Description
In Thinking with AI, computer scientist John McCormick explores one of the oldest and most fundamental questions in the field, “Can machines think?” first posed by Alan Turing. Drawing on his detailed understanding of how modern AI systems work, the author attempts to clarify the boundaries between human thinking and machine processing.
In a simple and understandable way, he explains the ideas behind the two main pillars of the 21st century AI revolution: deep neural networks and reinforcement learning. The book examines the world’s most famous AI systems, such as AlphaGo and ChatGPT, comparing their similarities and differences with the processes of the human brain, and challenging the concept of emergent intelligence.
Book Features
- A comprehensive examination of Alan Turing’s historical question about the ability of machines to think, with a look at today’s technologies.
- Simple and tangible explanations of complex concepts such as deep neural networks and reinforcement learning for non-specialist audiences
- Analyzing the working process of artificial intelligence masterpieces such as computer vision models, AlphaGo, and ChatGpatty
- Structural comparison between data processing mechanisms in computer systems and human brain functions
- Discovering new perspectives on “emerging intelligence” and proving that the boundaries of humanity are maintained despite the simulation of thought
Book specifications
- Publisher: Thinking EdTech
- Instructor/Author: Amelia King
- Number of pages: 143
- Number of chapters: 25
- Format: pdf
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File size
1.33 MB
