Key developments: Researchers announced an ultra-small nanolaser that may let microchips send data via light instead of electricity, a shift that could halve the energy needed for computing. In parallel, a new AI methodology dramatically cuts the power required for machine‑learning tasks, addressing the sector’s growing share of U.S. electricity use. Additionally, engineers are testing oilfield wastewater as a cooling medium for data centers, offering a way to slash freshwater consumption while still managing heat.
Why they matter: Computing power drives everything from cloud services to scientific research, and its energy footprint is rising rapidly. Cutting chip energy by 50% and reducing AI power consumption can lower overall carbon emissions and operating costs. Sustainable cooling solutions further reduce the environmental impact of massive data‑center farms, which are typically water‑intensive.
What to watch next: Follow the scaling of nanolaser‑based photonic interconnects from lab prototypes to commercial chips, monitor adoption timelines for the low‑energy AI algorithms across major AI platforms, and track field trials of wastewater‑based cooling systems to see if they achieve the promised water savings without compromising performance. [[1, 2]]