AI has learned to write: Natural Language Generation in a nutshell
In recent years, the application of artificial intelligence (AI) in the business world has exploded. Many businesses are now using AI to automate tasks or processes that were once done manually. One area of AI that is seeing particular growth is natural language generation (NLG).
NLG is the process of automatically creating text from data. This text can then be used to generate reports, handle communications with customers, or provide information for other business applications.
NLG has many practical uses in the business world. It is often used to transform data into easy-to-understand text that can be read by nontechnical employees. This eliminates the need for companies to hire additional employees to manually create reports or handle customer service inquiries. Some classic examples of NLG applications are the automatic creation of the “readability score” used by e-reading systems (e.g., Kindle), the automated summaries that appear on some websites (e.g., Wikipedia), and chatbots, which can often be found on company websites or social media platforms.
In this article, we will introduce you to the basics of NLG and discuss some examples of how it is used. In addition, we will answer a few common questions about NLG as well as provide resources for those interested in digging deeper into the usages and applications of NLG.
What does NLG do?
Natural language generation is the process of automatically creating readable text from structured data (i.e., numerical and/or categorical values). NLG allows companies to turn complex data sets into easily understandable information without having to manually create reports or handle customer service inquiries themselves.
NLG technologies allow computers to take data in a format that is easy for them to understand (e.g., a table of numbers or a list of categorical values) and generate text that is easy for humans to read. This text can be used to summarize data, generate reports, or provide information in customer service interactions.
How does NLG work?
There are many different ways to generate text using NLG technology. However, all NLG applications rely on two key components: a data set and a natural language generation algorithm.
The data set is the source of information that is used to generate text. This data can be in any form, but it is typically in the form of numerical and/or categorical values. For example, businesses might use sales data to generate a sales report, or they could use product descriptions and photos to generate materials for their website.
The natural language generation algorithm (i.e., “NLG engine”) uses the data set to automatically generate text that is easy for humans to read while following any formatting guidelines provided by the user. This generation process can involve both straightforward and more complex operations, including summarization, extrapolation based on trends, creative writing, etc.
What are some common applications of NLG?
There are many different applications for natural language generation, but some of the most common ones include:
- Generating reports: NLG can be used to automatically generate reports based on data sets. This eliminates the need for businesses to hire additional employees to manually create reports.
- Handling customer service inquiries: NLG can be used to automatically generate responses to customer service inquiries. This eliminates the need for businesses to hire additional employees to handle customer service inquiries.
- Generating website content: NLG can be used to automatically generate website content, such as summaries of data or descriptions of products. This eliminates the need for businesses to hire additional employees to write this content.
FAQs:
Here are some common questions businesses have about natural language generation, along with brief answers:
- Do I need to have any technical expertise in order to use an NLG platform? Because most natural language generation platforms are web-based, there is no need for technical expertise.
- Do I need to hire new employees in order to use an NLG platform? No. You can continue using the same employees you already have, and an NLG platform will save you money by eliminating the need for additional (and often expensive) employees.
- Will my employees become obsolete once we start using an NLG platform? No. NLG platforms actually require a lot of human input in order to generate text that is easy for humans to read. Your employees will still be an important part of the process.
- How much does an NLG platform cost? Prices vary, but most NLG platforms are priced competitively when compared to the cost of hiring additional employees.
Further reading
If you’re still curious about natural language generation, or if you have specific questions about how it could benefit your business, here are a few resources you can use to learn more:
- The Natural Language Generation website: This website provides a comprehensive overview of NLG, including examples of how it can be used in business applications.
- The NLG Wiki: This wiki is a resource for anyone interested in learning more about natural language generation. It includes a variety of resources, including white papers, case studies, and tutorials.
- The AI Conference series: This conference series focuses on artificial intelligence and includes a number of sessions that cover natural language generation. Sessions from past conferences are available online.
The bottom line
Natural language generation can save businesses time and money by automating tasks that would otherwise require the hiring of additional employees. If you’re curious about how NLG could benefit your business, be sure to explore the resources listed above.