Whether we like it or not, AI isn’t going away. The adoption of this technology across all major tech companies and many industries has cemented its place in our contemporary culture, at least for the time being. We as modelers may as well make our peace with it, and learn how to make it work for us and our hobby.
Readers of my previous articles on AI in the field of model railroading will understand the potential benefits that this emerging technology offers us as model railroader, as well as the developments and advances this emerging field has made in just the past year.
Recently, here at the Model Railroader offices, we’ve experimented with AI, otherwise known as large language models (LLMs), to better understand what this technology can offer those in our hobby. The best use case which I have found has been that of a troubleshooting tool, particularly for those with little experience in the hobby or a lack of information regarding prototype railroading.
Experienced model railroaders have probably experienced, at one point or another, what one may call “layout attrition.” In other words: modeler’s block, a feeling of creative absence or inadequacy. I have found that LLMs can be a useful tool to break through this feeling. Of course, there’s no substitution to real, human creativity. That’s a spark which cannot be duplicated nor imitated, and this use case for LLMs does not seek to achieve it. Rather, this exercise intends to use chat-based LLMs such as ChatGPT or Google Gemini as a tool to spark or rekindle creativity within a model railroader experiencing modeler’s block. It is also a useful exercise for beginner model railroaders looking to start in the hobby but are unsure where – or how – to start.
Now, I’ve found that with chat-based LLM programs, such as those listed above, it’s best to start with a broad prompt, and narrow your focus from there. Keeping this in mind, I began with the prompt “What railroad should I model.” I think I won’t be faulted for preemptively narrowing my inquiry with a starting point like that.
The response I received was surprisingly long-winded. Now, on the one hand, a long-winded response shouldn’t be surprising when starting with a broad prompt; that’s how this exchange works. Start with a narrow prompt, receive a narrow response; Start with a broad prompt, receive a broad response. However, I was surprised by the length of the response based on my previous experiences with chat-based LLMs. This was a more in-depth response than I have come to expect, even from a beginning prompt.
The response was broken down into five categories of consideration, which are as follows:
Finally, some examples of railroads one might consider for their model railroad were listed, which included, unsurprisingly, Union Pacific, Norfolk Southern, and Amtrak, among others. Additionally, interesting possible scenic considerations were included, namely a mountainous region or an urban/industrial setting, along with regions and railroads which would logically fit with these scenic features.
ChatGPT or other LLMs can be useful as a troubleshooting tool for beginning model railroaders, or for any modelers who have hit a creative roadblock. While this emerging technology is a useful tool, it of course is no replacement for the genuine, human creative spark which sits at the center of our hobby. Large Language Models like ChatGPT can sit on the proverbial tool belt of the model railroader, but they are no replacement for passion, skill, and experience.
Recently I wanted to get some ideas for painting/weathering N scale waterfront buildings. I asked Claude “What color is best for waterfront buildings on an n scale model layout”. I got a four page response with details on colors, blends, and weathering techniques, as well as some very on point observations about N scale. A small part of the AI response:
“For waterfront/harbor buildings, some historically accurate and visually effective colors include:
Weathered gray – Mimics old wooden structures exposed to salt air and sea spray
Faded white – Common for New England style waterfront buildings
Pale blue-gray – Historically used for many coastal structures
Light tan/beige – Represents sun-bleached wood or stucco
Muted red – Traditional color for many waterfront warehouses and fish processing buildings
Since N scale is so small, I recommend:
Using slightly lighter shades than you might think – darker colors can make details disappear at this scale
Adding subtle weathering effects to break up solid colors
Including slight variations in tone to create visual interest
Avoiding pure white as it can look too stark at this scale”
As for the best weathered gray for N scale, it gave this answer:
“Weathered Gray (most versatile for wooden structures):
Base: Vallejo Model Color Light Gray (70.990)
Wash: Highly diluted Army Painter Dark Tone ink
Drybrush: Vallejo Light Ghost Gray (70.883)
Optional: Add subtle blue-gray tint with thin glaze of Vallejo Neutral Gray (70.992)”
On the other hand, when I asked it to give me updates on a law case I teach, it made up imaginary cases. Hallucinations are a real danger.