신문이나 뉴스를 보다보면 본 적이 없다고 할 수 없는 게 인공지능이란 단어가 아닌가 싶습니다. 인공지능이 이렇게 대두되기 까지는 기계학습, 얕은학습, 깊은학습 등이 혼재 되어 그 성장을 이끌었다고 할 수 있습니다. 이번 발표에서는 그러한 개념들에 대한 특징과 연결고리, 구분되는 차이점에 대해 이해하고, 그간의 발전해 온 애플리케이션들을 살펴봅니다. 특히, 기계학습에서 다섯 종족(Tribes)이라 불리는 기호주의자(Symbolists), 연결주의자(Connectionists), 진화주의자(Evolutionaries), 베이즈 주의자(Bayesians), 유추주의자(Analogizers)의 철학과 성격을 살펴보고, 각 종족이 갖는 영향력을 논의합니다. 또한 인공지능을 4단계로 구분하여, 기계를 학습시키는 연구들이 어떻게 인공지능에 받아들여 졌는지 지능과 관련지어 논의해 보겠습니다. 이후 시간이 허락한다면 앞으로의 인공지능의 발전 방향과 예측되는 불확실한 미래에 대해 논의할 예정입니다.

1. 2019.05.30.
kyunghoon@core.today
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—

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20. —
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40. 40
Bowl 1 Bowl 2

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Bowl 1 Bowl 2

42. 42
Bowl 1 Bowl 2

43. 43
Bowl 1 Bowl 2
Bowl 1? or Bowl 2?

44. 44
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70. 70
1997 ~
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