 We all know it's not sustainable for health care to be 16% of our GDP and growing. We all know it's not sustainable to spend $8,000 per year per individual on health care. That doesn't translate around the world. So we're creating devices that will democratize medicine. We're different than other companies that are working in health care, health care devices or health care software in a critical way. You have a huge number of companies doing software, but they don't have anything unique in terms of the information that they're feeding that software. You have a smaller set of companies but large companies that are building wearables. You have Apple coming out with an eye watch. But those wearables really aren't looking at the world in a new way. They're using standard electronics. And so what we do, we make a sensor that can see something that no one else can see. What we're doing is adding, if you will, senses to electronics. So a cell phone can see. A microphone allows electronics to hear. We're allowing electronics to see in new ways. So if you think about the medical fields, you think about ultrasound, you think about CAT scan, you think about MRI, we want to add all of those capabilities to electronics. We're one of the only groups in the world, if not the only group in the world, that can take a device and allow it to have a sense that it's never had before. Our team showed that with IonTorrent when we were the only team in the world that was able to make a chip that can see chemistry. Now we're making chips that can see lots of different things. But what we learned from IonTorrent and what we learned from 454, while it was great to have a first device, while it was great to be able to do something that no one could do before, we wanted to do more. We wanted to be able to accumulate the knowledge from separate experiments. We're taking advantage of the fact that in 2014, you can have a cloud that has all the proper regulatory approvals to put medical information in it. So now we have a device and a place to store information, not on one patient, but tens of thousands of patients, hundreds of thousands of patients, or even millions of patients. So first device, the ability to accumulate that information. And now, for the first time, we have algorithms that can handle the information. Previously, you could never finish what people had referred to as the virtuous circle of AI, where you would have information, you process that information, and you would make your applications better and better. But if you've noticed what's happened in speech recognition, in translation, in image recognition, a new technology or new methodology called deep learning has cracked all of those problems. Computers can now understand what we say. Computers can now translate text. Computers can now search images. We're taking advantage of our experience and ability to make devices. We're taking advantage of the world putting a huge investment into clouds that are ready for healthcare. And we're taking advantage of being a first mover and having a new type of information and applying deep learning to it. It's an amazing moment. It really is a renaissance.