eCourse
IP and AI: Navigating Implications for Patentability, Licensing, and the Practice of Law
Contains material from Jan 2024
IP and AI: Navigating Implications for Patentability, Licensing, and the Practice of Law
4.25 out of 5 stars
What was the overall quality of the course (presentation, materials, and technical delivery)?
Rate the overall teaching effectiveness and presentation skills of faculty for the course.
How would you rate the value of the materials provided as part of the course?
Technical Questions?
512.475.6700
service@utcle.org
- System Test
-
$105 Add to Cart
Session 01: Does Intelligence Equal Competence? Navigating Artificial Intelligence in the Practice of Law - Artificial Intelligence may be embedded in tools, or may even be a tool itself, that helps lawyers better meet client needs. But, it is no different than other conventional tools and technologies used by lawyers—they must be used in conjunction with a lawyer’s duty to provide competent representation.
Session 02: IP Considerations for Generative AI - My company is at the edge of technology: we use generative AI for software development to invent a new product. Should and can we file a patent application naming the generative AI as an inventor, and what patenting strategy should we adopt? What are the IP implications of using open source software (OSS) to train the generative AI or if the generative AI itself is an OSS model?
Session 03: Inventing Tomorrow: A Guide to Claiming and Patenting AI Creations - This presentation covers various topics on patents in AI including: why we should pursue patents in AI (open source vs. IP rights), how we can claim an AI invention (target, detectability, eligibility), and additional thoughts on the future landscape of AI patents.
Session 04: License on Transfer: Lessons Learned from The Founder and Implications for AI - The license on transfer network (lotnet.com) reduces the patent assertion entity problem for 3,200 plus member companies covering approximately four million patent assets by leveraging a royalty-free networked patent license. The founder of the lot network shares lessons learned over the past decade, implications for the future, and opportunities for similar collaborative efforts in AI.
Session 02: IP Considerations for Generative AI - My company is at the edge of technology: we use generative AI for software development to invent a new product. Should and can we file a patent application naming the generative AI as an inventor, and what patenting strategy should we adopt? What are the IP implications of using open source software (OSS) to train the generative AI or if the generative AI itself is an OSS model?
Session 03: Inventing Tomorrow: A Guide to Claiming and Patenting AI Creations - This presentation covers various topics on patents in AI including: why we should pursue patents in AI (open source vs. IP rights), how we can claim an AI invention (target, detectability, eligibility), and additional thoughts on the future landscape of AI patents.
Session 04: License on Transfer: Lessons Learned from The Founder and Implications for AI - The license on transfer network (lotnet.com) reduces the patent assertion entity problem for 3,200 plus member companies covering approximately four million patent assets by leveraging a royalty-free networked patent license. The founder of the lot network shares lessons learned over the past decade, implications for the future, and opportunities for similar collaborative efforts in AI.
Includes: Video Audio Slides
- Total Credit Hours:
- 2.00 | 0.75 ethics
- Credit Info
- TX, CA
- TX MCLE credit expires: 1/31/2025
Preview mode.
You must be signed in, have purchased this eCourse,
and the eCourse must be active
to have full access.
Preview Sessions
Credit
Show session details
1.
Does Intelligence Equal Competence? Navigating Artificial Intelligence in the Practice of Law (Jan 2024)
Daniel H. Shulman
0.50
0.50
0.00
0.50 | 0.50 ethics
Preview Materials
Download session materials for offline use
Session 1
—28 mins
0.50 | 0.50 ethics
Does Intelligence Equal Competence? Navigating Artificial Intelligence in the Practice of Law (Jan 2024)
Artificial Intelligence may be embedded in tools, or may even be a tool itself, that helps lawyers better meet client needs. But, it is no different than other conventional tools and technologies used by lawyers—they must be used in conjunction with a lawyer’s duty to provide competent representation.
Originally presented: Nov 2023 Advanced Patent Law Institute
Daniel H. Shulman,
Vedder Price P.C. - Chicago, IL
Show session details
2.
IP Considerations for Generative AI (Jan 2024)
Patrick Njeim
0.50
0.25
0.00
0.50 | 0.25 ethics
Preview Materials
Download session materials for offline use
Session 2
—30 mins
0.50 | 0.25 ethics
IP Considerations for Generative AI (Jan 2024)
My company is at the edge of technology: we use generative AI for software development to invent a new product. Should and can we file a patent application naming the generative AI as an inventor, and what patenting strategy should we adopt? What are the IP implications of using open source software (OSS) to train the generative AI or if the generative AI itself is an OSS model?
Originally presented: Nov 2023 Advanced Patent Law Institute
Patrick Njeim,
Kilpatrick Townsend & Stockton - Seattle, WA
Show session details
3.
Inventing Tomorrow: A Guide to Claiming and Patenting AI Creations (Jan 2024)
Charlene Liu, Hong Shi
0.75
0.00
0.00
0.75
Preview Materials
Download session materials for offline use
Session 3
—51 mins
0.75
Inventing Tomorrow: A Guide to Claiming and Patenting AI Creations (Jan 2024)
This presentation covers various topics on patents in AI including: why we should pursue patents in AI (open source vs. IP rights), how we can claim an AI invention (target, detectability, eligibility), and additional thoughts on the future landscape of AI patents.
Originally presented: Nov 2023 Advanced Patent Law Institute
Charlene Liu,
Haynes Boone, LLP - San Francisco, CA
Hong Shi,
Haynes Boone, LLP - Austin, TX
Show session details
4.
License on Transfer: Lessons Learned from The Founder and Implications for AI (Jan 2024)
Eric Schulman
0.25
0.00
0.00
0.25
Preview Materials
Download session materials for offline use
Session 4
—19 mins
0.25
License on Transfer: Lessons Learned from The Founder and Implications for AI (Jan 2024)
The license on transfer network (lotnet.com) reduces the patent assertion entity problem for 3,200 plus member companies covering approximately four million patent assets by leveraging a royalty-free networked patent license. The founder of the lot network shares lessons learned over the past decade, implications for the future, and opportunities for similar collaborative efforts in AI.
Originally presented: Nov 2023 Advanced Patent Law Institute
Eric Schulman,
Fish & Richardson P.C. - Redwood City, CA