  We argue that hardware modularity plays a key role in the convergence of
Robotics and Artificial Intelligence (AI). We introduce a new approach for
building robots that leads to more adaptable and capable machines. We present
the concept of a self-adaptable robot that makes use of hardware modularity and
AI techniques to reduce the effort and time required to be built. We
demonstrate in simulation and with a real robot how, rather than programming,
training produces behaviors in the robot that generalize fast and produce
robust outputs in the presence of noise. In particular, we advocate for
mammals.
