A woman holds a cell phone in front of a computer screen displaying the DeepSeek logo (Photo by Artur Widak, NurPhoto via Getty Images) At this month’s Paris AI Summit, the global conversation around ...

Knowledge distillation is an increasingly influential technique in deep learning that involves transferring the knowledge embedded in a large, complex “teacher” network to a smaller, more efficient ...

Businesses are increasingly aiming to scale AI, but they often encounter constraints such as infrastructure costs and computational demands. Although large language models (LLMs) offer great potential ...

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’ model. Doing ...

What if the most powerful artificial intelligence models could teach their smaller, more efficient counterparts everything they know—without sacrificing performance? This isn’t science fiction; it’s ...

If you’ve ever used a neural network to solve a complex problem, you know they can be enormous in size, containing millions of parameters. For instance, the famous BERT model has about ~110 million.