Future Timeline

The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. 1950s: The Georgetown experiment in 1954 involved fully automatic translation of more than sixty Russian sentences into English. The authors claimed that within three or five years, machine translation would be a solved problem. However, real progress was much slower, and after the ALPAC report in 1966, which found that ten-year-long research had failed to fulfill the expectations, funding for machine translation was dramatically reduced. 1960s: When the “patient” exceeded the very small knowledge base, ELIZA might provide a generic response, for example, responding to “My head hurts” with “Why do you say your head hurts?”. 1970s: During this time, the first many chatterbots were written (e.g., PARRY). 1980s: An important development (that eventually led to the statistical turn in the 1990s) was the rising importance of quantitative evaluation in this period. 1990s: As a result, a great deal of research has gone into methods of more effectively learning from limited amounts of data. 2000s: These algorithms take as input a large set of “features” that are generated from the input data. The following is a list of some of the most commonly researched tasks in natural language processing. A coarse division is given below. Given a sound clip of a person or people speaking, determine the textual representation of the speech.