The future is already here, and becoming more evenly distributed every day. Just back in 2006, when I first went off to college, the field of AI was, academically, considered a joke. And some people, somehow, still see it this way, even as almost every day new AIs are released that cost millions to train and demonstrate ever more impressive abilities. The key advancement is that new AIs can do a multitude of different tasks well, instead of being hyper-specialized. In this they are a form of early proto-AGI: artificial general intelligence, considered the holy grail of the field. These AIs have the ability to write convincing essays about many subjects, or play hundreds of types of games, or create AI-artwork of almost anything imaginable at the click of a button, and come bearing techno-angelic names like PaLM, Gato, GPT-3, DALL-E 2, Imagen, etc.
In response to these new AI models there is a rising class of AI critics, who downplay the results by focusing on terminology, fuzzy benchmarks, and minimization—and if the tide takes down your sandcastle, just build it further up the beach.