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Today's tutorial is about conditional random fields (CRFs) and their connection to hidden Markov models (HMMs). CRFs can be seen as a broader form of HMMs, with HMMs being a specific case of CRFs. The video explores the reasons for using CRFs over simpler models and the considerations involved in transitioning from specific to more complex models in data science. The speaker also mentions using a new microphone and asks for feedback on the sound quality.