Showing posts with label MIT. Show all posts
Showing posts with label MIT. Show all posts

Artificial Intelligence - Who Was John McCarthy?

 


John McCarthy  (1927–2011) was an American computer scientist and mathematician who was best known for helping to develop the subject of artificial intelligence in the late 1950s and pushing the use of formal logic in AI research.

McCarthy was a creative thinker who earned multiple accolades for his contributions to programming languages and operating systems research.

Throughout McCarthy's life, however, artificial intelligence and "formalizing common sense" remained his primary research interest (McCarthy 1990).

As a graduate student, McCarthy first met the concepts that would lead him to AI at the Hixon conference on "Cerebral Mechanisms in Behavior" in 1948.

The symposium was place at the California Institute of Technology, where McCarthy had just finished his undergraduate studies and was now enrolled in a graduate mathematics program.

In the United States, machine intelligence had become a subject of substantial academic interest under the wide term of cybernetics by 1948, and many renowned cyberneticists, notably Princeton mathematician John von Neumann, were in attendance at the symposium.

McCarthy moved to Princeton's mathematics department a year later, when he discussed some early ideas inspired by the symposium with von Neumann.

McCarthy never published the work, despite von Neumann's urging, since he believed cybernetics could not solve his problems concerning human knowing.

McCarthy finished a PhD on partial differential equations at Princeton.

He stayed at Princeton as an instructor after graduating in 1951, and in the summer of 1952, he had the chance to work at Bell Labs with cyberneticist and inventor of information theory Claude Shannon, whom he persuaded to collaborate on an edited collection of writings on machine intelligence.

Automata Studies received contributions from a variety of fields, ranging from pure mathematics to neuroscience.

McCarthy, on the other hand, felt that the published studies did not devote enough attention to the important subject of how to develop intelligent machines.

McCarthy joined the mathematics department at Stanford in 1953, but was fired two years later, maybe because he spent too much time thinking about intelligent computers and not enough time working on his mathematical studies, he speculated.

In 1955, he accepted a position at Dartmouth, just as IBM was preparing to establish the New England Computation Center at MIT.

The New England Computation Center gave Dartmouth access to an IBM computer that was installed at MIT and made accessible to a group of New England colleges.

McCarthy met IBM researcher Nathaniel Rochester via the IBM initiative, and he recruited McCarthy to IBM in the summer of 1955 to work with his research group.

McCarthy persuaded Rochester of the need for more research on machine intelligence, and he submitted a proposal to the Rockefeller Foundation for a "Summer Research Project on Artificial Intelligence" with Rochester, Shannon, and Marvin Minsky, a graduate student at Princeton, which included the first known use of the phrase "artificial intelligence." Despite the fact that the Dartmouth Project is usually regarded as a watershed moment in the development of AI, the conference did not go as McCarthy had envisioned.

The Rockefeller Foundation supported the proposal at half the proposed budget since it was for such an unique field of research with a relatively young professor as author, and because Shannon's reputation carried substantial weight with the Foundation.

Furthermore, since the event took place over many weeks in the summer of 1955, only a handful of the guests were able to attend the whole period.

As a consequence, the Dartmouth conference was a fluid affair with an ever-changing and unpredictably diverse guest list.

Despite its chaotic implementation, the meeting was crucial in establishing AI as a distinct area of research.

McCarthy won a Sloan grant to spend a year at MIT, closer to IBM's New England Computation Center, while still at Dartmouth in 1957.

McCarthy was given a post in the Electrical Engineering department at MIT in 1958, which he accepted.

Later, he was joined by Minsky, who worked in the mathematics department.

McCarthy and Minsky suggested the construction of an official AI laboratory to Jerome Wiesner, head of MIT's Research Laboratory of Electronics, in 1958.

McCarthy and Minsky agreed on the condition that Wiesner let six freshly accepted graduate students into the laboratory, and the "artificial intelligence project" started teaching its first generation of students.

McCarthy released his first article on artificial intelligence in the same year.

In his book "Programs with Common Sense," he described a computer system he named the Advice Taker that would be capable of accepting and understanding instructions in ordinary natural language from nonexpert users.

McCarthy would later define Advice Taker as the start of a study program aimed at "formalizing common sense." McCarthy felt that everyday common sense notions, such as comprehending that if you don't know a phone number, you'll need to look it up before calling, might be written as mathematical equations and fed into a computer, enabling the machine to come to the same conclusions as humans.

Such formalization of common knowledge, McCarthy felt, was the key to artificial intelligence.

McCarthy's presentation, which was presented at the United Kingdom's National Physical Laboratory's "Symposium on Mechansation of Thought Processes," helped establish the symbolic program of AI research.

McCarthy's research was focused on AI by the late 1950s, although he was also involved in a range of other computing-related topics.

In 1957, he was assigned to a group of the Association for Computing Machinery charged with developing the ALGOL programming language, which would go on to become the de facto language for academic research for the next several decades.

He created the LISP programming language for AI research in 1958, and its successors are widely used in business and academia today.

McCarthy contributed to computer operating system research via the construction of time sharing systems, in addition to his work on programming languages.

Early computers were large and costly, and they could only be operated by one person at a time.

McCarthy identified the necessity for several users throughout a major institution, such as a university or hospital, to be able to use the organization's computer systems concurrently via computer terminals in their offices from his first interaction with computers in 1955 at IBM.

McCarthy pushed for study on similar systems at MIT, serving on a university committee that looked into the issue and ultimately assisting in the development of MIT's Compatible Time-Sharing System (CTSS).

Although McCarthy left MIT before the CTSS work was completed, his advocacy with J.C.R.

Licklider, future office head at the Advanced Research Projects Agency, the predecessor to DARPA, while a consultant at Bolt Beranek and Newman in Cambridge, was instrumental in helping MIT secure significant federal support for computing research.

McCarthy was recruited to join what would become the second department of computer science in the United States, after Purdue's, by Stanford Professor George Forsythe in 1962.

McCarthy insisted on going only as a full professor, which he believed would be too much for Forsythe to handle as a young researcher.

Forsythe was able to persuade Stanford to grant McCarthy a full chair, and he moved to Stanford in 1965 to establish the Stanford AI laboratory.

Until his retirement in 2000, McCarthy oversaw research at Stanford on AI topics such as robotics, expert systems, and chess.

McCarthy was up in a family where both parents were ardent members of the Communist Party, and he had a lifetime interest in Russian events.

He maintained numerous professional relationships with Soviet cybernetics and AI experts, traveling and lecturing there in the mid-1960s, and even arranged a chess match between a Stanford chess computer and a Russian equivalent in 1965, which the Russian program won.

He developed many foundational concepts in symbolic AI theory while at Stanford, such as circumscription, which expresses the idea that a computer must be allowed to make reasonable assumptions about problems presented to it; otherwise, even simple scenarios would have to be specified in such exacting logical detail that the task would be all but impossible.

McCarthy's accomplishments have been acknowledged with various prizes, including the 1971 Turing Award, the 1988 Kyoto Prize, admission into the National Academy of Sciences in 1989, the 1990 Presidential Medal of Science, and the 2003 Benjamin Franklin Medal.

McCarthy was a brilliant thinker who continuously imagined new technologies, such as a space elevator for economically transporting stuff into orbit and a system of carts strung from wires to better urban transportation.

In a 2008 interview, McCarthy was asked what he felt the most significant topics in computing now were, and he answered without hesitation, "Formalizing common sense," the same endeavor that had inspired him from the start.


~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram


You may also want to read more about Artificial Intelligence here.



See also: 


Cybernetics and AI; Expert Systems; Symbolic Logic.


References & Further Reading:


Hayes, Patrick J., and Leora Morgenstern. 2007. “On John McCarthy’s 80th Birthday, in Honor of His Contributions.” AI Magazine 28, no. 4 (Winter): 93–102.

McCarthy, John. 1990. Formalizing Common Sense: Papers, edited by Vladimir Lifschitz. Norwood, NJ: Albex.

Morgenstern, Leora, and Sheila A. McIlraith. 2011. “John McCarthy’s Legacy.” Artificial Intelligence 175, no. 1 (January): 1–24.

Nilsson, Nils J. 2012. “John McCarthy: A Biographical Memoir.” Biographical Memoirs of the National Academy of Sciences. http://www.nasonline.org/publications/biographical-memoirs/memoir-pdfs/mccarthy-john.pdf.



Artificial Intelligence - What Is The ELIZA Software?

 



ELIZA is a conversational computer software created by German-American computer scientist Joseph Weizenbaum at Massachusetts Institute of Technology between 1964 and 1966.


Weizenbaum worked on ELIZA as part of a groundbreaking artificial intelligence research team on the DARPA-funded Project MAC, which was directed by Marvin Minsky (Mathematics and Computation).

Weizenbaum called ELIZA after Eliza Doolittle, a fictitious character in the play Pygmalion who learns correct English; that play had recently been made into the successful film My Fair Lady in 1964.


ELIZA was created with the goal of allowing a person to communicate with a computer system in plain English.


Weizenbaum became an AI skeptic as a result of ELIZA's popularity among users.

When communicating with ELIZA, users may input any statement into the system's open-ended interface.

ELIZA will often answer by asking a question, much like a Rogerian psychologist attempting to delve deeper into the patient's core ideas.

The application recycles portions of the user's comments while the user continues their chat with ELIZA, providing the impression that ELIZA is genuinely listening.


Weizenbaum had really developed ELIZA to have a tree-like decision structure.


The user's statements are first filtered for important terms.

The terms are ordered in order of significance if more than one keyword is discovered.

For example, if a user writes in "I suppose everyone laughs at me," the term "everybody," not "I," is the most crucial for ELIZA to reply to.

In order to generate a response, the computer uses a collection of algorithms to create a suitable sentence structure around those key phrases.

Alternatively, if the user's input phrase does not include any words found in ELIZA's database, the software finds a content-free comment or repeats a previous answer.


ELIZA was created by Weizenbaum to investigate the meaning of machine intelligence.


Weizenbaum derived his inspiration from a comment made by MIT cognitive scientist Marvin Minsky, according to a 1962 article in Datamation.

"Intelligence was just a characteristic human observers were willing to assign to processes they didn't comprehend, and only for as long as they didn't understand them," Minsky had claimed (Weizenbaum 1962).

If such was the case, Weizenbaum concluded, artificial intelligence's main goal was to "fool certain onlookers for a while" (Weizenbaum 1962).


ELIZA was created to accomplish precisely that by giving users reasonable answers while concealing how little the software genuinely understands in order to keep the user's faith in its intelligence alive for a bit longer.


Weizenbaum was taken aback by how successful ELIZA became.

ELIZA's Rogerian script became popular as a program renamed DOCTOR at MIT and distributed to other university campuses by the late 1960s—where the program was constructed from Weizenbaum's 1965 description published in the journal Communications of the Association for Computing Machinery.

The application deceived (too) many users, even those who were well-versed in its methods.


Most notably, some users grew so engrossed with ELIZA that they demanded that others leave the room so they could have a private session with "the" DOCTOR.


But it was the psychiatric community's reaction that made Weizenbaum very dubious of current artificial intelligence ambitions in general, and promises of computer comprehension of natural language in particular.

Kenneth Colby, a Stanford University psychiatrist with whom Weizenbaum had previously cooperated, created PARRY about the same time that Weizenbaum released ELIZA.


Colby, unlike Weizenbaum, thought that programs like PARRY and ELIZA were beneficial to psychology and public health.


They aided the development of diagnostic tools, enabling one psychiatric computer to treat hundreds of patients, according to him.

Weizenbaum's worries and emotional plea to the community of computer scientists were eventually conveyed in his book Computer Power and Human Reason (1976).

Weizenbaum railed against individuals who neglected the presence of basic distinctions between man and machine in this — at the time — hotly discussed book, arguing that "there are some things that computers ought not to execute, regardless of whether computers can be persuaded to do them" (Weizenbaum 1976, x).


Jai Krishna Ponnappan


You may also want to read more about Artificial Intelligence here.



See also: 


Chatbots and Loebner Prize; Expert Systems; Minsky, Marvin; Natural Lan￾guage Processing and Speech Understanding; PARRY; Turing Test


Further Reading:


McCorduck, Pamela. 1979. Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence, 251–56, 308–28. San Francisco: W. H. Freeman and Company.

Weizenbaum, Joseph. 1962. “How to Make a Computer Appear Intelligent: Five in a Row Offers No Guarantees.” Datamation 8 (February): 24–26.

Weizenbaum, Joseph. 1966. “ELIZA: A Computer Program for the Study of Natural Language Communication between Man and Machine.” Communications of the ACM 1 (January): 36–45.

Weizenbaum, Joseph. 1976. Computer Power and Human Reason: From Judgment to Calculation. San Francisco: W.H. Freeman and Company



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