That's from this comment here: https://github.com/tldraw/tldraw/issues/8082#issuecomment-39...Well that's embarrassing! I reported it as if it wasn't a joke. I thought the joke issue was this one about translating everything to Chinese: https://github.com/tldraw/tldraw/issues/8092

The way I phrased that point was "The investigators allege repeatedly visiting daycare centers which did not, factually, have children physically present at the facility despite reimbursement paperwork identifying specific children being present at that specific time. The investigators demonstrated these lies on timestamped video, and perhaps in another life would have been YouTube stars."

It will. There will be people whose skillset is advanced prompting.

All image models can generate images that were not in its training dataset, but it can't generate reductive extreme cases like your example.

Good question! It's likely because there are lots of different accents of Spanish that are distinct from each other. Our labels only capture the native language of the speaker right now, so they're all grouped together but it's definitely on our to-do list to go deeper into the sub accents of each language family!

We're working on getting there. What got us out of our seats to build this was realizing that LLMs still struggled with the fairly basic data modeling and distributed systems problems that existing payments providers pose. Any solution they came up with was only ever narrowly correct, brittle, and a nightmare to maintain

give the product a go and lmk how vibe coding payments performs