Griffin Melson - Alan Turing's Computing Machinery and Intelligence
Sep 10, 2023
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Griffin Melson discusses Alan Turing's Computing Machinery and Intelligence with Cooper and Taylor. They explore Lacan's concept of masculine and feminine position, compare programming include statements to brainstem functions, understand programming functions and the problem of forgetting in machine learning. They also delve into the potential of quantum computing to break encryption and discuss who decides what is important. The episode wraps up with a farewell from the hosts.
Turing argues that machines can imitate humans through natural behavior and social assumptions.
Turing introduces Turing completeness, stating that any machine can simulate any other machine.
Machines' ability to think is questioned, but their influence and interaction with human lives are deemed important.
Deep dives
Turing proposes an imitation game
Turing introduces the imitation game, where a man, a woman, and an interrogator participate. The man's goal is to convince the interrogator that he is a man, while the woman aims to deceive the interrogator into thinking she is the man. The game raises the question of whether machines can successfully imitate humans.
Turing discusses the nature of machines
Turing explores the nature of machines and their potential to think. He argues that man is essentially a machine, and therefore, it is possible for machines to think. He highlights the importance of understanding machines' behaviors and the ability to imitate humans naturally, particularly through the use of stereotypes and social assumptions.
Turing explains the universality of computers
Turing asserts that all digital computers are fundamentally equivalent, regardless of their programming language or design. He introduces the concept of Turing completeness, stating that any machine capable of executing a certain set of operations can simulate any other machine.
Turing counters objections to machine thinking
Turing addresses objections to the concept of machines thinking. He dismisses theological objections by questioning the superiority of humans and their possession of souls. He also counters the argument that machines cannot think because they are designed by humans, emphasizing the universality of machine behavior. Turing concludes by highlighting the need for machine learning and its role in the thinking process.
The Potential of Quantum Computing and Encryption
Quantum computing has the potential to break traditional encryption completely, leading to concerns about data security. While there are attempts to develop quantum encryption, skepticism remains about its effectiveness. The fear is that as intellectual property becomes increasingly important, physical protocols to prevent unauthorized access may be implemented.
Thinking, Learning, and Knowing in Relation to Machines
The distinction between thinking and learning in relation to machines is explored. While machines might be capable of learning, the concept of thinking raises questions and hierarchical distinctions. The podcast suggests that knowing might be a more applicable term when discussing machines. The importance lies not in whether machines can think, but in how they influence and interact with human lives.
This week, Griffin joined Cooper and Taylor for a look at Alan Turing's Computing Machinery and Intelligence. We dig into what it means to think, and what a machine and a human might share or how they differ when it comes to thinking.
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