Many sophisticated machine learning (ML) products recently have been introduced as general-purpose content-creation tools. The one that has garnered the most attention was ChatGPT, a chatbot powered by the large language model (LLM) GPT-3.5.
An LLM is a type of ML model that performs various natural language processing tasks—such as recognizing, summarizing, translating, and generating text; answering questions; and carrying on a conversation. An LLM is developed by deep learning techniques, and training its artificial neural networks requires a massive amount of data. Deep learning is a type of ML, and ML is a subfield of AI. Since ChatGPT outputs new content as a response to a user’s inquiry, it is considered a tool in the realm of generative AI.
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Dick’s novel “The Penultimate Truth” already showed us how AI that writes according to prompt can be corrupted
By David Gill, Published June 10, 2023 10:59AM (EDT)
Philip K. Dick had some strange ideas about the future. In his 40-plus novels and 121 short stories, the science fiction author imagined everything from “mood organs” which allow users to dial up an emotional state including “the desire to watch TV, no matter what’s on” to pay-per-use doors that refuse entrance or exit without sufficient coinage.
Characters in Dick’s mind-bending novel “Ubik” (published in 1969 and set in 1992) include a psionic talent scout named G.G. Ashwood, who wears “natty birch-bark pantaloons, hemp-rope belt, peekaboo see-through top and train engineer’s tall hat” and a taxi driver wearing “fuchsia pedal pushers, pink yak fur slippers, a snakeskin sleeveless blouse, and a ribbon in his waist-length dyed white hair.”
As usual, librarians will have to deal with this, if only because we live in the same reality as the rest of the world and have not been granted a pass on modernity so that we can sit by the library fireplace with our library cat and read all day. In case you haven’t heard, we’ve gone digital.
A search engine researcher explains the promise and peril of letting ChatGPT and its cousins search the web for you.
By Chirag Shah, Published March 19, 2023
The prominent model of information access and retrieval before search engines became the norm – librarians and subject or search experts providing relevant information – was interactive, personalized, transparent and authoritative. Search engines are the primary way most people access information today, but entering a few keywords and getting a list of results ranked by some unknown function is not ideal.
A new generation of artificial intelligence-based information access systems, which includes Microsoft’s Bing/ChatGPT, Google/Bard and Meta/LLaMA, is upending the traditional search engine mode of search input and output. These systems are able to take full sentences and even paragraphs as input and generate personalized natural language responses.
At first glance, this might seem like the best of both worlds: personable and custom answers combined with the breadth and depth of knowledge on the internet. But as a researcher who studies the search and recommendation systems, I believe the picture is mixed at best.
By: Jonathan McMichael, Undergraduate Success Librarian
AI writing can mimic style, but it cannot mimic substance yet. The release of a powerful, free and easy-to-use large language model platform, Open AI’s ChatGPT, raises interesting questions about the future of writing in higher education.
As the Undergraduate Success Librarian, I have a unique perspective on generative AI, like ChatGPT, that I want to share along with some advice for instructors and students on adapting to AI’s presence in higher education.
What is ChatGPT?
How does it work? ChatGPT is an interface that allows you to interact with artificial intelligence through text inputs and responses. The AI on the other side of the interface is a language model called GPT-3. It produces human-like text by parsing and analyzing the massive corpus of text information (large language) it has been trained on to predict what is likely to come next in a string of words. This makes GPT-3 a type of Generative AI because it uses machine learning to generate new content based on a given set of input data. So, when you give ChatGPT a prompt like “describe losing your sock in the dryer in the style of the declaration of independence” it (in simplified terms) identifies relevant data within its large language dataset, notices patterns within that dataset and then generates a set of text that seems most like the things it identified.*