As more and more companies adopt artificial intelligence (AI) in a variety of sectors, these AI are inevitably put in positions where they have to interact with human beings. From customer support chatbots to virtual assistants like Amazon’s Alexa, these use cases necessitate teaching an AI how to listen, learn, and understand what humans are saying to it and how to respond.
One method for teaching AI how to communicate with humans is natural language processing (NLP). Sitting at the intersection at AI, computer science, and linguistics, natural language processing’s goal is to create or train a computer capable of not just understanding the literal words humans say but also the contextual implications and nuances found in their language.
As the AI industry has grown in prominence, so too has the NLP industry. A report from Allied Market Research valued the global NLP market at $11.1 billion in 2020, and it is expected to grow to $341.5 billion by 2030. Within that valuation lies a myriad of both promising startups and experienced tech veterans pushing the science further and further.
- History of Natural Language Processing
- Benefits of Natural Language Processing
History of Natural Language Processing
Natural language processing has been part of AI research since the field’s infancy. Alan Turing’s landmark paper Computer Machinery and Intelligence, in which the famous Turing Test was introduced, includes a task...
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