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NLG tools can be used to create personalized, easy to read travel plans. Probably the most dangerous use case is using NLG solutions to spread personalized propaganda and misinformation. Unfortunately, this is the risk of making the current flow of political disinformation even more dangerous and personalized. Automated contents require high-quality structured data. Therefore content automation fits well in areas such as finance, sports, or weather, where data providers make sure that data is accurate and reliable.
Natural language generation is limited to providing answers to prewritten questions by analyzing the given data. Algorithms cannot ask new questions, detect needs, recognize threats, solve problems, or give their thoughts and interpretation on topics such as social and policy change. Thanks to machine learning, the quality of NLG content is likely to keep improving.
However, auto-generated articles tend to be less original than human-written ones. NLG algorithms rely on data and assumptions. Both may contain biases and errors. As a result, algorithms could produce prejudiced outcomes that were unintended and contain errors.
If you have questions on Natural Language Generation vendors, feel free to check our sortable, regularly updated list of NLG companies or contact us:. Your feedback is valuable. We will do our best to improve our work based on it. Cem founded the high tech industry analyst AIMultiple in Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He led technology strategy and procurement of a telco while reporting to the CEO.
He has also led commercial growth of deep tech companies that reached from 0 to 3M annual recurring revenue within 2 years. Cem regularly speaks at international technology conferences. Your email address will not be published.
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Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads. Cookie Duration Description IDE 1 year 24 days Used by Google DoubleClick and stores information about how the user uses the website and any other advertisement before visiting the website. With NLG software, massive datasets can be instantly translated into human-readable formats without the need for a data scientist or analyst to sit down and think about how best to put everything into words.
With this load of their backs, analysts can spend more time doing their jobs, and management can rest assured that their reports are highly accurate. Here, every piece of data is labeled according to its type or perhaps to certain attributes.
This way, NLG software can make valid associations between datasets regardless of their size or complexity. Many data-driven applications are deployed on massive scales, often having to communicate important statistics hundreds if not thousands of times. For example, a university ranking website could use NLG to translate a database of university data e. Since the ranking website would have to create hundreds of these profiles, hiring human writers to do the task would be inefficient.
Instead, NLG software could automatically convert university data into entire articles or, at the very least, short descriptions of each university. Monotony comes in other forms, too; chatbots, for example, constantly take user requests data , process them, and then provide a valid and understandable response. The monotony in this case comes from the high volume of user inputs.
Where it would take a human staff much more time and effort to respond to these user inputs i. Performing analysis is a major part of the technical writing process, especially for reports and summaries related to data.
While most quantitative analyses are completed long before writing the report, qualitative analyses are often left to the writer; in other words, though analytical software may crunch the numbers, writers still have to make sense of what the numbers actually mean.
NLG software is often helpful here. Where a writer might spend time trying to best string different data points into an understandable sentence, NLG software does so instantly and eloquently. NLG software is used by anyone who needs to convert data into a readable summaries or reports. While this functionality makes NLP software a perfect fit for those in analytical fields, many other users can also benefit from using NLP software.
NGL software has quickly become an essential tool for business intelligence and analytics, making data more accessible and understandable to everyone throughout the enterprise. While some analysts can do this, NGL software has made the process much easier. By putting business data into clear words, analysts and management alike are more likely to discover new trends in data—some of which might have gone unnoticed by analysts! This capability also makes business intelligence and analytics more accessible.
With NGL software enabling analytics beyond the roles of analysts, everyone can now take part in the business intelligence process. NGL software benefits finance and investment firms similarly to how it benefits business intelligence and analytics. However, graphs and narratives are perhaps even more important in finance, where individuals across many backgrounds and technical abilities rely on financial data to make important decisions.
Graphs and narratives have been crucial to financial reporting for far longer than NGL software has existed. Whether a financial team needs to present quarterly data to management or share stock trends with an investor, graphs and narratives are the key to keeping everyone on the same page.
Before NGL software, however, financial analysts would have to construct these graphs themselves, often producing accompanying financial reports to help non-analysts interpret the graphs.
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