In an era where AI replaces technical proficiency, humans must strengthen their 'episteme' capabilities responsible for problem-setting and value judgment.
LG AI Research has unveiled the SciNO framework, which enables stable causal discovery even in high-dimensional data environments.
LG AI Research has unveiled the SciNO framework, which supports stable causal relationship inference even in high-dimensional data.
LG AI Research has developed K-EXAONE, a large-scale AI model that maximizes both efficiency and performance.
LG AI Research has developed K-EXAONE, a large-scale AI model that maximizes efficiency and reasoning capability.
LG AI Research runs an AI Ethics Seminar to build trustworthy AI that goes beyond technological innovation to enrich human life.
LG AI Research is running an AI ethics seminar from the philosophical perspective that AI should be a tool that helps humans actively grow.
LG AI Research has developed the RAPID platform, which makes design and analysis easy, to improve the efficiency of industrial automation.
LG AI Research unveiled a multi-phase reinforcement learning framework and RL-Studio optimized for complex industrial settings.
LG AI Research has unveiled Multi-Phase RL, a reinforcement learning framework capable of complex stage-by-stage transitions, along with its platform RL-Studio.
LG AI Research unveiled the AEGIS platform, which detects anomalies at manufacturing sites through collaboration between expert knowledge and AI, at AAAI 2026.
LG AI Research unveiled AEGIS, a platform where domain experts' knowledge and AI collaborate to detect anomalies in manufacturing sites.
As we prepare for the era of Agentic AI, which goes beyond simple text generation to carry out goals, securing observability through ontology is key.
LG AI Research showcased structural reasoning technology combining knowledge graphs and LLMs at AAAI 2026, demonstrating agent reliability and efficiency.
LG AI Research has released EXAONE 4.5, a multimodal model that understands text and images simultaneously, as an open-weight model.
LG AI Research has unveiled EXAONE 4.5, an open-weight VLM that processes visual information and language simultaneously.
LG AI Research and VUMC collaborated to present a next-generation cancer research model leveraging 3D spatial biology and pathology AI.
LG AI Research collaborated with VUMC to unveil next-generation cancer research achievements combining 3D/4D spatial biology and AI.
LG AI Research has developed a mid-to-long-term forecasting model based on a Causal Map that structures the causal relationships of lithium prices using an LLM.
This introduces a technology that maximizes infrastructure efficiency by reallocating idle GPU resources—caused by traffic fluctuations in LLM services—to model training and research.
We built an efficient scheduling pipeline that reallocates idle GPU resources, which occur due to traffic fluctuations in LLM services, for research and training purposes.
This post covers the concept and key technical directions of Robot Foundation Models (RFM), robots that perform tasks by directly interacting within physical environments.
We look at the two core technical directions of Robot Foundation Models (RFM), which go beyond LLMs in virtual worlds to interact with the physical environment.
LG AI Research has proposed 'Cluster-Aware Upcycling,' a technology that solves the problem of redundancy among experts when converting existing Dense models into MoE.
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