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LLMs process text, but only after it was converted to a stream of tokens. As a result, LLMs are not very good at answering questions about letters in the text. That information was lost during the tokenization.

Humans process photons, but only after converting them into nerve impulses via photoreceptor cells in the retina, which are sensitive to wavelengths ranges described as "red", "green" or "blue".

As a result, humans are not very good at distinguishing different spectra that happen to result in the same nerve impulses. That information was lost by the conversion from photons to nerve impulses. Sensors like the AS7341 that have more than 3 color channels are much better at this task.



Yet I can learn there is a distinction between different spectra that happen to result in the same nerve impulses. I know if I have a certain impulse, that I can't rely on it being a certain photon. I know to use tools, like the AS7341, to augment my answer. I know to answer "I don't know" to those types of questions.

I am a strong proponent of LLM's, but I just don't agree with the personification and trust we put into its responses.

Everyone in this thread is defending that ChatGPT can't count for _reasons_ and how its okay, but... how can we trust this? Is this the sane world we live in?

"The AGI can't count letters in a sentence, but any day not he singularity will happen, the AI will escape and take over the world."

I do like to use it for opinion related questions. I have a specific taste in movies and TV shows and by just listing what I like and going back and forth about my reasons for liking or not liking it's suggestions, I've been able to find a lot of gems I would have never heard of before.




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