Memory cache

Memory cache in AI is an optimization technique that speeds up inference (the process of generating responses) and reduces computational cost.

Core ideas:

• AI models require heavy mathematical calculations; repeating these from scratch every time is slow and power-hungry.
• Caching saves the results of certain calculations so they can be reused for future queries or later steps in a conversation.
• This reduces the number of computations needed, making inference faster and more efficient.
• A key example is KV (key–value) caching in transformer models, which stores intermediate representations so the model doesn’t have to recompute them for each new token, accelerating response generation and saving energy.