From senses to sensitivity.
Machines are becoming increasingly capable of seeing, hearing, touching, locating and measuring the world around them. Sensing Machine looks at what comes next: how those signals become perception, context and appropriate action.
The project uses sensing in two related ways. The first is literal: machine senses such as vision, audio, touch, smell, motion, radio, depth and physiological signals. The second is broader: sensitivity to human context, nuance, intent, emotion, ambiguity and uncertainty.
A simple framework.
Sense the signals. Perceive the situation. Interpret context and human complexity. Act with sensitivity to what is happening.
Why Sensing Machine?
Much of modern AI begins with a prompt or a pre-existing digital representation. Sensing Machine is interested in systems that meet reality earlier: before the world has been translated into a clean instruction, label or database row.
It is not presented as a finished product or a claim that human complexity can be perfectly measured. It is a compact research identity around a question: what does a machine need to sense in order to understand?
Explore.
Start with the manifesto, then explore AI sensing, machine perception, human sensing and embodied AI.