Part 6/9:
In addition to this architecture, Deepseek incorporates two groundbreaking technologies: multi-head latent attention and multi-token prediction. The first enhances the model's ability to remember information, which is especially valuable for lengthy documents and conversations, while the latter accelerates its response generation, increasing output speeds by nearly 80%.
Compressive testing further reveals that when Deepseek is refined into a 4-bit format, its size reduces to 352 GB, making it feasible to operate on high-end personal computers, like the Mac Studio. This is monumental as it paves the way for running sophisticated AI on compact, less power-hungry devices, potentially redefining the deployment landscape of artificial intelligence.