Events

How should we study something like "AI"—a subject of social and capital investment that rests more on speculative promises than given technologies or use cases? Drawing on political economic analyses of the tech sector, as well as a broader set of speculative fabulation practices by fellow data centre scholars, the talk will place AI in the past tense in order to assess both what it was and what it can become.

Associate Research Officer Terry Stewart explores why brains are far more energy-efficient than AI systems, highlighting differences in how they process information. It examines how brain-inspired algorithms and neuromorphic hardware could make AI more efficient by mimicking how the brain represents time and space.