Takumi Abe

Takumi Abe (阿部 巧, born May 26, 1991) is a Japanese football player for Thespakusatsu Gunma.

Takumi Abe
阿部 巧
Personal information
Full name Takumi Abe
Date of birth (1991-05-26) May 26, 1991
Place of birth Ōta, Tokyo, Japan
Height 1.66 m (5 ft 5 12 in)
Playing position(s) Defender
Club information
Current team
Thespakusatsu Gunma
Number 5
Youth career
2004–2009 FC Tokyo Youth
Senior career*
Years Team Apps (Gls)
2010–2013  FC Tokyo 8 (0)
2010Yokohama FC (loan) 16 (1)
2012Yokohama FC (loan) 39 (1)
2013 Matsumoto Yamaga 9 (0)
2014–2016 Avispa Fukuoka   57 (1)
2017– Thespakusatsu Gunma 35 (0)
* Senior club appearances and goals counted for the domestic league only and correct as of 23 February 2018

Club statistics

Updated to 23 February 2018.[1][2][3]

Club performance League Cup League Cup Total
Season Club League AppsGoals AppsGoals AppsGoals AppsGoals
Japan League Emperor's Cup J. League Cup Total
2010FC TokyoJ1 League00000000
Yokohama FCJ2 League16110-171
2011FC Tokyo8000-80
2012Yokohama FC39100-401
2013Matsumoto Yamaga9020-110
2014Avispa Fukuoka34010-350
201521120-231
2016J1 League10203060
2017Thespakusatsu GunmaJ2 League35010-360
Total 163390301753
gollark: > There is burgeoning interest in designing AI-basedsystems to assist humans in designing computing systems,including tools that automatically generate computer code.The most notable of these comes in the form of the first self-described ‘AI pair programmer’, GitHub Copilot, a languagemodel trained over open-source GitHub code. However, codeoften contains bugs—and so, given the vast quantity of unvettedcode that Copilot has processed, it is certain that the languagemodel will have learned from exploitable, buggy code. Thisraises concerns on the security of Copilot’s code contributions.In this work, we systematically investigate the prevalence andconditions that can cause GitHub Copilot to recommend insecurecode. To perform this analysis we prompt Copilot to generatecode in scenarios relevant to high-risk CWEs (e.g. those fromMITRE’s “Top 25” list). We explore Copilot’s performance onthree distinct code generation axes—examining how it performsgiven diversity of weaknesses, diversity of prompts, and diversityof domains. In total, we produce 89 different scenarios forCopilot to complete, producing 1,692 programs. Of these, wefound approximately 40 % to be vulnerable.Index Terms—Cybersecurity, AI, code generation, CWE
gollark: https://arxiv.org/pdf/2108.09293.pdf
gollark: This is probably below basically everywhere's minimum wage.
gollark: (in general)
gollark: <@!319753218592866315> Your thoughts?

References

  1. Nippon Sports Kikaku Publishing inc./日本スポーツ企画出版社, "J1&J2&J3選手名鑑ハンディ版 2018 (NSK MOOK)", 7 February 2018, Japan, ISBN 978-4905411529 (p. 247 out of 289)
  2. Nippon Sports Kikaku Publishing inc./日本スポーツ企画出版社, "2017 J1&J2&J3選手名鑑 (NSK MOOK)", 8 February 2017, Japan, ISBN 978-4905411420 (p. 220 out of 289)
  3. Nippon Sports Kikaku Publishing inc./日本スポーツ企画出版社, "2016J1&J2&J3選手名鑑", 10 February 2016, Japan, ISBN 978-4905411338 (p. 146 out of 289)


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