Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

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

simonwillison.net

Post reply on HN
Print view View original

341–350 of 453 posts

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

#341

Post by aaron695 »

brundolf wrote: post #165
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…

I find this type of problem is what current AI is best at: where the actual logic isn't very hard, but it requires pulling together and assimilating a huge amount of fuzzy, known information from various sources They are, after all, information-digesters

[dead]

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

#342

Post by spaceman_2020 »

fire_lake wrote: post #177
brundolf wrote: post #165

Earlier quoted context omitted.

I find this type of problem is what current AI is best at: where the actual logic isn't very hard, but it requires pulling together and assimilating a huge amount of fuzzy, known information from various sources They are, after all, information-digesters

Which also fits with how it performs at software engineering (in my experience). Great at boilerplate code, tests, simple tutorials, common puzzles but bad at novel and complex things.

This is also why I buy the apocalyptic headlines about AI replacing white collar labor - most white collar employment is mostly creating the same things (a CRUD app, a landing page, a business plan) with a few custom changes

Not a lot of labor is actually engaged in creating novel things.

The marketing plan for your small business is going to be the same as the marketing plan for every other small business with some changes based on your current situation. There’s no “novel” element in 95% of cases.

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

#343

Post by sothatsit »

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 tried this using a photo I took with metadata removed, and the thought process initially started thinking the photo was of Adelaide. But then, the reasoning moved on to realise that some features didn't match what it expected of Adelaide, and instead came up with the correct answer of Canberra. It then narrowed it down further to the exact Suburb the photo was taken in.

When I used GPT-4o, it got the completely wrong answer. It gave the answer of Melbourne, which is quite far off.

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

#344

Post by inopinatus »

brundolf wrote: post #165
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…

I find this type of problem is what current AI is best at: where the actual logic isn't very hard, but it requires pulling together and assimilating a huge amount of fuzzy, known information from various sources They are, after all, information-digesters

Be that as it may, do not forget that in the pursuit of the most textually plausible output, gaps may be filled in for you.

The mistake, and it's a common one, is in using phrases like "the actual logic" to explain to ourselves what is happening.

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

#346

Post by geniium »

I find this mindblowing.

A few years ago we were disocovering AI chat. AI could create sentences and have a basic conversation with us.

Today, it can identify a photo location with minimal "direct' information on it.

Where will it be in 3 years?? Crazy time to be alive.

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

#347

Post by esjeon »

parsimo2010 wrote: post #36

I’m sure there are areas where the location guessing can be scary accurate, like the article managed to guess the exact town as its backup guess. But seeing the chain of thought, I’m confident there are many areas that it will be far less precise. Show it a picture of a trailer park somewhere in Kansas (exclude any signs with the trailer park name and location) and I’ll bet the model only manages to guess the state c…

> Run any location experiments outside of California if you want to get an idea of how good your software performs outside of the tech bubble.

I really agree with this because I'm seeing much lower accuracy than what people claim here. I live in Korea, and GPT repeatedly falls back to Seoul almost automatically, and, when I nudge it, jumps to Busan, the second-largest city ~400KM away from Seoul. It's not working so great with other smaller cities and cultural heritages. It fat-fingers a lot if no textual information is present in the photo itself.

GPT also doesn't understand actual geography at all. I managed to get it to nail down which corner of a building is present in the photo, and yet it could never conclude that the photo was taken from a park right across from that corner. Instead, it keeps hopping around popular landmarks in the region, basically miles away from the building it correctly identified. Oh, why, why, why...

Basically it's overhyped rn. It does perform impressively well with clearly visible elements - something anyone can already do with google. It's not like it performs super-human level location tracking. I mean, people can do real crazy things based on shadow details, reflection, items, etc.

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

#348

Post by yard2010 »

brundolf wrote: post #165
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…

I find this type of problem is what current AI is best at: where the actual logic isn't very hard, but it requires pulling together and assimilating a huge amount of fuzzy, known information from various sources They are, after all, information-digesters

It's just a huge database with nothing except fuzzy search

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

#349

Post by jdiff »

westmeal wrote: post #275
jdiff wrote: post #259

Earlier quoted context omitted.

Definitely matches my experience as well. I've been working away on a very quirky, non-idiomatic 3D codebase, and LLMs are a mixed bag there. Y is down, there's no perspective distortion or Z buffer, there are no meshes, it's a weird place. It's still useful to save me from writing 12 variations of x1 = sin(r2) - cos(r1) while implementing some geometric formula, but absolutely awful at understanding how those fit in…

I gotta ask what are you actually doing because it sure sounds funky

Working on extending the [Zdog](https://zzz.dog) library, adding some new types and tooling, patching bugs I run into on the way.

All the quirks inherit from it being based on (and rendering to) SVG. SVG is Y-down, Zdog only adds Z-forward. SVG only has layering, so Zdog only z-sorts shapes as wholes. Perspective distortion needs more than dead-simple affine transforms to properly render beziers, so Zdog doesn't bother.

The thing that really throws LLMs is the rendering. Parallel projection allows for optical 2D treachery, and Zdog makes heavy use of it. Spheres are rendered as simple 2D circles, a torus can be replicated with a stroked ellipse, a cylinder is just two ellipses and a line with a stroke width of $radius. LLMs struggle to even make small tweaks to existing objects/renderers.

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

#350

Post by c7b »

> Technology can identify locations from photographs now.

Tbf, it could do that before, and probably still better than the LLM: https://youtube.com/watch?v=ts5lPDV--cU But seeing it as what appears to be an emergent capability in such a general model is something else.

Post reply on HN