2016年1月27日 星期三

Marvin Minsky (1927–2016), artificial intelligence,The Society of Mind /The Emotion Machine: ( )




Marvin Minsky, who combined a scientist's thirst for knowledge with a philosopher's quest for ...
Farewell, Marvin Minsky (1927–2016)
Stephen Wolfram Blog - 6 hours ago
人工智慧先驅離世,7件事看馬文·閔斯基對科技發展的貢獻
撰文者:愛范兒 發表日期:2016/01/27
美國當地時間 2016 年 1 月 24 日,人工智慧先驅Marvin Minsky(馬文·閔斯基)因腦溢血與世長辭,享年 88 歲。Marvin Minsky 一生有諸多成就,以下 7 個僅作為引子,希望讓更多人有興趣深入瞭解這位人工智慧研究的奠基人。

第一個神經元網路模擬器

1951 年,Marvin Minsky 提出了關於「思維如何萌發並形成」的一些基本理論,並建造了世界上第一個神經元網路模擬器——Snarc(Stochastic Neural Analog Reinforcement Calculator),它能夠在其 40 個「代理」 (Agent)和一個獎勵系統的幫助下穿越迷宮。
neuron-SNARC-GJLoan2011-x640
在 Snarc 的基礎上,Minsky 還通過綜合利用自己多學科的知識,使機器具備了基於過去行為預測當前行為的能力。
基於 agent 的計算和分散式智慧是當前人工智慧研究中的一個熱點,Snarc 雖然還比較粗糙和不夠靈活,但是人工智慧研究中最早的嘗試之一。

創立 MIT 人工智慧計畫

1956 年,Marvin Minsky 和 John McCarthy 一起發起了被視為人工智慧起點的「達特茅斯會議」,兩人也聯合提出了「人工智慧」的概念。
1959 年,兩者又一同創立了 MIT(麻省理工)人工智慧計畫,這個計畫後來演變成了世界上第一座專攻人工智慧的實驗室——MIT AI 實驗室有意思的是,除了進行人工智慧研究,MIT AI 實驗室也幫助塑造一種電腦和軟體設計的文化,對於現代計算產業(computing industry)有著深遠影響。它為「電子資訊應該免費獲得」這一理念埋下了種子,這一理念後來協助推展了開源軟體運動。

圖靈獎獲得者

1969 年,年僅 42 歲的 Marvin Minsky 獲得了電腦科學領域的最高獎項——圖靈獎,他是第一位獲此殊榮的人工智慧學者。圖靈獎是國際電腦協會(ACM)於 1966 年設立的,又叫 A.M. 圖靈獎,其名稱取自電腦科學的先驅、英國科學家阿蘭 · 圖靈。圖靈一般每年只獎勵一名電腦科學家,有「電腦界的諾貝爾獎」之稱。

出版《The Society of Mind》

1985 年,Marvin Minsky 出版了一本開創性的著作《The Society of Mind》。這部著作提出了「智慧不是任何單獨的機制的產物」這一觀點——Intelligence is not the product of any singular mechanism but comes from the managed interaction of a diverse variety of resourceful agents。
som_book
Marvin Minsky 認為,人類實際上就是某種機器,人類的大腦是由許多半自主但不智慧的「代理(agent)」所構成的。他有一句話廣為流傳:「大腦無非是肉做的機器而已(the brain happens to be a meat machine)。」

《2001太空漫遊》的顧問

史丹利·庫柏力克執導《2001太空漫遊》時,專門去請教了 Marvin Minsky,電影裡面的人工智慧電腦 HAL 9000 應該是什麼樣子?
「原來他們有一個裝飾著彩色標籤的電腦。史丹利·庫柏力克問我,您覺得這個怎麼樣? 」在接受《科學發現》雜誌採訪時,Marvin Minsky 說道,「我認為這個電腦實際上應該只是由許多小黑盒子組成,因為電腦需要通過引線來傳遞資訊以知道它裡面在做什麼。」於是庫柏力克把原來的裝飾撤掉,設計了一個簡單的 HAL 9000 電腦。
Hal9000
另外值得一提的是,電影裡有這樣一個場景:HAL 9000 接受 BBC 的訪問,他認為自己「完全不會犯錯」,另一個受採訪的科學家表示 HAL 也會有真實情感。這部電影折射了當時人工智慧專家的一些預測:機器會很快擁有人類水準的智慧。同時,這部電影也引發了對人工智慧或許會變成一件壞事的擔憂。

虛擬實境早期提倡者

Marvin Minsky 也是虛擬實境(virtual reality)早期的宣導者。20 世紀 80 年代,Minsky 發表了一篇論文,提出了 Telepresence 遠端控制系統。
Marvin Minsky 設想,人們穿上一個佈滿感測器的、像肌肉一樣的裝置,肩膀、手部、手指的每一個動作都準確無誤地複製到另一個地方的移動機械手柄上。「它允許人體驗某種事件,而不需要真正介入這種事件」。
1688074
Minsky 認為,這種遠端作業系統能改變製造、能源和醫院等行業的生產方式。完整的論文點這裡
Exoskeleton_Robot_1950s

業界巨星的導師 Marvin Minsky

在 MIT 教出了不少電腦科學的超級巨星,如 Ray Kurzweil(雷·庫茨魏爾),Google 工程總監,同時是未來學家、奇點大學校長;Gerald Sussman,傑出的 AI 研究人員,也是 MIT 的電子工程的教授;Patrick Winston,在 Minsky 教授退休後接管了 AI 實驗室。
雷·庫茨魏爾如此 Marvin Minsky:「在人工智慧、認知心理學、數學、計算語言學、機器人和光學等諸多領域作出了巨大的貢獻,近年來,他一直致力於讓機器具備人類常識推理的能力。對於我來說,他是一位非常值得尊敬的導師。」
附:Marvin Minsky 在 TED 上的演講影片
本文授權轉載自:愛范兒
分享圖來自:Sethwoodworth分享於Wikipedia, cc by 3.0






Marvin Minsky

photo: wikipediaFULL SCREEN



Marvin Minsky honored for lifetime achievements in artificial intelligence

The MIT professor emeritus earns the BBVA Foundation Frontiers of Knowledge Award for his pioneering work and mentoring role in the field of artificial intelligence.


Ellen Hoffman, Media Lab
January 17, 2014


MIT Media Lab professor emeritus Marvin Minsky, 86, a pioneer in the field of artificial intelligence, has won the BBVA Foundation Frontiers of Knowledge Award in the information and communications technologies category.

The BBVA Foundation cited his influential role in defining the field of artificial intelligence, and in mentoring many of the leading minds in today’s artificial intelligence community. The award also recognizes his contributions to the fields of mathematics, cognitive science, robotics, and philosophy.

In learning of the award, which brings a prize of $540,000, Minsky reconfirmed his conviction that one day we will develop machines that will be as smart as humans. But he added “how long this takes will depend on how many people we have working on the right problems. Right now there is a shortage of both researchers and funding.”

Minsky joined the Department of Electrical Engineering and Computer Science faculty in 1958, and co-founded the Artificial Intelligence Laboratory (now the Computer Science and Artificial Intelligence Laboratory) the following year. In 1985, he became a founding member of the Media Lab, where he was named the Toshiba Professor of Media Arts and Sciences, and where he continues to teach and mentor.

Commenting on the award, Nicholas Negroponte, co-founder and chairman emeritus of the Media Lab, says, “Marvin’s genius is accompanied by extreme kindness and humor. He listens well, and is oracle-like in his capability to debug an enormously complex situation with a simple, short phrase. Through the 47 years we have known each other, he has taught me to tackle the big problems.”

Patrick Winston, the Ford Professor of Artificial Intelligence and Computer Science and former director of MIT’s Artificial Intelligence Lab, says, “One day, when I was wondering what I wanted to do, I went to one of Marvin's lectures, invited by a friend. At the end, I said to myself, I want to do what he does. And ever since, that is what I have done.”

Minsky views the brain as a machine whose functioning can be studied and replicated in a computer, which would teach us, in turn, to better understand the human brain and higher-level mental functions. He has been recognized for his work focusing on how we might endow machines with common sense — the knowledge humans acquire every day through experience. How, for example, do we teach a sophisticated computer that to drag an object on a string, you need to pull not push — a concept easily mastered by a two-year-old child.

Minsky’s book, “The Society of Mind” (1985) is considered the seminal work on exploring intellectual structure and function, and for understanding the diversity of the mechanisms interacting in intelligence and thought. Other achievements include building the first neural network simulator (SNARC), as well as mechanical hands and other robotic devices. Minsky is the inventor of the earliest confocal scanning microscope. He was also involved in the inventions of the first "turtle," or cursor, for the LOGO programming language (with Seymour Papert), and the "Muse" synthesizer for musical variations (with Ed Fredkin). His most recent book, “The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind,” was published in 2006.

Minsky has received numerous awards, among them the ACM Turing Award, the Japan Prize, the Royal Society of Medicine Rank Prize (for Optoelectronics) and the Optical Society (OSA) R.W. Wood Prize.

Minsky graduated from Harvard University in 1950, and received his PhD from Princeton University in 1954. He was appointed a Harvard University Junior Fellow from 1954 to 1957.

The BBVA Foundation was established by the BBVA Group, a global financial service group based in Spain. The Frontiers of Knowledge Awards, established in 2008, honor achievements in the arts, science, and technology. They focus on contributions of lasting impact for their originality, theoretical significance and ability to push back the frontiers of the known world.

*****
這本的確是經典.二十幾年前讀完它時還相信它是本好的散文.我比較有興趣的是它(AI大藍圖)出版至今對業界的影響
Marvin Minsky (馬文·閔斯基 -- 麻省理工學院人工智慧實驗室的創始人之一, 美國工程院和美國科學院院士, 美國人工智慧領域科學家) 的經點鉅著 The Society of Mind 上線

The Society of Mind

Marvin Minsky
[homepage]

prologue

1 Building blocks

1.1 The agents of the mind

1.2 The mind and the brain

1.3 The society of mind

1.4 The world of blocks

2 Wholes and parts

2.1 Components and connections

2.2 Novelists and reductionists

2.3 Parts and wholes

2.4 Holes and parts

2.5 easy things are hard

2.6 confusion

2.7 Are people machines?

3 conflict and compromise

3.1 conflict

3.2 Noncompromise

3.3 hierarchies

3.4 Heterarchies

3.5 destructiveness

3.6 Pain and pleasure simplified

4 the self

4.1 the self

4.2 one self or many?

4.3 the soul

4.4 the conservative self

4.5 exploitation

4.6 self-control

4.7 long-range plans

4.8 ideals

5 individuality

5.1 circular causality

5.2 unanswerable questions

5.3 the remote-control self

5.4 personal identity

5.5 fashion and style

5.6 traits

5.7 permanent identity

6 insight and introspection

6.1 consciousness

6.2 signals and signs

6.3 thought-experiments

6.4 B-Brains

6.5 Frozen reflection

6.6 momentary mental time

6.7 the causal now

6.8 thinking without thinking

6.9 heads in the clouds

6.10 worlds out of mind

6.11 in-sight

6.12 internal communication

6.13 self-knowledge is dangerous

7 problems and goals

7.1 intelligence

7.2 uncommon sense

7.3 the puzzle principle

7.4 problem solving

7.5 learning and memory

7.6 reinforcement and reward

7.7 local responsibility

7.8 difference-engines

7.9 intentions

7.10 genius

8 a theory of memory

8.1 k-lines: a theory of memory

8.2 re-membering

8.3 mental states and dispositions

8.4 partial mental states

8.5 level-bands

8.6 levels

8.7 fringes

8.8 societies of memories

8.9 knowledge-trees

8.10 levels and classifications

8.11 layers of societies

9 summaries

9.1 wanting and liking

9.2 gerrymandering

9.3 learning from failure

9.4 enjoying discomfort

10 papert's principle

10.1 piaget's experiments

10.2 reasoning about amounts

10.3 priorities

10.4 papert's principle

10.5 the society-of-more

10.6 about piaget's experiments

10.7 the concept of concept

10.8 education and development

10.9 learning a hierarchy

11 the shape of space

11.1 seeing red

11.2 the shape of space

11.3 nearnesses

11.4 innate geography

11.5 sensing similarities

11.6 the centered self

11.7 predestined learning

11.8 half-brains

11.9 dumbbell theories

12 learning meaning

12.1 a block-arch scenario

12.2 learning meaning

12.3 uniframes

12.4 structure and function

12.5 the function of structures

12.6 accumulation

12.7 accumulation strategies

12.8 problems of disunity

12.9 the exception principle

12.10 how towers work

12.11 how causes work

12.12 meaning and definition

12.13 bridge-definitions

13 seeing and believing

13.1 reformulation

13.2 boundaries

13.3 seeing and believing

13.4 children's drawing-frames

13.5 learning a script

13.6 the frontier effect

13.7 duplications

14 reformulation

14.1 using reformulation

14.2 means and ends

14.3 seeing squares

14.4 brainstorming

14.5 the investment principle

14.6 parts and holes

14.7 the power of negative thinking

14.8 the interaction-square

15 Consciousness and memory

15.1 momentary mental state

15.2 self-examination

15.3 memory

15.4 memories of memories

15.5 the immanence illusion

15.6 many kinds of memory

15.7 memory rearrangements

15.8 anatomy of memory

15.9 interruption and recovery

15.10 losing track

15.11 the recursion principle

16 emotion

16.1 emotion

16.2 mental growth

16.3 mental proto-specialists

16.4 cross-exclusion

16.5 avalanche effects

16.6 motivation

16.7 exploitation

16.8 stimulus vs. simulus

16.9 infant emotions

16.10 adult emotions

17 development

17.1 sequences of teaching-selves

17.2 attachment-learning

17.3 attachment simplifies

17.4 functional autonomy

17.5 developmental stages

17.6 prerequisites for growth

17.7 genetic timetables

17.8 attachment-images

17.9 different spans of memories

17.10 intellectual trauma

17.11 intellectual ideals

18 reasoning

18.1 must machines be logical?

18.2 chains of reasoning

18.3 chaining

18.4 logical chains

18.5 strong arguments

18.6 magnitude from multitude

18.7 what is a number?

18.8 mathematics made hard

18.9 robustness and recovery

19 Words and ideas

19.1 the roots of intention

19.2 the language-agency

19.3 words and ideas

19.4 objects and properties

19.5 polynemes

19.6 recognizers

19.7 weighing evidence

19.8 generalizing

19.9 recognizing thoughts

19.10 closing the ring

20 context and ambiguity

20.1 ambiguity

20.2 negotiating ambiguity

20.3 visual ambiguity

20.4 locking-in and weeding-out

20.5 micronemes

20.6 the nemeic spiral

20.7 connections

20.8 connection lines

20.9 distributed memory

21 trans-frames

21.1 the pronouns of the mind

21.2 pronomes

21.3 trans-frames

21.4 communication among agents

21.5 automatism

21.6 trans-frame pronomes

21.7 generalizing with pronomes

21.8 attention

22 expression

22.1 pronomes and polynemes

22.2 isonomes

22.3 de-specializing

22.4 learning and teaching

22.5 inference

22.6 expression

22.7 causes and clauses

22.8 interruptions

22.9 pronouns and references

22.10 verbal expression

22.11 creative expression

23 comparisons

23.1 a world of differences

23.2 differences and duplicates

23.3 time blinking

23.4 the meanings of more

23.5 foreign accents

24 frames

24.1 the speed of thought

24.2 frames of mind

24.3 How trans-frames work

24.4 default assumptions

24.5 nonverbal reasoning

24.6 direction-nemes

24.7 picture-frames

24.8 how picture-frames work

24.9 recognizers and memorizers

25 frame arrays

25.1 one frame at a time?

25.2 frame-arrays

25.3 the stationary world

25.4 the sense of continuity

25.5 expectations

25.6 the frame idea

26 language-frames

26.1 understanding words

26.2 understanding stories

26.3 sentence-frames

26.4 a party-frame

26.5 story-frames

26.6 sentence and nonsense

26.7 frames for nouns

26.8 frames for verbs

26.9 language and vision

26.10 learning language

26.11 grammar

26.12 coherent discourse

27 censors and jokes

27.1 demons

27.2 suppressors

27.3 censors

27.4 exceptions to logic

27.5 jokes

27.6 humor and censorship

27.7 laughter

27.8 good humor

28 the mind and the world

28.1 the myth of mental energy

28.2 magnitude and marketplace

28.3 quantity and quality

28.4 mind over matter

28.5 the mind and the world

28.6 minds and machines

28.7 individual identities

28.8 overlapping minds

29 the realms of thought

29.1 the realms of thought

29.2 several thoughts at once

29.3 paranomes

29.4 cross-realm correspondences

29.5 the problem of unity

29.6 autistic children

29.7 likenesses and analogies

29.8 metaphors

30 mental models

30.1 knowing

30.2 knowing and believing

30.3 mental models

30.4 world models

30.5 knowing ourselves

30.6 freedom of will

30.7 the myth of the third alternative

30.8 intelligence and resourcefulness

appendix

postscript

glossary


The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind [1] is a book by cognitive scientist Marvin Lee Minsky. The book is a sequel to Minsky's earlier book Society of Mind.
Minsky argues that emotions are different ways to think that our mind uses to increase our intelligence. He challenges the distinction between emotions and other kinds of thinking. His main argument is that emotions are "ways to think" for different "problem types" that exist in the world. The brain has rule-based mechanism (selectors) that turns on emotions to deal with various problems. The book reviews the accomplishments of AI, what and why it is complicated to accomplish in terms of modeling how human beings behave, how they think, how they experience struggles and pleasures.[2]

Reviews[edit]

In a book review for the Washington Postneurologist Richard Restak states that:[3]
Minsky does a marvelous job parsing other complicated mental activities into simpler elements. ... But he is less effective in relating these emotional functions to what's going on in the brain.

Outline[edit]

Minsky outlines the book as follows:[citation needed]
  1. "We are born with many mental resources."
  2. "We learn from interacting with others."
  3. "Emotions are different Ways to Think."
  4. "We learn to think about our recent thoughts."
  5. "We learn to think on multiple levels."
  6. "We accumulate huge stores of commonsense knowledge."
  7. "We switch among different Ways to Think."
  8. "We find multiple ways to represent things."
  9. "We build multiple models of ourselves."

Other reviews[edit]

Author's Prepublication Draft[edit]

External links[edit]

References[edit]

  1. Jump up^ Minsky, Marvin (2006). The Emotion Machine. Simon & Schuster. ISBN 0-7432-7663-9.
  2. Jump up^ "The Emotion Machine". Book review & textbook buyback site BlueRectangle.com. Retrieved 2010-06-30.
  3. Jump up^ Mind Over Matter, Richard Restak, Washington Post

沒有留言:

網誌存檔