What is Watson’s approach to training custom models?

Watson’s approach to training custom models involves using user-supplied data to create tailored AI solutions. This means that users can provide specific datasets that are relevant to their particular domain or needs, allowing the model to learn from that context. This customized training is crucial because it enables the model to better understand the nuances and specific characteristics of the data, leading to improved accuracy and relevance in its outputs for particular applications.

By using tailored datasets, Watson can effectively utilize the specific knowledge and requirements of different industries, enabling businesses to leverage AI in a way that closely aligns with their unique challenges and opportunities. This level of customization makes Watson particularly powerful for various use cases, as it facilitates deep learning from data that are particularly relevant to the user's goals and objectives.