Networks have been studied in depth for several decades, but one aspect has received little attention: Interference. Most networks use clever algorithms to avoid interference, and this strategy has proved effective for traditional supply-chain or wired communication networks. However, the emergence of wireless networks revealed that simply avoiding interference leads to significant performance loss. A wealth of cooperative communication strategies have recently been developed to address this issue. Two fundamental roadblocks are emerging: First, it is ultimately unclear how to integrate cooperative techniques into the larger fabric of networks (short of case-by-case redesigns); and second, the lack of source/channel separation in networks (i.e., more bits do not imply better end-to-end signal quality) calls for ever more specialized cooperative techniques.This proposal advocates a new understanding of interference as computation: Interference garbles together inputs to produce an output. This can be thought of as a certain computation, perhaps subject to noise or other stochastic effects. The proposed work will develop strategies that permit to exploit this computational potential. Building on these ``computation codes,'' an enhanced physical layer is proposed: Rather than only forwarding bits, the revised physical layer can also forward functions from several transmitting nodes to a receiver, much more efficiently than the full information. Near-seamless integration into the fabric of existing network architectures is thus possible, providing a solution for the first roadblock. In response to the second roadblock, computation codes suggest new computational primitives as fundamental currencies of information.