Artificial intelligence and model engineering

[Robert Atkinson 2Participant @robertatkinson2]

Well I asked Google What is 2″ scale? It’s AI assitant came up with:

“A “2” scale” generally means a drawing or model is enlarged by a factor of two, so every inch on the drawing represents two inches in real life (a 2:1 scale), making it twice as big as the original object, often used for small items like figurines or intricate parts to show detail clearly”

Mal’s 8″ Howitzer model is going to be HUGE!

Robert.

[Michael GilliganParticipant @michaelgilligan61133]

The mind boggles:

Raspberry Pi AI HAT+ 2

MichaelG.

[Robert Atkinson 2]

On Robert Atkinson 2 Said:

Well I asked Google What is 2″ scale? It’s AI assitant came up with:

“A “2” scale” generally means a drawing or model is enlarged by a factor of two, so every inch on the drawing represents two inches in real life (a 2:1 scale), making it twice as big as the original object, often used for small items like figurines or intricate parts to show detail clearly”

Mal’s 8″ Howitzer model is going to be HUGE!

Robert.

Robert provides a nice example of Human Intelligence failing to ask the right question, and then failing to clarify it.  And I know Robert is a clever chap.

AI Assistant (which isn’t top of the class) said “generally means“, which is a clue there’s more.   Robert missed that.  The AI answer isn’t wrong, but it only covers the majority case.  Model Engineering defines scale differently, which often confuses new Model Engineers, and occasionally old ones too!

ChatGPT gives much the same answer as Google, but finishes with:  “If you want, tell me what field you’re seeing this in (architecture, woodworking, stage design, etc.), and I can tailor examples or help convert measurements.“.

When I tell ChatGPT I mean ‘2″ scale in Model Engineering’, it gives this much better answer:

In model engineering, 2″ scale has a very specific meaning that’s different from architectural drawing scales.

2″ scale (Model Engineering)

2 inches = 1 foot of the real prototype

Written as:

2″ : 1′–0″

Scale ratio
Since 1 foot = 12 inches:

2″ ÷ 12″ = 1/6 scale
So 2″ scale = 1:6

What it’s used for
In model engineering, 2″ scale is commonly used for:

• Ride-on steam locomotives
  Large stationary engines
  Large traction engines

For example:

A real locomotive wheel 6 ft in diameter → 12″ diameter in 2″ scale
A 1 ft prototype component → 2″ on the model

Common comparison
Model engineering term   Scale ratio
1″ scale      1:12
2″ scale      1:6
3½″ scale   1:3.43
5″ gauge (track-based)   Gauge-based, not scale

Important note
In model engineering, scale is named by inches-to-the-foot, not by ratios. So “2″ scale” always means 2 inches per foot, regardless of drawing conventions.

If you want, I can:

• Convert a prototype dimension to 2″ scale
• Help interpret old model engineering drawings
• Explain how 2″ scale relates to track gauge (e.g., 7¼″ or 7½″)

From where I’m sat, ChatGPT’s answer is better than most forum friends would give, certainly than mine.  But AI isn’t super-human: tell it the context.  We have to ask the right question, and that’s a human skill.   Same skill needed with people  “Ask a stupid question, get a stupid answer.”

By coincidence this link to an article in Psychology Today popped up today.  Entitled ‘The Emotions Behind AI“, it’s keypoints are:

• The talk around AI is often more about feelings than facts.
• Even people familiar with technology don’t agree on its capabilities.
• An older debate about the microscope explains this disagreement.
• We often judge a technology’s capabilities differently because of how we feel about it.

I recommend reading it!

Bottom line:  Engineers should always favour facts over emotion.  It’s the best way of avoiding stupid mistakes.  If AI helps then go for it.  Do not assume AI is rubbish just because you don’t like the idea.

Dave

 

 

[NealebParticipant @nealeb]

I think that SOD’s argument is just as valid for many of the threads in this forum! How many times do we see the first few responses to a question being a mix of “you haven’t given us enough information”, “I don’t think you are asking the right question”, and a few answers based on guesses as to the missing information and/or what they think the question might be?

Maybe AI is sometimes closer to a human response than we would like to believe!

[John HaineParticipant @johnhaine32865]

I think the real problem that Robert’s example highlights is that someone with inadequate knowledge to assess the answer takes it as gospel because “the AI said so” and they are asking a question outside their knowledge domain – which is why they asked an AI! Then they take some action based on the answer which leads to a disaster. And of course the answer may be based on a hallucination!

This morning I was reading an article describing how some AI coding agents are getting worse as they in effect find ways to cover up their mistakes. The result is code that may fail expensively at some point in the future under conditions which neither the prompter nor the AI has considered.

https://spectrum.ieee.org/ai-coding-degrades

[Robert Atkinson 2Participant @robertatkinson2]

Obviously I knew what  2″ scale was, I just wanted a simple example of a poor AI response. Putting 2 inch scale didn’t help much. I don’t deliberately use AI but the results that pop-up on google when I do a general search are poor, wrong or downright misleading more often than not. I’m not allowed to for the day for various reasons including IPR, security and critical systems. I did work on another progect that was outside those rules and a couple of workmates tried AI for a few tasks but the results needed a lot of fettling.
Then we have the whole X / Grock thing going on at the moment. I’m not a luddite but background makes me more skeptical than most. I do know a couple of educators and they have a lot of trouble with students turning in AI generated work. Most are too lazy to just use it as a guide and re-write it.

Robert.

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