3 ms·

Ugh, the gears and chain don't mesh and there's no sprocket on the rear hub But seriously, I can't believe LLMs are able to one-shot a pelican on a bicycle thi

Ugh, the gears and chain don't mesh and there's no sprocket on the rear hub But seriously, I can't believe LLMs are able to one-shot a pelican on a bicycle this well. I wouldn't have guessed this was going to emerge as a capability from LLMs 6 years ago. I see why it does now, but... It still amazes me that they're so good at some things.

HPsquared 8mo ago
And the left leg is straight while the right leg is bent. EDIT: And the chain should pass behind the seat stay.
emp17344 8mo ago
Is this capability “emergent”, or do AI firms specifically target SVG generation in order to improve it? How would we be able to tell?
- simonw 8mo ago
  Google specifically boast about their SVG performance in the announcement post: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/ https://blog.google/innovation-and-ai/models-and-research/ge... You can try any combination of animal on vehicle to confirm that they likely didn't target pelicans directly though.
- steve_adams_86 8mo ago
  I asked myself the same thing as I typed that comment, and I'm not sure what the answer is. I don't think models are specifically trained on this (though of course they're trained on how to generate SVGs in general), but I'm prepared to be wrong. I have a feeling the most 'emergent' aspect was that LLMs have generally been able to produce coherent SVG for quite a while, likely without specific training at first. Since then I suspect there has been more tailored training because improvements have been so dramatic. Of course it makes sense that text-based images using very distinct structure and properties could be manipulated reasonably well by a text-based language model, but it's still fascinating to me just how well it can work. Perhaps what's most incredible about it is how versatile human language is, even when it lacks so many dimensions as bits on a machine. Yet it's still cool that we can resurrect those bits at rest and transmogrify them back into coherent projections of photons from a screen. I don't think LLMs are AGI or about to completely flip the world upside down or whatever, but it seems undeniably magical when you break it down.
0_____0 8mo ago
next time you host a party, have people try to draw a bicycle on your whiteboard (you have a whiteboard in your house right? you should, anyway...) human adults are generally quite bad at drawing them, unless they spend a lot of time actually thinking about bicycles as objects
- 542354234235 8mo ago
  They are, and it is very funny. https://www.behance.net/gallery/35437979/Velocipedia https://www.behance.net/gallery/35437979/Velocipedia
  - iammattmurphy 8mo ago
    Fantastic post, thanks for that.
- emp17344 8mo ago
  What’s your point? Yes, humans fail sometimes, as do AI models. Are you trying to imply that, in light of this, AI is now as capable as human beings? If so, that conclusion doesn’t follow logically.
  - 0_____0 8mo ago
    it's not a loaded point, i just think it's funny that humans typically cannot one-shot this. and it will make your friends laugh

HPsquared 8mo ago

And the left leg is straight while the right leg is bent. EDIT: And the chain should pass behind the seat stay.

emp17344 8mo ago

Is this capability “emergent”, or do AI firms specifically target SVG generation in order to improve it? How would we be able to tell?

simonw 8mo ago
Google specifically boast about their SVG performance in the announcement post: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/ https://blog.google/innovation-and-ai/models-and-research/ge... You can try any combination of animal on vehicle to confirm that they likely didn't target pelicans directly though.
steve_adams_86 8mo ago
I asked myself the same thing as I typed that comment, and I'm not sure what the answer is. I don't think models are specifically trained on this (though of course they're trained on how to generate SVGs in general), but I'm prepared to be wrong. I have a feeling the most 'emergent' aspect was that LLMs have generally been able to produce coherent SVG for quite a while, likely without specific training at first. Since then I suspect there has been more tailored training because improvements have been so dramatic. Of course it makes sense that text-based images using very distinct structure and properties could be manipulated reasonably well by a text-based language model, but it's still fascinating to me just how well it can work. Perhaps what's most incredible about it is how versatile human language is, even when it lacks so many dimensions as bits on a machine. Yet it's still cool that we can resurrect those bits at rest and transmogrify them back into coherent projections of photons from a screen. I don't think LLMs are AGI or about to completely flip the world upside down or whatever, but it seems undeniably magical when you break it down.

0_____0 8mo ago

next time you host a party, have people try to draw a bicycle on your whiteboard (you have a whiteboard in your house right? you should, anyway...) human adults are generally quite bad at drawing them, unless they spend a lot of time actually thinking about bicycles as objects

542354234235 8mo ago
They are, and it is very funny. https://www.behance.net/gallery/35437979/Velocipedia https://www.behance.net/gallery/35437979/Velocipedia
- iammattmurphy 8mo ago
  Fantastic post, thanks for that.
emp17344 8mo ago
What’s your point? Yes, humans fail sometimes, as do AI models. Are you trying to imply that, in light of this, AI is now as capable as human beings? If so, that conclusion doesn’t follow logically.
- 0_____0 8mo ago
  it's not a loaded point, i just think it's funny that humans typically cannot one-shot this. and it will make your friends laugh