The document discusses several things that need to be done to prepare for AI technology: 1. The government and opposition must work together concretely, without just focusing on politics. They should set clear national goals, such as becoming a global AI leader within 5 years. 2. Strengthen the foundation of mathematics, computer science, and AI concepts in secondary school curriculum. 3. Increase graduate students (with scholarships for international students) focusing on basic research and new ideas at the forefront of the world. 4. Connect companies and universities to apply new concepts. Enact laws to regulate abusive uses of AI while educating the public to prepare for this technology.

1. เทคโนโลยีที่จํากีดความสามารถของ AI
ชิดชนก เหลือสินทรัพย์
ภาควิชาคณิตศาสตร์และวิทยาการคอมพิวเตอร์
จุฬาลงกรณ์มหาวิทยาลัย
สํานักวิทยาศาสตร์ ราชบัณฑิตสภา

2. AI ความฉลาดที่ทําขึ้นโดยวิธีการคํานวณและ algorithms เพื่อให้คอมพิวเตอร์ดูฉลาด
www.tutorialspoint.com
blog.computedby.com
vintageteardown.com
Intel 8080
Apple A6
CMOS NOR

3. github.comLewisMatosMiniMaxTicTacToe
ยิ่งมองล่วงหน้าหลายตา ก็ยิ่งมี
โอกาสชนะสูง ขนาดของ memory
ความเร็วของการค้นหา
AI 1

4. Fixed features, fixed data during tree construction
No plasticity
Dzone.com
Rule‐based intelligence
AI 1

5. If student is true then
if income is high then …
Else
if income is high then …
if income is medium then …
Use logical condition; separating line orthogonal to feature space
AI 1

6. www.youtube.com
thai.bestpriceupdate.com
www.jnto.or.th
Which one is a real image ?

7. AI 1
Searching and logic‐based intelligence are not efficient enough to solve
complex problems
Need new concepts and technology
Why (How) can we distinguish real images from drawn images?
Can we formulate mathematical models to imitate this capability?
We must understand how the brain works.
But it is not easy to do so.
First obstacle

8. www.youtube.com
AI 2

9. representing a line or a plane or
a hyperplane
male face group
female face group
a boy face or a girl face
www.fg2015.orgblog.webkid.io
AI 2

10. Elliptic function
male face group
female face group
hyperplane
AI 2

11. AI 2
What are the best features to represent each face?

12. www.michaelchimenti.com
AI 2
Deep learning

13. Need many neurons – high computational cost – require more power consumption
Slow learning time – require high performance computer
AI 2

14. Interestingengineering.com
Small intelligent sensor
Size and battery power are critical factors

15. www.slideshare.net/kleinerperkins/internet‐trends‐2017‐report

16. Forbes.com

17. Karlrupp.com

18. Karlrupp.com

19. There’s a Big Obstacle to the Pentagon’s
New Strategy to Speed AI to Troops
Defense officials want to accelerate the delivery of
artificial-intelligence tools from the lab to the field. But it's
hard to obtain the massive data streams that make AI
work.
Technology Editor,
Defense One
FEBRUARY 14, 2019

20. The problem is that when you start looking at just
how much data is required for A.I. to achieve
human‐level intelligence, you soon start to realize
that our current and near‐term data storage
alternatives will simply not work, pushing A.I. out
by decades. For example, to fully encode the 40
trillion cells in a human body would require 60
zetabytes of digital storage. Which means that even
at one penny per petabyte, it would cost
somewhere on the order of $5 trillion to create a
digital twin for every human on the planet. That's
about 25 percent of U.S. GDP.

21. An even better example, and one closer to home, is that of
autonomous vehicles (AVs).
For example, if an AV generates 20 terabytes of data a day (which is an
incredibly conservative estimate), the storage requirements would
amount to 7.3 petabytes yearly. At the current costs of cloud data
storage, that would amount to approximately $3 million annually. That's
60 times the cost of the automobile!

22. www.slideshare.net/kleinerperkins/internet‐trends‐2017‐report

23. Technological obstacles:
How to learn streaming data online ?
How to make a neural network achieve minimum number of neurons
and have high plasticity during learning?
How to make AI algorithms executable by the limitation of battery power?

24. Solutions
Discard‐after‐learn concept
Use mathematical shapes to capture streaming data
Use recursive functions to reduce computational c omplexity

27. AI trust in the enterprise
While CEOs are eager to implement AI, employees are less
enthusiastic, the report found. Top barriers to AI adoption in
the enterprise include the following:
Lack of AI talent (46%)
Regulatory/security risk (40%) Managing AI and ML in the
enterprise (free PDF) on TechRepublic.
Inefficient infrastructure support (37%)
Insufficient quality/quantity of data (36%)
Employee trust (33%)
Consumer trust (32%)
Lack of support from senior leadership (26%)
Human factors
Managing AI and ML in the enterprise (free PDF) on TechRepublic.

28. Emerging economies lead in AI adoption
According to the study,
Indonesia ranks first in terms of AI implementation (65%),
followed by China (63%) and India (62%).
These three topped more developed economies such as
South Korea (57%),
Singapore (50%),
Japan (47%) and
Taiwan (44%).
www.appier.com

29. AUTONOMOUS KILLING MACHINES?
In contrast, suggestions to limit some very specific applications of AI seem to merit
much closer examination and action. A major case in point is the development of
autonomous weapons that employ AI to decide when to fire, with how much force
to apply, and on what targets.
Suggestions to limit some very specific applications of AI seem to merit much
closer examination and action. A major case in point is the development of
autonomous weapons.
A group of robotics and AI researchers, joined by public intellectuals and
activists, signed an open letter that was presented at the 2015 International
Conference on Artificial Intelligence, calling for the United Nations to ban the
further development of weaponized AI that could operate “beyond meaningful
human control.”

30. JOB COLLAPSE?
Oddly, the area in which AI is already having a significant impact and is
expected to have major, worldwide, transformative effects is more often
discussed by economists rather than by AI mavens.
From 2000 to 2010, 1.1 million secretarial jobs disappeared, as did 500,000 jobs for
accounting and auditing clerks. Other job types, such as travel agents and data entry
workers, have also seen steep declines due to technological advances
Amitai Etzioni is University Professor and professor of
international affairs at George Washington University in
Washington, DC. Oren Etzioni is chief executive officer of the
Allen Institute for Artificial Institute and professor of computer
science at the University of Washington.

31. Prof Stephen Hawking, one of Britain's pre‐
eminent scientists, has said that efforts to
create thinking machines pose a threat to our
very existence.
He told the BBC:"The development of full
artificial intelligence could spell the end of the
human race."
กลัวมากไป

32. สิ่งที่ต้องทําเพื่อเตรียมตัวกับเทคโนโลยี AI
รัฐบาล ฝ่ายค้าน ต้องร่วมกันทําให้เป็นรูปธรรม
อย่ามัวแต่เน้นการเมือง ด่ากันในสภา แย่งอํานาจกัน
1. ตั้งเป้าหมายของประเทศให้ชัดเจนว่าจะเป็น ผู้นําเทคโนโลยี AI ของโลกให้ได้ภาย 5 ปีนี้
2. ปูพื้นคณิตศาสตร์ วิทยาการคอมพิวเตอร์ แนวคิด AI ให้นักเรียนตั้งแต่ ชั้นมัธยม
3. เพิ่มนักศึกษาโท เอก (ให้ทุนนักเรียนต่างชาติ) เน้นงานวิจัยพื้นฐานที่เป็นความรู้ใหม่ แนวคิดใหม่ของโลก
4. โยงบริษัทกับมหาวิทยาลัยเพื่อนําแนวคิดใหม่ไปประยุกต์
5. ออกกฎหมายควบคุมการใช้เทคโนโลยี AI ที่เอาไปใช้ในการทําชั่ว
6. ให้การศึกษาเทคโนโลยี AI แบบง่ายต่อประชาชนทุกระดับ เพื่อเตรียมตัวรับพายุของเทคโนโลยีนี้