台灣人工智慧學校中部智慧醫療專班開學執行長談話 日期: 2019/09/22 09:00 - 12:30 (日) 地點: 彰基福懋大樓：B1 國際會議廳（500彰化縣彰化市建寶街20號） Google Map) 主辦單位: 台灣人工智慧學校 協辦單位: 台中榮總、中國醫藥大學附設醫院、彰化基督教醫院

1. :
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3. 3(Slide Credit: McKinsey&Company)

4. 4
https://youtu.be/_5cU_JcJRPg

5. Healthy Diseased
Hemorrhages
No DR Mild DR Moderate DR Severe DR Proliferative DR
1 2 3 4 5

6. arxiv.org/abs/1703.02442
Tumor localization score (FROC):
model: 0.89
pathologist: 0.73
(Slide Credit: Google Brain)

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https://www.youtube.com/watch?v=ljBOzdKuX7A

8. /
AI outperformed 20 corporate lawyers at legal work
8
Challenge: review risks contained in five non-disclosure agreements (NDAs).
AI vs. associates and in-house lawyers from global firms such as Goldman Sachs, Cisco and Alston &
Bird, as well as general counsel and sole practitioners.
AI matched the top-performing lawyer for accuracy – both achieved 94%. Collectively, the lawyers
managed an average of 85%, with the worst performer recording 67%.
AI: 26 seconds; lawyers’ average: 92 minutes, where the speediest lawyer took 51 minutes
https://www.weforum.org/agenda/2018/11/this-ai-outperformed-20-corporate-lawyers-at-
legal-work/

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Mobile computing, inexpensive sensors collecting terabytes of data, and the rise
of machine learning that can use that data will fundamentally change the way
the global economy is organized.
- Fortune,“CEOs:The Revolution is Coming,” March 2016

11. 2017.03

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• SRB
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• (e-Taiwan)
• (M-Taiwan)
•
• WiMAX
H.T. Kung
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13. 2000: Mobile Device1980: PC 1990: Internet 2015:AI + IoT
Taiwan’s next opportunity?

15. March – November in 2017
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18. AI
01
02
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04

19. Project θ Weekly Meetings at NCTU
and Also Online with Academia Sinica
June 6, 2017

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21. #1
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22. LCD Panel Defects
22(Slide Credit: IBM)

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Typical PCB defects

24. Typical defects after
SMT (Surface-Mount Technology) process
…
24
https://www.researchmfg.com/2011/02/soldering-defect-symptom/

25. More SMT/DIP Defect Examples
25

26. Convolution Neural Networks +Transfer Learning
Pre-trained using 14-million image dataset
ResNet with > 8-million parameters
Input
images
Model training /
inference
OK
OK

27. –
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4 ; 5%
AOI : , 60 /
( 2 / =
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: 30 / = 120 /
: + NVIDIA GPU: 10 ~ 15
: +
: 0.01% 5%
: 166.67 / sec ➔ 1440

28. –
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12.9%
8~10 3,000,000
+ NVIDIA GPU: 10 ~ 15
+
1%
10%
8,640,000 / = 100 /

29. #2
29

30. : 61%QualityIndex

31. 31
: 61%
: 98%
QualityIndex

32. Especially important for equipment with high failure cost (such as motors in machine tools)
Also important for expensive consumables (such as blades used in precision cutting machines)
32
#3

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#4

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Pigment 1 Pigment 2 Pigment 3: 70% to 95%

37. PROJECT Θ TEAM HAS SOLVED
10+ PROBLEMS
FROM 10+ COMPANIES
37

38. LOOKS IT WORKS OUT, BUT …
38

39. 2017/06/26 Project θ Meeting
39

40. 1,000x

41. 01
02
03
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AI

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43. / 43http://bangqu.com/g394k4.html

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http://aiacademy.tw/opening-video-180127/

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48. http://aiacademy.tw/
/
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AI
+

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50. 2018/01/27
2018/04/12
2018/05/12
2018/07/21
2018/08/18
2018/09/02
2018/09/29
2018/11/10
2018/12/08
2018/12/15
2019/01/05
2019/01/26
2019/02/23
2019/03/16
2019/04/20
2019/05/04
2019/05/18
2019/06/01
2019/06/28
2019/07/13

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65. 4,900

66. GPU x 500+

67. (30+)

68. PIXNET
68

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75. 75

76. The First Few Weeks…
76

77. 77

78. 78

80. PCB
3D
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84. 84

85. 85

86. AI “ ”
86

87. 87

88. AI河川天眼通LINE Bot

89. 89

90. AI + AI
AI