Ever wondered how a virtual assistant, such as Google Home or Amazon’s Alexa, responds when asked a question? The answer is with natural language generation
Companies that aren’t investing in artificial intelligence (AI) risk falling behind their competitors. Yet because AI is an umbrella term for several different technologies that each have distinct uses, it is often challenging to know which solution is right for a particular work process.
The most well-known subsets of AI are robotic process automation for automating repetitive tasks, machine-learning to give computer systems the ability to “learn” and improve work processes, and natural language processing (NLP), which enables machines to analyse and understand humans’ imperfect way of writing or talking.
A lesser-known AI technology, however, is natural language generation (NLG). At its simplest, an NLG platform is a computer process that can generate natural language text and speech from pre-defined data. At its most advanced, it powers the responses given by AI assistants, such as Google Home and Amazon’s Alexa, when asked a question.
Though currently relatively nascent, the technology has huge potential for many industries, including journalism, finance, business service and healthcare, for both customer-facing and internal work processes.
Using Natural Language Generation to translate data
A booming use case for NLG is as a tool to translate the hordes of data businesses now collect into intelligent, understandable and actionable insights. A platform can be given a set of rules and parameters to work within, and then fed structured data to output reports, paragraphs and emails that appear as though written by a human.
Automated Insights’ NLG platform, called Wordsmith, was originally built to generate sports post-match recaps and player notes, but the company is now seeing an upswing in demand from firms wanting to generate business intelligence reports.
These include marketing analysis and coherent narratives derived from data straight into company dashboards, so complex statistics can be easily understood by everyone in an organisation without being verbally explained by analysts.
“This automates their expertise in a way everyone can understand to alleviate some of the manual work. Every company is collecting data and people want to know what it means immediately; NLG translates it into something anyone can read and understand,” explains the company’s marketing manager Laura Pressman.
Heidi Vella 