Even though the natural language is not new, the technology is developing quickly due to the growing interest in human-to-machine communications, as well as the availability of massive data, powerful computation, and improved algorithms.
More language-based data may now be analysed by machines than humans, without tiring and in a reliable, unbiased manner. Automation will be essential to effectively evaluate text and audio data given the astonishing volume of daily unstructured data, from social media to medical records.
Here in this blog, let’s look deeper into natural language processing and its benefits.
What is Natural Language Generation (NLG)?
The practice of employing artificial intelligence to produce language for various applications is known as natural language generation (NLG). NLG systems are employed in various applications, such as customer service chatbots and voice-activated assistants like Siri and Alexa.
Even though these systems can’t yet simulate human speech without conceptual cues from a user or programmer, they can produce natural-sounding text and sentences.
Advantages Of NLG:
The benefits of the Natural Language Generation go beyond what people typically think about adopting AI. It has several advantages for marketing and corporate management, including:
- Automated Content Creation
The primary function of NLG is to organise material processed in earlier stages of NLP and NLU into a structured form. NLG can automate the output and provide documentable forms of data, such as analytics reports, product descriptions, data-centric blog entries, etc., by putting this well-structured data in a carefully designed template.
In this scenario, computers that have been algorithmically programmed are completely free to produce material in the format that content creators like. The only action they can take is to advertise it to the target market via well-known media outlets.
- Significant Reduction in Human Involvement
Hiring and training data-literate workers are no longer necessary with Natural Language Generation in place. As far as business theories are concerned, human force is essential to comprehending customers’ requirements and translating them into written narratives.
With Natural Language Generation, however, machines are designed to carefully examine consumer requests, find crucial business-relevant insights, and create summaries based on them.
- Predictive Inventory Management
Given that some products have very high margins, the success of inventory management for any store results in a significant increase in company goals and overall consequent profit. Data is crucial in the supply chain, output, and sales analytics. Based on this information, store managers can decide how to keep inventory at optimal levels.
When it comes to sophisticated NLG, it can serve as an interactive medium for data analysis and streamline and enlighten the entire reporting process. The finest predictive model with clear instructions and suggestions on managing inventories and performing well in stores is available to managers using natural language generation.
Limitations of NLG:
Even while it might save you time, in the long run, you must plan on devoting a significant amount of person hours—not robot hours—to the project before it is operational.
Additionally, it is necessary to identify and organise the metadata, keywords, and other data sources essential to creating the content. NLG will only function with this.
Like human authors, NLG takes time to become familiar with a brand’s distinct voice. However, given the AI/ML component of NLG, it might take the robots longer. Therefore, it could take some time to understand what makes your brand unique.
Additionally, AI cannot fully replace human writers, particularly in inventiveness. Your editors are also safe because the text needs to be edited and proofread in case the prose isn’t up to par.
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When smartly configured, chatbots will be much more intelligent and give more than just simple chats for problems and answers; they will also engage, clarify, and enlighten through advanced NLG.
Advanced Natural Language Generation will aid in establishing a far superior network of engagement between managers, executives, employees, and customers to empower business dynamics and produce accurate output in the shortest amount of time. This network will be synchronised with enterprise-specific workflow management.
When it comes to the topic of whether AI is beneficial or harmful, the answer is complex. It is not absurd to be afraid of omnipotent machines behaving like people. Elon Musk has often cautioned that AI will soon match human intelligence, which will be frightening because humanity’s survival would be on the line.
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