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.

Imagine a shift where AI know-how is as crucial as scientific expertise. The EU AI Act now compels life sciences sectors to enhance AI literacy by February 2025, with stricter rules by 2026. For example, one biotech firm revamped its training to cover both technical risks and benefits, reflecting European Commission directives. This regulation offers a clear example of proactive industry change. [Takeaway: Update your team’s AI training now to stay ahead in regulatory compliance.]