Show HN: A narrative walk through AI history, paper by paper (1936–2025) (github.com)

A new project titled "A narrative walk through AI history, paper by paper (1936–2025)" aims to create a cohesive and accessible account of artificial intelligence's evolution. Spanning 66 chapters across eight distinct eras, this resource is designed for a broad audience—from curious teenagers to seasoned engineers—seeking to understand the significant milestones and concepts that have shaped the field. Each chapter provides a plain-language summary of pivotal papers and theories, contextualizing their importance without overwhelming readers with jargon or complex mathematics. This initiative is significant for the AI/ML community as it fills a notable gap in the existing literature by offering a structured narrative that connects the dots in AI history. Instead of scattered information across journals and Wikipedia, it presents a sequential exploration of key developments, such as the Turing Test, the birth of neural networks, and breakthroughs in deep learning. Readers can embark on a 12-15 hour journey through the timeline, enhancing their understanding of how past ideas laid the groundwork for today's advancements, including modern generative models like GPT-3 and AlphaFold. Each chapter is also interconnected, enabling continuous reading and engagement.