Intellectual Property Law
New Matter SUMMER 2024, VOLUME 49, EDITION 2
Content
- 2023 Patent Case Review
- 2024 New Matter Author Submission Guidelines
- Contents
- Copyright Roundup
- Editorial Board
- Inside This Issue
- INTELLECTUAL PROPERTY SECTION Executive Committee 2023-2024
- INTELLECTUAL PROPERTY SECTION Interest Group Representatives 2023-2024
- IP and Art: An International Perspective
- Letter from the Chair
- Letter from the Editor-in-Chief
- MCLE Self-Study Article
- Ninth Circuit Report
- Online Cle For Participatory Credit
- Quarterly International IP Law Update
- The California Lawyers Association Intellectual Property Alumni
- TTAB Decisions and Developments
- Updates on New Non-Compete Laws in California
- Weber, Inc. v. Provisur Technologies, Inc.
- What Happened to the Rogers Test After the Jack Daniels Supreme Court Case?
- The Licensing Corner
The Licensing Corner
MATTHEW DEDON
The Law Office of Matthew Dedon
A COMPARISON OF U.S. AND CHINESE APPROACHES TO GENERATIVE AI
Artificial Intelligence (AI) has been a buzzword for the past few years. AI refers to systems that are designed to respond to a particular set of inputs. These systems analyze input data and respond according to the instructions built into the system. Generative-AI (GenAI) is a subset of AI that generates new content output in response to input from a user. GenAI receives prompts and uses its training data and models, frequently consisting of enormous quantities of human-authored works, to ultimately create a wide array of new content output.
A key distinction between the two systems is that traditional AI is primarily used to analyze data and make predictions, while generative AI goes a step further by creating new data similar to its training data. In other words, traditional AI excels at pattern recognition, while GenAI excels at pattern creation.1