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AI World Clocks

clocks.brianmoore.com

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Re: AI World Clocks

#271

Post by jampa »

andix wrote: post #236
baltimore wrote: post #21

Since the first (good) image generation models became available, I've been trying to get them to generate an image of a clock with 13 instead of the usual 12 hour divisions. I have not been successful. Usually they will just replace the "12" with a "13" and/or mess up the clock face in some other way. I'd be interested if anyone else is successful. Share how you did it!

I gave this "riddle" to various models: > The farmer and the goat are going to the river. They look into the sky and see three clouds shaped like: a wolf, a cabbage and a boat that can carry the farmer and one item. How can they safely cross the river? Most of them are just giving the result to the well known river crossing riddle. Some "feel" that something is off, but still have a hard time to figure out that wolf,…

There are few examples of this as well:

https://www.reddit.com/r/singularity/comments/1fqjaxy/contex...

Re: AI World Clocks

#272

Post by phire »

emp17344 wrote: post #126
Scene_Cast2 wrote: post #27

Earlier quoted context omitted.

I've noticed that image models are particularly bad at modifying popular concepts in novel ways (way worse "generalization" than what I observe in language models).

Maybe LLMs always fail to generalize outside their data set, and it’s just less noticeable with written language.

Most image models are diffusion models, not LLMs, and have a bunch of other idiosyncrasies.

So I suspect it's more that lessons from diffusion image models don't carry over to text LLMs.

And the Image models which are based on multi-mode LLMs (like Nano Banana) seem to do a lot better at novel concepts.

Re: AI World Clocks

#273

Post by andix »

jampa wrote: post #271
andix wrote: post #236

Earlier quoted context omitted.

I gave this "riddle" to various models: > The farmer and the goat are going to the river. They look into the sky and see three clouds shaped like: a wolf, a cabbage and a boat that can carry the farmer and one item. How can they safely cross the river? Most of them are just giving the result to the well known river crossing riddle. Some "feel" that something is off, but still have a hard time to figure out that wolf,…

There are few examples of this as well: https://www.reddit.com/r/singularity/comments/1fqjaxy/contex...

It really shows how LLMs work. It's all about probabilities, and not about understanding. If something looks very similar to a well known problem, the llm is having a hard time to "see" contradictions. Even if it's really easy to notice for humans.

Re: AI World Clocks

#274

Post by tsunamifury »

Uehreka wrote: post #123
bar000n wrote: post #87

Earlier quoted context omitted.

It should be pretty clear already that anything which is based (limited?) to communicating words/text can never grasp conceptual thinking. We have yet to design a language to cover that, and it might be just a donquijotism we're all diving into.

I don’t think that’s clear at all. In fact the proficiency of LLMs at a wide variety of tasks would seem to indicate that language is a highly efficient encoding of human thought, much moreso than people used to think.

Yea it’s amazing that the parent post literally misunderstands the fundamental realities of LLMs and the compression they reveal in linguistics even if blurry is incredible.

Re: AI World Clocks

#276

Post by jahewson »

vohk wrote: post #208
Dilettante_ wrote: post #196

Earlier quoted context omitted.

"How is engineering a real science? You just build the bridge so it doesn't fall down."

Nah. Actual engineers have professional standards bodies and legal liability when they shirk and the bridge falls down or the plane crashes or your wiring starts on fire. Software "engineers" are none of those things but can at least emulate the approaches and strive for reproducibility and testability. Skilled craftsman; not engineers. Prompt "engineers" is yet another few steps down the ladder, working out mostly b…

Engineers use their ingenuity. That’s it.

If physical engineers understood everything then standards would not have changed in many decades. Safety factors would be mostly unnecessary. Clearly not the case.

Re: AI World Clocks

#278

Post by addandsubtract »

abixb wrote: post #266
bspammer wrote: post #225

Earlier quoted context omitted.

If you're keeping all the generated clocks in a database, I'd love to see a Facemash style spin-off website where users pick the best clock between two options, with a leaderboard. I want to know what the best clock Qwen ever made was!

We might be on to creating a new crowd-ranked LLM benchmark here.

A pelican wearing a working watch

Re: AI World Clocks

#279

Post by komali2 »

jquery wrote: post #125
otterley wrote: post #89

Watching this over the past few minutes, it looks like Kimi K2 generates the best clock face most consistently. I'd never heard of that model before today! Qwen 2.5's clocks, on the other hand, look like they never make it out of the womb.

I’ve been using Kimi K2 a lot this month. Gives me Japanese->English translations at near human levels of quality, while respecting rules and context I give it in a very long, multi-page system prompt to improve fidelity of translation for a given translation target (sometimes markup tags need to be preserved, sometimes deleted, etc.). It doesn’t require a thinking step to generate this level of translation quality,…

> GPT and Gemini love to interrupt my novels and tell me certain behavior is illegal or immoral, and censor various anatomical words

Lol, are you using ai to create fan translations of エロ漫画 ?

Re: AI World Clocks

#280

Post by jdietrich »

lanewinfield wrote: post #94

hi, I made this. thank you for posting. I love clocks and I love finding the edges of what any given technology is capable of. I've watched this for many hours and Kimi frequently gets the most accurate clock but also the least variation and is most boring. Qwen is often times the most insane and makes me laugh. Which one is "better?"

Clock drawing is widely used as a test for assessing dementia. Sometimes the LLMs fail in ways that are fairly predictable if you're familiar with CSS and typical shortcomings of LLMs, but sometimes they fail in ways that are less obvious from a technical perspective but are exactly the same failure modes as cognitively-impaired humans.

I think you might have stumbled upon something surprisingly profound.

https://www.psychdb.com/cognitive-testing/clock-drawing-test

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