The white paper explains how Technology Assisted Review (TAR) has evolved from TAR 1.0, which required static datasets and expert training, to TAR 2.0, which learns continuously from reviewers. Both approaches, however, rely on older supervised machine learning that struggles with today’s complex, high-volume datasets. Advanced AI, combining deep learning and natural language processing, improves accuracy by understanding context, reusing prior coding, and scaling for big data. In HSR Second Requests, TAR enhanced with advanced AI can cut responsive sets by over 40%, maintain stability during negotiations, and ensure faster, defensible compliance.

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