The second one has caused hours of entertainment over the past year or so. My kids find the LLM's failed clues and profuse apologies for getting these wrong hilarious, so it's become a family activity with me performing dramatic readings of the chat transcript with them. The LLM's apologies also seem to get more exaggerated as the context increases and the LLM seems to get more deranged.
I'd prefer the models to get better at SVG. I really hate working with the rasters that diffusion models generate, but the vector outputs are just really bad even when tokenizable like SVG. I've done some experimentation with trying to make these work better with some newer techniques with some success. But I also think the SVG Paths mini-language may be a bit too concise and unforgiving for LLMs to consistently get them right without specialized training.
The second one has caused hours of entertainment over the past year or so. My kids find the LLM's failed clues and profuse apologies for getting these wrong hilarious, so it's become a family activity with me performing dramatic readings of the chat transcript with them. The LLM's apologies also seem to get more exaggerated as the context increases and the LLM seems to get more deranged.
I'd prefer the models to get better at SVG. I really hate working with the rasters that diffusion models generate, but the vector outputs are just really bad even when tokenizable like SVG. I've done some experimentation with trying to make these work better with some newer techniques with some success. But I also think the SVG Paths mini-language may be a bit too concise and unforgiving for LLMs to consistently get them right without specialized training.