NLP is a relatively new field that is advancing so rapidly that significant new advances are being announced every few days. For example, in just the past fortnight Amazon have announced the release of their AlexaTM 20B language model with significant improvements in summarisation and translation and OpenAI have released Whisper – a new open-source machine learning model for multi-lingual automatic speech recognition.

What does this mean in practical terms for business? Here are five things that computers are now very good at, which most businesses do not know about, and where there are significant efficiencies and opportunities to be realised immediately:

Translating text from one language to another

Computers can now do this almost as well as humans and orders of magnitude more efficiently. Google translate is already obsolete. Any business that produces text in multiple languages should be looking at how technology can do this cheaper, quicker and better. Amazon’s AlexaTM 20B language model is just the latest advance in this space.

Writing compelling, persuasive business prose quickly and cheaply

Businesses that write blogs, tenders, proposals or marketing copy can benefit from using modern NLP capabilities to produce high-quality content more quickly and more efficiently. No one would create a financial model without using Excel. In the very near future, no-one will write professional prose without using AI writing support. This technology is here now but is not yet widely adopted. My own business, AutogenAI, is building enterprise-level text production solutions in exactly this space.

Transcribing from human speech more quickly and more accurately than most human transcribers

Automating speech-to-text not only unlocks the potential for businesses to save money on expensive transcription services but it also makes possible the transcription of far more spoken content. For example, it is now possible and economical to capture and efficiently share everything that is said at all company meetings across the globe.

Understanding and categorising human language

This has applications across most businesses. For example, tech can now be used to understand customer reviews and social media posts. This can be used to identify trends in customer sentiment, spot opportunities for improvement, or simply to better understand how customers feel about a product or service.

Summarising long pieces of text

This was considered a very difficult problem in NLP but recent advances have catapulted computers forward. It is now possible for a computer to read a long document and produce a shorter summary that captures the main points. This is applicable across almost all business areas and functions. For example, a computer can read through a large number of legal documents and produce a summary of the key points.

Language technology is going to transform the world over the next decade. We want to demonstrate what it can deliver now.