This paper describes work in progress, an architecture for an expressive machine, which learns, senses and responds to its environment with ‘creative’ output. This is not to mimic a human or any other known biological organism, but an attempt to investigate what it might mean for a machine to do this ‘on its own terms’. This hardware and software system forms the functional core of a large-scale interactive art installation, which plays with transduction between the material and non-material worlds, and between signals/stimuli in multiple forms. The meaning of ‘expression’ is discussed in reference to the machine. Some recent artworks from other artists are briefly reviewed, artworks which also employ a machine’s-eye view of the world. I discuss what expression might mean for these machines, and who or what might be the intended audience. Following from the artistic impetus for my work, the design rationale for the machine is presented. A modular architecture, with asynchronous messaging, allows for experimentation with various methods of pattern recognition, sensing and activation. Some sensing and expression modes are described in more detail. A neural network is trained to process live video input stream, to ‘taste’ what the machine is seeing in the world. A Responsive Markov Model is developed, with an automated method to extract vocabulary from selected sources (amongst others, Shakespeare’s sonnets and Molly Bloom’s ending monologue in James Joyce’s Ulysses) and the ability to respond to particular stimuli, in real time, in generating new texts.