0:00:00.760,0:00:04.656
Since 2009, the world has been stuck

0:00:04.680,0:00:09.816
on a single narrative[br]around a coming global food crisis

0:00:09.840,0:00:12.280
and what we need to do to avoid it.

0:00:13.040,0:00:17.400
How do we feed[br]nine billion people by 2050?

0:00:18.440,0:00:23.056
Every conference, podcast[br]and dialogue around global food security

0:00:23.080,0:00:24.776
starts with this question

0:00:24.800,0:00:26.536
and goes on to answer it

0:00:26.560,0:00:31.000
by saying we need to produce[br]70 percent more food.

0:00:33.160,0:00:35.976
The 2050 narrative started to evolve

0:00:36.000,0:00:40.880
shortly after global food prices[br]hit all-time highs in 2008.

0:00:41.440,0:00:44.216
People were suffering and struggling,

0:00:44.240,0:00:45.776
governments and world leaders

0:00:45.800,0:00:48.416
needed to show us[br]that they were paying attention

0:00:48.440,0:00:50.040
and were working to solve it.

0:00:51.760,0:00:55.536
The thing is, 2050[br]is so far into the future

0:00:55.560,0:00:57.560
that we can't even relate to it,

0:00:58.280,0:01:00.016
and more importantly,

0:01:00.040,0:01:02.296
if we keep doing what we're doing,

0:01:02.320,0:01:04.680
it's going to hit us[br]a lot sooner than that.

0:01:06.080,0:01:09.360
I believe we need to ask[br]a different question.

0:01:10.280,0:01:12.616
The answer to that question

0:01:12.640,0:01:15.200
needs to be framed differently.

0:01:17.120,0:01:19.856
If we can reframe the old narrative

0:01:19.880,0:01:22.336
and replace it with new numbers

0:01:22.360,0:01:24.440
that tell us a more complete pictures,

0:01:25.720,0:01:28.896
numbers that everyone can understand

0:01:28.920,0:01:30.120
and relate to,

0:01:31.320,0:01:34.000
we can avoid the crisis altogether.

0:01:36.560,0:01:39.416
I was a commodities trader in my past life

0:01:39.440,0:01:41.616
and one of the things[br]that I learned trading

0:01:41.640,0:01:44.520
is that every market has a tipping point,

0:01:45.360,0:01:48.936
the point at which[br]change occurs so rapidly

0:01:48.960,0:01:50.816
that it impacts the world

0:01:50.840,0:01:52.800
and things change forever.

0:01:54.080,0:01:56.680
Think of the last financial crisis,

0:01:57.800,0:01:59.480
or the dot-com crash.

0:02:00.920,0:02:03.240
So here's my concern.

0:02:04.760,0:02:06.816
We could have a tipping point

0:02:06.840,0:02:08.976
in global food and agriculture

0:02:09.000,0:02:10.895
if surging demand

0:02:10.919,0:02:17.320
surpasses the agricultural system's[br]structural capacity to produce food.

0:02:18.240,0:02:22.976
This means at this point supply[br]can no longer keep up with demand

0:02:23.000,0:02:25.256
despite exploding prices,

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unless we can commit[br]to some type of structural change.

0:02:30.560,0:02:32.336
This time around,

0:02:32.360,0:02:34.936
it won't be about stock markets and money.

0:02:34.960,0:02:36.336
It's about people.

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People could starve[br]and governments may fall.

0:02:41.200,0:02:45.736
This question of at what point[br]does supply struggle

0:02:45.760,0:02:47.416
to keep up with surging demand

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is one that started off as an interest[br]for me while I was trading

0:02:51.120,0:02:53.896
and became an absolute obsession.

0:02:53.920,0:02:56.856
It went from interest to obsession

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when I realized through my research[br]how broken the system was

0:03:00.560,0:03:04.880
and how very little data was being used[br]to make such critical decisions.

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That's the point I decided to walk away[br]from a career on Wall Street

0:03:09.920,0:03:12.416
and start an entrepreneurial journey

0:03:12.440,0:03:14.400
to start Gro Intelligence.

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At Gro, we focus on bringing this data

0:03:18.400,0:03:20.656
and doing the work to make it actionable,

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to empower decision-makers at every level.

0:03:24.880,0:03:26.496
But doing this work,

0:03:26.520,0:03:28.776
we also realized that the world,

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not just world leaders,

0:03:30.480,0:03:34.736
but businesses and citizens[br]like every single person in this room,

0:03:34.760,0:03:36.840
lacked an actionable guide

0:03:37.760,0:03:42.376
on how we can avoid[br]a coming global food security crisis.

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And so we built a model,

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leveraging the petabytes[br]of data we sit on,

0:03:47.360,0:03:49.760
and we solved for the tipping point.

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Now, no one knows[br]we've been working on this problem

0:03:54.200,0:03:57.800
and this is the first time[br]that I'm sharing what we discovered.

0:04:00.200,0:04:04.840
We discovered that the tipping point[br]is actually a decade from now.

0:04:06.280,0:04:08.616
We discovered that the world

0:04:08.640,0:04:13.000
will be short 214 trillion calories

0:04:14.960,0:04:16.399
by 2027.

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The world is not in a position[br]to fill this gap.

0:04:22.400,0:04:24.000
Now, you'll notice

0:04:24.960,0:04:29.256
that the way I'm framing this[br]is different from how I started,

0:04:29.280,0:04:31.416
and that's intentional, because until now,

0:04:31.440,0:04:34.656
this problem has been[br]quantified using mass:

0:04:34.680,0:04:37.496
think kilograms, tons, hectograms,

0:04:37.520,0:04:39.600
whatever your unit of choice is in mass.

0:04:40.280,0:04:42.880
Why do we talk about food[br]in terms of weight?

0:04:43.360,0:04:44.776
Because it's easy.

0:04:44.800,0:04:48.296
We can look at a photograph[br]and determine tonnage on a ship

0:04:48.320,0:04:50.576
by using a simple pocket calculator.

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We can weigh trucks,[br]airplanes and oxcarts.

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But what we care about[br]in food is nutritional value.

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Not all foods are created equal,

0:05:02.200,0:05:03.960
even if they weigh the same.

0:05:04.920,0:05:07.376
This I learned firsthand

0:05:07.400,0:05:10.400
when I moved from Ethiopia[br]to the US for university.

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Upon my return back home,

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my father, who was so excited to see me,

0:05:16.600,0:05:20.200
greeted me by asking why I was fat.

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Now, turns out that eating

0:05:26.760,0:05:31.616
approximately the same amount of food[br]as I did in Ethiopia, but in America,

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had actually lent[br]a certain fullness to my figure.

0:05:36.760,0:05:40.856
This is why we should care about calories,

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not about mass.

0:05:42.560,0:05:45.320
It is calories which sustain us.

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So 214 trillion calories[br]is a very large number,

0:05:52.720,0:05:55.856
and not even the most dedicated of us

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think in the hundreds[br]of trillions of calories.

0:05:58.840,0:06:00.960
So let me break this down differently.

0:06:01.880,0:06:05.216
An alternative way to think about this

0:06:05.240,0:06:08.096
is to think about it in Big Macs.

0:06:08.120,0:06:10.736
214 trillion calories.

0:06:10.760,0:06:13.976
A single Big Mac has 563 calories.

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That means the world will be short[br]379 billion Big Macs in 2027.

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That is more Big Macs[br]than McDonald's has ever produced.

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So how did we get[br]to these numbers in the first place?

0:06:30.040,0:06:31.240
They're not made up.

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This map shows you[br]where the world was 40 years ago.

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It shows you net calorie gaps[br]in every country in the world.

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Now, simply put,

0:06:42.760,0:06:45.776
this is just calories[br]consumed in that country

0:06:45.800,0:06:48.856
minus calories produced[br]in that same country.

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This is not a statement[br]on malnutrition or anything else.

0:06:51.680,0:06:55.696
It's simply saying how many calories[br]are consumed in a single year

0:06:55.720,0:06:57.576
minus how many are produced.

0:06:57.600,0:07:00.976
Blue countries are net calorie exporters,

0:07:01.000,0:07:02.376
or self-sufficient.

0:07:02.400,0:07:04.440
They have some in storage for a rainy day.

0:07:05.080,0:07:07.896
Red countries are net calorie importers.

0:07:07.920,0:07:09.856
The deeper, the brighter the red,

0:07:09.880,0:07:11.120
the more you're importing.

0:07:12.200,0:07:16.656
40 years ago, such few countries[br]were net exporters of calories,

0:07:16.680,0:07:18.252
I could count them with one hand.

0:07:19.360,0:07:21.456
Most of the African continent,

0:07:21.480,0:07:24.096
Europe, most of Asia,

0:07:24.120,0:07:26.136
South America excluding Argentina,

0:07:26.160,0:07:27.880
were all net importers of calories.

0:07:28.560,0:07:32.180
And what's surprising is that China[br]used to actually be food self-sufficient.

0:07:32.680,0:07:35.640
India was a big net importer of calories.

0:07:37.080,0:07:39.440
40 years later, this is today.

0:07:39.960,0:07:43.440
You can see the drastic transformation[br]that's occurred in the world.

0:07:44.040,0:07:47.536
Brazil has emerged[br]as an agricultural powerhouse.

0:07:47.560,0:07:50.816
Europe is dominant in global agriculture.

0:07:50.840,0:07:53.816
India has actually flipped[br]from red to blue.

0:07:53.840,0:07:56.096
It's become food self-sufficient.

0:07:56.120,0:07:58.576
And China went from that light blue

0:07:58.600,0:08:01.240
to the brightest red[br]that you see on this map.

0:08:02.280,0:08:04.640
How did we get here? What happened?

0:08:05.960,0:08:08.800
So this chart shows you India and Africa.

0:08:09.440,0:08:11.760
Blue line is India, red line is Africa.

0:08:12.440,0:08:16.576
How is it that two regions[br]that started off so similarly

0:08:16.600,0:08:18.736
in such similar trajectories

0:08:18.760,0:08:20.896
take such different paths?

0:08:20.920,0:08:22.960
India had a green revolution.

0:08:24.000,0:08:28.096
Not a single African country[br]had a green revolution.

0:08:28.120,0:08:29.336
The net outcome?

0:08:29.360,0:08:31.056
India is food self-sufficient

0:08:31.080,0:08:34.456
and in the past decade[br]has actually been exporting calories.

0:08:34.480,0:08:38.440
The African continent now imports[br]over 300 trillion calories a year.

0:08:39.280,0:08:43.576
Then we add China, the green line.

0:08:43.600,0:08:46.280
Remember the switch[br]from the blue to the bright red?

0:08:47.120,0:08:50.176
What happened and when did it happen?

0:08:50.200,0:08:53.056
China seemed to be[br]on a very similar path to India

0:08:53.080,0:08:55.856
until the start of the 21st century,

0:08:55.880,0:08:57.560
where it suddenly flipped.

0:08:58.400,0:09:00.416
A young and growing population

0:09:00.440,0:09:03.536
combined with significant economic growth

0:09:03.560,0:09:05.976
made its mark with a big bang

0:09:06.000,0:09:08.480
and no one in the markets saw it coming.

0:09:09.520,0:09:13.256
This flip was everything[br]to global agricultural markets.

0:09:13.280,0:09:16.096
Luckily now, South America

0:09:16.120,0:09:21.336
was starting to boom[br]at the same time as China's rise,

0:09:21.360,0:09:25.360
and so therefore, supply and demand[br]were still somewhat balanced.

0:09:26.320,0:09:27.720
So the question becomes,

0:09:28.640,0:09:30.240
where do we go from here?

0:09:31.800,0:09:33.336
Oddly enough,

0:09:33.360,0:09:34.560
it's not a new story,

0:09:35.800,0:09:39.176
except this time[br]it's not just a story of China.

0:09:39.200,0:09:41.576
It's a continuation of China,

0:09:41.600,0:09:43.696
an amplification of Africa

0:09:43.720,0:09:45.680
and a paradigm shift in India.

0:09:46.600,0:09:48.120
By 2023,

0:09:49.000,0:09:54.056
Africa's population is forecasted[br]to overtake that of India's and China's.

0:09:54.080,0:09:56.736
By 2023, these three regions combined

0:09:56.760,0:09:59.920
will make up over half[br]the world's population.

0:10:01.400,0:10:05.416
This crossover point starts to present[br]really interesting challenges

0:10:05.440,0:10:07.176
for global food security

0:10:07.200,0:10:10.600
and a few years later,[br]we're hit hard with that reality.

0:10:12.120,0:10:15.480
What does the world look like in 10 years?

0:10:17.120,0:10:21.016
So far, as I mentioned,[br]India has been food self-sufficient.

0:10:21.040,0:10:24.440
Most forecasters predict[br]that this will continue.

0:10:25.200,0:10:26.400
We disagree.

0:10:27.160,0:10:31.296
India will soon become[br]a net importer of calories.

0:10:31.320,0:10:33.576
This will be driven both by the fact

0:10:33.600,0:10:37.096
that demand is growing[br]from a population growth standpoint

0:10:37.120,0:10:38.376
plus economic growth.

0:10:38.400,0:10:39.656
It will be driven by both.

0:10:39.680,0:10:42.376
And even if you have[br]optimistic assumptions

0:10:42.400,0:10:44.296
around production growth,

0:10:44.320,0:10:46.440
it will make that slight flip.

0:10:46.960,0:10:50.880
That slight flip[br]can have huge implications.

0:10:51.800,0:10:56.336
Next, Africa will continue[br]to be a net importer of calories,

0:10:56.360,0:10:59.360
again driven by population growth[br]and economic growth.

0:11:00.120,0:11:04.016
This is again assuming optimistic[br]production growth assumptions.

0:11:04.040,0:11:05.456
Then China,

0:11:05.480,0:11:08.056
where population is flattening out,

0:11:08.080,0:11:10.056
calorie consumption will explode

0:11:10.080,0:11:13.096
because the types of calories consumed

0:11:13.120,0:11:16.640
are also starting to be[br]higher-calorie-content foods.

0:11:17.600,0:11:19.336
And so therefore,

0:11:19.360,0:11:21.216
these three regions combined

0:11:21.240,0:11:24.536
start to present a really interesting[br]challenge for the world.

0:11:24.560,0:11:28.656
Until now, countries with calorie deficits

0:11:28.680,0:11:31.256
have been able to meet these deficits

0:11:31.280,0:11:33.120
by importing from surplus regions.

0:11:33.720,0:11:36.536
By surplus regions, I'm talking about

0:11:36.560,0:11:39.696
North America, South America and Europe.

0:11:39.720,0:11:42.136
This line chart over here shows you

0:11:42.160,0:11:46.456
the growth and the projected growth[br]over the next decade of production

0:11:46.480,0:11:48.776
from North America,[br]South America and Europe.

0:11:48.800,0:11:50.216
What it doesn't show you

0:11:50.240,0:11:53.680
is that most of this growth is actually[br]going to come from South America,

0:11:54.640,0:11:56.056
and most of this growth

0:11:56.080,0:12:00.480
is going to come[br]at the huge cost of deforestation.

0:12:02.240,0:12:06.016
And so when you look[br]at the combined demand increase

0:12:06.040,0:12:09.360
coming from India, China[br]and the African continent,

0:12:10.200,0:12:13.016
and look at it versus[br]the combined increase in production

0:12:13.040,0:12:15.816
coming from India,[br]China, the African continent,

0:12:15.840,0:12:18.200
North America, South America and Europe,

0:12:19.280,0:12:24.696
you are left with[br]a 214-trillion-calorie deficit,

0:12:24.720,0:12:26.456
one we can't produce.

0:12:26.480,0:12:30.416
And this, by the way, is actually assuming[br]we take all the extra calories

0:12:30.440,0:12:32.821
produced in North America,[br]South America and Europe

0:12:33.880,0:12:38.120
and export them solely[br]to India, China and Africa.

0:12:39.200,0:12:42.680
What I just presented to you[br]is a vision of an impossible world.

0:12:43.520,0:12:45.360
We can do something to change that.

0:12:46.400,0:12:48.696
We can change consumption patterns,

0:12:48.720,0:12:50.976
we can reduce food waste,

0:12:51.000,0:12:54.216
or we can make a bold commitment

0:12:54.240,0:12:56.560
to increasing yields exponentially.

0:12:57.720,0:12:59.856
Now, I'm not going to go into discussing

0:12:59.880,0:13:02.376
changing consumption patterns[br]or reducing food waste,

0:13:02.400,0:13:05.456
because those conversations[br]have been going on for some time now.

0:13:05.480,0:13:06.696
Nothing has happened.

0:13:06.720,0:13:10.176
Nothing has happened[br]because those arguments

0:13:10.200,0:13:13.136
ask the surplus regions[br]to change their behavior

0:13:13.160,0:13:15.600
on behalf of deficit regions.

0:13:16.880,0:13:19.456
Waiting for others[br]to change their behavior

0:13:19.480,0:13:21.976
on your behalf, for your survival,

0:13:22.000,0:13:23.496
is a terrible idea.

0:13:23.520,0:13:25.120
It's unproductive.

0:13:25.560,0:13:30.280
So I'd like to suggest an alternative[br]that comes from the red regions.

0:13:31.960,0:13:34.336
China, India, Africa.

0:13:34.360,0:13:37.656
China is constrained in terms[br]of how much more land it actually has

0:13:37.680,0:13:39.216
available for agriculture,

0:13:39.240,0:13:43.016
and it has massive[br]water resource availability issues.

0:13:43.040,0:13:46.680
So the answer really lies[br]in India and in Africa.

0:13:47.840,0:13:52.776
India has some upside[br]in terms of potential yield increases.

0:13:52.800,0:13:55.376
Now this is the gap[br]between its current yield

0:13:55.400,0:13:58.520
and the theoretical[br]maximum yield it can achieve.

0:13:59.720,0:14:02.936
It has some unfarmed[br]arable land remaining, but not much,

0:14:02.960,0:14:05.240
India is quite land-constrained.

0:14:06.240,0:14:08.896
Now, the African continent,[br]on the other hand,

0:14:08.920,0:14:12.216
has vast amounts of arable land remaining

0:14:12.240,0:14:14.920
and significant[br]upside potential in yields.

0:14:16.080,0:14:18.176
Somewhat simplified picture here,

0:14:18.200,0:14:23.216
but if you look at sub-Saharan[br]African yields in corn today,

0:14:23.240,0:14:26.720
they are where North American[br]yields were in 1940.

0:14:28.600,0:14:32.336
We don't have 70-plus years[br]to figure this out,

0:14:32.360,0:14:34.896
so it means we need to try something new

0:14:34.920,0:14:37.080
and we need to try something different.

0:14:38.400,0:14:40.560
The solution starts with reforms.

0:14:41.880,0:14:45.856
We need to reform and commercialize

0:14:45.880,0:14:48.416
the agricultural industries in Africa

0:14:48.440,0:14:49.640
and in India.

0:14:50.320,0:14:52.456
Now, by commercialization --

0:14:52.480,0:14:55.616
commercialization is not[br]about commercial farming alone.

0:14:55.640,0:14:58.216
Commercialization is about leveraging data

0:14:58.240,0:15:00.536
to craft better policies,

0:15:00.560,0:15:02.176
to improve infrastructure,

0:15:02.200,0:15:04.056
to lower the transportation costs

0:15:04.080,0:15:08.336
and to completely reform[br]banking and insurance industries.

0:15:08.360,0:15:11.456
Commercialization[br]is about taking agriculture

0:15:11.480,0:15:15.576
from too risky an endeavor[br]to one where fortunes can be made.

0:15:15.600,0:15:18.856
Commercialization[br]is not about just farmers.

0:15:18.880,0:15:23.160
Commercialization is about[br]the entire agricultural system.

0:15:24.840,0:15:28.896
But commercialization[br]also means confronting the fact

0:15:28.920,0:15:32.336
that we can no longer place[br]the burden of growth

0:15:32.360,0:15:34.480
on small-scale farmers alone,

0:15:36.600,0:15:41.856
and accepting that commercial farms[br]and the introduction of commercial farms

0:15:41.880,0:15:44.576
could provide certain economies of scale

0:15:44.600,0:15:46.840
that even small-scale[br]farmers can leverage.

0:15:48.040,0:15:52.016
It is not about small-scale farming[br]or commercial agriculture,

0:15:52.040,0:15:53.896
or big agriculture.

0:15:53.920,0:15:59.176
We can create the first successful models[br]of the coexistence and success

0:15:59.200,0:16:02.976
of small-scale farming[br]alongside commercial agriculture.

0:16:03.000,0:16:06.016
This is because, for the first time ever,

0:16:06.040,0:16:09.776
the most critical tool[br]for success in the industry --

0:16:09.800,0:16:11.296
data and knowledge --

0:16:11.320,0:16:13.560
is becoming cheaper by the day.

0:16:14.720,0:16:18.136
And very soon, it won't matter[br]how much money you have

0:16:18.160,0:16:19.616
or how big you are

0:16:19.640,0:16:23.936
to make optimal decisions[br]and maximize probability of success

0:16:23.960,0:16:26.440
in reaching your intended goal.

0:16:27.320,0:16:30.920
Companies like Gro are working[br]really hard to make this a reality.

0:16:31.600,0:16:36.176
So if we can commit[br]to this new, bold initiative,

0:16:36.200,0:16:38.216
to this new, bold change,

0:16:38.240,0:16:43.656
not only can we solve[br]the 214-trillion gap that I talked about,

0:16:43.680,0:16:46.280
but we can actually set the world[br]on a whole new path.

0:16:46.960,0:16:51.056
India can remain food self-sufficient

0:16:51.080,0:16:55.840
and Africa can emerge[br]as the world's next dark blue region.

0:16:57.240,0:16:59.456
The new question is,

0:16:59.480,0:17:03.616
how do we produce 214 trillion calories

0:17:03.640,0:17:07.800
to feed 8.3 billion people by 2027?

0:17:08.760,0:17:10.240
We have the solution.

0:17:10.960,0:17:12.760
We just need to act on it.

0:17:13.520,0:17:14.736
Thank you.

0:17:14.760,0:17:18.119
(Applause)