# Column: Yongduck Kim on Securing AI Patents

AI Times has published a column by IPLEX patent attorney Yongduck Kim. His experience includes IP work for companies in Korea and overseas, including LG Electronics, Samsung Electronics, Baidu, SUALAB and MakinaRocks, in fields such as AI, smart factories and blockchain.

Source: https://www.iplexlaw.co.kr/en/blog/845881

HOME / NEWS & INSIGHTS NEWS & INSIGHTS Column: Yongduck Kim on Securing AI Patents AI Times has published a column by IPLEX patent attorney Yongduck Kim. His experience includes IP work for companies in Korea and overseas, including LG Electronics, Samsung Electronics, Baidu, SUALAB and MakinaRocks, in fields such as AI, smart factories and blockchain. IPLEX News 2023.05.17 published IPLEX 3 min read AI Times published patent attorney Yongduck Kim's column on AI technology trends and patent protection. He works on AI, smart-factory and blockchain IP matters for clients including LG Electronics, Samsung Electronics, Baidu, SUALAB and MakinaRocks. Read the column "What can be protected by patent in the field of artificial intelligence?" In general, companies that develop AI technologies often develop technologies across a whole area rather than a specific area. However, in terms of securing a patent, securing one patent for a technology across the entire area may result in an excessively narrow scope of rights. Therefore, it is good to have a patent on each of the specific areas. A filing focused only on where AI is used may overlook the technical contributions made during model development. However, if you only have a patent for the application, the problem is that the key technologies that take the most time and effort to develop AI models are not properly protected by patents. So, how do you secure an AI patent? As a developer, you need to think about what happens when you develop an AI model. Potential patent areas include data collection; preprocessing such as deriving data attributes, augmentation, generalization and noise filtering; defining and training models, including training environments, model implementations and hyperparameter optimization; physical implementations such as neural-network devices and circuits; network architecture; and inference, including processing and using model outputs. Protecting technically substantive improvements across these areas can support a coherent patent portfolio and help demonstrate technical capability. - Excerpt from the column Read the original article ↗ Read the Korean source This article reflects the information available when it was published. Contact us to discuss your circumstances. Discuss this topic ↗ All articles TALK TO IPLEX Discuss your IP questions We consider your technology and business needs together. ↗ Contact us Newer Lunit Patents for AI-Based Medical Image Analysis ↗ Older Predicting Industrial Equipment’s Remaining Useful Life with AI ↗ Related insights IPLEX News 2026.08.20 AI Paper Analysis: In-Place Test-Time Training Most large language models are deployed with fixed weights after training. Even when a user supplies a long document, the model processes its tokens within the attention mechanism and context window without directly adapting its weights to that document. In-Place Test-Time Training explores an alternative... ↗ Read article IPLEX News 2026.08.03 Column: C3.ai Patents and the Future of Enterprise AI Agents AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on generative AI patents. ↗ Read article IPLEX News 2026.07.29 Ideas Become Business Assets When They Become Rights Startup IP work must align protection before disclosure, payment within the project's funding period and the documentation needed for expense reconciliation. At IPLEX, Managing Partner Yongduck Kim analyzes a startup's technology, brand and product appearance to guide patent, trademark and design applications... ↗ Read article

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