How AI actually ‘thinks’ without thinking?

The source materials offer both a broad overview of Artificial Intelligence (AI) and its societal implications and a detailed, historical, and mathematical examination of neural networks (NN). The first source, excerpts from "Demystifying AI," focuses on explaining fundamental AI concepts like machine learning and deep learning to a general audience, discussing current applications such as autonomous vehicles, and exploring ethical concerns like bias and the future of work. Conversely, the second source, a mathematical introduction to neural networks, traces the history of AI from its ambitious beginnings through "AI winters" to modern breakthroughs like AlphaGo, dedicating significant attention to the mathematical underpinnings of NN design, learning algorithms like backpropagation and gradient descent, and specialized architectures like Convolutional Neural Networks (CNNs). Both texts address supervised, unsupervised, and reinforcement learning, with the mathematical text providing deeper context on how these learning techniques are practically realized in systems like AlphaGo through Monte Carlo Tree Search (MCTS). Ultimately, the materials provide complementary perspectives on AI, covering both the general use cases and risks and the technical evolution and mathematical theory of the technology. Free Online Image Compressor :- https://30tools.com/image-compressor Compress your images online for free. Reduce the file size of your JPG, PNG, and WebP photos by up to 80% while maintaining excellent visual quality. on https://30tools.com/ Get More tools here....