A very long time ago, the ancient Egypt Philosopher and founder of Hermetism, Hermes Trismegistus, mentioned that by discovering the true nature of the gods, man has been able to reproduce it. But of course, this philosophical foundation of the ability of man to create machines is not to be downplayed while it is argued that the invention of the (first-generation) actionable digital computer in the 1940s triggered interests and investment in the sphere of Artificial Intelligence. In the 1950s the Turing Test was heavily lauded after Alan Turing speculated about the possibility of creating machines that think. According to the scientist and inventor, If a machine could carry on a conversation over a teleprinter that was indistinguishable from a conversation with a human being, then it was reasonable to say that the machine was thinking.
For many years now, AI and the Big data have been attracting a lot of buzzes. These concepts constitute the passion of modern tech enthusiasts and data scientists. The new generation literature is replete with tales of the same subject as both idealists and realists in the field dicker in their attempt to contribute to knowledge. You will marvel at the ingenuity of contemporary AI writers in their fictional creation of realities.
In the DC Comics book, we are made to understand the travails of young Victor Stone, an exceptionally intelligent boy who contrary to his science inclined parents had demonstrated a high level of genius and passion for athletics before witnessing a twist of fate which made him half human and half machine. Victor barely survived the spell of a ghastly accident after he was operated on by his scientist father, Dr. Silas Stone. Dr. Stone used all of his advanced scientific knowledge to save his only child’s life, and rebuild him into a superior being that was now more machine than man. As a cyborg, Victor was now far stronger than the average person, and could interface with computers and emit various types of energy that made him a formidable fighter and superhero. This technological transformation process would enduringly impact the history of work and economic breakthrough for the human race.
Apparently what at some point in time we had probably discountenanced as mere science fiction is fast becoming a gospel truth as we are now forced to think of the alarming substitution of human efforts with machines which are quite paradoxically the function of the former. As it is estimated that the wearable AI market will reach $180 billion by 2025, the doomsayers are out echoing the disruptive tendencies of AI in the work industry and how it may fully displace manpower in the next couple of decades. But according to the optimists, the emergence of AI in the work industry should be the least of the worries of humans as it is an invention which will take care of all the mundane tasks that employees currently handle, freeing their time to be more creative and perform the work that machines cannot. The impact of AI technologies on business is projected to increase labour productivity by up to 40 percent and enable people to make more efficient use of their time. According to the Accenture research institute, the impact of AI could double annual economic growth rates in 2035 by changing the nature of work and creating a new relationship between man and machine.
No doubt the application of machines and optimization of the big data has helped humanity thus far. Agriculture is increasingly expanding its sphere of influence through AI and optimization of the big data. This development which led to the birth of the concepts, precision Agriculture and smart farming inspired a paradigm shift in Agricultural practices and agribusiness. A new class of farmers called smart farmers have now emerged to make fortunes from of Agriculture without necessarily exerting their brawns or going through the toils experienced by the traditional farmers.
Through the application of technologies such as GPS, sensor tech, ICT, high-tech greenhouse, drones and robotics in farming activities, farmers are steadily recording headways in production optimization and crop sustainability. AI systems are really helping to improve harvest quality and control. For instance, sensor technologies aid farming in areas such as detecting diseases in plants, pests, and poor plant nutrition on farms. AI sensors can detect and target weeds and then decide which herbicides to apply within the right buffer zone. This helps to prevent over application of herbicides and excessive toxins that find their way in our food. AI has also proved useful in harvesting as robotics are now being utilized by companies to pick foods. For instance, companies like Harvest Croo produced autonomous strawberry picking machines and abundant robotics which operate on the basis of machine vision and sensor fusion to harvest mature apple from trees.
Another area where farmers are exploiting AI is in the use of the algorithm and seasonal forecasting models to improve agricultural accuracy and increase productivity. Farmers are able to leverage the algorithm and available data to predict upcoming weather patterns in order to make informed decisions. For example, In Córdoba, FENALCE which is a government body that compiles information on maize plantations, harvests, yields and costs, set up a web-based platform to collect and maintain data from individual farms. Local experts uploaded information on soils after visiting farms at various stages of the crop development, while IDEAM, Colombia’s weather agency, supplied weather information from six stations in the region. This allowed researchers to match daily weather station information with individual fields and the various stages of the growing season. The researchers used machine learning algorithms and expert analysis to measure the impact of different weather, soil conditions and farming practices on yields. They noticed that improving soil drainage to reduce run-off likely reduces yields when rainfall is lower, whereas doing the same in areas with a lot of rain boosts yields. This shows advice on crops needs to be site-specific. The study demonstrated that the amount of phosphorus applied, the seed rate, and field run-off capacity had a major impact on yield levels. Findings from this research allowed experts to guide small farmers towards the best practices to use in order to produce high, stable yields.
The Chatbots and the smart home helper, Alexa, are another important contribution of AI to Agriculture. Through this system, farmers could get advice and answers to various questions as well as recommendations on specific farm problems.
Taking to view the current trend in Agriculture and farming inspired by AI and data science, one can only agree that the sector is one with monumental prospects. By improving on this trend, it is anticipated that the Agric sector will have doubled if not tripled its current $ 5 trillion capacity by 2050.