Race Conditions
In Data Science and Artificial Intelligence, a race condition occurs when two or more processes or threads access shared data and try to change it at the same time, resulting in unpredictable and erroneous behavior. This can happen when the order of execution of these processes or threads is not guaranteed, and the outcome depends on the timing of their execution. Race conditions can lead to data corruption, deadlocks, and other issues that can affect the accuracy and reliability of the results obtained from the system. To prevent race conditions, synchronization mechanisms such as locks, semaphores, and barriers can be used to ensure that only one process or thread can access the shared data at a time.
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