Artificial intelligence functions by combining huge amounts of data with fast processing, using advanced algorithms to learn from distinct patterns and data similarities. The subfields of AI are:
This automates the building of analytical models, using neural network methods, research, principles of physics and statistical analysis to find and deliver insights into data. It does so, however, without being directly programmed for what to look for, what to conclude or where to look for it.
A neural network is a kind of robot or machine composed of interconnecting units (such as neuron) whose function is to process data and information by reacting to external inputs, communicating the data from one unit to the next. This process involves the units discovering meaning and connections in the data and information passed through.
Deep learning utilizes the aforementioned neural networks to take advantage of the advancement of computational power and improvement of training for AI to understand and learn complex patterns in massive amounts of data. One common use for this is speech recognition.
This subfield strives towards a human-like interaction with other machines. Essentially, utilizing cognitive computing, the primary objective it for a machine or robot to simulate processes of humans by interpreting images, data and speech, and producing identical outcomes, such as speaking coherently in a response.
Computer vision is reliant upon the recognition of patterns and the use of deep learning to recognize and understand what a picture or video footage consists of. This involves the AI processing, analyzing and understanding images and ultimately training AI to interpret its surroundings.
Natural Language Processing
Natural language processing is computers’ ability to examine, understand and ultimately autonomously generate the languages of humans. The next step along this path is natural language interaction, which involves humans communicating with computers and robots using common language to carry out certain tasks.
Essentially, the objective of AI is to develop increasingly sophisticated software and technology that can turn inputs into reason and output explanations through understanding.
For Agrinteligente, we understand that the Americas is a major market for artificial intelligence in the agriculture industry, with demand consistently increasing over the past few decades for sustainable solutions as impacts from climate change begin to be felt, with this issue expected to see demand accelerate as the years go by.
We aim to deliver increasingly intelligent, practical and direct solutions in the areas of crop management, weather mitigation, yield predictions, planting accuracy and efficiency, and general data analysis to help farmers in the fields. Far from taking the jobs of farmers, we aim to use AI to put the power and information in the hands of farmers, allowing them to do what they do best with the tool necessary for success.