I'm fascinated by AI and want to understand the fundamentals: what neural networks are, how nodes, weights, and biases work, how training changes a model, how it processes a prompt, and how the field developed. I understand that AI is built on mathematics, but ADHD makes multi-step calculations difficult for me, especially when I have to keep track of several steps at once. I'm not trying to become an AI researcher yet or understand every equation. I'd like a clear, deeper conceptual overview first, and I'm wondering how much mathematics is really necessary at that stage. Can computers or AI tools handle the difficult calculations while I focus on understanding the ideas?
3 Answers
You can build a strong conceptual understanding before learning the underlying math. Start with the ideas: a neural network is a collection of connected numerical operations; weights control how strongly inputs affect later calculations; biases shift the results; and training adjusts those values so the model produces better answers. For language models, the system processes text as numerical tokens and predicts what token is likely to come next. You do not need to calculate everything by hand to understand that process. Just keep in mind that a complete technical understanding eventually requires topics such as algebra, probability, calculus, and linear algebra.
Neural networks were not invented by one person or all at once. Their history includes early mathematical models of artificial neurons, the perceptron, backpropagation, and later advances in computing power and data. Python is commonly used because libraries can express the model and training process conveniently, but Python itself is not what makes a system intelligent. The learning comes from an optimization process that adjusts many parameters based on examples.
A good learning path is to begin with visual explanations of perceptrons, layers, weights, activation functions, loss, and gradient descent. Then try a tiny neural network where a computer performs the arithmetic for you. That lets you connect the concepts to real behavior without getting stuck on carrying numbers through long equations. ADHD does not mean you cannot learn this; studying one small concept at a time and using diagrams or interactive examples may work better than trying to hold the whole model in your head at once.
That’s the level I’m looking for right now. I want to understand how information moves through a network, how training changes the weights, and how a model turns an input into a response before deciding whether to study the deeper mathematics.