I tried it on gpt4o with an upload of the image and "What do you see?" as prompt and it said "monkey". So ymmv, these tools can't be evaluated with just a bunch of gotcha prompts and ignorance of how to use them effectively
It's not a gotcha to give it the data points and ask it to analyze. Uploading this data in image form is effectively a leading question tuned to the specific data, and an analysis tool that needs that kind of leading question is not good at its job.
Without an image? No, not at all. It's supposed to make its own image. And it did make its own image. But it didn't properly analyze the image it made.
That's a feature that would need to be implemented. There's no reason to think it could look at the image of the plot it generated automatically, but feeding it the image it generated back to it is no different to if it did view it automatically
The point of telling it to explore the data is so I don't have to think of every angle myself. Humans can get an understanding from visuals that LLMs can't match, apparently, even without gimmicks.
The llm is able to see the gorilla when shown the image in the same way you would show a human an image.
Imagine if you gave someone the raw data and told them to write code to graph the output but on to a screen they couldn't see. They would not be able to tell you it's a gorilla until you turn the monitor around and show them.
Humans are still better at seeing the image, sure (for now), but the llm is a tool with certain features and abilities. You can't make up a scenario that is misusing the tool and then pretend that it doesn't work - especially when it seems you want it to use it without applying your own brain power to the process
And to be clear, I'm open to criticism of llms and exploration of their limitations - but I'm tired of hearing complaints that amount to PEBKAC.