Distillation Can Make AI Models Smaller and Cheaper

The article discusses a technique called "distillation" that can make AI models smaller and more cost-effective. Distillation involves using a large, complex model to train a smaller, simpler model, which can then be deployed more efficiently. The key advantage of distillation is that it allows researchers to leverage the knowledge and capabilities of a powerful, resource-intensive model without having to use that model directly. The smaller, distilled model can be deployed on devices with limited computing power, making AI technologies more accessible and widely applicable. The article notes that distillation is a fundamental technique in the field of machine learning and has been used to create various AI models, including language models and computer vision systems. By making AI models more compact and cheaper to run, distillation can help democratize the technology and enable its use in a wider range of applications.