January 23, 2025

Interpretive Summary: Artificial intelligence for livestock: a narrative review of the applications of computer vision systems and large language models for animal farming

Interpretive Summary: Artificial intelligence for livestock: a narrative review of the applications of computer vision systems and large language models for animal farming

By: Guilherme L Menezes, Gustavo Mazon, Rafael E P Ferreira, Victor E Cabrera, Joao R R Dorea

Implications:

  • AI is already integrated into many daily tasks, including facial recognition and airport security, and its use is expanding into agriculture.
  • AI supports data-driven decision-making in livestock production, particularly in dairy farming.
  • Computer vision systems (CVS) are applied in dairy farming for animal identification, behavior monitoring, feeding intake, body weight estimation, and disease detection.
  • Natural language processing (NLP) and large language models (LLMs) offer potential for optimizing data integration, dimensionality reduction, and knowledge retrieval in agriculture.
  • There is a significant knowledge gap in the use of LLMs in animal farming, presenting opportunities for new research and technological advancements.

Artificial intelligence (AI) has become essential for decision-making across various industries. The number of research projects involving AI increased by 2.5 times between 2010 and 2018 compared to the previous decade (Lu, 2019). Companies investing in AI have seen significant improvements in sales, employment, and market value (Babina et al., 2024). This growth explains the increase in AI-related jobs from 2007 to 2018. By 2025, global AI investments are expected to reach 200 billion U.S. dollars (Goldman Sachs, 2023).

Read more in Animal Frontiers.