ABSTRACT
To understand the risks that AI poses and to learn what measures we can take to mitigate them, it is essential to have a basic understanding of the technology itself: how it works, how it is used, and where its strengths and weaknesses lie. This chapter describes key concepts in machine learning (ML), the approach that powers most modern AI systems, with a particular focus on the technologies that power Large Language Models such as OpenAI's GPT-4 or Google's Gemini. The chapter also introduces the phenomenon of scaling laws, where AI systems' performance improves predictably as the amounts of data and computation used during their training are increased. The recent pace of progress in AI research has fuelled debate which is briefly reviewed here on whether we should expect to see AI systems in the coming decades that match or surpass human performance on most cognitive tasks.
