By 2026, the amount of data generated at the edge is overwhelming memory bandwidth and power budgets. Lucas explains how a technique called near-sensor compression is moving data reduction from the CPU to the sensor itself. He walks through a concrete example: a 4K image sensor that outputs 400 megabytes per second, and how a dedicated compression engine can shrink that by 60 percent with no visible quality loss. Luna asks about the trade-offs in latency and energy, and Lucas points to a 2025 paper from Samsung showing a 45 percent power reduction in an always-on camera pipeline. They also discuss how this approach is spreading to lidar, microphones, and even IoT temperature sensors. The episode closes with the question of whether near-sensor compression could become a standard IP block in every system-on-chip.

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