The argument has never changed the argument has always been the same.
LLMs do not think, they do not perform logic they are approximating thought. The reason why CoT works is because of the main feature of LLMs, they are extremely good at picking reasonable next tokens based on the context.
LLM are good and always have been good at three types of tasks:
- Closed form problems where the answer is in the prompt (CoT, Prompt Engineering, RAG)
- Recall from the training set as the Parameter space increases (15B -> 70B -> almost 1T now)
- Generalization and Zero shot tasks as a result of the first two (this is also what causes hallucinations which is a feature not a bug, we want the LLM to imitate thought not be a Q&A expert system from 1990)
If you keep being fooled by LLM thinking they are AGI after every impressive benchmark and everyone keeps telling you that in practice LLM are not good at tasks that are poorly defined, require niche knowledge, or require a special mental model that is on you.
I use LLM every day I speed up many tasks that would take 5-15 mins down to 10-120 seconds (worst case for re-prompts). Many times my tasks take longer than if I had done it myself because it’s not my work im just copying it. But overall I am more productive because of LLM.
Does LLM speeding up your work mean that LLM can replace Humans?
Personally I still don’t think LLM can replace Humans at the same level of quality because they are imitating thought not actually thinking. Now the question among the corporate overlords is will you reduce operating costs by XX% per year (wages) but reducing the quality of service for customers. The last 50 years have shown us the answer…
LLMs do not think, they do not perform logic they are approximating thought. The reason why CoT works is because of the main feature of LLMs, they are extremely good at picking reasonable next tokens based on the context.
LLM are good and always have been good at three types of tasks:
- Closed form problems where the answer is in the prompt (CoT, Prompt Engineering, RAG)
- Recall from the training set as the Parameter space increases (15B -> 70B -> almost 1T now)
- Generalization and Zero shot tasks as a result of the first two (this is also what causes hallucinations which is a feature not a bug, we want the LLM to imitate thought not be a Q&A expert system from 1990)
If you keep being fooled by LLM thinking they are AGI after every impressive benchmark and everyone keeps telling you that in practice LLM are not good at tasks that are poorly defined, require niche knowledge, or require a special mental model that is on you.
I use LLM every day I speed up many tasks that would take 5-15 mins down to 10-120 seconds (worst case for re-prompts). Many times my tasks take longer than if I had done it myself because it’s not my work im just copying it. But overall I am more productive because of LLM.
Does LLM speeding up your work mean that LLM can replace Humans?
Personally I still don’t think LLM can replace Humans at the same level of quality because they are imitating thought not actually thinking. Now the question among the corporate overlords is will you reduce operating costs by XX% per year (wages) but reducing the quality of service for customers. The last 50 years have shown us the answer…