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Today's tutorial is about Conditional Random Fields (CRFs) and their relationship with Hidden Markov Models (HMMs). CRFs can be seen as a more generalized form of HMMs, with HMMs being a specific instance of CRFs. The video aims to explore why transitioning from specific models like HMMs to more complex ones like CRFs is necessary in data science. The narrator mentions using a new microphone and asks for feedback on the audio quality. The tutorial sets the stage for understanding the importance of CRFs in modeling data.