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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

#331

Post by hammock »

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 looks at vegetation, terrain, architecture, road infrastructure, signage, and it just knows seemingly everything about all of them.

Someone explain to me how this is dystopian. Are Jeopardy champions dystopian too?

It’s not crazy to be able to ID trees and know their geographic range, likewise for architecture, likewise for highway signs. Finding someone who knows all of these together is more rare , but imo not exactly dystopian

Edit: why am I being downvoted for saying this? If anyone wants to go on a walk for me I can help them ID trees, it’s a fun skill to have and something anyone can learn

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

#332

Post by ultimafan »

simonw wrote: post #208
ultimafan wrote: post #207

Earlier quoted context omitted.

I've definitely noticed that there's a huge trend of technology at any cost apologists on HN that can't pause to imagine the real world impacts of how AI products they're championing will actually be used. It's terrifying that people exist that have no problem making the world a shittier place and hiding behind a cover of "well it's not the technology that's evil but the people abusing it" as if each tool given to ba…

"Seriously, what's the utility of developing and making something like this public use?" An interesting question for me here is if these models were deliberately trained to enable this capability, or if it's a side-effect of their vision abilities in general. If you train a general purpose vision-LLM to have knowledge of architecture, vegetation, weather conditions, road signs, street furniture etc... it's going to b…

It seems like a high hurdle in today's world but I still think developers (or inventors of anything really) should think if the benefits of what they're making really outweigh how their invention will actually end up being used.

It's not a large leap of logic for anyone in touch with reality to realize that if a general purpose vision AI is going to be able to predict photo locations bad actors are going to use it for that and a lot of them will be people that would otherwise not have had the technological knowhow of accomplishing it themselves.

I know I probably come off more than a little bit insufferable about this but I'm tired of seeing novelty inventions pop up, everyone has fun for a little bit geeking out over them then they're mostly forgotten outside of niche applications until they show up back in the news when they've been used for the latest sextortion/blackmail/catfishing/whatever scam.

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

#333

Post by zharknado »

charcircuit wrote: post #251
cco wrote: post #187

Earlier quoted context omitted.

Meh, meta is so boring and uninteresting to me personally. Knowing you're in Kenya because of the snorkel, that's just simple memorization. Pick up on geography, architecture, language, sun and street position; that's what I love. It's clearly necessary to compete at the high level though.

How is stuff like geography, architecture, or language not memorization either?

I think it’s more productive to ask, “why would someone attribute a different value to learning about the geography, architecture, and language of a region vs. learning about the characteristics of the hardware and software one specific company used to take a picture of it?”

I think asking that question helps move past the surface question of how information was learned (memorization) to the core issue of which learning we value and why.

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

#334

Post by sandspar »

People say that being an influencer or streamer is future-proof after AI. "People will still want to watch other people" etc. I dunno. Tim Ferris once remarked that having a fan base of 1 million is like having a fan base of a city. And a city of 1 million people contains all sorts of people, including murderers. I dunno if I'd want to stream video games from my house if it meant my most obsessed, scary fan could trivially find my address. On top of that, AI facial identification will get much better. E.g. a photo of your face may be enough to diagnose you with future diseases and mental instabilities etc. Just seems like a bad time to have photos of yourself online.

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

#335

Post by josephg »

jdiff wrote: post #259
fire_lake wrote: post #177

Earlier quoted context omitted.

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.

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…

Yeah I have the same experience. I’ve done some work on novel realtime text collaboration algorithms. For optimisation, I use some somewhat bespoke data structures. (Eg I’m using an order-statistic tree storing substring lengths with internal run-length encoding in the leaf nodes).

ChatGPT is pretty useless with this kind of code. I got it to help translate a run length encoded b-tree from rust to typescript. Even with a reference, it still introduced a bunch of new bugs. Some were very subtle.

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

#336

Post by tyre »

gf000 wrote: post #274
imatworkyo wrote: post #265

Earlier quoted context omitted.

how often are we truly writing actual novel programs that are complex in a way AI does not excel at? There are many types of complex, and many times complex for a human coder, are trivial for AI and its skillset.

Depends on the field of development you do. CRUD backend app for a business in a common sector? It's mostly just connecting stuff together (though I would argue that an experienced dev with a good stack takes less time to write it as is than painstakingly explaining it to an LLM in an inexact human language). Some R&D stuff, or even debugging any kind of code? It's almost useless, as it would require deep reasoning,…

Wait I’ve found it very good at debugging. It iteratively states a hypothesis, tries things, and reacts from what it sees.

It thinks of things that I don’t think of right away. It tries weird approaches that are frequently wrong but almost always yield some information and are sometimes spot on.

And sometimes there’s some annoying thing that having Claude bang its head against for $1.25 in API calls is slower than I would be but I can spend my time and emotional bandwidth elsewhere.

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

#338

Post by cyral »

simonw wrote: post #95
HarHarVeryFunny wrote: post #87

Earlier quoted context omitted.

I don't see how this is mind blowing, or even mildly surprising! It's essentially going to use the set of features detected in the photo as a filter to find matching photos in the training set, and report the most frequent matches. Sometimes it'll get it right, sometimes not. It'd be interesting to see the photo in the linked story at same resolution as provided to o3, since the licence plate in the photo in the stor…

If you want to be impressed I suggest trying this yourself on your own photos. I don't consider it my job to impress or mind-blow people: I try to present as realistic as possible a representation of what this stuff can do. That's why I picked an example where its first guess was 200 miles off!

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.

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

#339

Post by cyral »

tompagenet2 wrote: post #164

I thought from this [0] that o3 makes up using python when it doesn't actually do so, or have I misunderstood or unduly trusted that link? [0] https://transluce.org/investigating-o3-truthfulness

It can definitely make up reasoning (including code) for how it got to an answer. However o3 can run python actually. I tried uploading an image and it ran a bunch of scripts to crop and change the brightness in an attempt to get a clearer view of various features.

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

#340

Post by AlexCoventry »

nurettin wrote: post #326
jeswin wrote: post #321

Earlier quoted context omitted.

> novel and complex things a) What's an example? b) Is 90% (or more) of programming mundane, and not really novel?

If you'd like a creative waste of time, make it implement any novel algorithm that mixes the idea of X with Y. It will fail miserably, double down on the failure and hard troll you, run out of context and leave you questioning why you even pay for this thing. And it is not something that can be fixed with more specific training.

Can you give an example? Have you tried it recently with the higher-end models?
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