The Infe Log | Latency and AI Evolution

"For an AI to feel like a thought, it must happen at the same speed as one."

The AI revolution has, until now, been a patient one. We have grown accustomed to waiting seconds for a model to "think," accepting the loading spinner as a necessary tax on the magic of generation. But as AI moves into the core of creative and operational workflows, the loading spinner is no longer a tax—it's a wall.

The Human Interface Limit

Human cognition operates on a precise temporal scale. A delay of 100 milliseconds is the ceiling for a response to feel instantaneous. When you cross that threshold, you break the flow. You transition from a "conversation" with an agent to "interfacing" with a computer.

The Infe Standard

Sub-100ms TTFT is the new baseline.

Our edge infrastructure ensures that the first token of any response arrives before your brain has time to register a pause.

Why the Edge Matters

Latency isn't just a compute problem; it's a physics problem. Light takes time to travel through fiber optics. By moving the inference engine to the edge of the network—physically closer to where the user lives—we bypass the "middle-mile" congestion that plagues traditional cloud providers.

At Infe.io, we have optimized our entire stack, from the custom LPU kernels at the core to the anycast routing at the edge, to ensure that latency is treated as what it truly is: a bug that needs to be fixed.