Aja Huang

Nowadays, Aja Huang has become a topic of general interest that has captured the attention of a wide public. The relevance of Aja Huang has generated a debate that ranges from political and social spheres to everyday conversations. For decades, Aja Huang has been the subject of study and research in different fields of knowledge, which has given rise to vast accumulated knowledge about its importance and impact on modern society. In this article, we will explore the various facets of Aja Huang and its influence on our daily lives, analyzing its evolution over time and its future implications.

"Huang Shih-chieh" redirects here. For the Taiwanese politician, see Huang Hsin-chieh.

Aja Huang (Chinese: 黃士傑; pinyin: Huáng Shìjié; Wade–Giles: Huang Shih-chieh; born 1978) is a Taiwanese computer scientist and expert on artificial intelligence. He works for DeepMind and was a member of the AlphaGo project.

Born in 1978,[1] Huang received a bachelor's degree from National Chiao Tung University in 2001, a master's degree from National Taiwan Normal University in 2003, and a Ph.D degree from National Taiwan Normal University in 2011.[2] One of his doctoral supervisors was Rémi Coulom.[3][4] He began to develop computer Go program Erica in 2004,[citation needed] which became the champion in the 2010 Computer Olympiad.[2]

Huang joined DeepMind in 2012 and became a member of AlphaGo project in 2014.[2][3] He is one of the first authors of DeepMind's paper on AlphaGo Fan in 2016[5] and a major author of the paper on AlphaGo Zero in 2017.[6] During the 2016 match AlphaGo v. Lee Sedol and the 2017 Future of Go Summit, Huang placed stones on the Go board for AlphaGo.[1][7]

References

  1. ^ a b "AlphaGo設計師黃士傑：「最強的學習技能在人類的腦袋裡」" (in Chinese). Financial Times. 14 November 2017. Retrieved 7 December 2017.
  2. ^ a b c "黄士杰博士 远不止AlphaGo的人肉臂" (in Chinese). Sina.com.cn. 1 June 2017. Retrieved 7 December 2017.
  3. ^ a b "独家专访"AlphaGo之手"黄士杰：机器是没有感情的，而我会微笑" (in Chinese). Ifeng.com. 7 June 2017. Retrieved 7 December 2017.
  4. ^ "AlphaGo的核心作者黄士杰：穿过狗的棋局的他的手" (in Chinese). Ifeng.com. 14 March 2016. Retrieved 7 December 2017.
  5. ^ Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.Closed access icon
  6. ^ Silver, David; Schrittwieser, Julian; Simonyan, Karen; Antonoglou, Ioannis; Huang, Aja; Guez, Arthur; Hubert, Thomas; Baker, Lucas; Lai, Matthew; Bolton, Adrian; Chen, Yutian; Lillicrap, Timothy; Fan, Hui; Sifre, Laurent; Driessche, George van den; Graepel, Thore; Hassabis, Demis (19 October 2017). "Mastering the game of Go without human knowledge" (PDF). Nature. 550 (7676): 354–359. Bibcode:2017Natur.550..354S. doi:10.1038/nature24270. ISSN 0028-0836. PMID 29052630. S2CID 205261034.Closed access icon
  7. ^ "How Google's AI Viewed the Move No Human Could Understand". Wired.com. 14 March 2016. Retrieved 7 December 2017.