Time | Presenter (click name for video) | Organization | Topic | ||
9:00-9:10 | Dean Alderucci & Sean Tu | Carnegie Mellon / West Virginia U College of Law | Welcoming Remarks | ||
9:10-9:30 | Deputy Director Laura Peter | US Patent & Trademark Office | Keynote Address | ||
AI in the World IP Offices | |||||
9:30–9:45 | US Patent & Trademark Office | Artificial Intelligence Tools for Patents at the USPTO | |||
9:45–10:00 | European Patent Office | Transformer models speaking the language of patents (abstract) | |||
10:00–10:15 | World Intellectual Property Organization | WIPO Translate and other AI tools developed at WIPO (abstract) | |||
10:15–10:30 | FIPS, Russian Patent Office | ||||
10:30–10:45 | UK Intellectual Property Office | AI-assisted Patent Prior Art Searching – A Research Study (abstract) | |||
IP Australia | Machine Learning Patent Tools at IP Australia | ||||
10:45–11:15 | How Should AI Be Improved to Support Patent Offices | ||||
Matthew Such | US Patent & Trademark Office | ||||
Alexander Klenner-Bajaja | European Patent Office | ||||
Bruno Pouliquen | World Intellectual Property Organization | ||||
Oleg Ena | FIPS, Russian Patent Office | ||||
Graham Rivers-Brown | UK Intellectual Property Office | ||||
11:15-11:30 | Break | ||||
AI and the Patent System | |||||
11:30-11:45 | UC Irvine Law | ||||
11:45-12:00 | Paul Weiss | Investigating Cohort Similarity | |||
12:00–12:15 | Vanderbilt Law School | AI and patents: A few new, some obvious, and some possibly useful comments | |||
12:15-12:30 | Boston University | Reliance on Science in Patenting | |||
12:30-12:45 | Foley & Lardner | Considerations for AI IP in Business Collaborations (abstract) | |||
12:45-1:00 | Carnegie Mellon / West Virginia U College of Law | ||||
1:00-1:15 | California Western School of Law | ||||
1:15 – 1:30 | Break | ||||
AI in Practice | |||||
1:30-1:45 | Balancing Your Portfolio | ||||
1:45-2:00 | Oracle | ||||
2:00–2:15 | Kilpatrick Townsend / Triangle IP | ||||
2:15-2:30 | Foley & Lardner | AI-Based Patent Analytics For Patent Validity Challenges – Where Are The Greatest Opportunities To Apply AI Right Now? | |||
2:30-2:45 | Break | ||||
Customized Machine Learning for Patents | |||||
2:45-3:00 | Carnegie Mellon | NLP for Claim Limitations and Claim Scope | |||
3:00-3:15 | Artificial Researcher IT GmbH | Domain Knowledge makes Artificial Intelligence Smart (abstract) | |||
3:15-3:30 | Stanford Law School | ||||
3:30-3:45 | Specif.io / McDermott Will & Emery | ||||
3:45-4:00 | PQAI | ||||
4:00-4:15 | University of New Mexico | Processing Patent Images (video of extended presentation) (abstract)abstract | |||
4:15-4:30 | Carnegie Mellon | NLP to Classify Beauregard Claims | |||
4:30-4:45 | Carnegie Mellon | NLP for Identifying Term Definitions in Patent Specifications | |||
4:45 | Dean Alderucci & Sean Tu | Closing Remarks | |||