Part 3/12:
A key part of this process involves "crippling" some synopses— deliberately removing names, places, and specific details to create a baseline of low-quality input. Conversely, higher-quality synopses contain detailed character names, settings, times, and specific plot points. By grading these different summaries on a scale (e.g., from 1 to 5), the system can differentiate between generic and well-constructed synopses, providing clear benchmarks for improvement.
Incorporating Generative Adversarial Networks (GANs): The Core Architecture
The heart of the workflow employs a GAN-like structure, where a generator creates synopses based on input variables such as genre, tone, characters, setting, and timeframe, while a discriminator evaluates their quality.