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Google's patent US20250131984A1 presents a method for sequence error correction using neural networks, focusing on improving accuracy in detecting and correcting errors in sequences such as DNA or text. The patent describes a system that leverages deep learning models—specifically artificial neural networks (ANNs)—to identify errors in sequences and suggest corrections based on the context surrounding the error. Overview of the Patent's Core Concept The patent centres on using neural networks to analyse sequences and correct errors by understanding the context of each element (e.g., a word in a sentence or a base in a DNA sequence). This approach contrasts with traditional rule-based error correction methods, which rely on predefined rules and often fail to handle complex or ambiguous cases. Key Components of the System Input Sequence Processing The system receives a sequence, such as a sentence or a DNA read, and identifies target elements that may contain errors. Co...