Symbolic AI, sometimes referred to as Good Old-fashioned AI, has its roots in the earliest days of the AI project. It seeks to represent reasoning using explicit data structures often drawn from logic. Symbolic AI systems have the advantage of being comparatively easy to understand and analyse and potentially allow compact forms of representation and communication. Their disadvantages tend to include inflexibility, a high knowledge engineering cost, and difficulty handling non-symbolic, statistical and analogue processes such as vision and motion. This talk will cover a brief history of the field and current topics within it as well as looking at proposals for combining symbolic and non-symbolic reasoning.