Sort of. The deep-learning AI revolution started with back propagation techniques (80s) that made neural nets trainable. But since then it's taken a long time t

Sort of. The deep-learning AI revolution started with back propagation techniques (80s) that made neural nets trainable. But since then it's taken a long time to get to the relatively recent architectural breakthroughs like transformers (2017) and modern-diffusion (2020) which lead to chat-gpt and dall-e. All of the big AI breakthroughs now are based on neural nets vs classical machine learning which grouped a bunch of statistical, regression, and optimization type models together. Modern AI is the synthesis of new techniques and old ideas plus huge datasets and huge computing power.