The document discusses several topics related to artificial intelligence and machine learning including: 1. It discusses how data has become more valuable than oil and how machine learning models are trained using large amounts of labeled data. 2. It provides an overview of the machine learning process and compares traditional programming to machine learning approaches. 3. It outlines the typical workflow for traditional big data processing versus machine learning including data collection, storage, analysis, and model training.

1. In The AI Era,
Is Data Still The New Oil?
2022.9
Hanwha Systems/ICT
David Yushin KIM

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. (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. (Source: globaleurope.eu/globalization/how-can-consumers-benefit-from-big-data-and-ai/)

5. (Source: rapidminer.com/glossary/deep-learning-vs-machine-learning/)

6. (Source: vas3k.com/blog/machine_learning/)

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. (Source: Hidden Technical Debt in Machine Learning Systems, NIPS 2015)
Real-world ML systems

9. (Source: devopedia.org/artificial-intelligence)
Machine Learning Process

10. (Source: www.aihub.or.kr/)

11. (Source: captain-whu.github.io/DOTA/dataset.html)

12. (Source: www.kdnuggets.com/2017/09/cartoon-machine-learning-class.html)

13. 업무전문가
개발자 수준
전문가
복잡하지 않은 대시보드/
사용자가 많은 경우
복잡한 요구사항을 수용해야 하는 경우
Traditional BigData Process

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

17. HAiQV NILE Platform Diagram

18. HAiQV NILE Platform

19. HAiQV NILE Platform

20. HAiQV NILE Platform

21. HAiQV NILE Platform

22. HAiQV NILE Platform

23. (Source: Hidden Technical Debt in Machine Learning Systems, NIPS 2015)
Real-world ML systems

24. (Source: Cognitive Computing Architectures for Machine (Deep) Learning at Scale, MDPI 2017)

25. (Source: blogs.nvidia.com/blog/2020/09/03/what-is-mlops/)

26. (Source: twitter @drangshu)

27. (Source: planningengineer.net/your-plan-and-the-reality)

29. Connecting
the Dots
(Source: www.comptia.org/blog/channeltrends-connecting-the-dots-between-tech-and-business)