Today, Xerox PARC remains an active operation with a host of commercial clients, focused in areas that include printed electronics, data and analytics, cleantech, and contextual intelligence. The Xerox Palo Alto Research Center, which most people refer to as Xerox PARC, is one of the most fabled institutions in Silicon Valley. PARC is also where Steve Jobs and early Apple engineers took inspiration for aspects of the Macintosh computer.
Internet of Things Opportunity
How do I do low cost, highly distributed sensing if I’m going to put the things on the Internet? If it takes $100 to put a smart computer on a bottle of vaccine to measure its temperature during shipping, well I won’t do that.
If I want to put a temperature sensor on a bottle of vaccine for 50 cents, I don’t need a whole lot of intelligence, and it’s gotten cheaper with silicon to cram more and more intelligence. But I want is price down at a dollar with a smart label sensor to sense those things.
We’re working on technologies, like printed electronics, to make very low-cost electronics that are smart enough. We think that’s the Internet of Everyday Things.
The Internet of Things is about Googling reality. It’s about right now; my body is the sensor. I see things, I hear things, I sense the world around me. Why does that have to be geosynchronous and why does it have to be synchronous in time and space from where I’m at, which is what my sensors normally are.
I can instrument and understand what my customers are doing with my products across the world now. I can see if those devices are starting to fail. I can adapt their behavior to be responsive to the local environment. [For example,] GE and their jet engines: when a plane’s running into a headwind, the jet engine can run differently because it knows I’m in that situation.
Couple the Internet of Things with data analytics and machine learning to make sense of all that data, to get a job done.
The Future of Internet of Things
I think there are interesting long-term opportunities for what we call ‘systems of systems. For example, satellite swarms. Right now, we build one big satellite and send it up in space; that satellite is expensive and if it fails you’re done.
Instead, what if instead I could build a series of small satellites that are all individually re-deployable but can are controllable in a coordinated way. So, it’s a swarm of 50 satellites, small and cheap. If one dies, that’s okay.
When I want a lot of imagery on a certain place, I’ll aim 50 of them at the same location; when I don’t, I distribute them [more broadly]. There’s a challenge because you’ve got a complex system and you’re redesigning it constantly during use because you want it to do different things. As pieces fail and don’t fail, you task them to look at different problems, to sense different things. There’s a whole science around AI planning and managing that system of systems.
But, back to my human-computer team. In the end, those systems are being tasked by a human. How does a human interact and manage that level of complexity while ensuring the system has local autonomy and understands what the human is trying to do? We’re working in that space.
Think about the Google autonomous car. When you’ve got thousands of autonomous cars on a road, how do they behave together? And how do they behave with the humans who interact with them? We think that’s where the next wave of complexity will occur in automation. It’s going to be systems of systems interacting.
So the next challenges in IoT development is not just about Security. It is more into how to make them working together and behave the interaction between human and device. You can also read the whole script of discussion here.