Training AI Writing Assistants with Your Own Books and Writing

Table of Contents

• Understanding the Effort Involved in Training AI Models
• Creating a Robust Prompt for an AI Assistant
• Iteratively Improving AI Writing with Edits and Feedback
• Benefits of Creating Your Own AI Assistant
• Joining a Community to Stay Ahead of AI Writing Trends

Understanding the Effort Involved in Training AI Models

Training AI models like large language models requires significant effort and resources. As the video transcript notes, many people mistakenly believe you can just throw books and text into a system and it will produce a capable AI assistant. However, curating quality training data actually involves substantial human labor.

Specifically, the training data needs to be divided into small chunks or snippets of text, say 1,000 to 2,000 words each. More importantly, humans have to go through each snippet and add descriptive metadata labels indicating what that piece of text represents or demonstrates.

For instance, metadata could specify that a snippet shows how to effectively build setting description in a story. Other chunks might be labeled to showcase proper plot progression, character development strategies, cliffhanger endings, and so on. This contextual metadata is crucial for the AI to learn how to mimic and properly apply different writing techniques later on.

Metadata and Curating Training Data

Essentially, the metadata provides the contextual clues that prevent AI writing from deteriorating or 'going off the rails' as noted in the video. Without clear indicators that tell the AI model what specific principles or skills a chunk of text exhibits, it cannot easily extract meaningful patterns to inform future writing attempts. Therefore, training a robust AI writing assistant requires curating a dataset spanning different writing scenarios and formatting each data snippet with descriptive metadata labels. Putting together such a customized dataset demands extensive human judgment, effort and domain expertise.

Providing Context to Avoid Going Off the Rails

The video also emphasizes the strategy of supplying an AI writing model with significant contextual information to make its job clearer and constrain its responses. This preventative approach aligns with the need for meticulous training data curation discussed above. By feeding the AI assistant explicit details like intended style, audience, story premise, characters, previous plot events, etc., it can better align its writing with expectations. We restrict the context to around 4,000 words focused only on the most directly relevant information to avoid overwhelming the model.

Creating a Robust Prompt for an AI Assistant

The transcript demonstrates a system for prompting an AI writing model effectively. It constructs what's termed a "mega prompt" pulling together the exact pieces of contextual data found most helpful for guiding quality writing.

These key prompt components cover the established story style, characters, worldbuilding/setting details, premise and hook, and previous plot progression. Keeping each aspect concise yet informative provides optimum context without confusion.

After laying this foundation, the next step or 'beat' of the story to be written is clearly specified within the prompt. Explicitly designating the goals and constraints for the AI allows it to stay focused and avoid expanding beyond the requested scope into unrelated territory.

Iteratively Improving AI Writing with Edits and Feedback

Once the assistant generates a draft chunk of writing, the video explains how to further refine its skills through an iterative process. The initial AI attempt is edited and built upon through human input, enhancing areas like style, voice consistency and quality description.

Crucially, these edits are then fed back to the AI so it can analyze the changes and learn from them. Asking it to describe the differences made and quantify the improvements allows the model to solidify positive writing patterns.

By repeatedly providing edited samples as feedback, the AI progressively sharpens its performance in line with the preferred style and approach. This trains it over an ongoing collaboration centered around a specific project like a novel draft.

Benefits of Creating Your Own AI Assistant

Combining the training strategies covered above illustrates the advantage of cultivating a customized AI writing companion tuned to an individual author's creative process.

General AI tools accessible online tend to produce variable or unreliable results given their broad, unfocused training. But by feeding your own writing samples, favorites passages, editing changes and metadata labels, a model can better assimilate your distinctive style.

The video promises that this level of personalization ensures writing beats or snippets that integrate smoothly within a unified story or book draft. The AI grows accustomed to your unique voice, tone, structure and other literary qualities through tailored learning.

Joining a Community to Stay Ahead of AI Writing Trends

Lastly, the transcript emphasizes the value of connecting with other writers actively experimenting with AI assistants. Especially given the rapid advancement of this technology, belonging to an engaged community provides multiple benefits.

You can exchange ideas and troubleshooting strategies with peers also navigating the learning process with AI writing tools. A diverse group exploring different specialized applications ensures exposure to a range of innovative techniques.

Together, members can identify emergent best practices for leveraging AI to enhance proficiency. This feeds collective progress that is so crucial amidst an complex, fast-changing technological landscape like artificial intelligence.

FAQ

Q: Why can't we just train an AI model on books we already have?
A: Training data needs metadata and organization into small chunks of text, which is very labor intensive.

Q: What is the ideal word count for prompts to AI?
A: 300-500 words tends to keep AI on track without overwhelming it.

Q: How can we improve an AI assistant's writing over time?
A: Provide edits and feedback so the AI can learn iteratively from your style.

Q: What are the benefits of training your own AI writing assistant?
A: You can customize it for your genre, voice, characters, and writing style.

Q: Why join a community focused on AI writing?
A: To collaborate, stay on top of new developments, and avoid being left behind as the technology advances.