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. LLM and NLP (natural language processing) are two terms often used together as LLM models have pretty much revolutionised the field of NLP – machines can now understand and generate text at an almost human-like level and at an unprecedented scale too.
Above: video of Thomas Wood presenting Harmony at the AICamp meetup on 27 March 2024
How NLP Enhances Healthcare Delivery and Operations (+ 8 NLP Strategies and 8 Applications) In recent years, there has been a lot of news about Natural Language Processing (NLP) and its applications for healthcare. NLP is the field of computer science and AI focusing on getting computers to understand how we speak and write. NLP is changing healthcare for a number of reasons. For example, in many healthcare systems there is an overwhelming amount of patient information and notes that need quick sorting. NLP in healthcare helps improve patient care and makes healthcare work better.
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? What role will AI play in creative industries in the future? Artists are worried that DALL-E could put them out of a job. Creative writers are raising the alarm about ChatGPT. Hollywood actors are worried about their voices being cloned. Before long, a similar debate could arise about AI-generated music.
Fast Clinical AI We are developing a natural language processing (NLP) tool, Fast Clinical AI, for identifying risk, cost, recruitment and enrolment criteria, and consent complexities of clinical trials using natural language processing, which can be integrated to data sources from trial management platforms, allowing pharma companies to leverage AI in their operations.
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. A prime example is how Google’s algorithm works to provide relevant results when people enter specific search terms.
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. It is unknown exactly how and when AI will become impactful in law, but it is important to prepare for this change.
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