Jeff Hawkins hacks the human brain (Cont.)
Like the brain, it's a memory system arranged in a hierarchy of nodes where patterns and sequences of patterns are stored. These memory nodes pass information between levels as it comes streaming in over time from sensors connected to whatever is being observed - X-ray images, traffic patterns on highways or phone networks, engine or equipment performance. The idea is to first train an HTM by showing it enough data to create an accurate model and then set it loose to make predictions based on constantly changing new information from the real world.
When he first heard about Numenta, Atkinson, the former Apple (Charts) engineer, practically begged Hawkins to let him work there. In addition to his impeccable software credentials, Atkinson also knows a thing or two about the brain. Before Steve Jobs sidetracked him in the late 1970s, he spent 10 years pursuing a Ph.D. in neuroscience (which, like Hawkins, he never finished). At a meeting in Hawkins's office, Atkinson noticed the 1979 issue of Scientific American and pointed out his name in the credits: He had created the cover art, a 3-D computer graphics image of the brain. Atkinson was a shoo-in.
While not exactly an employee, Atkinson was one of the few early outside developers at Numenta and is given special access to weekly engineering meetings. Taking a page from his Apple days, he's developing simple demo applications to teach other programmers how to write software for a Numenta computer. One of his apps, for instance, can identify any of 15 languages based on a snippet of text. Another is training a computer to distinguish between the writings of authors such as Mark Twain and Nathaniel Hawthorne based solely on its knowledge of their previous works.
The key difference between an HTM and a regular computer is that you don't program an HTM. It learns by itself through observation. This could fundamentally change the relationship between the programmer and the computer. "The programmer's job is no longer to tell it what to do," Atkinson notes. "An HTM can deliver more intelligence than the programmer has because it can learn things the programmer does not understand."
Ultimately, this simple fact could have profound implications. "As we build smart computers, will we feel dumb because we don't understand how this machine gets the answers right?" Saal asks. "I think that's about to happen."