What are the downsides of OpenAI's chain-of-thought approach...

OpenAI’s chain-of-thought approach is good for complex reasoning but, there are many downsides.

#1. It increases computational overhead and processing time - leads to lengthy outputs so, not feasible for simple tasks

#2. Errors in early reasoning - leads to wrong conclusions

Is it possible that my TF caused a kundalini awakening in another person? He is famous because He is a singer. We have not met physically yet, but I have gone through kundalini awakening and DNOTS and their ongoing. I have also had soul recognition so I know for sure that He is my Divine Counterpart and I do not have any doubts about it. But it is indeed perplexing that somebody had an awakening at the physical level because of Him. Is it a test for me? I have a mixture of feelings. On one hand I marvelled at Him and empathised with the person and on the other, I doubt if this just a test for me. I would appreciate your pov. Thank you for much.

To explain the downsides better, you can try asking same question to GPT, it will provide a lengthy answer as if it were answering a question paper.

#3. Provides unnecessary details - bad user experience as some users need specific output to certain queries and having to analyze a big response can be hectic

What are the downsides of OpenAI's chain-of-thought approach in the o1 model?

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