Karpathy maps the inference chain from 1970s sci-fi to LLMs
The post reframes today's AI as the end point of a contingent chain rather than an obvious trajectory, which sharpens how readers judge current forecasts. Practitioners and analysts studying AI's historical drivers get a compact map linking computing, networking, data, Moore's law and scaling economics. It also clarifies why capital and capability now concentrate in a handful of labs that train and deploy copies of a few models.
