The "AI Winter" refers to a period in the history of artificial intelligence (AI) when interest and investment in AI declined significantly due to a series of failures and limitations in the research and development of AI systems.
The term "winter" refers to an extended period of time in which AI research and development suffered a significant setback, leading to a decline in funding and investment in research in the field.
The first "AI Winter" occurred in the 1970s, when AI had boomed in the previous decade, but the technology failed to live up to expectations. This led to a decline in investment and interest in AI until the 1990s, when the rise of the web and the increase in computer processing power revived interest in AI.
Since then, there have been occasional concerns about the possibility of a new "AI Winter", as AI remains an evolving technology with many challenges and limitations. However, AI has continued to advance and today is in use in a wide variety of practical applications in many different industries.
Machine learning is a branch of artificial intelligence (AI) that is based on making a system capable of learning from the information it receives.
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