What does the term 'smart systems' refer to in AI?

The term 'smart systems' in AI primarily refers to systems that learn from data to improve performance. This characteristic is central to artificial intelligence, as it allows these systems to adapt based on experiences and input they receive over time. By utilizing various machine learning algorithms, smart systems can identify patterns within data, refine their processes, and enhance their decision-making capabilities without needing explicit programming for every new scenario. This learning ability is pivotal to the evolution and effectiveness of AI applications in various fields, including agriculture.

While smart systems can perform tasks, analyze data, and contribute to decision-making processes, their distinctive trait lies in the learning aspect. This capacity for continuous improvement sets them apart from traditional systems that follow predefined rules and lack the flexibility to adapt based on new information. The focus on learning from data fosters a dynamic system that can respond to changing conditions or requirements, making it invaluable in applications like yield monitoring, where accuracy and adaptation to variable factors are crucial for success.