Marvin Minsky—an MIT computer science professor, artificial intelligence pioneer, and a personal friend of mine—died on Sunday of a massive cerebral brain hemorrhage at age 88.
Marvin Minsky—the father of Artificial Intelligence (AI)—is dead at 88 but his work will continue as his most far-reaching futuristic visions have yet to be achieved.
Minsky's career was defined early on in his first book on "automatic computation"—a topic that was too far ahead of its time in 1967 to be recognized as valuable. In 1969 he described artificial intelligence (AI) in his seminal text Perceptrons: An Introduction to Computational Geometry (1969)—the first text dedicated to neural networks (although their ability to learn had been defined by Donald Hebb as far back as 1949).
Many a debate I had with Minsky over the merits of artificial intelligence (AI) versus artificial neural networks. Minsky had used AI to teach computers to play (and win) at games like checkers, to speak using voice synthesis and to perform other amazing tasks in their day. However, he considered neural networks a dead-end study in the 1970s favoring AI, which could be controlled with clear and understandable "expert system" rules written by programmers and engineers. Neural networks could capture knowledge, he admitted, but their internal structure is just as decipherable as that of real brains. Finally, however, Minsky embraced neural networks due to limitations in the AI "expert systems" he so loved. Today expert systems are gone, and we hardly differentiate between AI and neural networks, especially the "deep learning" variety made possible by today's ultra-fast computers that can simulate multi-layer versions of neural networks that Minsky had invented in his book "Perceptrons" but was limited in realizing by the computers of his time.
Minsky was still ahead of today's "deep learning" neural networks in his 1986 book, Society of Mind which followed his 1985 book Robotics: The First Authoritative Report from the Ultimate High-Tech Frontier. In Society of Mind he envisioned robotic brain's with heterogeneous deep learning neural networks that interacted with one another to produce not just artificial intelligence, but genuine machine intelligence on-par with that of the human brain.
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