Big data og kunstig intelligens i akvakultur

Offentlig prosjektsammendrag

This project aims to develop AI-driven tools to enhance AquaGen's breeding operations and data processing. Leveraging AquaGen's extensive image, genotype, and sequence data, we will use advancements in computer vision, machine learning, large language models, and simulation software to innovate in aquaculture. The primary objective is to create proprietary tools for automating phenotypic trait detection, improving genotyping efficiency, and refining breeding value predictions. The key challenge is effectively utilizing large datasets for actionable insights, which requires custom software development and new analytical methods. We will conduct systematic R&D, combining in-house development with collaboration from partners like Thermo Fisher and NMBU's CIGENE research center, positioning AquaGen as a leader in aquaculture innovation.