The Federal Circuit holds that patents claiming machine learning optimization for television scheduling and network mapping do not satisfy Section 101 patent-eligibility. The court applies the Alice two-step framework, finding the claims directed to an abstract idea and lacking an inventive concept beyond generic computing.

Key points

• Patent claims address dynamic TV scheduling and network mapping via machine learning optimization.
• Federal Circuit applies Alice two-step test, finding the claims directed to abstract ideas.
• Claims lack inventive concept, using generic ML and conventional computer components only.

Why it matters: This decision underscores the need for clear technical innovations in AI patent applications, shaping how future machine learning-based inventions will be assessed for eligibility.