Shinycroak

During a Mastodon conversation between Signal Foundation President Meredith Whittaker and data scientist and activist Emily Gorcenski it was pointed out that most of the techniques that are called “AI” date to the 1970s and 1980s. Some predate modern computing. Ms. Whittaker: Deep learning techniques date from the 1980s, & “AI” had been hot/cold for decades, not slow until 2012. There was no new “single idea” in 2012. What WAS new, & propelled the AI boom, was concentrated resources (data/compute) controlled by tech cos. – link Ms. Gorcenski: Backpropagation dates back to the 60s. Deep learning neural nets used to be called “group methods of data handling” and date back to 1978 or so, when the first 8-layer (polynomial) neural network was developed. Fuzzy approximation networks and radial basis function networks hail from a similar era. Weiner explored the polynomial chaos in the 40s, the Karhunen-Loeve transform predates that iirc. - link Everything that could be do

Because of my limited knowledge, I have chosen to present these as disconnected notes rather than a more organized essay. However, I have not seen many of these thoughts before, so I hope this short note adds something new to the ongoing discourse. It’s not, really. Not intelligence, anyway. It doesn’t know truth from falsehood, or right from wrong. The technologies that are called artificial intelligence, ( diffusion models and large language models) , are basically very large grammars. They seem to replicate part of brain visual and speech centers, but no other neurological functions. In brain damaged people, there is a thing called confabulation . Confabulation is what happens when a damaged brain reaches for a memory and finds it’s not there. It just fills in the gaps. And I think that’s pretty much what an LLM does; it seems to be a replication of part of a brain but it has no real memory or logical capacity or ethics. A human author knows to fact check and not to plagiarize