KAPS GROUP LLC

Join us for a great Text Analytics Forum (Text Analytics Forum 2024 - The Leading Text Analytics Conference (text-analytics-forum.com)) and 4 co-located conferences: KMWorld, Taxonomy Boot Camp, Enterprise Search and Discovery, and Enterprise AI World. Use the code, TR200 to get $200 off. Some of the Highlights include: If the enterprise knew, what the enterprise knows Peio Popov, SVP Financial Services, Ontotext The proposed case study outlines the development of an information discovery application that integrates a knowledge graph with a large language model. The focus of the presentation will be on demonstrating how well-established knowledge management techniques can enhance the effectiveness and user-friendliness of contemporary Retrieval-Augmented Generation (RAG) information retrieval systems. Hybrid Approaches to Green Information Management: A Case Study Urmi Majumder, Principal Data Architecture Consultant, Enterprise Knowledge Nina Spoelker, KM Consultant, Enterprise Knowledge This session will explore how a large supply chain organization implements green information management to support sustainability goals. Presenters from Enterprise Knowledge will showcase a hybrid AI framework, combining heuristic and LLM-based approaches, to effectively analyze and reduce duplicate content across enterprise repositories at scale. The presentation will demonstrate the environmental benefits of reducing duplicate content, focusing on carbon footprint reduction. It will also address how this information generates aggregate statistics and resultant carbon footprint, pushing for a cultural shift towards greener information management. Attendees will gain insights into the practical implementation of AI-driven content analysis frameworks, the environmental impact of effective data management, and the importance of integrating ESG goals into information management strategies. Improved Regulatory Recommender in Healthcare: Right training, Right place, Right time Laura Rodriguez, Knowledge Manager, HealthStream Helmut Nagy, CPO, Semantic Web Company GmbH HealthStream maintains a data set of regulatory requirements for professional licensing for healthcare professionals and provides courses to meet many of these requirements. We want to explore a Regulatory Recommender that would use the tags applied to courses and regulations to pair an individual with the appropriate training material specific to their license, care setting, and state. It is critical that these recommendations be accurate as this is legal content that has implications for professionals maintaining licensure if we are suggesting incorrect courses to fulfil the requirements.

Join us for a great Text Analytics Forum (Text Analytics Forum 2024 - The Leading Text Analytics Conference (text-analytics-forum.com)) and 4 co-located conferences: KMWorld, Taxonomy Boot Camp, Enterprise Search and Discovery, and Enterprise AI World. Use the code, TR200 to get $200 off. Theme: New Synergies – New Solutions Some of the Highlights include: Intelligent Terminology matching using a Knowledge Graph and Vector database Jans Aasman, CEO, Franz Inc. In the era of big data and artificial intelligence, accurate and efficient terminology matching is critical for numerous applications, including information retrieval, data integration, and semantic search. This presentation introduces an innovative approach to intelligent terminology matching by leveraging a knowledge graph in conjunction with a vector database. Our method addresses the challenges of synonymy, polysemy, and contextual relevance in terminology matching. Attendees will gain insights into the technical details, practical implementation, and potential applications of this cutting-edge approach to terminology matching. Are You GenAI Ready? Kickstart Your Readiness Assessment Charity Queret, Chief GenAI Consultant, GenIQ Advisors   GenAI is poised to revolutionize industries, but are you ready to harness its potential? This session goes beyond the hype, equipping you with a practical framework to assess your organization's GenAI readiness. In this interactive session, you will: • Discover why a thorough readiness assessment is the secret weapon of successful GenAI adopters. • Unveil a structured framework to evaluate your organization's preparedness across these key metrics. Identify strengths to build on and weaknesses to address before GenAI implementation. Enhancing Content Strategy Information Management with Large Language Models and Symbolic AI: Techniques and Tools for Efficient Annotation and Indexing Sebastian Gabler, Chief Customer Officer, Semantic Web Company The advent of large language models (LLMs) has given these approaches a significant boost. Effective GenAI strategies, as suggested by Gartner and other analysts, now require efficient and accurate labeling of corpora at unprecedented volumes and speeds. Addressing the challenges of unlocking unknowns from latent content, guiding users in discovering new insights, and preventing hallucinations in GenAIs has become increasingly critical. This session will introduce key concepts and present interactive and automated tools for annotating, classifying, and indexing unstructured text and documents. A central concept is inference tagging, a method that extends document annotation beyond explicit concepts by deriving new information from ontologies and rules.

Join us for a great Text Analytics Forum (Text Analytics Forum 2024 - The Leading Text Analytics Conference (text-analytics-forum.com)) and 4 co-located conferences: KMWorld, Taxonomy Boot Camp, Enterprise Search and Discovery, and Enterprise AI World. Use the code, TR200 to get $200 off. Theme: New Synergies – New Solutions Hybrid text analytics (the intelligent interplay of human and software) has been an essential part of deriving value from enterprise text for many years, but with the revolutionary debut of ChatGPT has that changed? Does GPT/LLM make text analytics obsolete? Or does the interplay of text analytics and GPT/LLM create new synergies and new solutions that deliver even greater value than either alone? As the initial hype subsides, the answer is clear: New Synergies and New Solutions. Join us to explore what these new solutions are, what kinds of value they bring to the enterprise, how to build solutions that take advantage of their synergies, how text analytics makes the new AI smarter, and safer and much more. Some of the Highlights include: A three-hour workshop:   GenAI & Text Analytics: Creating a Foundation for Business Value Monday, November 18: 1:30 p.m. - 4:30 p.m. GenAI continues to astound, but it also continues to struggle to produce real business value outside of a few applications like customer support chat and the productivity gains of producing rough drafts. While those are valuable, there is so much more that GenAI could do if it can overcome its current well-known limitations. GenAI’s limitations include its tendency to hallucinate, that is, make up false facts. LLMs were trained on public information, but as we’ve seen many times, the content and vocabularies behind the enterprise firewalls are quite different; this is why transparency—understanding why it says what it does—is so important. Text analytics can refine the general answers of GenAI with text analytics precision. Learn how to set up both a text analytics and GenAI environment starting with selecting the right components (software, LLMs, etc.). Then get the basics for creating a text analytics foundation (autocategorization, data extraction, and more) and a GenAI approach that combines text analytics, prompt engineering, merging enterprise LLMs with the larger public LLMs, and RAG capability. This collaboration of text analytics and GenAI has the potential to transform how your business operates and competes. Join our experienced speaker and Text Analytics Forum chair to get tips and techniques to develop a strong foundation for business value in your organization. Ask the Experts Panel A panel of 4 text analytics experts who will answer questions that have been gathered before the conference, during the conference, and some additional questions from the program chair. This has always been one of our most popular features, so come prepared with your favorite questions and be ready to learn.

Join us for a great Text Analytics Forum (Text Analytics Forum 2024 - The Leading Text Analytics Conference (text-analytics-forum.com)) and 4 co-located conferences: KMWorld, Taxonomy Boot Camp, Enterprise Search and Discovery, and Enterprise AI World. Use the code, TR200 to get $200 off. Some of the Highlights include: Effective integration and responsible use of AI platforms into day-to-day Text Analytics Alice Chung, Sr. Analytics Manager - Medical Insights Lead, Genentech With the revolution and continuous introduction of AI technologies, how should one consider an effective integration and responsible use in day-to-day effort for text analysis. What are some of the synergies and watch outs that one should consider to deliver greater value and efficiencies for effective decision-making. In this session, we will talk about how best to adopt Hybrid text analytics (the intelligent interplay of human and software) and mindset to achieve the optimal outcome in a responsible way. . Even LLMs need metadata... Kyle Strand, Lead KM Specialist and Head of Library, Inter-American Development Bank (IDB) Fabiola Di Bartolo, Senior Associate, Inter-American Development Bank This presentation focuses on the application of Large Language Model (LLM) powered generative AI in improving knowledge discovery within our open access publications catalog. The integration of this technology facilitates more intuitive and effective interactions with our extensive corpus of over 13,000 publications. The LLM plays a role similar to that of a generalist. However, achieving precision and accuracy necessitates the detailed contextualization that metadata and knowledge graphs provide. These elements provide context akin to that of specialists, ensuring each piece of information is accurately contextualized and thus enhancing the overall reliability of the discovery process. We use a Retrieval-Augmented Generation (RAG) approach, leveraging advanced metadata and knowledge graphs to enrich AI-generated responses with relevant context. Text Analytics and Generative AI: A Winning Combination for Regulations Analysis Tom Sabo, Advisory Solutions Architect, SAS Meredith McGill, Sr Associate Technical Consultant, SAS Government organizations are responsible for reviewing public commentary to proposed regulations and responding to all comments, which can take thousands of hours. In this presentation, we offer a solution to address this challenge by automating the process with text analytics and generative AI. We will highlight how text analytics serves as a method to calibrate the data which is fed into generative AI models to enhance accuracy, time to value, and provide a layer of traceability to summaries. 

Today’s Theme – Implementation of Gen AI and Text Analytics: Join us for a great Text Analytics Forum (Text Analytics Forum 2024 - The Leading Text Analytics Conference (text-analytics-forum.com)) and 4 co-located conferences. Use the code, TR200 to get $200 off. Conference Theme: New Synergies – New Solutions Hybrid text analytics (the intelligent interplay of human and software) has been an essential part of deriving value from enterprise text for many years, but with the revolutionary debut of ChatGPT has that changed? Does GPT/LLM make text analytics obsolete? Or does the interplay of text analytics and GPT/LLM create new synergies and new solutions that deliver even greater value than either alone? As the initial hype subsides, the answer is clear: New Synergies and New Solutions. Join us to explore what these new solutions are, what kinds of value they bring to the enterprise, how to build solutions that take advantage of their synergies, how text analytics makes the new AI smarter, and safer and much more. Genius Without the Gibberish: How RAG and Text Analytics Boost Generative AI Reliability Mark Gross, President, Data Conversion Laboratory Retrieval-Augmented Generation (RAG) is a technique that allows LLMs to incorporate external information from a corpus of documents during the text generation process. This approach mitigates the hallucination problem by grounding LLM responses in verified data sources. The key components of text analytics—text preprocessing, natural language processing (NLP), entity extraction, and structuring data—play a critical role in this process. These techniques ensure that data fed into an LLM is clean, relevant, and structured in a way that maximizes the accuracy and reliability of the responses. From Prototype to Production: Navigating the Challenges of Implementing Generative AI Fernando Rejon Barrera, CTO, Zeta Alpha Join me as I share insights from our own development of Zeta Alpha's public Discovery platform in AI R&D, as well as from assisting enterprise clients across diverse sectors like chemical, HR, high-tech industrial, and regulatory industries on their path from prototype to production. Discover the pitfalls in treating Generative AI projects as standard software development endeavors, and learn how to avoid wasted effort on solutions that will soon be provided by LLM vendors. Tutorial: building your first genAI solution and enhancing its value with text analytics Sergei Ananyan, CEO, Megaputer Intelligence We provide a step-by-step tutorial demonstrating the creation of a gen AI-based solution for VoC data analysis. Attendees will learn the basics of prompt engineering, see how to adjust prompts to improve quality of results, what techniques help eliminate hallucinations, how to enhance the value of results with text analytics, and what additional engines can be used to produce easy-to-comprehend summary of results for decision makers.

Join us for a great Text Analytics Forum (Text Analytics Forum 2024 - The Leading Text Analytics Conference (text-analytics-forum.com)) and 4 co-located conferences: KMWorld, Taxonomy Boot Camp, Enterprise Search and Discovery, and Enterprise AI World. Use the code, TR200 to get $200 off. Theme: New Synergies – New Solutions Hybrid text analytics (the intelligent interplay of human and software) has been an essential part of deriving value from enterprise text for many years, but with the revolutionary debut of ChatGPT has that changed? Does GPT/LLM make text analytics obsolete? Or does the interplay of text analytics and GPT/LLM create new synergies and new solutions that deliver even greater value than either alone? As the initial hype subsides, the answer is clear: New Synergies and New Solutions. Some of the Highlights include: Human and machine intelligence working together Art Murray, CEO, Applied Knowledge Sciences, Inc. As generative AI continues its rapid evolution, the extent of its impact and the number of industries disrupted are increasing at an equally rapid pace. Whether the disruption represents a crisis or opportunity is up to us. But first, we need to step away from the hype, take a look under the hood, and see what’s really going on inside. Only then can we rationally think about how it might fit into the big picture. The Coming Union of Text Analytics and GenAI David Seuss, CEO, Northern Light Text analytics has been around a lot longer than generative AI (GenAI) and the technologies serve different purposes. But the combination of the two offers exciting potential for businesses. For instance, consider the possibilities of marrying the trend analysis and insight extraction capabilities of text analytics to GenAI's text summarization capabilities. The result might be thought of as a "consultant in a box" – a powerful fusion that promises to dramatically enhance productivity in functions like strategic analysis and planning Gen AI and Text Analytics in the Enterprise: Building an Application Platform Tom Reamy, CEO and Founder, KAPS Group For all the success that GPT has accomplished in the public sphere, it has a number of limitations within the enterprise that text analytics can overcome – if done correctly. This session will describe how text analytics’ auto-categorization and data extraction can overcome the 5 well-known limitations of Gen AI and at the same time, how the combination can greatly enhance a wide range of enterprise applications. For example, while RAG can help with hallucinations, the search component is only as good as the basic enterprise search, which we’ve seen needs text analytics to really shine.

Gen AI and Text Analytics: Fixing Flaws What is smarter and safer than Gen AI? The combination of text analytics and Gen AI! For how text analytics can fix many of Gen AI’s flaws, take a look at this video - https://lnkd.in/gs2GCENQ from a recent webinar, Deep Text and Dynamic Text, by Tom Reamy (KAPS Group www.kapsgroup.com ) and Kim Larsen (Luminoso www.luminoso.com ). We cover Gen AI Basics and the basic flaws: §General: –         Tendency to hallucinate –         Lack of transparency – no one knows how they work –         Amount and quality of data needed to train –         Security issues - Jailbreaks – get Gen AI to break its own rules §Enterprise: –         Public vocabulary, not reflective of enterprise language –         Fine tune with enterprise content – costly, low accuracy It ends with a discussion of how text analytics can fix the flaws §What do you get by adding TA? Accuracy! Which impacts all attempts to utilize and analyze documents. Two keys: Capturing high quality training content and detecting and fixing hallucinations.

Deep Text and Dynamic Text On September 17, Luminoso Technologies (http://www.luminoso.com/) and the KAPS Group (http://www.kapsgroup.com/)  did a webinar on Deep Text and Dynamic Text.  The primary theme was the synergies of deep text, which focuses on the detailed analysis of text to uncover hidden meanings and patterns, and dynamic text, which emphasizes real-time text processing for immediate insights. Some of the highlights were: ·      What are the fundamental capabilities of text analytics (deep text) and how to implement them ·      How unstructured text is a myth and how to use document structure for greater accuracy ·      Basic characteristics and value of dynamic text and how to combine deep text and dynamic text ·      The five layers of an enterprise text analytics platform and the applications that can be built on one ·      Gen AI basics and the fundamental flaws and issues of current Gen AI approaches ·      How text analytics can eliminate or alleviate those flaws and achieve real business value If you are interested in getting a copy and a video of the presentation, send an email with your name, company, and email address to tomr@kapsgroup.com

Webinar: Deep Text and Dynamic Text One Week Left to Register! Luminoso Technologies, a leader in natural language understanding, and KAPS Group, a renowned text analytics consulting firm, are excited to present a Webinar on the value of Deep Text & Dynamic Text which will take place on September 17, 2024, at 1 PM EDT. It will provide valuable insights into the synergies of deep text, which focuses on the detailed analysis of text to uncover hidden meanings and patterns, and dynamic text, which emphasizes real-time text processing for immediate insights. Participants will gain a comprehensive understanding of: ·      The key synergies and applications of deep text and dynamic text analytics. ·      How to leverage these technologies to drive business value. ·      Understanding the power of text analytics to make Gen AI smarter and safer. For more information and to register - https://lnkd.in/gUXWcGh5

Kim Larson is speaking at Deep Text & Dynamic Text. Check out the event details.