TL;DR Key Takeaways : Knowledge distillation enables large AI models to transfer their expertise to smaller, more efficient models using “soft labels,” enhancing scalability and deployment in ...

While model distillation, the method of teaching smaller, efficient models (students) from larger, more complex ones (teachers), isn't new, DeepSeek’s implementation of it is groundbreaking.

Distillation, also known as model or knowledge distillation, is a process where knowledge is transferred from a large, complex AI ‘teacher’ model to a smaller and more efficient ‘student ...

Knowledge distillation from LLMs to SLMs begins with two key components: a pre-trained LLM that serves as the “teacher,” and a smaller architecture that will become the SLM “student.” ...

Distillation is also a victory for advocates of open models, where the technology is made freely available for developers to build upon. DeepSeek has made its recent models also open for developers.

Leading artificial intelligence firms including OpenAI, Microsoft, and Meta are turning to a process called “distillation” in the global race to create AI models that are cheaper for consumers ...

Developers can use OpenAI’s platform for distillation, learning from the large language models that underpin products like ChatGPT. OpenAI’s largest backer, Microsoft, used GPT-4 to distil its ...

Distillation is now enabling less-capitalized startups and research labs to compete at the cutting edge faster than ever before. Using this technique, researchers at Berkeley said, they recreated ...

OpenAI has said that it believes that DeepSeek, the Chinese start-up behind the shockingly powerful AI model that launched last month, may have ripped off its technology. The irony is rich: We ...

Why ‘Distillation’ Has Become the Scariest Word for AI Companies DeepSeek’s success learning from bigger AI models raises questions about the billions being spent on the most advanced technology ...