In this episode, the guest discusses the idea of using raw data to extract hierarchies of abstractions and the challenges in developing learning systems that can form those hierarchies. They delve into the Wolfram language and Wolfram Alpha as representing the dream of what AI is meant to be, a full-scale computational language.
The integration of symbolic representation and statistical machine learning in identifying patterns in language and image processing. It serves as a tool to explore the world of computable knowledge.
Visual drag and drop programming systems are only useful for simple data flow and transformation. Once the system requires conditional logic and iteration, a visual system no longer provides an advantage over traditional programming.
The Wolfram Language is a full-scale computational language that allows the representation of things in the world computationally, making it easier to express computational ideas in ways that both humans and computers can read. This technology can be used for personal productivity enhancement and Stephen Wolfram has been working on it for a large part of his life.
The speaker believes that being intelligent in isolation is meaningless; interactive AI is important because human intelligence is based on our ability to interact with others.
The development of symbolic discourse language enables the creation of richly represented smart contracts that can better represent and process complex data. This computational language has the potential to revolutionize how contracts and laws are conducted in the future.