Talk:AI winter

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AI 'winter' necessarily follows from the spruiking of a concept having a basis only in the human imagination and no basis whatsoever in reality. There is no such thing as artificial intelligence. Never has been. And never will be. At least not by simulation implemented using digital computers. This is a necessary corollary arising from the study and understanding of the nature of deterministic computing. It is NOT possible for any deterministic computational system (eg an electronic digital computer) to emulate sentience (ie 'intelligence') in any way, shape or form. Persons who have studied and understoo\d computer science know this and do not expound 'artifical intelligence' using digital computers because they know that - by definition - it is NOT possible. And they possess intellectual honesty. However those who lack this understanding and/or do not possess intellectual honesty, or possess intellectual dishonesty DO expound the notion of 'artificial intelligence' using deterministic computing devices. Such people are examples of the phenomenon known as 'snake-oil salesmen'; that is, people seeking to enrich themselves by promoting a fraudulent notion among the ignorant. Currently there are very many persons promoting the notion of 'artificial intelligence' in a manifestly fraudulent manner only in order to enrich themselves.

The notion of 'artificial intelligence' is precisely, and only, that - a notion. As 'time travel' is a notion. Artificial intelligence has no [present] manifestation in reality because it CANNOT have a manifestation in [present] reality, just as time travel has no basis in [present -sic] reality because it CANNOT have any basis in [present] reality. — Preceding unsigned comment added by 122.151.210.84 (talk) 02:13, 27 June 2022 (UTC)

I started this page in Dec of 2005 (Talk::AI Winter ). After some work, I left it to others. So, this is a nice culmination after 18 years. ... But, AI is not solely machine learning by itself. And, from the position of many, there was really no "winter" at the core. Funny money disappeared. I think that we ought to get a handle on the cyclic ways of life, even within busyness. ... Anyone for a true multidisciplinary view that will be necessary for us to tame the beats of the buckets-of-bits? Also science? I see it lacking quite obviously as imagination runs wild like the kids at spring break. jmswtlk (talk) 01:52, 12 December 2023 (UTC)

Plagiarized section from Machine translation and the ALPAC report of 1966

This entire section appears to be nearly identical to content from source 6, with citations added for some of the claims from the article. My understanding is that this is considered plagiarism according to Wikipedia's guidelines. It appears the account that made this edit no longer exists. I've never edited Wikipedia before, so I'm not entirely sure what the appropriate action is here.

Natural language processing (NLP) research has its roots in the early 1930s and began its existence with the work on machine translation (MT). However, significant advancements and applications began to emerge after the publication of Warren Weaver's influential memorandum, Machine translation of languages: fourteen essays in 1949. The memorandum generated great excitement within the research community. In the following years, notable events unfolded: IBM embarked on the development of the first machine, MIT appointed its first full-time professor in machine translation, and several conferences dedicated to MT took place. The culmination came with the public demonstration of the Georgetown–IBM machine, which garnered widespread attention in respected newspapers in 1954.

Just like all AI booms that have been followed by desperate AI winters, the media tended to exaggerate the significance of these developments. Headlines about the Georgetown–IBM experiment proclaimed phrases like "The bilingual machine," "Robot brain translates Russian into King's English," and "Polyglot brainchild." However, the actual demonstration involved the translation of a curated set of only 49 Russian sentences into English, with the machine's vocabulary limited to just 250 words. To put things into perspective, a 2006 study made by Paul Nation found that humans need a vocabulary of around 8,000 to 9,000-word families to comprehend written texts with 98% accuracy. Snezbeh (talk) 23:24, 26 August 2025 (UTC)