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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

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.

The future of KM is not simply AI

Until KM systems can achieve trust in AI, a totally AI-centric workplace will be a fantasy. The future of KM will be based on collaborative work habits, fueled by technology that encourages knowledge sharing, enhances productivity, supports employees to have a healthy work life, and accepts that not every aspect of knowledge management is technology-reliant.

2023 Readers' Choice Award- Best Knowledge Graphs: Franz Inc. AllegroGraph - LLMs and Knowledge Graphs for AI in the Enterprise

Franz Inc. not only offers cutting-edge technology but also provides a suite of services for building industrial-strength Knowledge Graphs. By combining the semantic richness of AllegroGraph with the natural language processing capabilities of LLMs, organizations can unlock the full potential of their data, ensuring that AI-driven insights are grounded in facts.

The future of knowledge management: Talking to documents with generative AI

The fundamental pillars of KM—taxonomies, domain-specific data models, knowledge extraction, search, and text analytics—are as pertinent today as they ever were. Now, generative AI has rendered these constructs much more accessible to the enterprise. Its long-standing utility will be determined by surmounting models' tendencies to generate contrived, inaccurate responses while embedding them into core KM processes.

ViewPoints

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

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

Unlocking the Power of Knowledge Management for Enterprise AI with Anzo and Knowledge Guru

100 Companies that Matter in Knowledge Management 2024

A Blueprint for Transforming Paper-Intensive Processes

eBook: Navigating IM In an Evolving Remote/Hybrid World

Natural Language Processing Companies and Suppliers
Natural Language Processing Directory