I'm working on an eight-month study plan to prepare for potential postgraduate study in AI. The plan starts with foundational reading including Bostrom's Superintelligence, Brian Christian's The Alignment Problem, and Melanie Mitchell's Artificial Intelligence: A Guide for Thinking Humans. This initial phase aims to provide context around ethical considerations and societal implications before tackling more technical material.

The next phase focuses on machine learning fundamentals through resources like Goodfellow's Deep Learning, Bishop's Pattern Recognition and Machine Learning, and fast.ai's practical tutorials. I hope to then explore natural language processing using Jurafsky and Martin's Speech and Language Processing, along with some hands-on projects involving language models and transformers, areas that might complement my linguistics background. The final months would revisit AI safety and governance topics while working on practical applications. The goal is to develop a basic understanding across theory, implementation, and ethical considerations.