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  • Alibek Jakupov

Machine Learning and Music : Grace and Beauty (part II)


Music to hear, why hear’st thou music sadly? Sweets with sweets war not, joy delights in joy: Why lov’st thou that which thou receiv’st not gladly, Or else receiv’st with pleasure thine annoy? If the true concord of well-tuned sounds, By unions married, do offend thine ear, They do but sweetly chide thee, who confounds In singleness the parts that thou shouldst bear. Mark how one string, sweet husband to another, Strikes each in each by mutual ordering; Resembling sire and child and happy mother, Who, all in one, one pleasing note do sing: Whose speechless song being many, seeming one, Sings this to thee: ‘Thou single wilt prove none.’

William Shakespeare, Sonnet 8


In the previous article we discussed the timeline of the Artificial Intelligence from XVIII till XIX century.


In this article we are going to cover the next period of the fascinating history of the AI and music.



1913: Irving Berlin, Otto Harbach and Andrey Markov




A Markov chain is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event.

(Quote from Wikipedia)


Andrey Markov presented the techniques he applied to analyze a poem for the first time in 1913. We now know this technique as Markov chains.


At the same time, "Daddy, Come Home" of Irving Berlin was first published. This humorous song told the story from the point of view of a young boy calling his father on the telephone to ask him to leave work and deal with an assortment of family problems at home.

Yet, in 1913 Otto Harbach, an American lyricist and librettist of about 50 musical comedies, presented "The Bubble".



1950 "Goodnight, Irene", Pink Champagne and Learning Machine




In 1913 Alan Turing formed a principle of so-callled 'learning machine'. This principle stated that the 'learning machine' was able to learn and become artificially intelligent. This specific proposal prefigured the family of genetic algorithms. In one of the previous articles we covered one of the implementations of the genetic algorithm applied on the traveling salesman problem.


"Goodnight, Irene" (or "Irene, Goodnight,"), written in 3/4 time by Gordon Jenkins and The Weavers, became a 20th-century American folk standard. Even if the song was first recorded by American blues musician Huddie 'Lead Belly' Ledbetter in 1933, in 1950 it became the year-End number-one single. At the same time "Pink Champagne" by Joe Liggins was published and became the most popular song among R&B/Soul/Hip-hop compositions.


1951: "Cold, Cold Heart", "Too Young" and the first Neural Network



1951 saw the rise the SNARC, the first neural network machine, able to learn. It was developed by Marvin Minsky and Dean Edmonds. SNARC stands for Stochastic neural analog reinforcement calculator, which was a randomly connected network of approximately 40 Hebb synapses.


The most popular pop single of that period was "Too Young" Nat King Cole. The music was written by Sidney Lippman, the lyrics by Sylvia Dee and Nat King Cole recorded the most popular version. The same year Hank Williams recorded a country music and pop song, "Cold, Cold Heart".



1953: Machines Playing Checkers, "Kaw-Liga" and "Song from Moulin Rouge"



The most popular pop song in 1953 was the "Song from Moulin Rouge" by Percy Faith.The music was composed by Georges Auric and William Engvick wrote an english version of the original French lyrics by Jacques Larue. The most listened country single was "Kaw-Liga" by Hank Williams.


At this lovely period Arthur Samuel joined IBM's Poughkeepsie Laboratory. This step marked the beginning of his work on some of the very first machine learning programs that played checkers.


1957: Perceptron, "All Shook Up" and My Fair Lady


In 1957 Frank Rosenblatt was working at the Cornell Aeronautical Laboratory. At this period he invented the perceptron, an outstanding invention that was a true breakthrough and generated a great deal of excitement. Due to this fact it was widely covered in the media.


This year has also seen the "All Shook Up" by Elvis Presley which was the most listened pop single and the most listened pop album was My Fair Lady's Original Cast. Quote from Wikipedia:

My Fair Lady is a musical based on George Bernard Shaw's Pygmalion, with book and lyrics by Alan Jay Lerner and music by Frederick Loewe. The story concerns Eliza Doolittle, a Cockney flower girl who takes speech lessons from professor Henry Higgins, a phoneticist, so that she may pass as a lady. The original Broadway and London shows starred Rex Harrison and Julie Andrews. The musical's 1956 Broadway production was a notable critical and popular success. It set a record for the longest run of any show on Broadway up to that time. It was followed by a hit London production, a popular film version, and many revivals. My Fair Lady has been called "the perfect musical".

Hope you enjoyed this.


See you next time when we will discuss Machines Playing Tic-Tac-Toe and West Side Story.



References:

  1. Hayes, Brian. "First Links in the Markov Chain". American Scientist. Sigma Xi, The Scientific Research Society. 101 (March–April 2013): 92. doi:10.1511/2013.101.1. Retrieved 15 June 2016. "Delving into the text of Alexander Pushkin's novel in verse Eugene Onegin, Markov spent hours sifting through patterns of vowels and consonants. On January 23, 1913, he summarized his findings in an address to the Imperial Academy of Sciences in St. Petersburg. His analysis did not alter the understanding or appreciation of Pushkin's poem, but the technique he developed—now known as a Markov chain—extended the theory of probability in a new direction."

  2. Turing, Alan (October 1950). "Computing Machinery and Intelligence". Mind. 59 (236): 433–460. doi:10.1093/mind/LIX.236.433. Retrieved 8 June 2016.

  3. Crevier 1993, pp. 34–35 and Russell & Norvig 2003, p. 17

  4. McCarthy, John; Feigenbaum, Ed. "Arthur Samuel: Pioneer in Machine Learning". AI Magazine (3). Association for the Advancement of Artificial Intelligence. p. 10. Retrieved 5 June 2016.

  5. Rosenblatt, Frank (1958). "The perceptron: A probabilistic model for information storage and organization in the brain" (PDF). Psychological Review. 65 (6): 386–408. doi:10.1037/h0042519.

  6. Mason, Harding; Stewart, D; Gill, Brendan (6 December 1958). "Rival". The New Yorker. Retrieved 5 June 2016.

  7. Child, Oliver. "Menace: the Machine Educable Noughts And Crosses Engine Read". Chalkdust Magazine. Retrieved 16 Jan 2018.