Google has teamed up with Akamai to bring AI-generated responses closer to users. The new system stores answers from large language models at edge locations around the world. This means responses load faster because they come from nearby servers instead of distant data centers.

(Google’s Akamai AI Caches AI Model Responses at Edge Locations.)

The collaboration uses Akamai’s edge network to cache outputs from Google’s AI models. When a user asks a question, the system checks if the answer is already saved at the nearest edge point. If it is, the response is delivered right away. This cuts down wait time and reduces strain on central servers.

Edge caching works best for common or repeated queries. Popular questions get stored once and reused many times. That helps save computing power and energy. It also makes the experience smoother for users who expect quick replies.

Google says this setup improves performance without lowering quality. The cached answers are the same as those generated fresh each time. Security and privacy stay strong because no personal data is stored in the cache. Only general responses to public questions are saved.

This move shows how major tech companies are adapting infrastructure for the AI era. As more people use AI tools every day, speed and efficiency matter more than ever. Placing AI responses at the edge meets that need.

(Google’s Akamai AI Caches AI Model Responses at Edge Locations.)

Akamai’s global network includes thousands of locations. That reach lets Google serve users almost anywhere with minimal delay. Both companies believe this approach will support future growth in AI usage. They plan to expand the system as demand rises.