The growing use of AI/ML models in software introduces a peculiar challenge in patent litigation: the model may reveal what it does, without necessarily revealing why it does it. In conventional software, an expert can often trace source code, follow conditional logic, and identify the instructions responsible for a particular outcome. Machine learning is different. A trained model derives its behavior from training data and learned parameters. Its outputs may be identifiable

Sportswear is no longer just fabric stitched into form. Today, it is conceived in research facilities, engineered through digital knitting platforms, and shaped by structured innovation. The factors that once set athletic brands apart — logos, celebrity endorsements, or visual appeal — are now secondary to something deeper: material engineering and proprietary production methods. This article looks at the first of four dimensions that define modern adaptive sportswear: Design

Prior-art search, the DABUS inventorship cases, and the future of the profession. Part 1 of this article covered how generative AI is reshaping first-draft generation, claim drafting, and document quality control. This second part looks at AI-powered prior-art search, the ongoing legal debate over whether an AI system can be an inventor, and where the human-AI partnership in patent drafting is headed. AI-Powered Prior-Art Searching A comprehensive prior-art search is one of

AI-assisted drafting: first drafts, claim language, and prior-art research. Introduction Generative artificial intelligence (GenAI) is rapidly transforming industries that rely on knowledge-intensive work, from software development and healthcare to finance and legal services. One such industry is innovation and patents. Patent drafting was once regarded as one of the most time-consuming and meticulous tasks in innovation management. It is now being reshaped by AI systems c

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While international treaties establish broad principles for protecting biodiversity and traditional knowledge, the patentability of biodiversity-derived inventions is ultimately determined by national patent laws and examination practices. Although approaches differ across jurisdictions, patent offices generally assess whether inventions involving biological resources satisfy the requirements of patent eligibility, novelty, inventive step, and industrial applicability. In the

Recognizing that biodiversity-related disputes extend across national boundaries, several international legal instruments have sought to establish a fair balance between promoting innovation and protecting the rights of biodiversity-rich countries and Indigenous communities. 1. Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement The TRIPS Agreement, adopted under the World Trade Organization in the 1990s, established the first comprehensive global framewor

These cases illustrate the tension between patent protection, traditional knowledge, and equitable ownership of biodiversity. Case Study 1: The Turmeric Patent The Turmeric Patent remains one of the most influential examples of traditional knowledge serving as prior art within the patent system. In 1995, the United States Patent and Trademark Office (USPTO) granted U.S. Patent No. 5,401,504 for the use of turmeric in wound healing. The patent was subsequently challenged by In

Understanding Biodiversity and the Rise of Biopiracy Can naturally occurring biological resources be patented? Who owns the knowledge that Indigenous communities have preserved for centuries? And where should the law draw the line between discovering nature and inventing from it? These questions have become increasingly significant as scientific and technological advancements continue to unlock the immense commercial potential of biodiversity. Biodiversity, encompassing the w

1. INTRODUCTION: THE AGE OF TALKING MACHINES There was a time when AI assistants meant convincing Siri to set an alarm without accidentally calling your neighbor. The bar was low, expectations were modest, and most smart assistants could not hold a conversation longer than five seconds without losing track. Now we have AI models that write production grade code, summarize lawsuits, analyze patents, predict trends, simulate arguments, and even explain memes with surprising emo