Seventy years of mathematics built the thing we call AI (medium.com)

A recent essay highlights that the advent of AI, often perceived as a sudden breakthrough, is instead the culmination of seventy years of mathematical evolution. The narrative began in 1943 with Warren McCulloch and Walter Pitts, who proposed a model for neurons as mathematical switches, laying the groundwork for neural networks. Key milestones followed, including Claude Shannon’s theories on communication and Alan Turing’s explorations of machine intelligence, culminating in the development of the transformer architecture in 2017. This new model dramatically improved how AI processes language, allowing for parallel attention across sequences and powering modern chatbots and AI systems. This historical perspective underscores that AI's capabilities have existed conceptually for decades, only manifesting recently due to advancements in hardware and data availability. The essay dispels the myth of AI as a revolutionary force, framing it instead as a systematic and gradual accumulation of knowledge. It emphasizes that what appears to be AI’s intelligence is a complex mathematical framework devoid of true understanding, reinforcing philosophical debates about the nature of machine consciousness. Understanding these implications not only informs the AI/ML community about its rich past but also guides ongoing dialogue about the responsible future of AI technologies.