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Consider "modern" to mean NN/connectionist vs GOFAI AI attempts like CYC or SOAR. I dunno. The earliest research into what we now call "neural networks" dates
by mindcrime 3y ago
Consider "modern" to mean NN/connectionist vs GOFAI AI attempts like CYC or SOAR.
I dunno. The earliest research into what we now call "neural networks" dates back to at least the 1950's (Frank Rosenblatt and the Perceptron) and arguably into the 1940's (Warren McCulloch and Walter Pitts and the TLU "neuron"). And depending on how generous one is with their interpretation of certain things, arguments have been made that the history of neural network research dates back to before the invention of the digital computer altogether, or even before electrical power was ubiquitous (eg, late 1800's). Regarding the latter bit, I believe it was Jurgen Schmidhuber who advanced that argument in an interview I saw a while back and as best as I can recall, he was referring to a certain line of mathematical research from that era.
In the end, defining "modern" is probably not something we're ever going to reach consensus on, but I really think your proposal misses the mark by a small touch.
- HarHarVeryFunny 3y agoSure, the history of NNs goes back a while, but nobody was attempting to build AI out of perceptrons (single layer), which were famously criticized as not being able to even implement an XOR function. The modern era of NNs started with being able to train multilayer neural nets using backprop, but the ability to train NNs large enough to actually be useful for complex things AI research, can arguably be dated to the 2012 Imagenet competition when Geoff Hinton's team repurposed GPUs to train AlexNet. But, AlexNet was just a CNN, a classifier, which IMO is better just considered as ML, not AI, so if we're looking for the first AI in this post-GOFAI world of NN-based experimentation, then it seems we have to give the nod to transformer-based LLMs.