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This lecture covers the concept of eventual consistency in distributed systems, where data will eventually be consistent if no further updates are made, explaining the protocol used in Dynamo to achieve this. It also discusses the challenges of programming eventually consistent systems, the CAP Theorem, the tradeoff between consistency and latency, and the use of multiple-granularity locks. The instructor explains the Phantom Problem, deadlock prevention and detection, and the Two-Phase Locking protocol. The lecture concludes with a summary of different consistency models and their applications.