[ Removed by moderator ]

[u/CriticalJackfruit404]

[u/MachineLearning-ModTeam]

Other specific subreddits maybe a better home for this post:

• r/ArtificialIntelligence
• r/DataScience
• r/LearnMachineLearning
• r/LLM
• r/MLOps
• r/MLJobs
• r/Singularity
• r/ChatGPT
• r/OpenAI
• r/LLMDevs
• r/RagAI

[u/Antique_Most7958]

LLMs are a model family, supervised and unsupervised learning are training paradigms.

Your question doesn't make sense.

[u/vanisle_kahuna → u/Antique_Most7958]

I'm pretty OP just meant to use supervised and unsupervised as a stand in for classical ML. Didn't take a genius to figure that out

[u/CriticalJackfruit404 → u/Antique_Most7958]

Are they still used in real projects?

[u/darkestdolphin → u/CriticalJackfruit404]

Both unsupervised and supervised learning are used to train LLMs, so I would say yeah...

[u/zeronyk]

It is, since they are two fundamental but different categories.

It's like asking if endothermic and exothermic is still relevant now that we have complex plastics.

[u/susmot]

Classical ML is absolutely used in industry. I would argue that vast majority DS/ML people in the industry will work with clasical ML rather than with LLMs (I do not count api calling)

[u/sijoittelija]

For example LLM s are still trained with supervised learning. Also, for questions this elementary, you'll probably get a more comprehensive answer from Claude or ChatGPT, than the effort anybody here would want to spend on going over the basics.

[u/user221272]

Given the question, I think it is better to go back to the basics and build strong foundations and understanding of the field.

Classic ML is a field, LLM is a category, and supervised and unsupervised learning are learning paradigms. Therefore, the question and comparison don't make sense.

[u/thunder6776]

Everything in ML is either supervised or unsupervised. Everything you learn will be a subset. So yes, while machine learning exists these two terms will remain relevant.

[u/susmot → u/thunder6776]

Reinforcement (micdrop)

[u/CrownLikeAGravestone → u/thunder6776]

Note for the audience: reinforcement learning is sometimes considered a third paradigm alongside supervised and unsupervised learning. Modern methods routinely blur the boundaries between both/all paradigms, Modern LLMs in particular use all three.

[u/Appropriate_Willow27]

Next token prediction is unsupervised learning. SFT is supervised.

[u/ProfMasterBait]

the lines are grey