From algorithms that mimic honeybee navigation to spiking neural nets and tiny drones running on neuromorphic chips, efforts to copy the functions of insect and animal brains have major implications for AI and robotics.
Artficial intelligence (AI) has the potential to solve some of the world’s biggest challenges, from climate modelling to healthcare breakthroughs, but the associated computational power could come at a heavy environmental cost. Sophisticated deep learning and neural networks, developed by the likes of ChatGPT creator OpenAI, Google and Microsoft, run on networks of servers in data centres and require huge amounts of energy to power and water to remain cool.
The International Energy Agency has estimated that total electricity consumption in data centres could double from 2022 levels to 1,000TWh in 2026, equivalent to the annual electricity demand of Japan. Furthermore, analysis by The Washington Post and University of California estimated that ChatGPT consumes just over a...