Question: A patent attorney must file a report covering 4 AI-related patents selected from a pool of 6 machine learning patents and 5 natural language processing patents. How many ways are there to choose the 4 patents if at least one patent from each category must be included?

Fri, 01 May 2026 22:55:15 +0000

**How Many Ways Can a Patent Attorney Choose 4 AI Patents With At Least One from Each Category?**
*Understanding the Count Behind AI Patent Strategy in the U.S. Legal Landscape* Ever wondered how patent attorneys navigate the complexities of AI innovation reports in today’s fast-evolving tech landscape? A burning question among legal professionals and researchers alike is: How many ways can a patent attorney select four AI-related patents—drawn from a pool of 6 machine learning and 5 natural language processing patents—ensuring at least one from each category? This isn’t just a dry math query—it reflects real-world decision-making, compliance standards, and the strategic tracking of fast-moving innovations central to U.S. intellectual property frameworks. As machine learning and NLP surge in influence, understanding these patent pathways reveals critical insight into emerging AI governance and investment trends. **Why This Question Is Trending Now**
With AI accelerating across healthcare, finance, and enterprise software, patent filings related to machine learning (ML) and natural language processing (NLP) are skyrocketing. The U.S. Patent Office continues to receive hundreds of applications yearly, raising demand for structured, accurate reporting. Legal practitioners must assess patent candidate combinations with precision to support filings, prior art searches, and licensing strategies. Recognizing the exact count of viable patent groupings—without overlap or exclusion—empowers attorneys to align reports with evolving innovation hotspots while satisfying due diligence requirements. This context fuels both practical need and growing public interest. **How It Actually Works: The Math Behind Patent Selection**
To determine how many ways to choose 4 patents including at least one from machine learning (ML) and one from NLP, use combinatorics with clear constraints. Total patents: 6 ML + 5 NLP = 11 patents. Teams need exactly 4 patents, with at least one from each category.