1 00:00:01,426 --> 00:00:04,086 >> As an industrial scientist, a lot of what we try 2 00:00:04,086 --> 00:00:06,916 to do is learn from the - the world of academics 3 00:00:07,436 --> 00:00:10,536 that ask very interesting questions, internalize that, 4 00:00:10,536 --> 00:00:12,656 and turn that into things that help the company, help - 5 00:00:12,856 --> 00:00:14,966 help society in a broad sense, that's our mission, right? 6 00:00:15,676 --> 00:00:18,596 Proctor and Gamble is all about building products 7 00:00:18,596 --> 00:00:20,576 that make the lives of rural consumers better. 8 00:00:21,906 --> 00:00:24,696 That requires us to engineer products in very interesting 9 00:00:24,696 --> 00:00:28,866 and unique sort of ways, that physics, the understanding 10 00:00:28,866 --> 00:00:31,416 to make that, is often difficult to get, 11 00:00:31,926 --> 00:00:34,636 and this is a unique environment to get some very helpful 12 00:00:34,636 --> 00:00:36,666 and very useful information to design those products. 13 00:00:37,936 --> 00:00:40,536 Everything that we do in terms of extraction of - 14 00:00:40,756 --> 00:00:43,906 of information out of the data is all about the particles 15 00:00:43,906 --> 00:00:45,976 and what we can see, where they are, how they change in time. 16 00:00:46,436 --> 00:00:48,936 The M1 [phonetic] experiment was a great experiment to the extent 17 00:00:48,936 --> 00:00:51,186 that it provided some interesting nuances, 18 00:00:51,186 --> 00:00:54,436 some interesting ideas and concepts, but it was hard to get 19 00:00:54,436 --> 00:00:55,896 with kind of some of the fuzzier pictures, 20 00:00:55,896 --> 00:00:57,446 it was hard to get the quantitative information 21 00:00:57,446 --> 00:00:58,726 we needed. 22 00:00:58,726 --> 00:00:59,946 The confocal scope brings all 23 00:00:59,946 --> 00:01:01,156 that quantitative information in, 24 00:01:01,196 --> 00:01:03,736 so we really think we're going to get a lot more science, 25 00:01:03,736 --> 00:01:06,116 a lot more information out of the data this time around. 26 00:01:06,796 --> 00:01:08,686 I'd like to be in a position when these things go 27 00:01:08,686 --> 00:01:10,916 up on station, and - and are being run, 28 00:01:11,466 --> 00:01:12,766 we get the best data that we can. 29 00:01:13,286 --> 00:01:15,026 We can do that here on the ground, 30 00:01:15,026 --> 00:01:17,826 we can get some good sense of what it's going to tell us, 31 00:01:18,236 --> 00:01:19,976 make adjustments accordingly on ground 32 00:01:19,976 --> 00:01:21,176 so that all the time we spent 33 00:01:21,176 --> 00:01:22,596 on station is the most valuable time. 34 00:01:22,966 --> 00:01:26,176 I think exploration, getting to the moon, getting to Mars, 35 00:01:26,506 --> 00:01:27,976 it's about how you do these thing 36 00:01:28,246 --> 00:01:29,726 with as little material as possible. 37 00:01:30,426 --> 00:01:33,426 If we do our job right here, we create all 38 00:01:33,426 --> 00:01:34,916 of the things we need, all the products we need, 39 00:01:35,256 --> 00:01:38,006 with as little material as possible.