Balancing Functional Language in AI Patent Claims
In the rapidly evolving world of artificial intelligence (AI), securing patents is a critical task for innovators—and it's one that must be done right. However, the unique nature of AI technologies presents significant challenges when drafting and/or translating patents, particularly when it comes to the use of functional language in claims.
In the United States, recent decisions by the Patent Trial and Appeal Board (PTAB) have shed light on how 35 U.S.C. § 112(f), which deals with means-plus-function claim limitations, applies to AI inventions.
Rethinking Patent Quality: New Insights Challenge Old Assumptions
A recent report from the Sunwater Institute has challenged long-held beliefs about patent quality in the United States. Contrary to popular opinion, the U.S. Patent and Trademark Office (USPTO) is not overwhelmed with "bad patents." In fact, only 7% of U.S. patent claims are erroneously granted, one of the lowest rates among major patent offices worldwide.
The report reveals a surprising finding: the USPTO is more likely to erroneously reject or abandon valid patent claims than to grant invalid ones. Approximately 18% of abandoned U.S. patent claims are actually valid under patentability criteria. This discrepancy is even more pronounced in tech-heavy fields like computer networks and communications.