Machine learning as code has become a reality, with frameworks like Hugging Face's Transformers and PyTorch allowing developers to build and deploy models without extensive expertise. This shift enables more people to contribute to AI development, but also raises concerns about model bias and accountability. The trend is driven by the increasing availability of pre-trained models and libraries that simplify the process of building custom models. --- Why it matters: This matters because it lowers the barrier to entry for developers who want to build and deploy AI models, potentially accelerating innovation in areas like natural language processing and computer vision. Source: https://huggingface.co/blog/the-age-of-ml-as-code