WEBVTT 00:00:00.758 --> 00:00:05.446 We know more about other planets than our own, 00:00:05.446 --> 00:00:08.694 and today, I want to show you a new type of robot 00:00:08.694 --> 00:00:11.582 designed to help us better understand 00:00:11.582 --> 00:00:13.670 our own planet. 00:00:13.670 --> 00:00:15.260 It belongs to a category 00:00:15.260 --> 00:00:20.471 known in the oceanographic community as an unmanned surface vehicle, or USV, 00:00:20.471 --> 00:00:23.138 and it uses no fuel. 00:00:23.138 --> 00:00:27.267 Instead, it relies on wind power for propulsion, 00:00:27.267 --> 00:00:29.551 and yet it can sail around the globe 00:00:29.551 --> 00:00:31.641 for months at a time. 00:00:31.641 --> 00:00:34.155 So I want to share with you why we built it, 00:00:34.155 --> 00:00:35.963 and what it means for you. NOTE Paragraph 00:00:37.989 --> 00:00:42.596 A few years ago, I was on a sailboat making its way across the Pacific, 00:00:42.596 --> 00:00:45.479 from San Francisco to Hawaii. 00:00:45.479 --> 00:00:47.728 I had just spent the past 10 years 00:00:47.728 --> 00:00:51.901 working nonstop developing video games for hundreds of millions of users, 00:00:51.901 --> 00:00:55.224 and I wanted to take a step back and look at the big picture 00:00:55.224 --> 00:00:57.731 and get some much-needed thinking time. 00:00:58.109 --> 00:01:00.169 I was the navigator on board, 00:01:00.169 --> 00:01:03.762 and one evening, after a long session analyzing weather data 00:01:03.762 --> 00:01:05.414 and plotting our course, 00:01:05.414 --> 00:01:08.750 I came up on deck and saw this beautiful sunset, 00:01:08.750 --> 00:01:10.448 and a thought occurred to me; 00:01:10.448 --> 00:01:14.903 how much do we really know about our oceans? 00:01:14.903 --> 00:01:19.509 The Pacific was stretching all around me as far as the eye could see, 00:01:19.509 --> 00:01:21.516 and the waves were rocking our boat forcefully, 00:01:21.516 --> 00:01:25.696 a sort of constant reminder of its untold power. 00:01:25.696 --> 00:01:29.243 How much do we really know about our oceans? 00:01:29.243 --> 00:01:31.013 I decided to find out. NOTE Paragraph 00:01:32.497 --> 00:01:35.690 What I quickly learned is that we don't know very much, 00:01:35.690 --> 00:01:38.645 and the first reason is just how vast oceans are, 00:01:38.645 --> 00:01:41.010 covering 70 percent of the planet, 00:01:41.010 --> 00:01:46.188 and yet we know they drive complex planetary systems 00:01:46.188 --> 00:01:46.638 like global weather, 00:01:46.638 --> 00:01:48.244 which affect all of us on a daily basis, 00:01:48.244 --> 00:01:50.824 sometimes dramatically. 00:01:50.824 --> 00:01:54.424 And yet, those activities are mostly invisible to us. NOTE Paragraph 00:01:54.424 --> 00:01:58.733 Ocean data is scarce by any standards. 00:01:58.733 --> 00:02:04.577 Back on land, I had grown used to accessing lots of sensors, 00:02:04.577 --> 00:02:06.576 billions of them actually, 00:02:06.576 --> 00:02:13.766 but at sea, in situ data is scarce and expensive. 00:02:13.766 --> 00:02:17.919 Why? Because it relies on a small number of ships and buoys. 00:02:17.919 --> 00:02:21.083 How small a number was actually a great surprise. 00:02:21.083 --> 00:02:24.474 Our National Oceanic and Atmospheric Administration, 00:02:24.474 --> 00:02:26.121 better known as NOAH, 00:02:26.121 --> 00:02:28.474 only has 16 ships 00:02:28.474 --> 00:02:33.972 and there are less than 200 buoys offshore globally. 00:02:33.972 --> 00:02:35.813 It is easy to understand why. 00:02:35.813 --> 00:02:37.804 The oceans are an unforgiving place, 00:02:37.804 --> 00:02:41.161 and to collect in situ data, you need a big ship 00:02:41.161 --> 00:02:43.433 capable of carrying a vast amount of fuel 00:02:43.433 --> 00:02:45.442 and large crews, 00:02:45.442 --> 00:02:48.390 costing hundreds of millions of dollars each, 00:02:48.390 --> 00:02:54.223 or big buoys tethered to the ocean floor with a four-mile-long cable 00:02:54.223 --> 00:02:57.663 and weighted down by a set of train wheels 00:02:57.663 --> 00:03:02.740 which is both dangerous to deploy and expensive to maintain. NOTE Paragraph 00:03:02.740 --> 00:03:05.227 What about satellites, you might ask? 00:03:05.227 --> 00:03:07.153 Well, satellites are fantastic, 00:03:07.153 --> 00:03:09.733 and they have taught us so much about the big picture 00:03:09.733 --> 00:03:11.527 over the past few decades. 00:03:11.527 --> 00:03:13.736 However, the problem with satellites 00:03:13.736 --> 00:03:16.381 is they can only see through one micron 00:03:16.381 --> 00:03:18.284 of the surface of the ocean. 00:03:18.284 --> 00:03:23.028 They have relatively poor spatial and temporal resolution, 00:03:23.028 --> 00:03:25.560 and their signal needs to be corrected 00:03:25.560 --> 00:03:29.011 for cloud cover and land effects and other factors. NOTE Paragraph 00:03:30.262 --> 00:03:33.821 So what is going on in the oceans? 00:03:33.821 --> 00:03:35.884 And what are we trying to measure? 00:03:35.884 --> 00:03:39.421 And how could a robot be of any use? 00:03:39.421 --> 00:03:43.542 Let's zoom in a small cube in the oceans. 00:03:43.542 --> 00:03:46.743 One of the key things we want to understand is the surface, 00:03:46.743 --> 00:03:48.642 because the surface, if you think about it, 00:03:48.642 --> 00:03:52.212 is the nexus of all air-sea interaction. 00:03:52.212 --> 00:03:56.960 It is the interface through which all energy and gases must flow. 00:03:57.664 --> 00:03:59.929 Our Sun radiates energy, 00:03:59.929 --> 00:04:02.917 which is absorbed by oceans as heat 00:04:02.917 --> 00:04:05.413 and then partially released into the atmosphere. 00:04:05.683 --> 00:04:08.442 Gases in our atmosphere like CO2 00:04:08.442 --> 00:04:10.353 get dissolved into our oceans. 00:04:10.353 --> 00:04:14.841 Actually, about 30 percent of all global CO2 gets absorbed. 00:04:14.841 --> 00:04:18.576 Plankton and microorganisms release oxygen into the atmosphere, 00:04:18.576 --> 00:04:22.505 so much so that every other breath you take comes from the ocean. 00:04:22.770 --> 00:04:25.661 Some of that heat generates evaporation, which creates clouds 00:04:25.661 --> 00:04:27.978 and then eventually leads to precipitation, 00:04:27.978 --> 00:04:29.988 and pressure gradients create surface wind 00:04:29.988 --> 00:04:33.731 which move the moisture through the atmosphere. 00:04:33.731 --> 00:04:36.361 Some of the heat radiates down 00:04:36.361 --> 00:04:38.134 into the deep ocean 00:04:38.134 --> 00:04:40.019 and gets stored in different layers, 00:04:40.019 --> 00:04:43.465 the ocean acting as some kind of planetary-scale boiler 00:04:43.465 --> 00:04:44.986 to store all that energy 00:04:44.986 --> 00:04:48.645 which later might be released in short-term events like hurricanes 00:04:48.645 --> 00:04:51.592 or long-term phenomena like El Nino. 00:04:51.592 --> 00:04:55.867 These layers can get mixed up by vertical upwelling currents 00:04:55.867 --> 00:05:00.053 or horizontal currents, which are key in transporting heat 00:05:00.053 --> 00:05:01.917 from the tropics to the poles, 00:05:01.917 --> 00:05:04.659 and of course there is marine life, 00:05:04.659 --> 00:05:09.698 occupying the largest ecosystem in volume on the planet, 00:05:09.698 --> 00:05:12.305 from microorganisms to fish to marine mammals 00:05:12.305 --> 00:05:16.647 like seals, dolphins, and whales. NOTE Paragraph 00:05:16.647 --> 00:05:21.324 But all of these are mostly invisible to us. 00:05:21.324 --> 00:05:27.221 The challenge in studying those ocean variables at scale 00:05:27.221 --> 00:05:29.419 is one of energy, 00:05:29.419 --> 00:05:34.377 the energy that it takes to deploy censors into the deep ocean. 00:05:34.377 --> 00:05:37.298 And of course, many solutions have been tried, 00:05:37.298 --> 00:05:38.819 from wave-actuated devices 00:05:38.819 --> 00:05:40.244 to surface drifters 00:05:40.244 --> 00:05:43.520 to sun-powered electrical drives, 00:05:43.520 --> 00:05:46.071 each with their own compromises. 00:05:46.071 --> 00:05:49.154 Our team breakthrough came from an unlikely source, 00:05:49.154 --> 00:05:54.132 the pursuit of the world speed record in a wind-powered land yacht. 00:05:54.132 --> 00:05:56.569 It took 10 years of research and development 00:05:56.569 --> 00:05:58.898 to come up with a novel wing concept 00:05:58.898 --> 00:06:02.778 that only uses three watts of power to control 00:06:02.778 --> 00:06:06.047 and yet can propel a vehicle all around the globe 00:06:06.047 --> 00:06:08.492 with seemingly unlimited autonomy. 00:06:08.492 --> 00:06:12.428 By adapting this wing concept into a marine vehicle, 00:06:12.428 --> 00:06:15.899 we had the genesis of an ocean drone. NOTE Paragraph 00:06:15.899 --> 00:06:17.868 Now, these are larger than they appear. 00:06:17.868 --> 00:06:22.427 They are about 15 feet high, 23 feet long, seven feet deep. 00:06:22.427 --> 00:06:24.854 Think of them as surface satellites. 00:06:24.854 --> 00:06:27.477 They're laden with an array of science-grade sensors 00:06:27.477 --> 00:06:30.433 that measure all key variables, 00:06:30.433 --> 00:06:32.655 both oceanographic and atmospheric, 00:06:32.655 --> 00:06:37.035 and a live satellite link transmits this high-resolution data 00:06:37.035 --> 00:06:39.754 back to shore in real time. 00:06:39.754 --> 00:06:42.718 Our team has been hard at work over the past few years 00:06:42.718 --> 00:06:47.409 conducting missions in some of the toughest ocean conditions on the planet, 00:06:47.409 --> 00:06:49.897 from the Arctic to the tropical Pacific. 00:06:49.897 --> 00:06:52.726 We have sailed all the way to the polar ice shelf. 00:06:52.726 --> 00:06:55.231 We have sailed into Atlantic hurricanes. 00:06:55.231 --> 00:06:57.360 We have rounded Cape Horn, 00:06:57.360 --> 00:07:00.539 and we have slalomed between the oil rigs of the Gulf of Mexico. 00:07:00.539 --> 00:07:03.883 This is one tough robot. NOTE Paragraph 00:07:03.883 --> 00:07:07.067 Let me share with you a recent work that we did 00:07:07.067 --> 00:07:08.763 around the Pribilof Islands. 00:07:08.763 --> 00:07:12.518 This is a small group of islands deep in the cold Bering Sea 00:07:12.518 --> 00:07:15.126 between the US and Russia. NOTE Paragraph 00:07:15.126 --> 00:07:18.397 Now, the Bering Sea is the home of the walleye pollock. 00:07:18.397 --> 00:07:21.474 It is a white fish you might not recognize but you might likely have tasted 00:07:21.474 --> 00:07:25.589 if you enjoy fish sticks or ?? 00:07:25.589 --> 00:07:29.763 Yes, ?? looks like crab meat, but it's actually pollock. 00:07:29.763 --> 00:07:32.942 And the pollock fishery is the largest fishery in the nation, 00:07:32.942 --> 00:07:35.813 both in terms of value and volume, 00:07:35.813 --> 00:07:39.306 about 3.1 billion pounds of fish caught every year. 00:07:39.306 --> 00:07:42.418 So over the past few years, a fleet of ocean drones 00:07:42.418 --> 00:07:44.790 has been hard at work in the Bering Sea 00:07:44.790 --> 00:07:49.049 with the goal to help assess the size of the pollock fish stock. 00:07:49.049 --> 00:07:52.942 This helps improve the quota system that's used to manage the fishery 00:07:52.942 --> 00:07:55.407 and help prevent a collapse of the fish stock, 00:07:55.407 --> 00:07:58.375 and protects this fragile ecosystem. 00:07:58.375 --> 00:08:03.843 Now, the drones survey the fishing ground using acoustics, 00:08:03.843 --> 00:08:05.077 ie. of sonar. 00:08:05.077 --> 00:08:08.632 This sends a sound wave downwards 00:08:08.632 --> 00:08:11.724 and then the reflection, the echo from the sound wave 00:08:11.724 --> 00:08:14.404 from the seabed or schools of fish, gives us an idea of what's happening 00:08:14.404 --> 00:08:16.191 below the surface. 00:08:16.191 --> 00:08:20.054 Our ocean drones are actually pretty good at this repetitive task, 00:08:20.054 --> 00:08:24.034 so they have been gridding the Bering Sea day in, day out. NOTE Paragraph 00:08:24.034 --> 00:08:31.496 Now, the Pribilof Islands are also the home of a large colony of fur seals. 00:08:31.496 --> 00:08:36.374 In the 1950s, there were about two million individuals in that colony. 00:08:36.374 --> 00:08:38.075 Sadly, these days, 00:08:38.075 --> 00:08:40.759 the population has rapidly declined, 00:08:40.759 --> 00:08:42.647 and there's less than 50 percent of that number left, 00:08:42.647 --> 00:08:45.437 and the population continues to fall rapidly. NOTE Paragraph 00:08:45.437 --> 00:08:47.846 So to understand why, 00:08:47.846 --> 00:08:52.102 our science partner at the National Marine Mammal Laboratory 00:08:52.102 --> 00:08:55.263 has fitted a GPS tag on some of the mother seals, 00:08:55.263 --> 00:08:56.887 glued to their furs. 00:08:56.887 --> 00:08:59.678 And this tag measures location and depth 00:08:59.678 --> 00:09:02.242 and also has a really cool little camera 00:09:02.242 --> 00:09:04.494 that's triggered by sudden acceleration. 00:09:04.494 --> 00:09:08.145 Here is a movie taken by an artistically inclined seal 00:09:08.145 --> 00:09:12.132 giving us an unprecedented insight into an underwater hunt 00:09:12.132 --> 00:09:13.969 deep in the Arctic, 00:09:13.969 --> 00:09:16.364 and the shot of this pollock prey 00:09:16.364 --> 00:09:19.153 just seconds before it gets devoured. NOTE Paragraph 00:09:19.153 --> 00:09:22.744 Now, doing work in the Arctic is very tough, even for a robot. 00:09:22.744 --> 00:09:25.358 They had to survey a snowstorm in August 00:09:25.358 --> 00:09:28.491 and interferences from bystanders 00:09:28.491 --> 00:09:32.155 like this spotted seal enjoying a ride. NOTE Paragraph 00:09:32.155 --> 00:09:34.740 (Laughter) NOTE Paragraph 00:09:34.740 --> 00:09:41.896 Now, the seal tags have recorded over 200,000 dives over the season, 00:09:41.896 --> 00:09:43.982 and upon a closer look, 00:09:43.982 --> 00:09:47.266 we get to see the individual seal tracks 00:09:47.266 --> 00:09:49.643 and the repetitive dives. 00:09:49.643 --> 00:09:52.774 We are on our way to decode what is really happening 00:09:52.774 --> 00:09:54.284 over that foraging ground, 00:09:54.284 --> 00:09:56.481 and it's quite beautiful. 00:09:56.481 --> 00:09:59.907 Once you superimpose the acoustic data collected by the drones, 00:09:59.907 --> 00:10:02.135 a picture starts to emerge. 00:10:02.135 --> 00:10:06.451 As the seal leaves the islands and swims from left to right, 00:10:06.451 --> 00:10:10.986 they are observed to dive 00:10:10.986 --> 00:10:15.555 at a relatively shallow depth of about 20 meters, 00:10:15.555 --> 00:10:16.953 which the drone identifies is populated by small young pollock 00:10:16.953 --> 00:10:17.399 with low calorific content. 00:10:17.399 --> 00:10:21.350 The seals them swim much greater distance and start to dive deeper 00:10:21.350 --> 00:10:26.045 to a place where the drone identifies larger, more adult pollock 00:10:26.045 --> 00:10:28.117 which are more nutritious as fish. 00:10:28.117 --> 00:10:33.462 Unfortunately, the calories expended by the mother seals 00:10:33.462 --> 00:10:34.410 to swim this extra distance 00:10:34.410 --> 00:10:39.480 don't leave them with enough energy to lactate their pups back on the island, 00:10:39.480 --> 00:10:42.790 leading to the population decline. 00:10:42.790 --> 00:10:48.041 Further, the drones identify that the water temperature around the island 00:10:48.041 --> 00:10:49.749 has significantly warmed. 00:10:49.749 --> 00:10:54.133 It might be one of the driving forces that's pushing the pollock north 00:10:54.133 --> 00:10:56.988 and to spread in search of colder regions. 00:10:56.988 --> 00:10:59.186 So the data analysis is ongoing, but already we can see 00:10:59.186 --> 00:11:03.866 that some of the pieces of the puzzle from the fur seal mystery 00:11:03.866 --> 00:11:05.859 are coming into focus. NOTE Paragraph 00:11:05.859 --> 00:11:08.538 But if you look back at the big picture, 00:11:08.538 --> 00:11:11.238 we are mammals too, 00:11:11.238 --> 00:11:14.965 and actually the oceans provide up to 20 kilos of fish per human per year, 00:11:14.965 --> 00:11:16.693 and as we deplete our fish stocks, what can we humans learn 00:11:16.693 --> 00:11:19.932 from the fur seal story? 00:11:19.932 --> 00:11:23.363 And beyond fish, the oceans affect all of us daily 00:11:23.363 --> 00:11:25.305 as they drive global weather systems, 00:11:25.305 --> 00:11:27.848 which affect things like global agricultural output 00:11:27.848 --> 00:11:32.214 or can lead to devastating destruction of lives and property 00:11:32.214 --> 00:11:36.106 through hurricanes, extreme heat and floods. 00:11:36.106 --> 00:11:39.798 Our oceans are pretty much unexplored and ??, 00:11:39.798 --> 00:11:44.258 and today we still know more about other planets than our own. 00:11:44.258 --> 00:11:48.069 But if you divide this vast ocean in 6x6 degree squares, 00:11:48.069 --> 00:11:51.330 each about 400 miles long, 00:11:51.330 --> 00:11:53.896 you'd get about a thousand such squares, 00:11:53.896 --> 00:11:57.812 so little bit little, working with our partners, 00:11:57.812 --> 00:12:00.352 we are deploying one ocean drone in each of those boxes, 00:12:00.352 --> 00:12:02.962 the hope being that achieving planetary coverage 00:12:02.962 --> 00:12:07.148 will give us better insights into those planetary systems 00:12:07.148 --> 00:12:08.071 that affect humanity. 00:12:08.071 --> 00:12:09.619 We have been using robots 00:12:09.619 --> 00:12:13.209 to study distant worlds in our Solar System for a while now. 00:12:13.209 --> 00:12:16.440 Now it is time to quantify our own planet, 00:12:16.440 --> 00:12:20.532 because we cannot fix what we cannot measure, 00:12:20.532 --> 00:12:23.920 and we cannot prepare for what we don't know. NOTE Paragraph 00:12:23.920 --> 00:12:25.653 Thank you. NOTE Paragraph 00:12:25.653 --> 00:12:28.727 (Applause)