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엔터프라이즈 기업의 AI/ML 솔루션 활용을 통한 수익 창출 전략과 실제 성공 사례를 통해 지속 가능한 비즈니스 성장 방안을 탐구합니다.
Discover how SK hynix prepares for evolving HBM market demands, focusing on AI inference chips, customer customization, and strategic partnerships with TSMC and AI chip manufacturers.
Discover how on-device AI technology detects voice phishing in real-time using small language models and speech-to-text conversion, all while protecting user privacy through local processing.
Discover how SK Telecom developed advanced customer service AI agents using LLM orchestration, from simple responses to multi-agent systems handling complex telecommunications inquiries.
Explore how AI transforms university education through KAIST's innovative cases and research findings, focusing on effective human-AI collaboration for deeper learning experiences and educational advancement.
Discover how to build high-performance GPU clusters using NVLink virtualization and RDMA technologies for efficient AI infrastructure sharing and resource optimization in multi-tenant environments.
Discover SK하이닉스의 AI 시대 메모리 솔루션 전략과 HBM을 넘어선 차세대 컴퓨팅 아키텍처를 위한 CXL/PIM 기반 혁신적 메모리 기술 개발 방향
Discover optimal GPU infrastructure strategies for AI development, comparing on-premise and cloud solutions with focus on TCO minimization and SKT's GPUaaS collaboration with Lambda.
Discover SK Group's comprehensive AI talent development framework, from basic literacy to specialized roles like ML engineers and LLM developers, through structured learning, hands-on experience, and certification.
Discover how self-supervised learning revolutionizes multilingual speech recognition through SK Telecom's innovative approach using 500,000 hours of unlabeled data for enhanced accuracy and efficiency.
Discover how enterprises can implement generative AI with practical strategies, from private LLM adoption using SLM to workflow innovation, featuring Upstage's Solar-pro model and real-world success cases.
Discover how SK Telecom revolutionizes customer service through AI-powered callbots, chatbots, and assistant systems using LLM, voice recognition, and synthesis technologies.
Discover how to optimize AI data center operations using AWS container solutions, focusing on EKS portfolio, GenAI frameworks, and infrastructure efficiency with practical implementation tips.
Explore AI 모델 학습의 가속기 기술과 HBM의 발전 동향을 살펴보고, 대규모 AI 추론 비용 문제와 최신 서버향 AI 가속기 구조에 대한 심층적인 이해를 얻으세요.
Discover how to optimize AI models by understanding hardware components, with real success cases from Nota AI's on-device implementations and industry collaborations.
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