[d_burfoot]

It's strange to write a history of AI research without talking about the three big epochs:

- logical/symbolic AI, aka GOFAI, which led to work like SAT solvers and STRIPS planners

- classical label-based Machine Learning. Here the Perceptron was the starting point and the Support Vector Machine was the paradigmatic result.

- modern self-supervised raw-data ML, of which GPT is the pinnacle result.

It's very interesting to think about what motivated each era, what their blind spots were, and why people who worked in that timeframe couldn't see why the successor era was obviously (in retrospect) superior.

[visarga]

I’d split modern ML era in pre and post gpt3 (2020)

[AareyBaba]

You omitted the 90's when artificial life, genetic algorithms, subsumption architecture were the research topics.