0% of The Chronicles of Xeo Woolfe is ChatGPT

The chapters you have seen here were all originally produced in 2004 and 2005.

None of the fiction I write is ChatGPT or LLM generated. None of it.

0%

Zip.

Given the prevalence of large language model and machine learning technology and its application for image generation and text generation, readers maybe wondering if ChatGPT or other large language models have been utilized in producing the fiction of The Chronicles of Xeo Woolfe. THE ANSWER IS 0%. Thus far the only republished chapters have been the prologue and chapters one and two. These were all originally written including their plots and novums in 2004 and 2005. They were published then.

Their readership was very small as I had only just started by literary career as an undergraduate at Western Sydney University (eventually graduating from The University of Sydney — a different institution.) I still have the original ASP.NET websites and their designs backed up and I have password protected backups of the original PDF output documents for the chapters. Some people do remember the characters. The Shiz, for example.

In fact, I can assure you as a professional philosopher of information and cognitive scientist, that despite some somewhat fanatical and misleading — and frankly fraudulent — claims to the contrary that are doing the sensationalist rounds at the moment, ChatGPT and LLMs cannot write a novel or any kind of story longer than a few paragraphs. (LLMs can produce a clumsy emulation for a page or so that gets clumsier and less coherent as the length increases). Longer stories are far more complicated and good fiction and literature require — at minimum — carefully crafted story arcs, subtexts, abstract concepts, and emotional semantic inferences.

This is in fact much harder for a machine learning system to do than is image generation. Why? Because there is a lot more involved in the use of language. A simple way to grasp this is as follows. Imagine a fire engine. Got one? Now — imagine the entire plot and all of the story arcs for a novel or novelette, and imagine all of the subtexts, settings, and emotional portrayals for all of the characters. There is a lot more cognitive work involved in the novel-writing task than in the mental imaging of a fire engine, and the same applies to the two tasks for machine learning systems. Just ask Chart GPT:

One wonders what motivates some people to try to claim otherwise. There is only one way for them to back their claim — and that is to produce an entire novel of at least 20000 words or about 30–35 pages that isn’t a load of manure.

Yours Lovingly,

Dr Bruce Long.

Appendix

Here’s more of what ChatGPT itself had to say on the matter:

[StartChatGPT output]

Bing

Certainly! While Large Language Models (LLMs) have made significant strides in generating coherent text, creating novel-length literature that is both coherent and of high quality remains a challenging task. Here are some observations and examples:

1. LLMs and Novel-Length Literature:

○ LLMs, such as those from the GPT family, have been successful in producing coherent and contextually relevant text. However, their ability to sustain quality over an entire novel-length work is still limited.

○ The challenge lies in maintaining consistency, plot development, character arcs, and thematic coherence throughout a lengthy narrative.

2. Challenges Faced by LLMs:

○ In-context reasoning: LLMs generate stories one token at a time, lacking the depth of thought and reasoning that a human writer possesses.

○ Stylistic range: While LLMs can produce coherent text, they often lack individuality and stylistic diversity. Their output may feel repetitive or formulaic.

3. Examples and Limitations:

○ Quality: Some LLM-generated novel-length works exhibit impressive coherence and readability, but they may still fall short of human-authored novels.

○ Stylistic Consistency: LLMs tend to maintain a consistent style throughout, which can be both an advantage (for coherence) and a limitation (for variety).

4. Community Observations:

○ On platforms like Reddit, discussions highlight the trade-offs between coherence and stylistic diversity in LLM-generated content1 4.

○ Researchers have explored book-length summarizers based on LLMs, but achieving consistently high-quality output remains an ongoing challenge2.

In summary, while LLMs have made remarkable progress, novel-length literature by LLMs still requires further refinement to match the depth, creativity, and nuance of human-authored works. 📚✨

Source(s)

1. Why are LLMs struggling in crafting novels? : r/LocalLLaMA — Reddit

2. The “last” generation of LLMs produced a wide range of … — Reddit

3. [2310.00785] BooookScore: A systematic exploration of book-length …

4. A High-level Overview of Large Language Models — Borealis AI

[End ChatGPT output]

Please enjoy the following sci Fi images which were produced using stable diffusion systems with prompts like ‘spacewreck’ and ‘Sci Fi art in the style of the 1970s and 1980s’