Overcoming 35 U.S.C. § 101 Rejections in AI & Machine Learning Claims

Drafting patent specifications for Artificial Intelligence (AI) and Large Language Models (LLMs) requires navigating Step 2A and Step 2B of the USPTO's Revised Patent Subject Matter Eligibility Guidance under 35 U.S.C. § 101.

1. Anchor Claims to Specific Computer System Improvements

To avoid being categorized as a mathematical concept or abstract mental process under the Alice framework, claims must explicitly describe how the neural architecture or processing pipeline improves computational execution (e.g., reduced latency, optimized VRAM usage, or sparse tensor multiplication).

2. Detailed Enablement in Specification Embodiments

The detailed description must fully disclose loss function formulations, hyperparameter adjustment mechanisms, and data pre-processing flows. Broad functional claiming without structural backing in the specification triggers quick § 112 written description and § 101 eligibility rejections.