add errata

Author: rasbt

README.md

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-# *Machine Learning and AI Beyond the Basics* Book
+# *Machine Learning Q and AI Beyond the Basics* Book
 
 
 

errata/README.md

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+# Errata
+
+
+#### Chapter 8
+
+The following sentence in Chapter 8
+
+> Transformers are easy to parallelize because they take a fixed-length sequence of word or image tokens as input.
+
+Is misleading because we only work with fixed-size sequences specifically during pretraining, finetuning, and batched inference. I.e., where we collect multiple sequences in a batch. A better explanation could be the following:
+
+> Like other deep learning architectures, transformers facilitate parallelization in batch training by handling sequences of word or image tokens. Although they can process variable-length sequences, in practice, sequences are often padded or truncated to fixed lengths for efficient parallel computation across multiple sequences.