I took the MIT AI course 6.034 in 1972 from Patrick Winston. He taught that course periodically until his passing a couple years ago. The 2016? Lectures on MIT opencourseware. I would estimate there was 2/3 overlap between the 1972 and 2016 versions. That course is heavy on heuristics and not big data.
Around 1979 an MIT group lead by Gerald Sussman (still working) designed a workstation specifically to accelerate LISP. It was hypothesized a computer that ran LISP a thousand times faster would revolution AI. It did not. However the two LISP workstations that saw commercial sales did jump start the interactive graphics workstation market (UNIX, C and C++). Dedicated language machines could not keep up with the speed improvements of general CPUs.
On the other hand custom neural chips from Google, Apple, Nvidia (and soon MicroSoft) have really helped AI techniques based upon deep convolutional neural networks. Neural chips run orders of magnitude faster than general CPUs by using simpler arithmetic and parallelism.
> It was hypothesized a computer that ran LISP a thousand times faster would revolution AI. It did not. However the two LISP workstations that saw commercial sales did jump start the interactive graphics workstation market
It's very fitting then that GPUs have been so key in modern ML.
Around 1979 an MIT group lead by Gerald Sussman (still working) designed a workstation specifically to accelerate LISP. It was hypothesized a computer that ran LISP a thousand times faster would revolution AI. It did not. However the two LISP workstations that saw commercial sales did jump start the interactive graphics workstation market (UNIX, C and C++). Dedicated language machines could not keep up with the speed improvements of general CPUs.
On the other hand custom neural chips from Google, Apple, Nvidia (and soon MicroSoft) have really helped AI techniques based upon deep convolutional neural networks. Neural chips run orders of magnitude faster than general CPUs by using simpler arithmetic and parallelism.