AI upskilling 2020 for Natural Language Processing technologies
Natural language processing (NLP) has become one of the most widely available and interoperable data formats that is used by businesses to record and transmit their communications.
Leading source for data, machine learning, and AI information, Gradient Flow released a report that takes examines the growth of NLP in enterprises.
NLP lies at the centre of computer science of artificial intelligence by converting text into formats that are understandable for computer form. By 2025, the global NLP market is expected to reach over $34 billion, growing at a CAGR of 21.5%.
It allows for communication via speech, text, virtual conversation, and messaging or, putting it simply, the combination of artificial intelligence and computational linguistics.
In the report, the company revealed survey findings that provide insights into how companies are using NLP.
Ben Lorica, founder of Gradient Flow Founder said, “We found that businesses of all sizes are ramping up the use of their NLP applications to take advantage of how this still-emerging technology enhances automation and scale.
Lorica added, “Our survey provides a detailed analysis of how NLP is moving from research into practice.”
The applications of NLP in business are far-reaching where some of the most common use cases for NLP in business include chatbot technology, speech recognition, spam filters, and machine translation.
NLP can be applied in various areas including recruitment, advertising, customer service, healthcare, as well as market intelligence.
The survey was carried out by surveying close to 600 participants from more than 50 countries where a quarter of all survey respondents held technical leadership roles.
The survey found that more than half of the technical leaders of organisations who responded to the survey were increasing their NLP budgets by at least 10%.
Meanwhile, 31% of the respondents who are technical leaders stated that their budget allocation for natural language processing applications was at least 30% higher compared to 2019.
The same trend was found in responses by respondents from large companies with 5,000 or more employees.
Out of this, 39% of respondents who worked at large companies stated their NLP budget was at least 10% higher compared to 2019 while 21% of employees who worked at large companies stated their NLP budget was at least 30% higher compared to 2019.
The survey also revealed that the most popular application of NLP technologies was Document Classification, Named Entity Recognition (NER), Sentiment Analysis, and Knowledge Graphs.
The most popular, out of the four technologies were Document Classification and NER.
The survey also highlights an interesting finding, as NLP applications become more sophisticated and mission-critical, companies are turning to cloud services.
65% of respondents working at companies further along with the NLP adoption curve use at least one of the top NLP cloud services including Google, AWS, Azure, and IBM.