According to the cover story of New Yorker, “in the future, human beings are only helpers to robots”. It seems that the reality that concerns people the most is approaching in an accelerated pace. But what triggers this conclusion?
A report swept all kinds of medias across the world in May 2017, announcing AlphaGo, an AI program, beat Ke Jie, the world champion boasting the top ranking, by 3:0 at China Go Summit, which startled everyone. However, after 5 years, the rise of AlphaGo Zeo took the world by surprise.
The most powerful version in AlphaGo’s evolution, AlphaGo Zero easily defeated AlphaGo by 100:0 after only three days of self-study, without any priori knowledge of human beings. Mr. Jie KE, Chinese Go Master, stated at Weibo that “Being clean, pure and self-learning, AlphaGo is the strongest. Compared to its spontaneous advancement, human beings are redundant”.
”AlphaGo Zero beat the original AlphaGo by engaging in-depth self-learning and keeping on breaking through limits. Can we use such reinforcement learning to seek for development and leadership?
AlphaGo Zero自身深度学习、不断突破极限的精神才是其打败了原版AlphaGo的必杀技能，我们是否借鉴这种强化学习法（reinforcement learning）来寻求进步和保持领先的地位呢？”
Now, SAIF offers the opportunity to start our show. Forget about AlphaGo and ask yourself, “Are you ready to go?”
Organized by Shanghai Jiao Tong University Shanghai Advanced Institute of Finance Master of Finance Program, the International Young Leaders Financial Summit is the first platform designed for academic and practical exchange and interaction in topics related to finance among undergraduates. It seeks to develop the skills of leadership, communicate and organization of the participants, and offers an opportunity to communicate with industry and academic leaders face to face, present your capabilities in a variety of medias, and improve your understanding on academic theories and practices. This year, it will dedicate to two highly anticipated areas of Robo-advisor and Big Data Mining, looking for self-improvement and challenges.
We look forward to your participation and going beyond human limits in reinforcement learning!
By the way, don’t forget that winners will receive remarkable cash prizes. All teams participating in 2018 IYLFS will receive competition prizes.
Time for application: Nov. 13th to Nov. 30th, 2017 (GMT +8)
*Please submit a complete online application before deadline.请申请者在报名截止日前提交完整表单。
Who can apply: current undergraduate students.
Where to apply: Please click "read more" or scan the code below.
We welcome undergraduate students from around to world to participate in this competition, and we are sincerely looking forward to seeing you in Shanghai.