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인공지능 역사와

딥러닝 기술 소개2016. 8. 11

김 의 중

아이덴티파이

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Reinforcement Learning (RL)

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Alan Turing (1912 ~ 1954)

• 1936: Turing Machine

• 1941: Bombe (German Enigma Breaker)

• 1950: Turing Test

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Turing Machine (1936)

"On computable numbers, with an application to the Entscheidungsproblem“

Proceedings of the London Mathematical Society (1936)

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Z3 computer (1941)

First German

Programmable computer

that satisfied Turing

completeness

Konrad Zuse (1910 ~ 1995)

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Colossus Computer (1943)

Tommy Flowers, British

Engineer designed

Colossus with a collegue,

Max Newman to improve

Bombe that Turing

designed.

Tommy Flowers Max Newman

Colossus Mark2

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ENIAC (1945)

ENIAC (Electronic Numerical Integratorn And Computer)

developed by John Mauchly and J. Presper Eckert

at the University of Pennsylvania

with John von Neumann

Number of vacuum tubes : 17,480

ENIAC (1945)

John Mauchly J. Presper Eckert

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John von Neumann (1903 ~ 1957)

Computer by Institute for Advanced Study (1951)Report on EDVAC project (1945)

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IBM• Aiken Mark 1: Electromechanical computer (1944)

• IBM 603: First commercial computer (1946)

• IBM 701: First commercial scientific computer (1952)

• IBM 650: First mass-produced computer (1953)

• IBM 7000 series: First transistorized computer (1961)

• IBM System/360: IC-based Mainframe (1965)

• IBM PC: First personal computer (1981)

• IBM RS/6000: PowerPC-based HPC (1990)

• IBM BlueGene: Fastest computer (2004)

• IBM BlueGene/Q: Massively Parallel Computer (2013)

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Artificial IntelligenceDartmouth Conference (1946)

John McCarthy Marvin Minsky

Claude Shannon Nathaniel Rochester

Arthur Samuel

Ray SolomonoffOliver Selfridge

Hernert Simon Allen Newell

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Key members in AI inner circle

John McCarthy

Marvin Minsky

Nathaniel Rochester

Arthur Samuel

Hernert Simon

Allen Newell

LISP language, MIT AI LabMachine Learning, checker program on IBM 701

SNARC, MIT AI Lab

Designed IBM 701

Logic Theorist

General Problem Solver

Computational Cognitive

Psychology

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What is Artificial Intelligence?

Stuart Russel & Peter Norvig

“Artificial Intelligence: A Modern Approach”

1994 2003 2009

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AI Tree

Michael Mills, co-founder and chief strategy officer, Neota Logic

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Artificial Neural Network

대뇌피질

뉴런

시냅스

수상돌기

신경세포체

축색돌기

축색종말

Threshold Logic Unit (1943)

Warren McCullock Walter Pitts

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TLU

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Perceptron (1958)

Frank Rosenblatt’s Perceptron = TLU + Hebb’s Rule

weight factor

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SLP vs MLPx1

x2

yΣ |

x1

x2

y

Σ|θ=1

Σ|θ=1

Σ|θ=1

AND

OR

(1) (2) (3)

vs

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Deep Learning

Neuron = 1010

Synapse = 1014 (at birth) ~ 1013 (as growth)

Human Brain

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Feedforward Neural Network

. . .

. . .

. . .

. . .

. . .

입력층 출력층

은닉층

As being fed forward from input layer to output layer,

data become more unique value by weight factors

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Back Propagation

강아지 n

강아지 4

강아지 3

강아지 2

강아지 1

고양이?(예측값)

강아지(레이블)

피드포워드 (가중치 적용)

역전파 (가중치 수정)

비교

Paul Werbos (PhD thesis, Harvard University, 1974)

“Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences”

Adjustment process of weight factors by propagating error

from output layer to input layer as backward

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Gradient Descent

★

★

Min.

2D 3D

Find optimal weight factors minimizing quadratic objective function

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Convolution Neural Network

원본 이미지 컨볼루션 풀링 컨볼루션 풀링전체 연결된

신경망

강아지 (90%)

고양이 (30%)

인형 (10%)

비둘기 (0.5%)

컨볼루션 필터

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Regularization

★

★

L2 규제화 L1 규제화

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Use cases

image text

sound 𝑓(𝑡)

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Deep Learning Leaders

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Thank You

감사합니다