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After a brief lull in NLP research, due to a halt in funding for NLP research by the Automatic Language Processing Advisory Committee (ALPAC) formed by the US government, natural language processing acquired a new dimension with the “statistical revolution” of the 1980s. ELIZA, SHRDLU, and PARRY were all precursors of interest in NLP. Many attempts were then initiated to pass the Turing test. To fulfill Turing’s criteria, a machine has to understand a human’s natural language in order to frame an intelligent human-like response. Though the 1940s saw glimpses of NLP in machine translation, the now-so-popular “ Turing test” (also known as the imitation game), opened the possibilities of machines trying to comprehend the complex field of linguistics. In his paper “Computing Machinery and Intelligence” published in 1950, Alan Turing poses a revolutionary question - “Can machines think?”. With enough virtual assistants like Siri and Cortana in the market already, are we ready to pull off a Jarvis? Let’s see how NLP was used over the decades and where it’s future course lies. A subfield of AI, NLP is a machine’s ability to understand human language in speech or text thereby narrowing the communication gap between man and machine.
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If you want to reconstruct Jarvis in reality, Natural Language Processing (NLP) would be the first technology you would consider. Looks like a normal conversation with a personal assistant, doesn’t it?Įxcept that Jarvis isn’t a human being but a smart AI assistant capable of holding seamless conversations and available at your service, always. Stark that terabytes of calculations need to be done before an actual flight, only to be met with Tony’s cocky reply - “ Jarvis! Sometimes you gotta run before you can walk.”
HOW CAN I MAKE JARVIS PROGRAM MORE INTERLIGENT SERIES
Tony Stark then goes on to give a series of commands to check and access his uber-cool Ironman suit. NEWABOUT PAGE A Brief History of NLP Applications in the 21st Century