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Watching o3 guess a photo's location is surreal, dystopian and entertaining

simonwillison.net

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Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#401

Post by prezjordan »

SamPatt wrote: post #100
simonw wrote: post #81

Earlier quoted context omitted.

Is that flashcard deck a commercial/community project or is it something you assembled yourself? Sounds fascinating !

I made it myself. I use Obsidian and the Spaced Repetition plugin, which I highly recommend if you want a super simple markdown format for flashcards and use Obsidian: https://www.stephenmwangi.com/obsidian-spaced-repetition/ There are pre-made Geoguessr decks for Anki. However, I wouldn't recommend using them. In my experience, a fundamental part of spaced repetition's efficacy is in creating the flashcards yourself…

> In my experience, a fundamental part of spaced repetition's efficacy is in creating the flashcards yourself.

+1 to this, have found the same when going through the Genki Japanese-language textbook.

I'm assuming you're finding your workflow is just a little too annoying with Anki? I haven't yet strayed from it, but may check out your Obsidian setup.

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#403

Post by bonoboTP »

forgotTheLast wrote: post #245

I tried it twice with 4o and the results were comical: - picture taken on a road through a wooded park: It correctly guessed north america based on vegetation. Then incorrectly guessed Minnesota based on the type of fence. I tried to steer it in the right direction by pointing out license plates and signage but it then hallucinated a front license plate from Ontario on a car that didn't have any, then hallucinated a…

4o is not a "reasoning" model. o3 and o4 are.

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#404

Post by redbell »

SamPatt wrote: post #63

I play competitive Geoguessr at a fairly high level, and I wanted to test this out to see how it compares. It's astonishingly good. It will use information it knows about you to arrive at the answer - it gave me the exact trailhead of a photo I took locally, and when I asked it how, it mentioned that it knows I live nearby. However, I've given it vacation photos from ages ago, and not only in tourist destinations eit…

> It will use information it knows about you to arrive at the answer.. and when I asked it how, it mentioned that it knows I live nearby.

Oh! RIP privacy :(

I’ve pretty much given up on the idea that we can fully protect our privacy while still getting the most out of these services. In the end, it’s a tradeoff—and I’ve accepted that.

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#405

Post by zzzeek »

SamPatt wrote: post #63

I play competitive Geoguessr at a fairly high level, and I wanted to test this out to see how it compares. It's astonishingly good. It will use information it knows about you to arrive at the answer - it gave me the exact trailhead of a photo I took locally, and when I asked it how, it mentioned that it knows I live nearby. However, I've given it vacation photos from ages ago, and not only in tourist destinations eit…

GeoGuessr, well I guess that must have been a great training source for the models

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#406

Post by [deleted] »

xnx wrote: post #354
simonw wrote: post #268

Earlier quoted context omitted.

Yeah, the "generative" in "generative AI" gives a little bit of a false impression. I like Laurie Voss's take on this: https://seldo.com/posts/what-ive-learned-about-writing-ai-ap... > Is what you're doing taking a large amount of text and asking the LLM to convert it into a smaller amount of text? Then it's probably going to be great at it. If you're asking it to convert into a roughly equal amount of text it will b…

This quote sounds clever, but is very different than my experience. I have been very pleased with responses to things like: "explain x", "summarize y", "make up a parody dog about A to the tune of B", "create a single page app that does abc". The response is 1000x more text than the prompt.

[deleted]

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#407

Post by TrickyRick »

thegeomaster wrote: post #39

For all of the images I've tried, the base model (e.g. 4o) already has a ~95% accurate idea of where the photo is, and then o3 does so much tool use only to confirm its intuition from the base model and slightly narrow down. For OP's initial image, 4o in fact provides a more accurate initial guess of Carmel-by-the-Sea (d=~100mi The clue is in the CoT - you can briefly see the almost correct location as the very first…

I had a similar experience, I tried with some photos from various European cities and while it pretty much always got the city correct it was hilariously confidently incorrect in the exact location within the city. They were plausible but nowhere near the level of accuracy the article describes. All the images had distinctly recognizable landmarks which a resident of said city would know and which also have images available online given one knows the name of the landmark so I'm not particularly impressed.

In fact some of the answers were completely geographically impossible where it said "The image is taken from location X showing location Y" when it's not possible to see location Y if one is standing at location X. Like saying "The photo is taken in Central Park looking north showing the Statue of Liberty".

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#408

Post by simonw »

casey2 wrote: post #370
cyral wrote: post #338

Earlier quoted context omitted.

Reading the replies to this is funny. It's like the classic dropbox thread. "But this could be done with a nearest neighbor search and feature detection!" If this isn't mind blowing to someone I don't know if any amount of explaining will help them get it.

It's not mindblowing because there were public systems doing performing much better years earlier. Using the exact same tech. This is less like rsync vs drop box and more like you are freaking out over Origin or Uplay when Steam has been around for years.

Which public systems were those?

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#409

Post by jvvw »

olex wrote: post #131
joenot443 wrote: post #122

Earlier quoted context omitted.

Super cool, man. Watching pro Geoguessr is my latest break-time activity, these geo-gods never cease to impress me. One thing I'm curious about - in high level play, how much of the meta involves knowing characteristics about the photography/equipment/etc. that Google used when they shot it? Frequently I'll watch rainbolt immediately know an African country from nothing but the road, is there something I'm missing?

In the stream commentary for some of competitive Geoguessr I've watched, they definitely often mention the color and shape of the car (visible edges, shadow, reflections), so I assume pro players know which cars were used where very well.

Definitely. The season that coverage was done can be a big thing too. In Russia you'll be looking at the car, antenna type and the season as pretty much the first indicator where you might be.

Copyright year and camera gen is a big thing in some countries too.

Obviously they can still figure out a lot without all that and NMPZ obviates aspects of it (you can't hide camera gens, copyright and season and there are often still traces of the car in some manner). It's definitely not all 'meta' but to be competitive at that level you really do need to be using it. I think Gingey is the only world league player who doesn't use car meta.

Even as a fairly good but nowhere near pro player, it's weird how I associate particular places with particular types of weather. I think if saw Almaty in the summer for example it would feel very weird. I've decided not to deliberately learn car meta but still picked up quite a lot without trying and your 'vibe' of a place can certainly include camera gen.

Re: Watching o3 guess a photo's location is surreal, dystopian and entertaining

#410

Post by jdiff »

TeMPOraL wrote: post #361
roarcher wrote: post #312

Earlier quoted context omitted.

Yeah, but humans can be made to understand when and how they're wrong and narrow their focus to fixing the mistake. LLMs apologize and then proudly present the exact same output as before, repeatedly, forever spinning their wheels at the first major obstacle to their reasoning.

> LLMs apologize and then proudly present the exact same output as before, repeatedly, forever spinning their wheels at the first major obstacle to their reasoning. So basically like a human, at least up to young adult years in teaching context[0], where the student is subject to authority of the teacher (parent, tutor, schoolteacher) and can't easily weasel out of the entire exercise. Yes, even young adults will get…

As someone currently engaged in teaching the Adobe suite to high school students, that doesn't track with what I see. When my students are getting stuck and frustrated, I look at the problem, remind them of the constraints and assumptions the software operates under. Almost always they realize the problem without me spelling it out, and they reinforce the mental model of the software they're building. Often noticing me lurking and about to offer help is enough for them to pause, re-evaluate, and catch the error in their thinking before I can get out a full sentence.

Reminding LLMs of the constraints they're bumping into doesn't help. They haven't forgotten, after all. The best performance I got out of the LLMs in my project I mentioned upthread was a loop of trying out different functions, pausing, re-evaluating, realizing in its chain of thought that it didn't fit the constraints, and trying out a slightly different way of phrasing the exact same approach. Humans will stop slamming their head into a wall eventually. I sat there watching Gemini 2.5 Pro internally spew out maybe 10 variations of the same function before I pulled the tokens it was chewing on out of its mouth.

Yes, sometimes students get frustrated and bail, but they have the capacity to learn and try something new. If you fall into an area that's adjacent to but decidedly not in their training data, the LLMs will feel that pull from the training data too strongly and fall right into that rut, forgetting where they're at.

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