Development of highly intelligent computers requires a conceptual foundation that will overcome the limitations of the von Neumann architecture. Architectures for such a foundation should meet the following design goals: * Address the fundamental organizational issues of large-scale parallelism and sharing in a fully integrated way. This means attention to organizational principles, as well as hardware and software. * Serve as an experimental apparatus for testing large-scale artificial intelligence systems. * Explore the feasibility of an architecture based on abstractions, which serve as natural computational primitives for parallel processing. Such abstractions should be logically independent of their software and hardware host implementations. In this paper we lay out some of the fundamental design issues in parallel architectures for Artificial Intelligence, delineate limitations of previous parallel architectures, and outline a new approach that we are pursuing.