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.
Ready to take the next step in your NLP journey? Connect with top employers seeking talent in natural language processing. Discover your dream job!
Find Your Dream JobGuest post by Alex Nikic In the past few years, Generative AI technology has advanced rapidly, and businesses are increasingly adopting it for a variety of tasks. While GenAI excels at tasks such as document summarisation, question answering, and content generation, it lacks the ability to provide reliable forecasts for future events. GenAI models are not designed for forecasting, and along with the tendancy to hallucinate information, the output of these models should not be trusted when planning key business decisions. For more details, a previous article on our blog explores in-depth the trade-offs of GenAI vs Traditional Machine Learning approaches.

After this ruling, will tech companies move all model training to data centres that they consider “copyright safe”? Will we see a new equivalent of a “tax haven” for training AI models on copyrighted content? An “AI haven”? This article is not legal advice.

This free A/B test calculator will help you compare two variants of your website, A and B, and tell you the probability that B is better. You can read more about A/B testing in our earlier blog post on the subject. You may also be interested in our Chi-Squared sample size calculator which will help you calculate the minimum sample size needed to run a Chi-Squared test, given an expected standardised effect size.
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