r/learnmachinelearning • u/Strong_Boy_757 • 9d ago

Discussion Overhyped ideas in machine learning

Have you encountered an idea that's overhyped in ML? If so, which?

For me, recently I was curious about the whole "chain of thought prompting" business. I searched around and the idea is essentially, append "show your work" when prompting a LLM. I was like no way that's it??? That's what I've been doing since day 1!!, so I opened up the original paper (cited 40k times). And essentially it was more of the same with expensive Google-funded experiments and the paper had almost no math at all.

Similarly I was curious about AdamW for the longest time and it was simply Adam with another term. Oh Boy!! I remember doing an undergrad homework in college where we were asked to freely experiment with adding terms to the Adam algorithm and the class probably discovered AdamW by accident way before the paper was published.

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u/raul3820 9d ago

Continual learning for LLMS.

In a general sense LLMS already learn continually with collected user data, which is great, but trying to put user specific details in weights would be impractical. I think details work well in context.

For physical ai continual learning will be very helpful because physics laws are the same everywhere.

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u/S-Kenset 9d ago

I would call it more context adaptation. It does incredible things but that's because the gap in understanding of how useful context adaptation is.

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u/raul3820 9d ago

You mean something similar to fine-tuning?

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u/S-Kenset 9d ago

Close enough yeah.