Reza Negarestani wrote Cyclonopedia: Complicity with Anonymous Materials. See my post The twist of the pen. The ChatGPT training corpus seems to have picked up his interesting, apocalyptic writing style . Here are some “straight” AI glossary terms I am compiling, each followed by ChatGPT’s attempt to reconstruct them in the style of Cyclonopedia. Feed…More
AI through the looking glass
I invited ChatGPT again to configure elements of my glossary. See previous post A critical AI dictionary. This time I prompted the AI to reword some of the definitions in the manner of Lewis Carol’s Through the Looking Glass. Dall-e: A generative graphics product accessed via ChatGPT and other LLMs. DALL·E uses a transformer model…More
A critical AI dictionary
I am compiling a sensible glossary of AI terminology. I gave each to ChatGPT with the prompt: Please rewrite these glossary items in the style of Georges Bataille’s Critical Dictionary. I follow my own wording with ChatGPT’s response. Agent: An autonomous entity capable of taking data from its environment and performing actions to achieve specific…More
Curate your AI
Working against time constraints an author draws on productivity tools to speed the writing process. Back in the day, desktop word processing changed the game for most of us. I wrote my PhD and first book with MacWrite on a Mac Classic. Before that I probably used something like a Brother desktop computer, and before…More
Choose your critic
My last post looked at the potential of a large language model such as ChatGPT to operate as a critic. Developing further on that theme, it occurred to me that such a review may not always be in step with the author’s target readership. So, I presented ChatGPT with a 4,000 word book chapter titled…More
AI as critic
I listened recently to a radio program in which a collection of prominent entrepreneurs discussed some of the key examples this year of overhyped marketing. As an aside, one of the participants mentioned the disturbing error rate in ChatGPT’s responses to questions of fact, e.g. name ten distinguished alumni of the Fitzwilliam College, Cambridge? It’s…More
Meaning and attention
Understanding and misunderstandings in conversation often stem from emphasis. People tailor their responses based on where their conversational partners place emphasis. Attention distributions play a crucial role in inflecting responses in dialogue. Emphasis influences what comes next in a conversation, shaping the interaction between speaker and listener. Text-only conversational exchanges rely on context without additional cues. Attention, as demonstrated by LLMs, significantly affects the platform’s text generation capabilities and conversation continuation.More
Extending large language models
I’m in the process of identifying parallels between urban semiotics and large language models (LLMs), arguing that core facets of language competence parallel aspects of urban life, experiences and processes. We can identify eight core functions that contribute to the success of the Transformer model of LLMs, as deployed in ChatGPT and other chatbot platforms.…More
Urban scripts and contest
My previous post about scripts, language, and AI invites further reflection the role of scripts in the urban context. Theatrical-style scripts encompass the predictable and patterned ways in which individuals interact in urban settings. Think of how passengers might be expected to wait for those leaving the carriage before entering, give up their seat for…More
Scripts in the city
LLMs exhibit strong script-writing capabilities, crafting roles, settings, and dialogues based on extensive training. While they may not fully compose three-act plays, they excel in simulating dialogue and can assist in script creation. Scripts play a vital role in AI and cognitive science, offering efficient ways to convey information and understand various contexts, echoing the importance of scripts in language, cognition, urban contexts, and AI script writing.