ChatGPT in the agricultural sector: advantages and opportunities
Artificial intelligence technologies are increasingly being used in various sectors of the economy, including agriculture. A promising tool is ChatGPT, a generative AI model that can be used to automate many processes in the agricultural sector.
In this article we will see how ChatGPT can be used with its advantages and possibilities in the agricultural sector.
ChatGPT Technology Overview
ChatGPT is an innovative solution to create a chatbot capable of having a dialogue, finding bugs in codes, writing lines and scripts and even discussing. We won’t go into the technical details, but if you’re interested you can read more here or here. Our aim is to look at the function of this technology in the agricultural sector.
ChatGPT was trained using internet databases and reinforcement learning from human feedback. The neural network was trained several times to make its answers even more precise.
The main goal of developing ChatGPT was to make AI as user-friendly, correct and “human” as possible. The system offers multiple opportunities to automate various processes, reduce errors and improve work efficiency.
ChatGPT has many features and capabilities:
• Generate expressions, sentences or text to create content for websites or advertisements.
• Request a response based on the training information on which the neural network was trained.
• Solving problems, for example by formulating a concrete problem and suggesting possible solutions.
• Generate a variety of content, including ads, social media posts, news articles, and other types of text.
• Auto-complete phrases and expressions in applications when the user enters text in the search field or composes emails.
• Create different types of chatbots that can help with customer service: answering questions, learning customer preferences, or providing advice.
• Extracts information from the text and identifies the most important information in the text.
These are just some of the features of ChatGPT and its counterparts. Developers can use this technology to create innovative applications that not only save time and resources, but also better understand user needs and preferences.
How artificial intelligence is currently used in agriculture
Artificial intelligence is becoming increasingly popular and is also increasingly being used in agriculture. Nowadays, artificial intelligence technologies offer the opportunity to solve many emerging problems in the agricultural sector, from increasing yields to reducing agricultural production costs.
One of the companies using artificial intelligence to improve production is SmartAGRO, a Russian IT company specializing in the development and implementation of intelligent systems to solve complex problems in industrial agriculture.
‘s flagship product, Agroanalytics-IoT, automates up to 90% of business processes in the industry, drastically reducing crop losses.
Another developer of intelligent solutions in the agricultural sector is SR Data, a private Russian technology company that provides high- and ultra-high-resolution spatial images and analyses them using mathematical models and artificial intelligence systems. In addition to optical images, the company uses radar images to minimize the negative impact of time on the quality of the information extracted from the images. Such a solution makes sense and is necessary in the agricultural sector, as it enables professionals to receive high-quality data at the right time. However, the company cannot calculate vegetation rates directly from these images, so it uses AI algorithms to predict them.
A good example of the use of artificial intelligence in agriculture is automated greenhouses. Using today’s machine learning and data analytics systems, AI can help streamline factory management processes to increase production and reduce costs. The solution was developed in 2022 by a team from the Russian Agricultural Bank and the Moscow Institute of Physics and Technology, which participated in the Autonomous Greenhouse Challenge competition.
By analysing data from sensors and monitors in the greenhouse, including lighting, humidity, temperature and other parameters, AI algorithms determined the optimal parameters for plant growth. The system then automatically monitored and adjusted the environmental parameters. This greenhouse management system helps professionals to optimize the growing conditions of the plants and achieve higher yields.