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Data In AI_한화시스템_김유신.pdf

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Data In AI_한화시스템_김유신.pdf

  1. 1. In The AI Era, Is Data Still The New Oil? 2022.9 Hanwha Systems/ICT David Yushin KIM
  2. 2. (Source: www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data) The world’s most valuable resource is no longer oil, but data.
  3. 3. (Source: catalyticsconsulting.com/data-is-not-the-new-oil/) The phrase was first coined by Clive Humby in 2006. Michael Palmer expanded upon the quote to say that like Oil, Data is “valuable, but if unrefined, it cannot really be used” Because of its Availability and Reusability, Data can be much more lucrative to many more organizations, communities, and people than Oil alone could ever be.
  4. 4. (Source: globaleurope.eu/globalization/how-can-consumers-benefit-from-big-data-and-ai/)
  5. 5. (Source: rapidminer.com/glossary/deep-learning-vs-machine-learning/)
  6. 6. (Source: vas3k.com/blog/machine_learning/)
  7. 7. 𝑦 = 𝑓(𝑥) 𝑦 𝑓( ) 𝑥 𝑦 𝑓( ) 𝑥 COMPUTING COMPUTING COMPUTING 𝑥′ 𝑦′ Traditional Programming Machine Learning Computer Program (Algorithm, Rules) AI/ML Model (Algorithm, Networks) Labeled Data Training Inference
  8. 8. (Source: Hidden Technical Debt in Machine Learning Systems, NIPS 2015) Real-world ML systems
  9. 9. (Source: devopedia.org/artificial-intelligence) Machine Learning Process
  10. 10. (Source: www.aihub.or.kr/)
  11. 11. (Source: captain-whu.github.io/DOTA/dataset.html)
  12. 12. (Source: www.kdnuggets.com/2017/09/cartoon-machine-learning-class.html)
  13. 13. 업무전문가 개발자 수준 전문가 복잡하지 않은 대시보드/ 사용자가 많은 경우 복잡한 요구사항을 수용해야 하는 경우 Traditional BigData Process
  14. 14. Workflow 기반 Data 수집 Streaming Data 처리 Data 수집 (Optional) Hadoop 기반 분산 Data 저장 분석용 Data 저장 Data 저장 (Optional) Data 조회/분석 도구 Data 탐색/분석 공간 ML/DL Traditional BigData Process
  15. 15. HAiQV NILE Platform Diagram
  16. 16. HAiQV NILE Platform
  17. 17. HAiQV NILE Platform
  18. 18. HAiQV NILE Platform
  19. 19. HAiQV NILE Platform
  20. 20. HAiQV NILE Platform
  21. 21. (Source: Hidden Technical Debt in Machine Learning Systems, NIPS 2015) Real-world ML systems
  22. 22. (Source: Cognitive Computing Architectures for Machine (Deep) Learning at Scale, MDPI 2017)
  23. 23. (Source: blogs.nvidia.com/blog/2020/09/03/what-is-mlops/)
  24. 24. (Source: twitter @drangshu)
  25. 25. (Source: planningengineer.net/your-plan-and-the-reality)
  26. 26. Connecting the Dots (Source: www.comptia.org/blog/channeltrends-connecting-the-dots-between-tech-and-business)

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