2016年1月27日 星期三

Marvin Minsky (1927–2016), Pioneer in Artificial Intelligence


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

http://hcbooks.blogspot.tw/2013/11/the-society-of-mind-marvin-minsky.html



Photo
Marvin Minsky in a lab at M.I.T. in 1968. CreditM.I.T.
Marvin Minsky, who combined a scientist’s thirst for knowledge with a philosopher’s quest for truth as a pioneering explorer of artificial intelligence, work that helped inspire the creation of the personal computer and the Internet, died on Sunday night in Boston. He was 88.
His family said the cause was a cerebral hemorrhage.
Well before the advent of the microprocessor and the supercomputer, Professor Minsky, a revered computer science educator at M.I.T., laid the foundation for the field of artificial intelligence by demonstrating the possibilities of imparting common-sense reasoning to computers.
“Marvin was one of the very few people in computing whose visions and perspectives liberated the computer from being a glorified adding machine to start to realize its destiny as one of the most powerful amplifiers for human endeavors in history,” said Alan Kay, a computer scientist and a friend and colleague of Professor Minsky’s.
Fascinated since his undergraduate days at Harvard by the mysteries of human intelligence and thinking, Professor Minsky saw no difference between the thinking processes of humans and those of machines. Beginning in the early 1950s, he worked on computational ideas to characterize human psychological processes and produced theories on how to endow machines with intelligence.
Professor Minsky, in 1959, co-founded the M.I.T. Artificial Intelligence Project (later the Artificial Intelligence Laboratory) with his colleagueJohn McCarthy, who is credited with coining the term “artificial intelligence.”
Beyond its artificial intelligence charter, however, the lab would have a profound impact on the modern computing industry, helping to impassion a culture of computer and software design. It planted the seed for the idea that digital information should be shared freely, a notion that would shape the so-called open-source software movement, and it was a part of the original ARPAnet, the forerunner to the Internet.
Professor Minsky’s scientific accomplishments spanned a variety of disciplines. He designed and built some of the first visual scanners and mechanical hands with tactile sensors, advances that influenced modern robotics. In 1951 he built the first randomly wired neural network learning machine, which he called Snarc. And in 1956, while at Harvard, he invented and built the first confocal scanning microscope, an optical instrument with superior resolution and image quality still in wide use in the biological sciences.
His own intellect was wide-ranging and his interests were eclectic. While earning a degree in mathematics at Harvard he also studied music, and as an accomplished pianist, he would later delight in sitting down at one and improvising complex baroque fugues.
Photo
Marvin Minsky in an undated photo. CreditLouis Fabian Bachrach
Professor Minsky was lavished with many honors, notably, in 1969, the Turing Award, computer science’s highest prize.
He went on to collaborate, in the early ’70s, with Seymour Papert, the renowned educator and computer scientist, on a theory they called “The Society of Mind,” which combined insights from developmental child psychology and artificial intelligence research.
Professor Minsky’s book “The Society of Mind,” a seminal work published in the mid-1980s, proposed “that intelligence is not the product of any singular mechanism but comes from the managed interaction of a diverse variety of resourceful agents,” as he wrote on his website.
Underlying that hypothesis was his and Professor Papert’s belief that there is no real difference between humans and machines. Humans, they maintained, are actually machines of a kind whose brains are made up of many semiautonomous but unintelligent “agents.” And different tasks, they said, “require fundamentally different mechanisms.”
Their theory revolutionized thinking about how the brain works and how people learn.
“Marvin was one of the people who defined what computing and computing research is all about,” Dr. Kay said. “There were four or five supremely talented characters from back then who were early and comprehensive and put their personality and stamp on the field, and Marvin was among them.”
Marvin Lee Minsky was born on Aug. 9, 1927, in New York City. The precocious son of Dr. Henry Minsky, an eye surgeon who was chief of ophthalmology at Mount Sinai Hospital, and Fannie Reiser, a social activist and Zionist.
Fascinated by electronics and science, the young Mr. Minsky attended the Ethical Culture School in Manhattan, a progressive private school from which J. Robert Oppenheimer, who oversaw the creation of the first atomic bomb, had graduated. (Mr. Minsky later attended the affiliated Fieldston School in Riverdale.) He went on to attend the Bronx High School of Science and later Phillips Academy in Andover, Mass.
After a stint in the Navy during World War II, he studied mathematics at Harvard and received a Ph.D. in math from Princeton, where he met John McCarthy, a fellow graduate student.
Intellectually restless throughout his life, Professor Minsky sought to move on from mathematics once he had earned his doctorate. After ruling out genetics as interesting but not profound, and physics as mildly enticing, he chose to focus on intelligence itself.
“The problem of intelligence seemed hopelessly profound,” he told The New Yorker magazine when it profiled him in 1981. “I can’t remember considering anything else worth doing.”
To further those studies he reunited with Professor McCarthy, who had been awarded a fellowship to M.I.T. in 1956. Professor Minsky, who had been at Harvard by then, arrived at M.I.T. in 1958, joining the staff at its Lincoln Laboratory. A year later, he and Professor McCarthy founded M.I.T.’s AI Project, later to be known as the AI Lab. (Professor McCarthy left for Stanford in 1962.)
Professor Minsky’s courses at M.I.T. — he insisted on holding them in the evenings — became a magnet for several generations of graduate students, many of whom went on to become computer science superstars themselves.
Among them were Ray Kurzweil, the inventor and futurist; Gerald Sussman, a prominent A.I. researcher and professor of electrical engineering at M.I.T.; and Patrick Winston, who went on to run the AI Lab after Professor Minsky stepped aside.
Another of his students, Danny Hillis, an inventor and entrepreneur, co-founded Thinking Machines, a supercomputer maker in the early 1990s.
Mr. Hillis said he had so been taken by Professor Minsky’s intellect and charisma that he found a way to insinuate himself into the AI Lab and get a job there. He ended up living in the Minsky family basement in Brookline, Mass.
“Marvin taught me how to think,” Mr. Hillis said in an interview. “He had a style and a playful curiosity that was a huge influence on me. He always challenged you to question the status quo. He loved it when you argued with him.”
Professor Minsky’s prominence extended well beyond M.I.T. While preparing to make the 1968 science-fiction epic “2001: A Space Odyssey,” the director Stanley Kubrick visited him seeking to learn about the state of computer graphics and whether Professor Minsky believed it would be plausible for computers to be able to speak articulately by 2001.
Professor Minsky is survived by his wife, Gloria Rudisch, a physician; two daughters, Margaret and Juliana Minsky; a son, Henry; a sister, Ruth Amster; and four grandchildren.
“In some ways, he treated his children like his students,” Mr. Hillis recalled. “They called him Marvin, and he challenged them and engaged them just as he did with his students.”
In 1989, Professor Minsky joined M.I.T.’s fledgling Media Lab. “He was an icon who attracted the best people,” said Nicholas Negroponte, the Media Lab’s founder and former director.
For Dr. Kay, Professor Minsky’s legacy was his insatiable curiosity. “He used to say, ‘You don’t really understand something if you only understand it one way,’” Dr. Kay said. “He never thought he had anything completely done.”
Correction: January 27, 2016 
An obituary on Tuesday about Marvin Minsky, a pioneer in artificial intelligence, misstated the year he received the Turing Award, computer science’s highest prize. It was 1969, not 1970.


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

2016年1月24日 星期日

$28M challenge to figure out why brains are so good at learning人工智慧太厲害了,我們該怎麼辦? (洪士灝);A Computer That Can Hear a Marriage in Trouble






The challenge: Figure out why brains are so good at learning, and use that information to design computer systems that can interpret, analyze, and learn information as successfully as humans.


Grant could bring artificial intelligence closer to reality
NEWS.HARVARD.EDU
人工智慧太厲害了,我們該怎麼辦?
我們為什麼要推計算思維呢? 因為未來各行各業都需要與電腦合作,否則有可能被電腦和機器人淘汰,例如這篇【機器人搶工作 律師、藥劑師也遭殃】所談到的(註1)狀況。如果不懂計算思維,很容易就迷惘了。
最近像這樣的文章和書籍很多,研究未來學的人,認為人工智慧是未來的重要趨勢,極盡能事去想像未來,但究竟有多少真實會發生,有多少只是虛無飄渺的幻想? 我想,很少人有能力確定,不過當前許多學生都跑來研究人工智慧相關的議題,則已成為我在台大所看到的事實。
我三十年前在高中時,就對於人工智慧很感興趣,開始學LISP,後來進到台大念電機系,還是修了兩門人工智慧的課,也旁聽過神經網路,到密西根大學念書,也修過人工智慧,但我沒有繼續研究人工智慧,因為我覺得當時研究者走偏了,而且運算速度遠遠不足以支持有意義的人工智慧,所以根本做不出東西。
我猜對了,1990年代之後,人工智慧成為票房毒藥,沉寂了二十年。
我做電腦系統,看著電腦系統的效能持續成長,電腦系統的研究者想出各種方法來收割(harvest)不斷成長的電腦效能,過去這三十年,最忙碌的研究領域之二,是計算機結構和系統軟體,我有幸能優游於兩者之間,探討一些軟硬體整合的議題。
如今,單一處理機的運算能力,約為30年前人工智慧全盛時期的100萬倍(註2),而且只要願意付些許錢,就可以租用雲端的上百台電腦,運算能力更是30年前的一億倍以上。
要注意到,這一億倍的運算效能,是人工智慧東山再起的關鍵。沒有足夠的效能,電腦很難生出智慧。如今的運算效能,是否足以支持未來學想像中的人工智慧,就是一個大哉問。
大部份未來學專家的預測,都是基於摩爾定律(註3),但這幾年摩爾定律已經放緩,甚至有可能停滯,主要是成本考量。以往這麼多年透過個人電腦、電子商務、行動運算、雲端服務等應用,半導體產業有足夠的利潤做研發來支撐摩爾定律,但大數據分析和人工智慧是否足以繼續支撐摩爾定律? 如果摩爾定律停滯,那該如何是好?
有的人工智慧應用,需要比目前更高百倍的計算能力,有的要成為產品的前提,需要將龐大的運算能力縮小進到生活周邊,因此我認為我們做計算系統的,在產品化的過程中,還是扮演舉足輕重的角色,將來應該會有做不完的人工智慧系統設計的工作。
要創造出人工智慧的系統,關鍵在於要有能夠密切垂直整合的團隊,必須要有三種專家密切配合:
(1)領域專家,例如找律師、藥劑師來指導或教導電腦該領域的專業技能。
(2)人工智慧專家,綜合運用機器學習、數據分析、資料探勘等方式設計人工智慧。
(3)系統專家,提供人工智慧所需的系統整合、資料蒐集、處理和計算能力。
台灣比諸於其他許多國家,由於有硬體產業的基礎,非常適合發展「(3)系統專家」,加上台灣目前很多學生對人工智慧很有興趣,學得很快,所以我不擔心會短缺「(2)人工智慧專家」,台灣在各行各業也有很多領域專家,但是能否聚集人才成為優質研發團隊,是真正的重點。
我想,很多有識之士已經看到這個局面,這是值得台灣去發展的好機會。我希望國家和社會多投入一些資源鼓勵產學界共同組成「對」的團隊,來把握這樣的機會,讓學術界多做些有益於這類幫助國家產業發展的研發工作。
然而,在謀求發展的機會的同時,我們也應該做好教育的工作,讓未來的世代能夠好好面對電腦和機器人。與其教學生背誦記憶一堆電腦瞬間可解的問題,不如教他們如何活用電腦、想辦法與電腦和機器人共榮。
另外,科技的民主化以及財富的合理分配,也將會是越來越重要的課題。我們絕對不希望大家多年努力的成果,被少數資本家收割,讓科技成為資本家搜刮社會資源和剝奪勞工的打手 -- 這是社會大眾需要慎重看待的議題。
(註1)機器人搶工作 律師、藥劑師也遭殃
http://www.cw.com.tw/article/article.action?id=5073792
(註2)以摩爾定律概算,每18個月電腦效能增加一倍。
(註3)https://zh.wikipedia.org/wiki/摩爾定律

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待查:Simon 是否在1990年代提過一套"心理治療"軟體?




A Computer That Can Hear a Marriage in Trouble

Researchers try to harness technology to help therapists better help struggling couples


By programming a computer to analyze the speech of couples, researchers at the universities of Southern California and Utah could predict whether the relationship would improve, worsen or stay the same.ENLARGE
By programming a computer to analyze the speech of couples, researchers at the universities of Southern California and Utah could predict whether the relationship would improve, worsen or stay the same. ILLUSTRATION: JUSTIN RENTERIA
The human voice can reveal a great deal. Now, with the help of a computer, it can probably reveal whether your marriage is deteriorating.
By programming a computer to analyze the speech of couples, researchers at the universities of Southern California and Utah could predict whether the relationship would improve, worsen or stay the same. The computerized analysis, which focused entirely on aural qualities such as pitch and intensity, was compared with human assessments that took account of familiar features of the marital landscape, such as blame.
The computer turned out to be able to predict marital improvement or deterioration about as reliably as ratings provided by trained humans—in fact, even a little better.
The work is part of a flurry of research in recent years in which scientists have tried to glean useful information from closely examining therapy patients’ voices, gestures and word choices. The aim is to make talk therapy more effective.
In this case, the scientists worked with video recordings of 134 “chronically distressed couples” who had been married for an average of 10 years and had sought therapy for problems in the relationship. The study focused on three sets of sessions: one before therapy began, another after 26 weeks of therapy and a third after two years of treatment.
The researchers used their computer to rate the recorded voices for 74 acoustic features. These included such familiar ones as loudness but also more esoteric elements such as jitter and shimmer—described by Brian Baucom, one of the scientists, as measures of shakiness. The couples’ videotaped interactions—including words and body language—were also rated for various characteristics by teams of undergraduate psychology students who were extensively trained for the purpose.
Dr. Baucom says that prior research has shown that trained students can do better here than therapists because the students tend to follow the rating manual and rate more consistently for behaviors and feelings such as blame and sadness. Their ratings were then correlated with four possible outcomes from therapy: decline, no change, partial recovery and recovery. These correlations have predictive power, letting researchers anticipate actual outcomes for the couples (which were assessed two years after therapy ended).
But the computer did a bit better across the board in predicting marital changes. In predicting whether a recovery would occur, for instance, the computer achieved nearly 78% accuracy, beating the human ratings by two percentage points.
One big question: Can couples learn—perhaps from a smartphone app—to change their voices in a way that improves their marriage? Perhaps a stand-alone device, placed in the home, could sound an alarm when dialogue takes on troubling tones. Shrikanth S. Narayanan, another scientist who worked on the study, says that it’s conceivable. But the focus for now is simply to harness technology to help therapists do a better job in counseling couples.
“Still Together?: The Role of Acoustic Features in Predicting Marital Outcome,” Md Nasir, Wei Xia, Bo Xiao, Brian Baucom, Shrikanth S. Narayanan, Panayiotis Georgiou, Interspeech 2015 (Sept. 6)