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What we learned from the deep learning revolution
Ben Dickson, TechTalks - Technology solving problems... and creating new ones, 2023/04/10


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Good short article that summarizes an interview about a book in which "neuroscientist Terry Sejnowski discusses the early struggles of deep learning, its explosion into the mainstream, and the lessons learned from decades of research and development.". It's useful to keep in mind that the AI that everybody's talking about these days didn't develop overnight; it has been decades in the making and for a long time was considered "a fool's errand" while "symbolic AI dominated the most prestigious universities and research labs in the U.S.". But for current AI to succeed, reserachers had the rethink what they thought they knew. "The bottom line is you cannot trust your intuition. And what people in AI were trying to do was to automate by writing a program what their intuition told them intelligence was." The same will be true in other domains. When we say someone has 'learned', what does that mean? That they can recite a string of symbols? articulate a rule? offer an explanation? Not so. Never has been so.

Web: [Direct Link] [This Post]


PROPOSED Solid Working Group Charter
W3C, 2023/04/10


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Under Tim Berners-Lee, the Social Linked Data (Solid) project has worked for a very long time to develop a protocol and applications supporting a network for distributed linked data. This proposed working group builds on the Solid Protocol v.0.10.0 authored by the group. The idea is that "Solid storage enables fine-grained control over private data on a per-application and per-principal basis" while enabling interoperability and data sharing. I've always been supportive of the idea though from a third party perspective (albeit a long-time subscriber to the original Gitter and new Matrix discussion groups) it seems to me that the group's defining feature has been its lack of progress.

Web: [Direct Link] [This Post]


The Academic and Administrative Ethnocentrism of the Contemporary University
Miguel Angel Escotet, 2023/04/10


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This post feels like it suffers from a less than ideal translation, however I found the concept of 'acdemic ethnocentrism' useful and worth sharing. The idea is that university culture, rather than being based on the relationship between the student and the professor, is increasingly based around the interests and needs of the latter - the academic. Worse, this is giving way to a type of 'administrative ethnocentrism', where the culture and priorities of the institution are centred around the needs of the managers. "Today it is planned based on the academic body, more corporatism than academic. The physical spaces, the remuneration systems, the study programs, the structures, the organization of time, and other dimensions of university life respond preferably to the needs of the teacher and the administrator but not necessarily to those of the university's teaching or administration."

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How to cite ChatGPT
Timothy McAdoo, APA Style, 2023/04/10


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I'm sure people will find this increasingly useful in the future. "The results of a ChatGPT 'chat' are not retrievable by other readers, and although nonretrievable data or quotations in APA Style papers are usually cited as personal communications, with ChatGPT-generated text there is no person communicating. Quoting ChatGPT's text from a chat session is therefore more like sharing an algorithm's output; thus, credit the author of the algorithm with a reference list entry and the corresponding in-text citation "

Web: [Direct Link] [This Post]


We publish six to eight or so short posts every weekday linking to the best, most interesting and most important pieces of content in the field. Read more about what we cover. We also list papers and articles by Stephen Downes and his presentations from around the world.

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