In natural language processing, we have the concept of word vector embeddings and sentence embeddings. This is a vector, typically hundreds of numbers, which represents the meaning of a word or sentence.
We often hear about the potential for AI in healthcare, or how it could transform organisations like the UK’s National Health Service.
Large Language Models and NLP: Overview AI has seen remarkable advancements in recent years and one of its most notable ones is the development of LLMs or large language models.
Upcoming Tech Talk: at the AICamp AI Meetup (London): AI, Generative AI, LLMs Are you interested in how AI is transforming the field of social sciences?
How NLP Enhances Healthcare Delivery and Operations (+ 8 NLP Strategies and 8 Applications) Natural Language Processing (NLP) in healthcare is just what the industry needs.
Natural language processing (NLP) is revolutionising how businesses interact with information. But large language models, or LLMs (also known as generative models or GenAI) can sometimes struggle with factual accuracy and keeping up with real-time information.
The AI ethics debate: does generative AI harm creative industries? Artists are worried that DALL-E could put them out of a job.
In 2016, the British computer scientist and Turing Award winner Geoffrey Hinton stated: We should stop training radiologists now. It’s just completely obvious that within five years, deep learning is going to do better than radiologists.
Some finance companies have contacted Fast Data Science with a need for a very customised named entity recognition solution. Clients prepare lists of investments which could be funds or companies, and request a check on those companies.
What is NLP in business environments? Natural language processing (NLP) is a branch of AI (Artificial Intelligence), empowering computers to not just understand but also process and generate language in the same way that humans do.
We examine the potential influence of machine learning and AI on the legal industry. AI has transformed a number of industries but has not yet had a disruptive impact on the legal industry.
How can we analyse and predict pedestrian (foot traffic) data? In today’s hyperconnected world, our smartphones have become inseparable companions, constantly gathering and transmitting data about our whereabouts and movements.
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