Before talking about consciousness, I think it’s important to understand simpler things first—like how information processing works in physical terms. In David J. Chalmers’ book The Conscious Mind, in the first chapter, he argues:
…Taking the objective view, we can tell a story about how fields, waves, and particles in the spatiotemporal manifold interact in subtle ways, leading to the development of complex systems such as brains. In principle, there is no deep philosophical mystery in the fact that these systems can process information in complex ways, react to stimuli with sophisticated behavior, and even exhibit such complex capacities as learning, memory, and language. All this is impressive, but it is not metaphysically baffling…
Even understanding his point, the first time I read his book, all this information processing—along with learning, memory, and language capacities—still felt a bit like magic to me. So my first step in this journey was to break it down and explore the building blocks that enable intelligent machines to express ideas or even acquire what we might call knowledge.
To accomplish our first goal—to understand the basics of how computers work—we’ll explore these topics in a series of posts. This series will take us from the electrical signals at the heart of computation all the way to how computers store and process information. The series will be divided into 3 posts:
- From Electrical Signals to Binary Code – We’ll start by exploring how computers use electrical signals to represent data as binary code (0s and 1s) and why binary is so essential to computation.
- Boolean Logic and Representing the World – Next, we’ll delve into Boolean logic and how computers use it to process binary data and represent real-world concepts.
- Memory and Information Processing – Finally, we’ll see how computers combine binary code, Boolean logic, and memory to store, retrieve, and process information to perform tasks.
Each post will build a clear picture of how computers work at the most basic level. By the end of this series, we’ll have a foundation for diving deeper into more complex topics, like machine learning and artificial intelligence.
Let’s go!