This document discusses the work of Project θ, an AI team in Taiwan. It summarizes their work over 2017-2019 solving over 10 problems for 10+ companies. Some of the problems they addressed included detecting defects in LCD panels, PCB boards, and after surface mount technology processes. They also worked on applications like predicting the quality percentage of a pigment based on its ingredients. The team grew over time and had success scaling their work through the use of transfer learning and GPU acceleration. They have continued their efforts to apply AI to address real-world problems through their non-profit AI Academy Taiwan.

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3. 3(Slide Credit: McKinsey&Company)

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https://youtu.be/_5cU_JcJRPg

5. Healthy Diseased
Hemorrhages
No DR Mild DR Moderate DR Severe DR Proliferative DR
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6. arxiv.org/abs/1703.02442
Tumor localization score (FROC):
model: 0.89
pathologist: 0.73
(Slide Credit: Google Brain)

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AI outperformed 20 corporate lawyers at legal work
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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

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• SRB
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• (M-Taiwan)
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• WiMAX
H.T. Kung
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12. 2000: Mobile Device1980: PC 1990: Internet 2015:AI + IoT
Taiwan’s next opportunity?

14. March – November in 2017
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18. AI
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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
…
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https://www.researchmfg.com/2011/02/soldering-defect-symptom/

25. More SMT/DIP Defect Examples
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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

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4 ; 5%
AOI : , 60 /
( 2 / =
1104 / )
: 30 / = 120 /
: + NVIDIA GPU: 10 ~ 15
: +
: 0.01% 5%
: 166.67 / sec ➔ 1440

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

29. #2
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30. : 61%QualityIndex

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: 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)
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#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
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38. LOOKS IT WORKS OUT, BUT …
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39. 2017/06/26 Project θ Meeting
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40. 1,000x

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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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(1000 , )
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(900 , )
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( , )

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&
239 15-17F

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( , )

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( )

65. 4,900

66. GPU x 500+

67. (30+)

68. PIXNET
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76. The First Few Weeks…
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80. PCB
3D
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82. & A

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86. AI “ ”
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88. AI河川天眼通LINE Bot

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2018/11/17

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92. AI + AI
AI