text: Researchers in the 1960s and the 1970s were convinced that their methods would eventually succeed in 
  creating a machine with general intelligence and considered this the goal of their field.[327] In 1965 
  Herbert Simon predicted, "machines will be capable, within twenty years, of doing any work a man can 
  do".[328] In 1967 Marvin Minsky agreed, writing that "within a generation ... the problem of creating 
  'artificial intelligence' will substantially be solved".[329] They had, however, underestimated the difficulty 
  of the problem.[w] In 1974, both the U.S. and British governments cut off exploratory research in 
  response to the criticism of Sir James Lighthill[331] and ongoing pressure from the U.S. Congress to fund 
  more productive projects.[332] Minsky's and Papert's book*Perceptrons*was understood as proving that 
  artificial neural networks would never be useful for solving real-world tasks, thus discrediting the 
  approach altogether.[333] The "AI winter", a period when obtaining funding for AI projects was difficult, 
  followed.[9] 
  
  In the early 1980s, AI research was revived by the commercial success of expert systems,[334] a form of 
  AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for 
  AI had reached over a billion dollars. At the same time, Japan's fifth generation computer project inspired 
  the U.S. and British governments to restore funding for academic research.[8] However, beginning with 
  the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, longer- 
  lasting winter began.[10] 