Something GPT discourse has been demonstrating to me is that I'm not usually a very careful reader. I apparently skim a lot. Or maybe I skim GPT outputs because I'm biased in my expectations already?
Which one is more appropriate and/or typical will probably depend on what questions the five-year-old is asking, but I think it's reasonable to say the former is usually preferable to the latter.
It does in a sense because the radio waves need an approximate line of sight to reach your GPS receiver. Being high up gives them a large coverage.
Ian Calvert Computer, please find out how GPS works and explain it to me like I'm five years old
Sure thing! GPS stands for Global Positioning System. It's a way to find out where you are on Earth.
GPS works by using satellites that are way up in space. There are lots of these satellites orbiting around Earth, and they are always sending out signals. Your GPS receiver is a special device that can pick up these signals from the satellites.
The GPS receiver knows how far away it is from each satellite because of the time it takes for the signal to reach it. By figuring out how far away it is from a few different satellites, the GPS receiver can figure out exactly where it is on Earth.
So, if you have a GPS receiver in your car, phone, or on a special device like a watch, it can use the signals from the satellites to tell you exactly where you are and how to get to where you want to go. Does that make sense?
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I was also able to ask it to make it simpler and simpler and it did so pretty well.
You'd better know enough (and be alert enough) to tell the difference...
About half the (presumably human) "eli5 GPS" answers I found on Reddit made the same mistake, so chatGPT just copied an apparently popular misconception.
You'd be better off just saying "it uses satellites and stuff".
I think that's one of the biggest problems with using LLMs for accurate answers. A lot of the text that's very useful for modelling human language and questions is also full of factual errors and questionable opinions. Answers being wrong is a problem with old-fashioned web search too, but I think LLMs necessarily lean more on quantity rather than quality of content...
If you can do "here is the structured data, summarize it and make sure to present this information" it can do that quite well.
So far I've played with GPT doing a zero shot classification of HN titles and CSV hourly weather data to summary. In each case, it has done quite well.
Neither of those are things about what it "knows."
(Also, the UK comedy quiz show QI made the exact same mistake).
How will future LLMs be able to conduct that level of reasoning?
I feel it's appropriate in terms of simplicity, but I think providing a simple wrong explanation is really only worth it when the more accurate explanation is substantially harder to simplify, and I don't think explaining how GPS works falls into that category.
Something like this I think is more accurate without being any more complex:
> Imagine you are standing outside and you see lots of stars in the sky. Well, GPS works kind of like that, but instead of stars, there are satellites orbiting the Earth. These satellites are way up high, so you can always see some of them.
> When you have a GPS device, like a phone or a car, it can look for these satellites, and if it sees enough of them it can use math to figure out where you are.
> The satellites all broadcast a special code saying where each of them is. When you have a GPS device, like a phone or a car, it can listen to these codes and find out where and how far away different satellites are.
(Actually, this would be a fun thing to do with a class. Have a few kids march around the edges of the playground, saying things like “I’m next to the swingset now!”, and then ask one one kid to close their eyes, put them somewhere in the middle and ask them to guess where they’re standing.)