Search Results for: NLP

Deploying large language models (LLMs) in an enterprise setting requires management teams to adopt a strategic approach tailor-made for their organizations, which research consistently shows must consider various essential factors. 

This interview analysis is sponsored by NLP Logix and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

AI initiatives that cannot find ROI have no use in modern business. However, the path to ROI from enterprise-wide digital transformations is never a straight and narrow road. A pre-pandemic survey from MIT Sloan Management Review and Boston Consulting Group found that 70% of companies among those surveyed reported no value from their AI investments. 

In the era of big data, companies need help navigating through an overwhelming volume of unstructured data to uncover meaningful insights. The topic search process presents unique challenges in deciphering data signals and identifying critical information before problems escalate.

As a business practice, model development aims to create a dataset, tailored through machine learning, that can accurately predict outcomes or classify data based on input variables. By following a structured approach, developers can ensure that the model development process is efficient, effective, and reproducible.

Although not often regarded as a technological first-mover, the insurance industry has recently seen robust, even rapid, adoption and deployment of AI capabilities, particularly in those related to natural language processing (NLP). 

This article was originally written as part of a PDF report sponsored by expert.ai, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Episode Summary: In this episode of the podcast, we interview AIG’s Chief Data Science Officer, Dr. Nishant Chandra, about natural language processing (NLP) for internal and team communication. Dr. Chandra talks about how NLP can help with sharing documents with specific team members whose roles warrant viewing those documents.

Episode Summary: Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs.

Episode summary: In this week's interview on the AI in Industry podcast, we speak with Amir Konigsberg, the CEO of Twiggle, about the future of product search - and how eCommerce and retail brands can use natural language processing (NLP) to improve their user experience.