Companies like Symbolics and Lisp Machines Inc. built and sold specialized workstations optimized to run the Lisp programming language AI research depended on, employing engineers to design, sell and maintain them. Cheaper general-purpose workstations caught up in raw performance by the late 1980s, and the entire Lisp-machine industry collapsed within about two years — a symbol of the second AI winter.
Lisp machine engineer no longer exists as a living trade. Here is what erased it, and which profession took on the work.
1943–1956
The idea and the name
Warren McCulloch and Walter Pitts' 1943 paper modeling neurons as simple logical switches gave later researchers a mathematical starting point, and Alan Turing's 1950 proposal of a practical test for machine intelligence gave the question a public shape. Both ideas fed into the 1956 Dartmouth workshop, where John McCarthy and three colleagues coined 'artificial intelligence' for a summer meeting that produced far less technical progress than its organizers hoped, but permanently named the field they had just founded.
What else was happening then
1943
McCulloch and Pitts model the neuron mathematically
Warren McCulloch and Walter Pitts publish 'A Logical Calculus of the Ideas Immanent in Nervous Activity,' showing that networks of simplified, all-or-nothing neurons could in principle compute any logical function — a theoretical seed later credited as the ancestor of the artificial neural network.
1950
Turing proposes the imitation game
In 'Computing Machinery and Intelligence,' published in the journal Mind, Alan Turing sidesteps the question 'can machines think' and proposes a practical test instead, predicting that within fifty years a machine with about a billion bits of storage would fool an average interrogator at least 30% of the time.
1956
The Dartmouth workshop names the field
John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon's eight-week Dartmouth summer workshop coins the term 'artificial intelligence' and brings together roughly ten researchers who would go on to found much of the field's early research agenda.
1958
Rosenblatt builds the Perceptron
Frank Rosenblatt's Perceptron, first implemented in software and then in custom hardware at Cornell, learns to classify simple images by adjusting its own connection weights — the first working demonstration of a trainable artificial neural network.
Where that work lives now
Designs and tests the algorithms behind machine intelligence, in a field now racing to automate a growing share of its own research process.
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