Jeff Hawkins: Where open source and machine learning meet big data

The Palm pioneer has turned to neuroscience and big data to create a path to truly intelligent machines -- a path open to the community's contributions

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I'd sum it up as "using brain science to work out how to handle big data."

That's one way of looking at it. I'm a neuroscientist, so I always want to talk about the neuroscience, but from a hacker or coding point of view, yes. Today, what you can do with it is stream fast data to it, and it builds models of the data in an online fashion, meaning every record that comes in its updating the model, it makes predictions, and it can detect anomalies.

I'll give you an example, a simple example we actually did. People are interested in predicting energy usage. A building consumes energy throughout the day -- it's up and down depending on what the building is doing or what's going on. If you can predict what the energy consumption will be four hours from now or 24 hours from now, it's sometimes advantageous. You can pre-cool the building, you can do a thing called demand response where you basically buy energy at different prices. That's the kind of thing we do with our product Grok today. It works very well at that. Constantly learning, and if the patterns in the world change, it adapts to it automatically.

What was it that made you give up Palm Pilots and get into neuroscience instead?

I think that brain science -- understanding the brain and how it works and building intelligent machines -- is actually a bigger societal impact long-term than mobile computing. Much, much larger. You know, absolutely everyone in the world is going to have a computer in their pocket; it's a process for democratization and education, so thats all great. But people don't realize yet how big intelligent machines are going to be. It's sort of like starting the whole computing industry all over again.

In my OSCON talk, I mentioned that we're like the 1950s in computing. The 1950s in computing was when they were just starting to build computers, they were just starting to be useful, but we had decades of advances still to go. Today, we're starting to build intelligent machines that work on the principles of the brain, we're just getting started, and it's going to be decades. But where it's going, it's just going to be unbelievable. We're going to be able to make machines that are a million times faster at thinking than we are. We're going to be able to make machines that have much more memory than we do. We're going to be able to make machines that can sense things that we can't sense.

It's hard to know where its going to go, just as in the 1950s it was hard to know where the computer was going to go. But intelligent machines, machines that learn in the way that brains do, are just going to have an amazing impact on society, the Earth, and humanity.

How do you think being an open source project is going to contribute toward achieving that vision for you?

First of all, my goal has always been to make this happen sooner, to be a catalyst for this, so anything I can do to spread ideas is a good thing. I'm not in this at this point trying to make a lot of money. I'm in this because I think it's cool, it's fun, it's good to do, it's important.

Even though we made this technical, scientific discovery four years ago and we published it, I waited until we had real demand before we made an open source project. I wanted people to come to me, and they did! People came to us and said, "Can you give us the source code to this, it's really cool, we want to work on this," "I want to use my PhD thesis on this," "We want to embed it." So when people asked us, we said, "Great!" -- and of course this was my goal from the beginning.

You can't help but put these ideas out there -- putting the code out there, showing how this stuff works. Some number of people are going to pick it up, they're going to go, "This is great, I get it," they're going to invest in it. It's not something anyone can own, it's not one thing. it's like saying, "Could the computing industry be closed?" No, it couldn't, it had to have lots of competitors, lots of ideas, and this is like that.

This article, "Jeff Hawkins: Where open source and machine learning meet big data," was originally published at InfoWorld.com. Read more of the Open Sources blog and follow the latest developments in open source at InfoWorld.com. For the latest business technology news, follow InfoWorld.com on Twitter.

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