| dc.contributor.advisor | 吳文傑 | zh_TW |
| dc.contributor.advisor | Wu, Jack | en_US |
| dc.contributor.author (Authors) | 粟郁杉 | zh_TW |
| dc.contributor.author (Authors) | Shu, Yu Shan | en_US |
| dc.creator (作者) | 粟郁杉 | zh_TW |
| dc.creator (作者) | Shu, Yu Shan | en_US |
| dc.date (日期) | 2023 | en_US |
| dc.date.accessioned | 2-Aug-2023 13:44:01 (UTC+8) | - |
| dc.date.available | 2-Aug-2023 13:44:01 (UTC+8) | - |
| dc.date.issued (上傳時間) | 2-Aug-2023 13:44:01 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0108933027 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/146483 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 國際經營管理英語碩士學位學程(IMBA) | zh_TW |
| dc.description (描述) | 108933027 | zh_TW |
| dc.description.abstract (摘要) | This business plan is about the business analysis of DeepFlow, a product of InventAI, which is a startup team of Chunghwa Telecom Co., Ltd. That I currently serve as the Head of Business Development for the team. DeepFlow is a professional AI/ML model lifecycle management platform (MLOps), which also has automated machine learning functions (AutoML). Currently, it mainly serves data scientists and AI engineers, and has a complete workflow. Assist them to accmplish their daily work smoothly. Functions include: a comprehensive management platform for model development, training, inference, and deployment functions, making it easier for them to collaborate across teams. Manage the development tools such as model images and kits that need to be used during the model development process. Manage different versions of the training model, and the health management of the model after it goes online. This project report, in addition to using credible AI survey report data, conducts external market opportunity and risk analysis. Also study the potential competitors in domestic market. Product internal analysis, using STP analysis, starting from product strategy, main users, and market positioning, and analyzing DeepFlow`s product features through 4P analysis. Although AI products themselves have high technical content, it is not easy to quickly absorb and understand. I hope that through this business analysis, more people can understand that the sales of AI products are just like most commercial software. The core value is to solve human problems. I believe that technology always comes from human nature, and AI is an auxiliary tool, not a robot that replaces human beings. | en_US |
| dc.description.tableofcontents | 1. Executive Summary 1 2. Business Overview 3 2.1 Company introduction 3 2.2 Product description 3 2.2.1.AutoML 3 2.2.2 MLOps 4 2.3 Competitive advantage as an AI/ML platform 4 2.3.1 Powerful and Scalable Infrastructure 4 2.3.2 Advanced Algorithmic Capabilities 4 2.3.3 Easy-to-Use Interface and Workflow 5 2.3.4 Comprehensive Model Management 5 2.3.5 Integration and Compatibility 5 2.3.6 Automated and Customizable Pipelines 5 2.3.7 Robust Model Monitoring and Management 6 2.3.8 Support and Community 6 2.4 Mission and Vision 6 3. Market and External Analysis 7 3.1. Global Market Assessment 7 3.2. Taiwan Market Evaluation 8 3.3 Market Size Estimation 11 4. Competitor Analysis 12 4.1 Current situation of autoML in Taiwan’s market 12 4.2 Current situation of MLOps in Taiwan’s market 13 5. Internal analysis of DeepFlow (SWOT analysis) 14 5.1Strengths 14 5.2 Weaknesses 15 5.3 Opportunities 15 5.4 Threats 15 6. Marketing Strategy (STP &4P) 16 6.1 STP analysis 16 6.1.1 Segmentation 16 6.1.2 Targeting 16 6.1.3. Positioning 16 6.2 4P analysis 17 6.2.1 Product 17 6.2.2 Price 24 6.2.3 Place 25 6.2.4 Promotion 25 7. Business Model 26 7.1 Value Proposition 26 7.2 Customer Segments 27 7.3 Channels 27 7.4 Customer Relationships 27 7.5 Revenue Streams 27 7.6 Key Activities 27 7.7 Key Resources 28 8. Management and Functional Teams 28 8.1 Organizational structure 29 8.2 Company Culture 31 8.3 Company’s Benefit 32 9.Financial Operations & Statements 33 9.1 Company ownership and share (NT$50 million) 33 9.2 Revenue 34 9.3 Operating Cost & Expense 35 9.3.1 Operating Cost 38 9.3.2 Operating Expense 39 9.4 Income Statement 41 10.Scenario Analysis 42 11. Supply Side Key Partners 43 12. Conclusion and future expansion forecast 45 12.1 Conclusion 45 12.2Future expansion forecast 47 Reference 49 | zh_TW |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0108933027 | en_US |
| dc.subject (關鍵詞) | 人工智能 | zh_TW |
| dc.subject (關鍵詞) | 自動機器學習 | zh_TW |
| dc.subject (關鍵詞) | MLOps | zh_TW |
| dc.subject (關鍵詞) | DeepFlow | zh_TW |
| dc.subject (關鍵詞) | 人工智能發明 | zh_TW |
| dc.subject (關鍵詞) | AI | en_US |
| dc.subject (關鍵詞) | AutoML | en_US |
| dc.subject (關鍵詞) | MLOps | en_US |
| dc.subject (關鍵詞) | DeepFlow | en_US |
| dc.subject (關鍵詞) | InventAI | en_US |
| dc.title (題名) | DEEP FLOW AI與自動化機器學習平台 | zh_TW |
| dc.title (題名) | DEEP FLOW AI/ML PLATFORM | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | Hive Capital "Taiwan AI Industry Trend Report 2022" Hive Capital released "Taiwan AI Industry Trend Report 2022": AI applications are more mature, and two AI services have become the most popular https://meet.bnext.com.tw/articles/view/48919? IDC predicts that AI spending in the Asia-Pacific region will reach US$32 billion in 2025, and the Taiwan market continues to grow https://iknow.stpi.narl.org.tw/Post/Read.aspx?PostID=19040 Taipei, April 8, 2022 - According to IDC`s latest "Worldwide Artificial Intelligence Spending Guide" research, the Asia-Pacific region (excluding Japan) will increase its spending on AI systems from US$17.6 billion in 2022 to approximately US$3.2 billion in 2025. (It is estimated that the revenue growth rate from 2022 to 2025 will be 1.81 times, and this research uses a conservative value of 1.5 times to estimate)https://iknow.stpi.narl.org.tw/Post/Read.aspx?PostID=19040 Global artificial intelligence software market size ( Resource from IDC；ITRI Industrial Economics and Knowledge Center) Hype cycle for artificial intelligence, 2022 https://www.linkedin.com/pulse/whats-new-artificial-intelligence-from-gartner-hype-cycle-abdoullaev/ Enterprise ai maturity level2022 ( Resource from Hive Capital "Taiwan AI Industry Trend Report 2022") AI Application Trends 2022 ( Resource from Hive Capital "Taiwan AI Industry Trend Report 2022") 2020 大中華區人工智慧成熟度調查https://assets.ey.com/content/dam/ey-sites/ey-com/zh_tw/news/2020/9/ey-ms-ai-report-2020.pdf 2020-21_CIO大調查https://www.cio.com.tw/2020-21-cio-survey-report-pdf-download/ https://www.inventai.com.tw/ https://www.appier.com/en/ https://mobagel.com/ https://www.profetai.com/ https://www.infuseai.io/ | zh_TW |
