Mastering AI

ChatGPT’s 2022 launch sparked an AI arms race.

In 2019, Microsoft invested $1 billion in a then-largely unknown start-up: OpenAI. Together, the two companies developed a powerful supercomputer designed to train one of the most extensive AI programs ever created. The software, dubbed GPT-3, could process relationships among 175 billion data points, including vast amounts of text from web pages, books, and Wikipedia. It used this information to “predict the next most likely word” in any given sequence, allowing it to code, answer factual questions, and translate languages in a human-like manner. More notably, it gave these outputs in response to “natural language” prompts: instructions framed conversationally rather than in code. This development meant even non-technical users could use the AI.

Before the advent of GPT-3, AI achievements remained niche — for example, defeating human chess or Go champions. These case studies demonstrated AI’s ability to learn from experience. However, they didn’t translate into practical applications or a consumer-friendly experience. The commercial potential of GPT-3 convinced Microsoft to increase its investment in OpenAI, leading to...