AI BriefingLG AI Research news
The latest AI and developer news from LG AI Research, with short summaries.
Visit website →[AI Ethics Seminar EP.3] Introducing Major AI Toolkits for Designing Trustworthy AI Experiences and Practical Application Guidelines - LG AI Research BLOG
To design trustworthy AI experiences, this analyzes Microsoft's and Google's AI Toolkits and presents practical application guidelines.
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Explores the potential for autonomous collaboration among AI agents and the changes they could bring to social structures.
[AI Ethics Seminar EP.4] Building a Responsible AI Society Through AI Agents
It analyzes the autonomous decision-making and cooperation patterns of AI Agents through simulations and presents the need for ethical mechanisms.
LG AI Research Releases EXAONE 3.5 Open-Source Models
LG AI Research has released 3 EXAONE 3.5 open-source models that maximize performance and efficiency.
EXAONE 3.5 Released as Open Source with 3 Models - Achieves Frontier AI-level Performance, Top-Tier Instruction Following and Long Context
LG AI Research has released 3 EXAONE 3.5 models as open source, capturing both performance and cost-efficiency.
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LG AI Research is researching AI-based auto-routing technology to streamline complex PCB design processes.
LG AI Research Studies PCB Automatic Routing Technology
LG AI Research developed a PCB automatic routing technology that combines Grid-based and Continuous Space methods to solve complex constraint conditions.
LG AI Research: The Importance of AI Ethics Research
It analyzes deceptive patterns that can occur during the UI/UX design process of AI services and proposes ethical design approaches.
LG AI Research: A Benchmark Suite for Evaluating Neural Mutual Information Estimation on Unstructured Datasets
LG AI Research proposed a new benchmark that goes beyond the limitations of existing Gaussian-data-centric approaches to verify mutual information (MI) estimation performance on unstructured data.
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LG AI Research proposed a new benchmark that can rigorously verify mutual information (MI) estimation performance in unstructured data settings.
[NeurIPS 2024 Series] A B-spline-based Method for Normalizing Tabular Data Inputs - LG AI Research BLOG
LG AI Research has proposed a new technique that uses B-spline to dynamically normalize tabular data according to its complex distributions.
[NeurIPS 2024 Series] B-splines-based Input Normalization for Tabular Data
LG AI Research proposed a Tabular data normalization technique using B-splines that dynamically transforms according to data characteristics.
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LG AI Research has developed AGATa technology that improves training performance while preserving the structure of tabular data.
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LG AI Research unveiled AGATa, a new augmentation technique that maximizes training performance while preserving the structural characteristics of tabular data.
LG AI Research: Adaptive Information Routing Technology for Multimodal Time Series Forecasting
LG AI Research proposed AIR, a multimodal time series forecasting technology that reflects the characteristics of time series data and text data.
LG AI Research: Adaptive Information Routing Technology for Multimodal Time Series Forecasting
LG AI Research has proposed 'AIR,' a multimodal time series forecasting technique that uses text information to control the behavior of time series models.
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LG AI Research unveiled 'NEXUS,' an Agent AI system that tracks the lifecycle of complex datasets and analyzes legal risks.
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LG AI Research has unveiled 'NEXUS,' an Agent AI system that automatically analyzes and tracks the legal risks of datasets.
LG AI Research: The Convergence of Basic Science and AI
LG AI Research dramatically shortened new material development timelines using a molecular pre-training model that leverages 3D structures.
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LG AI Research shortened the development period for cosmetic efficacy materials from 2 years to a single day using knowledge distillation technology that leverages 3D molecular information.