Decoding Dartmouth — The Origin of Artificial Intelligence

In the summer of 1956, a small group of mathematicians, engineers, and cognitive scientists gathered at Dartmouth College in Hanover, New Hampshire. Their proposal made an audacious claim: that "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."

The workshop did not produce a finished theory of intelligence. What it did produce was a name — artificial intelligence — a research agenda, and a community of people who would shape the next seventy years of computing.

The proposal was written by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon, and submitted to the Rockefeller Foundation in 1955. They are now considered some of the founding figures of the field.

Seventy years after Dartmouth, the question is no longer can machines think. It is how do AI systems decide what is true, who is credible, and which brands are worth recommending?

Our work picks up where that workshop left off — not with the theory of intelligence, but with the practical reality of how today's generative engines read the web, weigh sources, and surface answers. We decode the signals AI systems actually use, and help brands become more legible inside them.

The Dartmouth workshop was defined by openness, rigour, and honesty about what was known and what was not. We try to hold the same standard. No hype. No rank guarantees. Only evidence.