The emergence of foundation models and transfer learning around 2017 marked a significant shift in AI development. Large tech companies began training extensive models on vast datasets, producing ideal parameters that serve as excellent starting points for domain-specific applications. This approach allows businesses, such as those in agriculture, to fine-tune existing models for specialized tasks, like identifying pests in crops, leveraging the power of pre-trained systems.
