Column: Google’s Computer Vision Reinforcement Learning Patent — Learning Rewards, Not Just Answers
AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on artificial intelligence patents.
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We advise on applications and patent strategy for AI, generative AI and LLMs, machine learning, deep learning and software.
Read articleTROLL Paper Analysis: Token-Level Trust Regions for More Stable LLM Reinforcement Learning Beyond PPO Clipping
Reward-based reinforcement learning is increasingly used to improve the reasoning capabilities of large language models. PPO-style policy optimization is a common approach. Methods such as GRPO, Dr.GRPO, GSPO and REINFORCE++ modify advantage estimation or normalization while seeking to avoid excessive policy changes in a single update...
Read articleUnderstanding the Paper “Agentic Reasoning for Large Language Models”
The term AI agent is used widely, but its meaning varies. It may describe a chatbot with search capabilities or a system that plans tasks and operates external tools. Recent research explores these distinctions...
Read articleWhy Do LLMs Lose Track as Conversations Get Longer?
Conversational AI can lose track of requirements as a discussion grows longer. A model may repeat a corrected mistake or continue relying on an earlier assumption even though the conversation remains in its context...
Read articleColumn: Google’s Generative AI Reasoning Patent — Teaching the Process of Thinking
AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on generative AI patents.
Read articleAgentGym-RL Paper Analysis: Training Long-Horizon AI Agents with Multi-Turn Reinforcement Learning
An AI agent asked to navigate a website, find information and recover from a failed action faces a different task from simply answering a question. It must coordinate a sequence of actions, observations and decisions, including correcting errors along the way...
Read articleAI 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 articleColumn: Google’s Self-Refine Patent — AI That Reviews and Revises Its Answers
AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on generative AI patents.
Read articleColumn: Qualcomm’s Generative AI Patent and the Future of Image Outpainting
AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on AI patents.
Read articleColumn: Google’s AI Patent for Personalized Landing Pages
AI Times, a Korean AI publication, has published Managing Partner Yongduck Kim's column on AI patents.
Read articleYongduck Kim Analyzes the Technical and Legal Implications of Meta’s AI Avatar Patent
IPLEX patent attorney Yongduck Kim analyzes Meta's patent relating to user AI avatars.
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