AI companies are facing challenges as rivals use a process called distillation to create smaller, cheaper versions of their large models. Distillation, similar to making strong liquor from a weak mash, involves using a large AI model (the teacher) to train a smaller one (the student) by feeding it responses from the teacher. This allows the smaller model to mimic the larger one without needing extensive data collection and training. Companies like Anthropic and OpenAI have caught others trying to distill their models, which threatens their investments and competitive edge. Distillation is appealing because it makes AI models more efficient and accessible, but it also raises concerns about intellectual property and competition.
QUESTION: How might the practice of distillation in AI development impact the future of technology and innovation?
What is AI model distillation, and why is it so hard to stop?
