? All the time?
So far, Aristo has passed the first-, second- and third-grade biology tests and is working his way through the fourth.
Etzioni estimates that Aristo needs at least one more year to pass fourth-grade biology, mostly because the team needs to figure out image recognition and visual processing so that the computer can interpret the diagrams. Five more to pass the eighth-grade test.
After that, who knows?
The implications of this work are incredibly complex.
“There’s a huge debate right now about whether simulating the human brain is necessary to get the kind of AI we want or whether simulating the human brain would be the equivalent of reproducing the brain,” said Jonathan Moreno, University of Pennsylvania bioethicist. “Nobody knows exactly what this means.”
