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Natural Language Processing
Natural Language Processing is the branch of artificial intelligence (AI) concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.

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Features

AI 100 Trailblazer: Openstream.ai® - Conversational AI for Visionaries

Openstream.ai serves global enterprises with a visionary platform continually tuned by world-class AI experts, orchestrating the latest AI approaches and tools to deliver state-of-the-art conversational experiences.

Gaining competitive advantage from non-textual information

With the right approaches, tools, and self-service facilities, it is possible for users possessing any degree of technical aptitude to quickly find and avail themselves of non-textual content.

How (and when) to update your KM strategy

Ensuring that KM endeavors support different access points, systems, and user preferences is a prime consideration for updating KM strategies. Vendors may also supply newfound capabilities (which an organization previously hadn't had access to) that warrant updating a KM strategy to avail organizations of new possibilities.

Using Generative AI for real-world KM solutions

The overarching utility derived from GenAI capabilities relies on organizations' proficiency to reduce redundancy to minimize inaccuracies, monitor outputs, and trace responses to the underlying data sources from which their responses are produced.

ViewPoints

The transformative role of AI in the next generation of records management

While there are many ways AI will disrupt and advance the records management process, these four key applications will make the biggest impact: automating document classification and tagging, records retention and data hygiene, leveraging natural language processing for record analysis and predictive analytics for records management.

Microsoft’s Copilot: A force multiplier for KM

Generative AI (GenAI) applications will increasingly transform organizations' IT platforms. Companies of any size that opt to create robust apps on their own, however, are in for a protracted, complex, and expensive experience.There's a better way: Buy into what I call a GenAI ecosystem from a vendor in whose tech you are already invested. These ecosystems are comprised of the sum of services customers mostly need to build and launch robust apps.

KM and AI: Experts look at what lies ahead for 2024

AI and dreams of its potential rocked this past year as companies moved quickly to embed and offer their own version of chat assistants, predictive and generative AI, and more

Columns

Pushing the boundaries of knowledge curation

Knowledge democratization occurs in two directions, seemingly engaged in an endless tug of war: acquisition and dissemination.

Truth, lies, and large language models

The good news is that the problem of chat AI's proclivity for hallucinating is well-recognized by the organizations creating these marvels, and they realize that it is a danger to the world and to their success, not necessarily in that order of priority. Until that problem is solved, chat AI engines need to lose their self-confidence and make it crystal clear that they are the most unabashed and charming liars the world has ever seen.

When is good enough enough?

Our goal should be to improve the quality of knowledge assets and their accuracy and relevance in use. Much of this will come from human expertise and effort, increasingly combined with the power of AI.

AI technologies upending traditional KM

If we are not careful and proactive about it, the concept and importance of knowledge itself may soon become blurred or lost.

Knowledge Management Whitepapers

CX Knowledge Manager Playbook

Extracting knowledge from your data:Learn how a semantic layer helps you find, access, integrate, and re-use your enterprise knowledge.

Unified Data Layer: Transforming Data Choas into Actionable Insight

2024 KMWorld Guide to KM Trends, Products, and Services

Natural Language Processing Companies and Suppliers
Natural Language Processing Directory