The rise of the Internet of Things (IoT), autonomous vehicles, and the push for microservices development all rely on the same basic software principle: increased autonomy for machines. To date, most of this autonomy has been accomplished by creating highly accurate, custom-built operating systems that operate within a closed system of components that operate on the same shared data models. The cost of increased autonomy has been limited ability to interact with other systems. Yet, in nature, crosssystem interaction is common and, indeed, essential. Recent work on how the brain works, how animals communicate, and how adaptation works shows that the key to success is not accuracy in communications, but the opposite approximation. It is approximate understanding that leads to interpretation, assumption, and creative thinking. Attempts to build computer systems that are ever more exact are actually heading us in the wrong direction. In this talk, Mike Amundsen draws on material from social sciences, communication theory, and systems design to outline a future model of computing that relies on fuzzy logic, approximation, and built-in inaccuracies to help create robust machine-to-machine communications that can lead to new autonomous software that can go beyond the original programming and result in new functionality and efficiencies when interacting with other systems. An internationally-known author and lecturer, Mike Amundsen travels throughout the United States and Europe, consulting and speaking on a wide range of topics including distributed network architecture, Web application development and cloud computing. His recent work focuses on the role hypermedia plays in creating and maintaining applications that can successfully evolve over time. He has more than a dozen books to his credit, the most recent of which is RESTful Web APIs.