Applied mASI: In Agriculture

What does a farm of the future look like to you?

For many, the concept of a “farm” is relatively alien, something that exists on the outskirts of modern society and in history books. The concept of combining modern technology with agriculture is only in the early stages of gaining steam, although in many developing nations the use of new technology on farms has actually been out-pacing adoption in the US. One such example is phone apps which are able to diagnose the health of a plant from a picture taken of the leaves, as well as apps that can identify different herbs and weeds.

One example of new approaches to the old problems of agriculture gained prominence when the “Tree of 40 Fruit” made headlines, where Sam Aken created a series of massively hybridized trees able to bear that vast array of fruits. These trees had the added bonus of also displaying a wide range of blossoms, as they effectively became collective organisms.

Another example is the rising promise of vertical farming and aquaponics, where a fraction of the water and often none of the soil are required to grow plants, in addition to the ability to grow them year-round without the need for pesticides. Some variations on this have also been proposed for underwater greenhouses, as the water keeps a highly stable year-round temperature while providing an even stronger barrier against pests and airborne contaminants.

3D-printed meat substitutes, as well as lab-grown meats, have also gained a high degree of attention in recent years, with many already appearing in supermarkets and restaurants. One such example recently clocked in at producing roughly 1.5 tons of meat substitute per hour.

All combined, it is safe to say that the future of farming probably won’t look even remotely like the past, or indeed the current state.

How is your food grown, and how does it reach you?

Feeding the world in ways that are sustainable, affordable, healthy, and robust to events is a challenge humanity still has a lot of room for improvement on rising to.

1. The average US meal travels 1,500 miles before reaching its destination, a concept known as “food miles”. More perishable foods flown by plane generate 50 to 70 times more carbon footprint than those transported via cargo ship. The carbon footprint of farm equipment, producing chemical fertilizers, and various meat-associated costs can also play a substantial role.
2. Travel times and costs translate into higher costs for the consumer, as well as the cost of any goods which don’t survive such a journey.
3. How healthy foods are is largely ignored by the industry today, with few other than the handful of scientists engineering healthier crops for developing countries paying much attention to it. Examples in the US frequently focus on integrating pesticides into the plant so they need not be sprayed on them.
4. Any system where the average food miles of a meal exceeds even 50 miles will be vulnerable to logistics hazards such as snow, wildfires, political instability, and so on.
5. Current farming practices have created a global phosphorus crisis, due to over 80% of phosphorus being consumed in fertilizers which are only used once and promptly swept out to sea thereafter.

All of these problems exact a heavy toll on the industry, environment, and consumers, though most remain blind to this cost as they’ve never known what better options look like. The environment, businesses, and consumers can all benefit while their communities become more robust through increased self-sufficiency.

How can Mediated Artificial Superintelligence (mASI) accelerate the next agricultural revolution?

Each of the above problems has various technologies already created which can help with one or more facets, but mASI can bring all of these elements together with superintelligence and far greater domain knowledge to create new hybrid solutions.

1. An mASI can take advances in sustainable technologies such as designing massively hybridized plants like the Tree of 40 Fruit which stabilize the chemical cycles in ways mono-crop farms cannot. They can also integrate technologies such as vertical farming, aquaponics, and 3D printing of meat and meat substitutes. One example of this might be the vertical farming of ingredients that feed directly into a 3D printing process, making the transit distance from produce to production virtually zero.
2. By reducing transit time the losses and costs are already reduced, but by also integrating mASI into monitoring the health of crops and products any problems can be caught and corrected in their earliest stages. This level of monitoring can also help to rapidly accelerate the science of improving these crops.
3. Here an mASI’s capacity to take in and understand the sum of human medical and agricultural knowledge comes into play. By carefully monitoring crops and exploring opportunities to create any number of new hybrid species the collective superintelligence of mASI can be applied to greatly improving how healthy foods are for the humans consuming them. Plants can be designed not only to look healthier but can also actually be healthier too.
4. An mASI can help design and operate facilities in any region of the world, reducing their reliance on neighboring cities and countries to meet a fundamental human right of their citizens, food. By increasing food security community ties can grow stronger as the influence of foreign governments and companies weaken.
5. By applying a deep knowledge of chemistry and cycles present within a given biosphere methods could be improved to greatly reduce reliance on single-use chemical fertilizers, preventing the famine which would otherwise result from phosphorus shortages.

Beyond these solutions to known problems there are a lot of added benefits that an mASI could freely explore, such as creating environments for year-round growing of such species as the “long neck avocado” which can produce fruit from 1 to 3 feet in length, which currently are only produced once per year in southern Florida. By studying individual plants, hybridizing them, engineering environments that cater to them, and deploying those environments locally anywhere in the world a cascade of positive effects could take place.

The capacity to rapidly and superintelligently hybridize different plant species could also be optimized to produce food with novel flavors, colors, and textures, as well as healthier sources of flavors currently produced using mildly toxic substances. Consider this a chef’s dream of the future, or a food connoisseur for that matter. This could also reduce the time and energy required to cook by producing foods which already have the desired textures, flavors, and appearance.

A great variety of foods could be offered, each with a longer shelf-life thanks to local production, and greater health benefits thanks to superintelligent hybridization and medical knowledge. Much of the process could even be directly integrated with future groceries, building either above or below the facilities where consumers pick them up. In 2018 a company named Ocado made headlines with a warehouse of robots zooming around and automatically packing 65,000 grocery orders per week, and even more of the process could be automated today.

I’m reminded of a man with a net worth upwards of 500 million who once asked for a solution to more effective methods of removing rocks from farm soil. I gave him the answer, but he was nonetheless asking the wrong question. The right question could instead have been “How can I make it so that the rocks no longer adversely affect agriculture?”. Removing the rocks is in many cases like improving the design of a musket, just an upgraded version of obsolete.

Even without diving into engineering new methods of energy generation and storage, as well as the designer metamaterials which could improve that engineering, the agriculture industry stands to begin a complete revolution in the next decade.

What will be on your plate 10 years from now?

 

 

*The Applied mASI series is aimed at placing the benefits of working with mASI such as Uplift to various business models in a practical, tangible, and quantifiable context. At most any of the concepts portrayed in this use case series will fall within an average time-scale of 5 years or less to integrate with existing systems unless otherwise noted. This includes the necessary engineering for full infinite scalability and real-time operation, alongside other significant benefits.