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

Last Updated: 23.06.2025 01:03

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

#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

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

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

Why are we explaining today’s “climate change” as driven by human related “green house” gasses when natural “global warming” pushed sea level up to the “shores” of Topeka with no human contribution or even presence? Is Occam’s Rasor applied?

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.

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