This new video explains natural language processing: what it is, how it works, and what can it do for your organisation. Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on giving computers the ability to understand human language, combining disciplines like linguistics, computer science, and engineering.
Companies need NLP because much of their crucial data, especially in industries like insurance, healthcare, and pharmaceuticals, exists as unstructured text in formats like PDFs, scanned documents, or audio, which computers struggle to process compared to clean numerical data.
The most effective way a business can get value out of NLP is by implementing it as part of a wider strategic and business-aware initiative, such as the development of a predictive risk model. This allows the company’s C-level to turn unstructured text documents into a quantifiable risk or cost estimate for the next quarter, delivering a phenomenal return on investment and a competitive advantage, especially in traditionally conservative industries. While lower-impact initiatives can save staffing costs (e.g., by triaging customer support), the highest impact comes from these larger strategic projects that provide predictive business insights.
Dive into the world of Natural Language Processing! Explore cutting-edge NLP roles that match your skills and passions.
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When can lawyers, litigants in person, and expert witnesses use AI in court documents? In the last few years in the UK, the USA, Canada, Ireland and other jurisdictions, cases have been reported where submissions were made to a court where the author of a document used generative AI tools such as ChatGPT to create those documents. This has wasted court time, resulted in submissions being rejected or even resulted in changes to cost awards.
A person has recently returned from a camping trip and has a fever. Should a doctor diagnose flu or Lyme disease? Would this be any different if they had not mentioned their camping trip? Here’s how LLMs differ from human experts.
How can you predict customer churn using machine learning and AI? In an earlier blog post, I introduced the concept of customer churn. Here, I’d like to dive into customer churn prediction in more detail and show how we can easily and simply use AI to predict customer churn.
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