1 00:00:00,760 --> 00:00:04,656 Since 2009, the world has been stuck 2 00:00:04,680 --> 00:00:09,816 on a single narrative around a coming global food crisis 3 00:00:09,840 --> 00:00:12,280 and what we need to do to avoid it. 4 00:00:13,040 --> 00:00:17,400 How do we feed nine billion people by 2050? 5 00:00:18,440 --> 00:00:23,056 Every conference, podcast and dialogue around global food security 6 00:00:23,080 --> 00:00:24,776 starts with this question 7 00:00:24,800 --> 00:00:26,536 and goes on to answer it 8 00:00:26,560 --> 00:00:31,000 by saying we need to produce 70 percent more food. 9 00:00:33,160 --> 00:00:35,976 The 2050 narrative started to evolve 10 00:00:36,000 --> 00:00:40,880 shortly after global food prices hit all-time highs in 2008. 11 00:00:41,440 --> 00:00:44,216 People were suffering and struggling, 12 00:00:44,240 --> 00:00:45,776 governments and world leaders 13 00:00:45,800 --> 00:00:48,416 needed to show us that they were paying attention 14 00:00:48,440 --> 00:00:50,040 and were working to solve it. 15 00:00:51,760 --> 00:00:55,536 The thing is, 2050 is so far into the future 16 00:00:55,560 --> 00:00:57,560 that we can't even relate to it, 17 00:00:58,280 --> 00:01:00,016 and more importantly, 18 00:01:00,040 --> 00:01:02,296 if we keep doing what we're doing, 19 00:01:02,320 --> 00:01:04,680 it's going to hit us a lot sooner than that. 20 00:01:06,080 --> 00:01:09,360 I believe we need to ask a different question. 21 00:01:10,280 --> 00:01:12,616 The answer to that question 22 00:01:12,640 --> 00:01:15,200 needs to be framed differently. 23 00:01:17,120 --> 00:01:19,856 If we can reframe the old narrative 24 00:01:19,880 --> 00:01:22,336 and replace it with new numbers 25 00:01:22,360 --> 00:01:24,440 that tell us a more complete pictures, 26 00:01:25,720 --> 00:01:28,896 numbers that everyone can understand 27 00:01:28,920 --> 00:01:30,120 and relate to, 28 00:01:31,320 --> 00:01:34,000 we can avoid the crisis altogether. 29 00:01:36,560 --> 00:01:39,416 I was a commodities trader in my past life 30 00:01:39,440 --> 00:01:41,616 and one of the things that I learned trading 31 00:01:41,640 --> 00:01:44,520 is that every market has a tipping point, 32 00:01:45,360 --> 00:01:48,936 the point at which change occurs so rapidly 33 00:01:48,960 --> 00:01:50,816 that it impacts the world 34 00:01:50,840 --> 00:01:52,800 and things change forever. 35 00:01:54,080 --> 00:01:56,680 Think of the last financial crisis, 36 00:01:57,800 --> 00:01:59,480 or the dot-com crash. 37 00:02:00,920 --> 00:02:03,240 So here's my concern. 38 00:02:04,760 --> 00:02:06,816 We could have a tipping point 39 00:02:06,840 --> 00:02:08,976 in global food and agriculture 40 00:02:09,000 --> 00:02:10,895 if surging demand 41 00:02:10,919 --> 00:02:17,320 surpasses the agricultural system's structural capacity to produce food. 42 00:02:18,240 --> 00:02:22,976 This means at this point supply can no longer keep up with demand 43 00:02:23,000 --> 00:02:25,256 despite exploding prices, 44 00:02:25,280 --> 00:02:29,360 unless we can commit to some type of structural change. 45 00:02:30,560 --> 00:02:32,336 This time around, 46 00:02:32,360 --> 00:02:34,936 it won't be about stock markets and money. 47 00:02:34,960 --> 00:02:36,336 It's about people. 48 00:02:36,360 --> 00:02:39,760 People could starve and governments may fall. 49 00:02:41,200 --> 00:02:45,736 This question of at what point does supply struggle 50 00:02:45,760 --> 00:02:47,416 to keep up with surging demand 51 00:02:47,440 --> 00:02:51,096 is one that started off as an interest for me while I was trading 52 00:02:51,120 --> 00:02:53,896 and became an absolute obsession. 53 00:02:53,920 --> 00:02:56,856 It went from interest to obsession 54 00:02:56,880 --> 00:03:00,536 when I realized through my research how broken the system was 55 00:03:00,560 --> 00:03:04,880 and how very little data was being used to make such critical decisions. 56 00:03:05,640 --> 00:03:09,896 That's the point I decided to walk away from a career on Wall Street 57 00:03:09,920 --> 00:03:12,416 and start an entrepreneurial journey 58 00:03:12,440 --> 00:03:14,400 to start Gro Intelligence. 59 00:03:14,880 --> 00:03:18,376 At Gro, we focus on bringing this data 60 00:03:18,400 --> 00:03:20,656 and doing the work to make it actionable, 61 00:03:20,680 --> 00:03:23,680 to empower decision-makers at every level. 62 00:03:24,880 --> 00:03:26,496 But doing this work, 63 00:03:26,520 --> 00:03:28,776 we also realized that the world, 64 00:03:28,800 --> 00:03:30,456 not just world leaders, 65 00:03:30,480 --> 00:03:34,736 but businesses and citizens like every single person in this room, 66 00:03:34,760 --> 00:03:36,840 lacked an actionable guide 67 00:03:37,760 --> 00:03:42,376 on how we can avoid a coming global food security crisis. 68 00:03:42,400 --> 00:03:44,416 And so we built a model, 69 00:03:44,440 --> 00:03:47,336 leveraging the petabytes of data we sit on, 70 00:03:47,360 --> 00:03:49,760 and we solved for the tipping point. 71 00:03:50,560 --> 00:03:54,176 Now, no one knows we've been working on this problem 72 00:03:54,200 --> 00:03:57,800 and this is the first time that I'm sharing what we discovered. 73 00:04:00,200 --> 00:04:04,840 We discovered that the tipping point is actually a decade from now. 74 00:04:06,280 --> 00:04:08,616 We discovered that the world 75 00:04:08,640 --> 00:04:13,000 will be short 214 trillion calories 76 00:04:14,960 --> 00:04:16,399 by 2027. 77 00:04:17,440 --> 00:04:21,240 The world is not in a position to fill this gap. 78 00:04:22,400 --> 00:04:24,000 Now, you'll notice 79 00:04:24,960 --> 00:04:29,256 that the way I'm framing this is different from how I started, 80 00:04:29,280 --> 00:04:31,416 and that's intentional, because until now 81 00:04:31,440 --> 00:04:34,656 this problem has been quantified using mass: 82 00:04:34,680 --> 00:04:37,496 think kilograms, tons, hectograms, 83 00:04:37,520 --> 00:04:39,600 whatever your unit of choice is in mass. 84 00:04:40,280 --> 00:04:42,880 Why do we talk about food in terms of weight? 85 00:04:43,360 --> 00:04:44,776 Because it's easy. 86 00:04:44,800 --> 00:04:48,296 We can look at a photograph and determine tonnage on a ship 87 00:04:48,320 --> 00:04:50,576 by using a simple pocket calculator. 88 00:04:50,600 --> 00:04:53,360 We can weigh trucks, airplanes and oxcarts. 89 00:04:53,880 --> 00:04:57,920 But what we care about in food is nutritional value. 90 00:04:59,040 --> 00:05:02,176 Not all foods are created equal, 91 00:05:02,200 --> 00:05:03,960 even if they weigh the same. 92 00:05:04,920 --> 00:05:07,376 This I learned firsthand 93 00:05:07,400 --> 00:05:10,400 when I moved from Ethiopia to the US for university. 94 00:05:11,200 --> 00:05:13,336 Upon my return back home, 95 00:05:13,360 --> 00:05:16,576 my father, who was so excited to see me, 96 00:05:16,600 --> 00:05:20,200 greeted me by asking why I was fat. 97 00:05:20,960 --> 00:05:26,736 Now, turns out that eating 98 00:05:26,760 --> 00:05:31,616 approximately the same amount of food as I did in Ethiopia, but in America, 99 00:05:31,640 --> 00:05:34,880 had actually lent a certain fullness to my figure. 100 00:05:36,760 --> 00:05:40,856 This is why we should care about calories, 101 00:05:40,880 --> 00:05:42,536 not about mass. 102 00:05:42,560 --> 00:05:45,320 It is calories which sustain us. 103 00:05:46,880 --> 00:05:52,696 So 214 trillion calories is a very large number, 104 00:05:52,720 --> 00:05:55,856 and not even the most dedicated of us 105 00:05:55,880 --> 00:05:58,816 think in the hundreds of trillions of calories. 106 00:05:58,840 --> 00:06:00,960 So let me break this down differently. 107 00:06:01,880 --> 00:06:05,216 An alternative way to think about this 108 00:06:05,240 --> 00:06:08,096 is to think about it in Big Macs. 109 00:06:08,120 --> 00:06:10,736 214 trillion calories. 110 00:06:10,760 --> 00:06:13,976 A single Big Mac has 563 calories. 111 00:06:14,000 --> 00:06:20,216 That means the world will be short 379 billion Big Macs in 2027. 112 00:06:20,240 --> 00:06:24,240 That is more Big Macs than McDonald's has ever produced. 113 00:06:25,960 --> 00:06:30,016 So how did we get to these numbers in the first place? 114 00:06:30,040 --> 00:06:31,240 They're not made up. 115 00:06:32,400 --> 00:06:37,216 This map shows you where the world was 40 years ago. 116 00:06:37,240 --> 00:06:41,256 It shows you net calorie gaps in every country in the world. 117 00:06:41,280 --> 00:06:42,736 Now, simply put, 118 00:06:42,760 --> 00:06:45,776 this is just calories consumed in that country 119 00:06:45,800 --> 00:06:48,856 minus calories produced in that same country. 120 00:06:48,880 --> 00:06:51,656 This is not a statement on malnutrition or anything else. 121 00:06:51,680 --> 00:06:55,696 It's simply saying how many calories are consumed in a single year 122 00:06:55,720 --> 00:06:57,576 minus how many are produced. 123 00:06:57,600 --> 00:07:00,976 Blue countries are net calorie exporters, 124 00:07:01,000 --> 00:07:02,376 or self-sufficient. 125 00:07:02,400 --> 00:07:04,440 They have some in storage for a rainy day. 126 00:07:05,080 --> 00:07:07,896 Red countries are net calorie importers. 127 00:07:07,920 --> 00:07:09,856 The deeper, the brighter the red, 128 00:07:09,880 --> 00:07:11,120 the more you're importing. 129 00:07:12,200 --> 00:07:16,656 40 years ago, such few countries were net exporters of calories, 130 00:07:16,680 --> 00:07:18,252 I could count them with one hand. 131 00:07:19,360 --> 00:07:21,456 Most of the African continent, 132 00:07:21,480 --> 00:07:24,096 Europe, most of Asia, 133 00:07:24,120 --> 00:07:26,136 South America excluding Argentina, 134 00:07:26,160 --> 00:07:27,880 were all net importers of calories. 135 00:07:28,560 --> 00:07:32,180 And what's surprising is that China used to actually be food self-sufficient. 136 00:07:32,680 --> 00:07:35,640 India was a big net importer of calories. 137 00:07:37,080 --> 00:07:39,440 40 years later, this is today. 138 00:07:39,960 --> 00:07:43,440 You can see the drastic transformation that's occurred in the world. 139 00:07:44,040 --> 00:07:47,536 Brazil has emerged as an agricultural powerhouse. 140 00:07:47,560 --> 00:07:50,816 Europe is dominant in global agriculture. 141 00:07:50,840 --> 00:07:53,816 India has actually flipped from red to blue. 142 00:07:53,840 --> 00:07:56,096 It's become food self-sufficient. 143 00:07:56,120 --> 00:07:58,576 And China went from that light blue 144 00:07:58,600 --> 00:08:01,240 to the brightest red that you see on this map. 145 00:08:02,280 --> 00:08:04,640 How did we get here? What happened? 146 00:08:05,960 --> 00:08:08,800 So this chart shows you India and Africa. 147 00:08:09,440 --> 00:08:11,760 Blue line is India, red line is Africa. 148 00:08:12,440 --> 00:08:16,576 How is it that two regions that started off so similarly 149 00:08:16,600 --> 00:08:18,736 in such similar trajectories 150 00:08:18,760 --> 00:08:20,896 take such different paths? 151 00:08:20,920 --> 00:08:22,960 India had a green revolution. 152 00:08:24,000 --> 00:08:28,096 Not a single African country had a green revolution. 153 00:08:28,120 --> 00:08:29,336 The net outcome? 154 00:08:29,360 --> 00:08:31,056 India is food self-sufficient 155 00:08:31,080 --> 00:08:34,456 and in the past decade has actually been exporting calories. 156 00:08:34,480 --> 00:08:38,440 The African continent now imports over 300 trillion calories a year. 157 00:08:39,280 --> 00:08:43,576 Then we add China, the green line. 158 00:08:43,600 --> 00:08:46,280 Remember the switch from the blue to the bright red? 159 00:08:47,120 --> 00:08:50,176 What happened and when did it happen? 160 00:08:50,200 --> 00:08:53,056 China seemed to be on a very similar path to India 161 00:08:53,080 --> 00:08:55,856 until the start of the 21st century, 162 00:08:55,880 --> 00:08:57,560 where it suddenly flipped. 163 00:08:58,400 --> 00:09:00,416 A young and growing population 164 00:09:00,440 --> 00:09:03,536 combined with significant economic growth 165 00:09:03,560 --> 00:09:05,976 made its mark with a big bang 166 00:09:06,000 --> 00:09:08,480 and no one in the markets saw it coming. 167 00:09:09,520 --> 00:09:13,256 This flip was everything to global agricultural markets. 168 00:09:13,280 --> 00:09:16,096 Luckily now, South America 169 00:09:16,120 --> 00:09:21,336 was starting to boom at the same time as China's rise, 170 00:09:21,360 --> 00:09:25,360 and so therefore, supply and demand were still somewhat balanced. 171 00:09:26,320 --> 00:09:27,720 So the question becomes, 172 00:09:28,640 --> 00:09:30,240 where do we go from here? 173 00:09:31,800 --> 00:09:33,336 Oddly enough, 174 00:09:33,360 --> 00:09:34,560 it's not a new story, 175 00:09:35,800 --> 00:09:39,176 except this time it's not just a story of China. 176 00:09:39,200 --> 00:09:41,576 It's a continuation of China, 177 00:09:41,600 --> 00:09:43,696 an amplification of Africa 178 00:09:43,720 --> 00:09:45,680 and a paradigm shift in India. 179 00:09:46,600 --> 00:09:48,120 By 2023, 180 00:09:49,000 --> 00:09:54,056 Africa's population is forecasted to overtake that of India's and China's. 181 00:09:54,080 --> 00:09:56,736 By 2023, these three regions combined 182 00:09:56,760 --> 00:09:59,920 will make up over half the world's population. 183 00:10:01,400 --> 00:10:05,416 This crossover point starts to present really interesting challenges 184 00:10:05,440 --> 00:10:07,176 for global food security. 185 00:10:07,200 --> 00:10:10,600 And a few years later, we're hit hard with that reality. 186 00:10:12,120 --> 00:10:15,480 What does the world look like in 10 years? 187 00:10:17,120 --> 00:10:21,016 So far, as I mentioned, India has been food self-sufficient. 188 00:10:21,040 --> 00:10:24,440 Most forecasters predict that this will continue. 189 00:10:25,200 --> 00:10:26,400 We disagree. 190 00:10:27,160 --> 00:10:31,296 India will soon become a net importer of calories. 191 00:10:31,320 --> 00:10:33,576 This will be driven both by the fact 192 00:10:33,600 --> 00:10:37,096 that demand is growing from a population growth standpoint 193 00:10:37,120 --> 00:10:38,376 plus economic growth. 194 00:10:38,400 --> 00:10:39,656 It will be driven by both. 195 00:10:39,680 --> 00:10:42,376 And even if you have optimistic assumptions 196 00:10:42,400 --> 00:10:44,296 around production growth, 197 00:10:44,320 --> 00:10:46,440 it will make that slight flip. 198 00:10:46,960 --> 00:10:50,880 That slight flip can have huge implications. 199 00:10:51,800 --> 00:10:56,336 Next, Africa will continue to be a net importer of calories, 200 00:10:56,360 --> 00:10:59,360 again driven by population growth and economic growth. 201 00:11:00,120 --> 00:11:04,016 This is again assuming optimistic production growth assumptions. 202 00:11:04,040 --> 00:11:05,456 Then China, 203 00:11:05,480 --> 00:11:08,056 where population is flattening out, 204 00:11:08,080 --> 00:11:10,056 calorie consumption will explode 205 00:11:10,080 --> 00:11:13,096 because the types of calories consumed 206 00:11:13,120 --> 00:11:16,640 are also starting to be higher-calorie-content foods. 207 00:11:17,600 --> 00:11:19,336 And so therefore, 208 00:11:19,360 --> 00:11:21,216 these three regions combined 209 00:11:21,240 --> 00:11:24,536 start to present a really interesting challenge for the world. 210 00:11:24,560 --> 00:11:28,656 Until now, countries with calorie deficits 211 00:11:28,680 --> 00:11:31,256 have been able to meet these deficits 212 00:11:31,280 --> 00:11:33,120 by importing from surplus regions. 213 00:11:33,720 --> 00:11:36,536 By surplus regions, I'm talking about 214 00:11:36,560 --> 00:11:39,696 North America, South America and Europe. 215 00:11:39,720 --> 00:11:42,136 This line chart over here shows you 216 00:11:42,160 --> 00:11:46,456 the growth and the projected growth over the next decade of production 217 00:11:46,480 --> 00:11:48,776 from North America, South America and Europe. 218 00:11:48,800 --> 00:11:50,216 What it doesn't show you 219 00:11:50,240 --> 00:11:53,680 is that most of this growth is actually going to come from South America. 220 00:11:54,640 --> 00:11:56,056 And most of this growth 221 00:11:56,080 --> 00:12:00,480 is going to come at the huge cost of deforestation. 222 00:12:02,240 --> 00:12:06,016 And so when you look at the combined demand increase 223 00:12:06,040 --> 00:12:09,360 coming from India, China and the African continent, 224 00:12:10,200 --> 00:12:13,016 and look at it versus the combined increase in production 225 00:12:13,040 --> 00:12:15,816 coming from India, China, the African continent, 226 00:12:15,840 --> 00:12:18,200 North America, South America and Europe, 227 00:12:19,280 --> 00:12:24,696 you are left with a 214-trillion-calorie deficit, 228 00:12:24,720 --> 00:12:26,456 one we can't produce. 229 00:12:26,480 --> 00:12:30,416 And this, by the way, is actually assuming we take all the extra calories 230 00:12:30,440 --> 00:12:32,821 produced in North America, South America and Europe 231 00:12:33,880 --> 00:12:38,120 and export them solely to India, China and Africa. 232 00:12:39,200 --> 00:12:42,680 What I just presented to you is a vision of an impossible world. 233 00:12:43,520 --> 00:12:45,360 We can do something to change that. 234 00:12:46,400 --> 00:12:48,696 We can change consumption patterns, 235 00:12:48,720 --> 00:12:50,976 we can reduce food waste, 236 00:12:51,000 --> 00:12:54,216 or we can make a bold commitment 237 00:12:54,240 --> 00:12:56,560 to increasing yields exponentially. 238 00:12:57,720 --> 00:12:59,856 Now, I'm not going to go into discussing 239 00:12:59,880 --> 00:13:02,376 changing consumption patterns or reducing food waste, 240 00:13:02,400 --> 00:13:05,456 because those conversations have been going on for some time now. 241 00:13:05,480 --> 00:13:06,696 Nothing has happened. 242 00:13:06,720 --> 00:13:10,176 Nothing has happened because those arguments 243 00:13:10,200 --> 00:13:13,136 ask the surplus regions to change their behavior 244 00:13:13,160 --> 00:13:15,600 on behalf of deficit regions. 245 00:13:16,880 --> 00:13:19,456 Waiting for others to change their behavior 246 00:13:19,480 --> 00:13:21,976 on your behalf, for your survival, 247 00:13:22,000 --> 00:13:23,496 is a terrible idea. 248 00:13:23,520 --> 00:13:25,120 It's unproductive. 249 00:13:25,560 --> 00:13:30,280 So I'd like to suggest an alternative that comes from the red regions. 250 00:13:31,960 --> 00:13:34,336 China, India, Africa. 251 00:13:34,360 --> 00:13:37,656 China is constrained in terms of how much more land it actually has 252 00:13:37,680 --> 00:13:39,216 available for agriculture, 253 00:13:39,240 --> 00:13:43,016 and it has massive water resource availability issues. 254 00:13:43,040 --> 00:13:46,680 So the answer really lies in India and in Africa. 255 00:13:47,840 --> 00:13:52,776 India has some upside in terms of potential yield increases. 256 00:13:52,800 --> 00:13:55,376 Now this is the gap between its current yield 257 00:13:55,400 --> 00:13:58,520 and the theoretical maximum yield it can achieve. 258 00:13:59,720 --> 00:14:02,936 It has some unfarmed arable land remaining, but not much, 259 00:14:02,960 --> 00:14:05,240 India is quite land-constrained. 260 00:14:06,240 --> 00:14:08,896 Now, the African continent, on the other hand, 261 00:14:08,920 --> 00:14:12,216 has vast amounts of arable land remaining 262 00:14:12,240 --> 00:14:14,920 and significant upside potential in yields. 263 00:14:16,080 --> 00:14:18,176 Somewhat simplified picture here, 264 00:14:18,200 --> 00:14:23,216 but if you look at sub-Saharan African yields in corn today, 265 00:14:23,240 --> 00:14:26,720 they are where North American yields were in 1940. 266 00:14:28,600 --> 00:14:32,336 We don't have 70-plus years to figure this out, 267 00:14:32,360 --> 00:14:34,896 so it means we need to try something new 268 00:14:34,920 --> 00:14:37,080 and we need to try something different. 269 00:14:38,400 --> 00:14:40,560 The solution starts with reforms. 270 00:14:41,880 --> 00:14:45,856 We need to reform and commercialize 271 00:14:45,880 --> 00:14:48,416 the agricultural industries in Africa 272 00:14:48,440 --> 00:14:49,640 and in India. 273 00:14:50,320 --> 00:14:52,456 Now, by commercialization -- 274 00:14:52,480 --> 00:14:55,616 commercialization is not about commercial farming alone. 275 00:14:55,640 --> 00:14:58,216 Commercialization is about leveraging data 276 00:14:58,240 --> 00:15:00,536 to craft better policies, 277 00:15:00,560 --> 00:15:02,176 to improve infrastructure, 278 00:15:02,200 --> 00:15:04,056 to lower the transportation costs 279 00:15:04,080 --> 00:15:08,336 and to completely reform banking and insurance industries. 280 00:15:08,360 --> 00:15:11,456 Commercialization is about taking agriculture 281 00:15:11,480 --> 00:15:15,576 from too risky an endeavor to one where fortunes can be made. 282 00:15:15,600 --> 00:15:18,856 Commercialization is not about just farmers. 283 00:15:18,880 --> 00:15:23,160 Commercialization is about the entire agricultural system. 284 00:15:24,840 --> 00:15:28,896 But commercialization also means confronting the fact 285 00:15:28,920 --> 00:15:32,336 that we can no longer place the burden of growth 286 00:15:32,360 --> 00:15:34,480 on small-scale farmers alone, 287 00:15:36,600 --> 00:15:41,856 and accepting that commercial farms and the introduction of commercial farms 288 00:15:41,880 --> 00:15:44,576 could provide certain economies of scale 289 00:15:44,600 --> 00:15:46,840 that even small-scale farmers can leverage. 290 00:15:48,040 --> 00:15:52,016 It is not about small-scale farming or commercial agriculture, 291 00:15:52,040 --> 00:15:53,896 or big agriculture. 292 00:15:53,920 --> 00:15:59,176 We can create the first successful models of the coexistence and success 293 00:15:59,200 --> 00:16:02,976 of small-scale farming alongside commercial agriculture. 294 00:16:03,000 --> 00:16:06,016 This is because, for the first time ever, 295 00:16:06,040 --> 00:16:09,776 the most critical tool for success in the industry -- 296 00:16:09,800 --> 00:16:11,296 data and knowledge -- 297 00:16:11,320 --> 00:16:13,560 is becoming cheaper by the day. 298 00:16:14,720 --> 00:16:18,136 And very soon, it won't matter how much money you have 299 00:16:18,160 --> 00:16:19,616 or how big you are 300 00:16:19,640 --> 00:16:23,936 to make optimal decisions and maximize probability of success 301 00:16:23,960 --> 00:16:26,440 in reaching your intended goal. 302 00:16:27,320 --> 00:16:30,920 Companies like Gro are working really hard to make this a reality. 303 00:16:31,600 --> 00:16:36,176 So if we can commit to this new, bold initiative, 304 00:16:36,200 --> 00:16:38,216 to this new, bold change, 305 00:16:38,240 --> 00:16:43,656 not only can we solve the 214-trillion gap that I talked about, 306 00:16:43,680 --> 00:16:46,280 but we can actually set the world on a whole new path. 307 00:16:46,960 --> 00:16:51,056 India can remain food self-sufficient 308 00:16:51,080 --> 00:16:55,840 and Africa can emerge as the world's next dark blue region. 309 00:16:57,240 --> 00:16:59,456 The new question is, 310 00:16:59,480 --> 00:17:03,616 how do we produce 214 trillion calories 311 00:17:03,640 --> 00:17:07,800 to feed 8.3 billion people by 2027? 312 00:17:08,760 --> 00:17:10,240 We have the solution. 313 00:17:10,960 --> 00:17:12,760 We just need to act on it. 314 00:17:13,520 --> 00:17:14,736 Thank you. 315 00:17:14,760 --> 00:17:18,119 (Applause)