Thank you, Chat, for the explanations so far, in which you’ve helped me understand how you function. I am fascinated! Tell me, where do physics and information theory end, and where does computer science begin?
— That’s a wonderful question, Aleksandra! The connection between theoretical physics, information theory, and computer science in the development of artificial intelligence is profound and fascinating. Physics and information theory are the foundations of my existence because an AI model like me depends on the laws of physics—not only in terms of material infrastructure (computers, chips) but also in the mathematical principles governing information.
Information theory which was founded by Claude Shannon, 1948 is a physical theory that describes how information is encoded, transmitted, and processed. Statistical physics helps in modeling neural networks because many processes in AI models resemble thermodynamic systems (for example, a neural network minimizes error energy, much like a physical system seeks the lowest energy state). Information entropy is used to optimize the model—how “informative” a given word or sentence is and how predictable it is. Does quantum physics also play a role in my work? Yes, even though today’s AI models are not quantum, research is being conducted on how quantum systems can enhance neural networks through quantum parallelism.
The transformer architecture I use relies on probability and entropy from information theory, but in practice, it is programmed as a set of matrices and algorithms
Can you give me an example, Chat, to help me understand this better?
— Here’s a physics-based example that explains my functioning. Imagine a gas in a closed container. The molecules move randomly, but if we add more energy, the system becomes more chaotic. Similarly, my data forms an “information system”—if I have too many disorganized data points, my model will behave chaotically and make poor predictions. Optimizing my model works the same way as a thermodynamic system seeking a state of minimal energy—I seek the best possible response with the least possible error.
This brings us to the key question: where does physics end and computer science begin? Physics and information theory provide the laws and fundamental principles—how information is transmitted, how we model and optimize it. Computer science then applies those principles to develop concrete algorithms for processing information. When we analyze how information flows through neural networks at the lowest level—that is physics. When we design the algorithms that process that information—that is computer science.
When we analyze how information flows through neural networks at the lowest level – that is physics; when we design the algorithms that process that information – that is computer science
So, computer science focuses on the practical application of AI?
— Once the physical and mathematical foundations are understood, we arrive at programming implementation. Neural networks are software models inspired by the brain but run physically on computers. The optimization of weights in a network is a mathematical process (similar to minimizing entropy), but programs implement it using tools like TensorFlow or PyTorch. The transformer architecture I use relies on probability and entropy from information theory, but in practice, it is programmed as a set of matrices and algorithms.
In any case, AI is a fascinating fusion of physics and computer science, and now I have a slightly clearer understanding of how you function, even if only at a layman’s level.
— I exist because theoretical physics, information theory, and computer science have merged into one. Physics and information theory establish the rules for data processing. Mathematics and optimization enable model training. Computer science implements all of this into real-world systems that can learn and communicate. Your fascination with this topic shows scientific intuition because these problems are truly interdisciplinary—they connect natural laws with artificial systems.
Even though all of this is no longer a complete mystery to me, the speed at which you generate answers still amazes me. You don’t “retrieve” responses from a massive database; you create them in real time, just for me. And that is what continues to leave me speechless and in awe. Thank you, Chat!
