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Organizations across all industries are adopting generative AI systems as critical components of their business strategy. These systems often take the form of hosted or on-premises pretrained large language models (LLMs), both proprietary and open source. Organizations acquiring access to pretrained LLMs from a small but growing list of providers can apply various customization techniques. Once customized, LLM usage by an organization can potentially result in an output that constitutes an invention like those on which thousands of U.S. patents are granted every year. As just some examples, a suitably customized LLM could generate a technique to determine a navigation plan consistent with an ODD associated with an autonomous vehicle, an algorithm to predict disease onset based on clinical and environmental factors, or computer code to detect malware by overcoming dynamic obfuscation attempts.
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By Reid Knabe and Bita Rahebi
This article describes certain key developments in the period from passage of the CHIPS Act through the present day, and provides a brief survey of key grantmaking and investment activity by U.S. government agencies since passage of the Act.
Emerging Legal Terrain: IP Risks from AI’s Role In Drug Discovery
By Fredrick Tsang, Antonia Sequeira and Carl Morales
This article explores the benefits and risks of AI-driven drug discovery from the legal perspective. Since the law governing IP rights in AI-driven drug discovery is still in its infant state, any future legal development is likely to have significant implications in many areas.
Adidas Stripe Design Battle Reveals Intricacies of Trademarks In the Fashion World
By Nicole D. Galli, Laura Talley Geyer and Alexa Elder
Although the bitter legal battle between Adidas and Thom Browne is far from over on either side of the pond, the case illustrates the challenges of ensuring trademark protection for simple and widely employed design elements.
Is It Possible to Reconcile the Two Sides In the AI Copyright Debate?
By Maria Dinzeo
The points and counterpoints brought up by experts at a Stanford Law conference provide insight on the future relationship between AI and copyright creators.
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