The slides are mainly proving the viability of using AI in different domains, evidenced by Tsai-Min's probing in AI-related competitions from 8 different domains within 2018.
The slides are mainly proving the viability of using AI in different domains, evidenced by Tsai-Min's probing in AI-related competitions from 8 different domains within 2018.
22. 陳昇瑋 / 從大數據走向人工智慧
持續的團隊支援
22
A common data platform and workflow is
crucial for enterprise success.
Data Engineer ML Engineer Biz Analyst DevOps DevOps +
ML Engineer
App
Developer
(Credit: IBM Systems Lab Services)
(all under the supervision of Data Scientist)
31. What we can and cannot today
What we can have
Safer car, autonomous car
Better medical image analysis
Personalized medicine
Adequate language translation
Useful but stupid chatbots
Information search, retrieval, filtering
Numerous applications in energy,
finance, manufacturing, commerce,
law, …
What we cannot have (yet)
Machine with common sense
Intelligent personal assistants
“Smart” chatbots
Household robots
Agile and dexterous robots
Artificial General Intelligence (AGI)
31
32. 陳昇瑋 / 人工智慧民主化在台灣
Strong AI Weak AI
Can think
Own conscious
Act as it can think
Consciousless
(1980)
43. 陳昇瑋 / 人工智慧民主化在台灣
AI outperformed 20 corporate lawyers at legal work
43
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/
44. 陳昇瑋 / 人工智慧民主化在台灣 44
(Source: Future of Jobs Report 2018, World Economic Forum)