Because they’re trained to generate images, not words.
There’s an anecdote about blind men whose sight was restored. They were adult men, who had felt cubes and heard about cubes, and could describe a cube. After their sight was restored, they were shown a cube and a sphere and were asked to identify them by sight. They were unable to, having never seen these objects before.
Many people (including very smart people) make the mistake of equating all forms of intelligence. They assume that computer programs have an intelligence level, and should be able to handle all tasks below that intelligence level, but machine learning models break our intuition for this. A model which has been trained on stock market data and is extremely intelligent in this area may be able to predict the stock market tomorrow. But if it has not been trained on words than it is no more able to write a sentence than a newborn baby. ChatGPT can eloquently generate words but it is completely unable to generate or understand pictures. (Ask ChatGPT to generate some ASCII-art.) Eventually OpenAI will create a sophisticated multi-modal model capable of generating poems or reading words in an image or predicting the stock market, but this model will be completely unable to answer questions about the physical world, because it’s only been trained on words and images.
GP likely meant GPT-4 (the LLM), not ChatGPT the product as a whole (which has additional models for doing things with images).
Feed original (not copy-pasted from the web) ASCII art of a foot into GPT-4 and I'd be very impressed if it can tell you it's a foot.
I'm actually mildly impressed it could generate ASCII art of a car, because that's a lot better than I've been able to get out of it (albeit on gpt3.5). Try anything more complex and I believe you'll see it's limitations.
With data analysis enabled, I’ve seen it try to use pytesseract to do OCR when you ask it to extract text from an image. (I’ve seen it fail with a timeout trying that on an image that it worked almost instantly on with a similar approach on my laptop.)
CogVLM and Llava can both read text from images I think, although I haven't tried this myself. They certainly describe images very accurately, including giving the pixel location.
Comments
Because they’re trained to generate images, not words.
There’s an anecdote about blind men whose sight was restored. They were adult men, who had felt cubes and heard about cubes, and could describe a cube. After their sight was restored, they were shown a cube and a sphere and were asked to identify them by sight. They were unable to, having never seen these objects before.
Many people (including very smart people) make the mistake of equating all forms of intelligence. They assume that computer programs have an intelligence level, and should be able to handle all tasks below that intelligence level, but machine learning models break our intuition for this. A model which has been trained on stock market data and is extremely intelligent in this area may be able to predict the stock market tomorrow. But if it has not been trained on words than it is no more able to write a sentence than a newborn baby. ChatGPT can eloquently generate words but it is completely unable to generate or understand pictures. (Ask ChatGPT to generate some ASCII-art.) Eventually OpenAI will create a sophisticated multi-modal model capable of generating poems or reading words in an image or predicting the stock market, but this model will be completely unable to answer questions about the physical world, because it’s only been trained on words and images.
Ok. I did both things.
I took a photo of my feet up on a stool in my living room, and told CharGPT to describe it.
It was reasonably (and rather surprisingly) successful.
I also told it to generate an ASCII image of a car. It did that, too.
GP likely meant GPT-4 (the LLM), not ChatGPT the product as a whole (which has additional models for doing things with images).
Feed original (not copy-pasted from the web) ASCII art of a foot into GPT-4 and I'd be very impressed if it can tell you it's a foot.
I'm actually mildly impressed it could generate ASCII art of a car, because that's a lot better than I've been able to get out of it (albeit on gpt3.5). Try anything more complex and I believe you'll see it's limitations.
chatpgt can in fact both read words in images and generate images
But ChatGPT is a product, not a model. Might there be an augmenting OCR process feeding it the image's text?
With data analysis enabled, I’ve seen it try to use pytesseract to do OCR when you ask it to extract text from an image. (I’ve seen it fail with a timeout trying that on an image that it worked almost instantly on with a similar approach on my laptop.)
CogVLM and Llava can both read text from images I think, although I haven't tried this myself. They certainly describe images very accurately, including giving the pixel location.