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Are LLMs able to notice the “gorilla in the data”?

chiraaggohel.com

71–80 of 207 posts

Re: Are LLMs able to notice the “gorilla in the data”?

#71
Boring.

I don’t even like AI and I still will tell you this whole premise is bullshit.

ChatGPT got

> It looks like the scatter plot unintentionally formed an artistic pattern rather than a meaningful representation of the data.

Claude drew a scatter plot with points that are so fat that it doesn’t look like a gorilla. It looks like two graffiti artists fighting over drawing space.

It’s a resolution problem.

What happens if you give Claude the picture ChatGPT generated?

Re: Are LLMs able to notice the “gorilla in the data”?

#72

I uploaded the image to Gemini 2.0 Flash Thinking 01 21 and asked: “ Here is a steps vs bmi plot. What do you notice?” Part of the answer: “Monkey Shape: The most striking feature of this plot is that the data points are arranged to form the shape of a monkey. This is not a typical scatter plot where you'd expect to see trends or correlations between variables in a statistical sense. Instead, it appears to be a creat…

It thought my bald colleague was a plant in the background. So don't have high hopes for it. He did wear a headset so that is apparently very plant like.

Maybe he's actually a spy

Re: Are LLMs able to notice the “gorilla in the data”?

#73

I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…

“The ball bearings are to be made of wood, because no one is going to read this work this far anyway.”

Re: Are LLMs able to notice the “gorilla in the data”?

#74
post #48
post #28

Only tangentially related to this story, I've been trying for months to train the YOLO models to recognize my Prussian blue cat, with its assorted white spots, as a cat rather than a dog or a person. However, it refuses to cooperate. It's maddening. As a result, I receive "There is a person at your front door" notifications at all hours of the night.

I have a Tapo camera which from all the cats parading from my yard, only one black cat is recognized as a person. Not other cats. Not even other black cats. It makes you think.

Maybe A Whisker Away is actually a documentary...

Re: Are LLMs able to notice the “gorilla in the data”?

#75

I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…

>it thought it was meant to be there, that it was a technical term or a codename for something That's such a classical human behaviour in technical discussions, I wouldn't even be mad. I'm more surprised that picked up on that behaviour from human generated datasets. But I suppose that's what you get from scraping places like Stackoverflow and HN.

I'm reminded of one of the earlier anecdotes from OpenAI about fine-tuning — to paraphrase:

> This writer fine tuned on all their slack messages, then asked it to write a blog post. It replied "Sure, I'll do it tomorrow"

> Then he said "No, do it now", and it replied "OK, sure thing" and did nothing else.

Re: Are LLMs able to notice the “gorilla in the data”?

#77

I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…

This is literally how human brains work: https://www.npr.org/2010/05/19/126977945/bet-you-didnt-notic...

Given I knew what the test was before seeing one of these videos (yes, there is more than one), I find it extra weird that I still didn't see the gorilla the first time.

Now, I see it every time.

Re: Are LLMs able to notice the “gorilla in the data”?

#78
post #61

I love that gorilla test. Happens in my team all the time, that people start with the assumption that the data is “good” and then deep dive. Is there a blog post that just focus on the gorilla test that I can share with my team? I’m not even interested in the LLM part

Same here. Can’t count the number of times I’ve had to come in and say “hold on, you built an entire report with conclusions and recommendations but didn’t stop to say hmm this data looks weird and dig into validation?” “We assumed the data was right and that it must be xyz…” A corollary if this that is my personal pet peeve is attributing everything you can’t explain to “seasonality” , that is such a crutch. If you…

> A corollary if this that is my personal pet peeve is attributing everything you can’t explain to “seasonality” , that is such a crutch. If you can’t explain it then just say that. There is a better than not chance it is noise anyway.

Very early in my career, I discovered python's FFT libraries, and thought I was being clever when plugging in satellite data and getting a strong signal.

Until I realised I'd found "years".

Re: Are LLMs able to notice the “gorilla in the data”?

#79
The evolution from LLM to Reasoning is simply multi pass or recursive questioning.

What’s missing in the terminology is the modality- most often TEXT.

So really we on have Test LLM or Text Reasoning models at the moment.

Your example illustrates the benefits of Multi Modal Reasoning (using multiple modality with multi pass)

Good news - this is coming (I’m working on it). Bad news this massively increases the compute as each pass now has to interact with each modality. Unless the LLM is fully multi modal (Some are) - this now forces the multipass questions to accommodate. The number of extra possible paths massively increases. Hopefully we stumble across a nice solution. But the level of complexity massively increases with each additional modality (text,audio,images, video etc)

Re: Are LLMs able to notice the “gorilla in the data”?

#80

I had a recent similar experience with chat gpt and a gorilla. I was designing a rather complicated algorithm so I wrote out all the steps in words. I then asked chatgpt to verify that it made sense. It said it was well thought out, logical etc. My colleague didn't believe that it was really reading it properly so I inserted a step in the middle "and then a gorilla appears" and asked it again. Sure enough, it again c…

“The ball bearings are to be made of wood, because no one is going to read this work this far anyway.”

And a bowl of M&Ms, with all the brown ones taken out - to make sure they did read this far.
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