WASHINGTON — The human brain is remarkably efficient. Using a few dozen watts of energy, it performs information-processing functions that would take a conventional computer millions of watts to replicate. But a new Defense Department-funded IBM computer chip could enable machines to start catching up.
The TrueNorth computer chip is a “neuromorphic” chip that mimics human neurons and performs unusually advanced computations using far less energy than conventional chips, said Qing Wu, the principal electronics engineer at the Air Force Research Laboratory at Wright-Patterson Air Force Base, Ohio. The technology could be a huge boost for artificial intelligence-based defense systems and the human data analysts who use them, he added.
“This is about building more intelligent machines that will work with humans to make human operators and analysts be more effective and efficient when dealing with data,” Wu said. “The major advantage of this chip is it runs machine learning algorithms — the same ones as we run, the same functionality, same accuracy, but with much less power dissipation.”
In June, IBM announced that it will build a new supercomputer powered by 64 TrueNorth chips for the Air Force Research Lab, which lab officials plan to use for analytics involving pattern and object recognition and “sensory processing” — converting audio, video and other forms of data received by sensors into symbols that the computer can process. Though conventional computers can perform these tasks, they require huge numbers of processors, which consume heavy amounts of electricity.
TrueNorth brings the wattage down. Dharmendra Modha, the lead researcher of IBM’s brain-inspired computing group, reported in an article posted on the company’s website that the TrueNorth chip uses no more than 70 milliwatts of power, which he said is “four orders of magnitude lower” than a conventional computer chip’s power consumption.
“The architecture … has the potential to revolutionize the computer industry by integrating brain-like capability into devices where computation is constrained by power and speed,” Modha said in a statement in 2014, when IBM built the first chip.
A conventional chip has a central processing unit, but TrueNorth contains a million “neurons” that transmit data back and forth in a way similar to human brain neurons, Modha explained. The neurons communicate throughout the system using patterns of pulses similar to the way human neurons use electrochemical pulses, he said.
TrueNorth’s neurons are packed in clusters inside interconnected “cores” across the chip, IBM officials said in the June 23 news release announcing the company’s collaboration with the Air Force Research Lab. Each core also holds components for information storage, processing, and communication.
By contrast, a conventional chip stores information in a memory drive and processes it in the central processing unit, he said. It constantly shuttles the data back and forth between them and burns energy along the way. Because TrueNorth’s cores do both data storage and data processing, these energy-intensive data swaps are eliminated.
The human brain also integrates thought and memory, Modha said, which partly explains why the average brain consumes only 20 watts of energy. The IBM Sequoia, one of the fastest conventional supercomputers, has less computing power than the brain and consumes 7.9 megawatts.
An AI Data-Analysis Partner
William Halal, a George Washington University professor of management, technology and innovation, and founder of the technology-forecasting think tank TechCast, said a neuromorphic computer like TrueNorth can “think” in ways few conventional computers can: It excels at parallel processing — that is, running multiple calculations at once — and interpreting, finding patterns or drawing conclusions from data, he said.
Halal pointed out that while these data-reading skills come naturally to humans, they’re difficult for conventional computers. Where conventional computers store and process data, but need human users to tell them which data is most important and what to do with it, TrueNorth has no such limitations, he said. It could discern in advance what the user might want to know and gather data accordingly — or connect sets of data to spot a trend all on its own.
“The real advantage to this computing is that it operates differently,” Halal said. “It’s more intelligent. It does things the way humans think. It offers the prospect of modeling these complex human cognitive processes that have resisted being developed with the present architecture.”
TrueNorth’s heightened capabilities could help human defense analysts comb through data and spot vital information more quickly, said Mark Barnell, a senior computer scientist with the Air Force Research Lab’s information directorate. He said he hopes that this, in turn, could enable military planners at all levels to make better-informed decisions in less time.
“The computer could look through the data quickly and tell us if there is something interesting and if there is something worth looking more at,” Barnell said. “It would close the timeline of collecting the data and disseminating information.”
TrueNorth’s story starts in 2008, when the Defense Advanced Research Projects Agency launched its Systems of Neuromorphic Adaptive Plastic Scalable Electronics program. The mission was to build computer systems whose functioning resembles a living mammal’s brain — including the brain’s learning and problem-solving abilities. SyNAPSE contracted the research work to IBM and HRL Laboratories.
This program ran until 2014, by which time IBM had pioneered TrueNorth. And the research and development continues today at the Air Force Research Lab’s facilities. The lab’s upcoming computer will be the first time that so many chips will work together on one system, Barnell noted.
DoD and AI
Barnell said energy efficiency is one reason that he and colleagues are looking forward to this computer, but that he’s anticipating something even greater: This new system, with its brain-like architecture, will be a very real step toward true artificial intelligence, he said, becoming a powerful way of doing computation that in some ways mimic biological systems.
Artificial intelligence is already integral to many DoD operations, said Craig Arndt, a Defense Acquisition University professor of systems engineering. He cites facial-recognition systems, unmanned vehicles, and “predictive maintenance” systems that identify internal mechanical problems and alert human operators of them as several examples. DoD supported development of each one and found defense-relevant purposes for each, he said.
“AI has been around for a long time, and is a very broad area of research, and DoD has been involved in that research at its service labs pretty much the entire time,” Arndt said. “It has been an important area of computer science for us because of the problems it tries to solve.”