Google Bard is an AI-powered chatbot by Google that supports writing, research, coding, and content summarization. Integrated with Gmail, Docs, and Search, it delivers real-time information, diverse responses, and productivity tools- helping users create, verify, and manage digital content efficiently across everyday workflows. In the swiftly evolving realm of artificial intelligence, Bard transcends being just another search engine; it serves as an experimental system that s

Natural Language Processing trends in 2023 highlight the rise of large language models, improved context awareness, multimodal learning, and industry-specific solutions. Advances in translation, voice assistants, and conversational AI enable more accurate understanding, automation, and knowledge management- helping organizations enhance communication, decision-making, and customer support across digital platforms. Natural Language Processing (NLP) is a sub-discipline of artif

ChatPDF is an AI-powered tool that enables users to interact with PDF documents through conversational queries. By summarizing content, answering page-specific questions, and supporting multilingual dialogue, ChatPDF helps readers quickly understand lengthy or complex files and locate relevant information without manual searching. Introducing ChatPDF: Your AI Assistant for PDF Comprehension   Enter the realm of ChatPDF, an innovative AI tool designed to enhance your PDF readi

Knowledge management leaders such as Dr. Moria Levy emphasize that generative AI is transforming KM from documentation-focused work to strategic leadership. By combining human expertise with automation, organizations can augment decision-making, guide digital change, and strengthen learning cultures- positioning KM professionals as key drivers of innovation and organizational resilience. I've always been an advocate for the power of knowledge management (KM). For over 25 year

AI integration in business focuses on using generative models through custom, off-the-shelf, or hybrid approaches to combine internal and external knowledge. By aligning data security, governance, and workflows, organizations can automate problem-solving, enhance innovation, and deliver personalized insights -maximizing value while managing cost, risk, and operational complexity.     AI is widely discussed today, with many exploring the opportunities it presents. Numerous org

AI marketing uses artificial intelligence to analyze customer data, automate decisions, and personalize campaigns across digital channels. By optimizing content creation, A/B testing, lead generation, and engagement timing, it helps organizations deliver targeted experiences, improve conversion rates, and adapt quickly to changing user behavior in competitive online markets. The digital world is constantly evolving, and as a result, marketing strategies need to adapt to keep

Modern taxonomy development combines AI tools and collaborative platforms to streamline classification of organizational knowledge. By using intelligent grouping, automated suggestions, and real-time collaboration, organizations can build flexible, user-centered structures faster- improving information retrieval, governance, and long-term usability across digital knowledge systems. Introduction Taxonomy, derived from the Greek words taksi (arrangement) and nomos (method/law),

Knowledge representation in AI is the process of structuring human knowledge- facts, concepts, rules, and experience- into formats machines can reason with. By combining relational, hierarchical, logical, and procedural models, AI systems can learn, infer, plan, and make decisions, enabling more accurate problem-solving, automation, and human-like understanding. The essential difference between humans and computers is human wisdom, which is based on advanced knowledge and exp

Generative AI enables machines to create text, code, and insights by learning patterns from large datasets. While powerful for summarization, translation, and brainstorming, it carries risks such as bias and limited transparency. Effective use requires critical thinking, verification, and thoughtful integration into knowledge and decision-making processes. Yes, ChatGPT and all other generative AI tools are here, and they are changing the way we work. The KMGN round table seri

ChatGPT is a conversational AI developed by OpenAI that generates human-like text for writing, summarizing, and problem-solving. It supports knowledge work by refining content, suggesting structures, and accelerating research- while requiring human review to manage accuracy, relevance, and ethical responsibility. Artificial intelligence is hardly a new concept to us. Nevertheless, as we are exposed to more and more options and tools, we realize that the relationship between m

New AI productivity tools use machine learning to automate content creation, design, audio, video, and knowledge management tasks. By reducing manual effort, improving accuracy, and accelerating workflows, these tools help individuals and organizations work faster, make better decisions, and focus on creativity and strategic value. The AI (artificial intelligence) world is everywhere and has recently gained momentum thanks to ChatGPT and Midjourney. Using various tools, artif

AI trends highlight the rapid expansion of intelligent systems across work, security, mobility, and creativity. Advances in large language models, cybersecurity, no-code platforms, and automation- driven by organizations like OpenAI- enable organizations to augment human skills, improve decision-making, and adopt scalable, data-driven solutions for long-term innovation and competitiveness. This year will probably see Artificial Intelligence advancing on its path to becoming t

AI-powered search engines use machine learning, NLP, and entity-based systems to understand user intent and deliver direct, relevant answers. Platforms like Google apply knowledge graphs, context analysis, and voice and visual search to improve accuracy, reduce search time, and help users find reliable information faster across digital environments. The field of search engines is evolving in recent years, especially due to the emergence of AI applications, which signify a hug

AI projects in organizations succeed when knowledge management and artificial intelligence are developed together. By sharing expertise, structuring information, and fostering collaboration, KM professionals help align AI initiatives with real business needs -enabling scalable solutions, cross-sector innovation, and sustainable value creation across diverse industries. KMGN. KM-AI course, 23rd session. Wrap up. 62 KMers' from India, Indonesia, U.A.E., Argentina, Israel, Italy

Human empowerment in the AI era, as emphasized by Dr. Moria Levy, means preparing society, organizations, and individuals to work alongside intelligent systems. Through ethics, upskilling, job redesign, and lifelong learning, people can retain strategic leadership, adapt to automation, and ensure AI enhances human creativity, judgment, and responsibility. KMGN, KM AI course. Session 22- nearly the end... Today I lead the conversation on our future- human beings, in an era of

Starting an AI journey as a knowledge manager means focusing first on business needs, not technology. As advised by Dr. Moria Levy, KM professionals should listen carefully, clarify challenges, align data and knowledge assets, and propose practical AI solutions- positioning themselves as essential partners in successful, value-driven digital transformation. KMGN KM-AI course, session 21. We are approaching the last set of lectures in this course. Today Annie led the session a

Successful AI projects rely on structured lessons learned and continuous improvement, as emphasized by Dr. Moria Levy. By using iterative reviews, bias analysis, and focused debriefings, organizations can reduce errors, improve model performance, and transform trial-and-error cycles into sustainable learning and long-term business value. KM AI KMGN course- Session 20. Today I spoke about Lessons Learned in AI projects. Lessons Learned debriefing sessions are critical in Artif

Managing business risks in KM-AI initiatives requires strong governance, simplified business rules, and diverse expert involvement. As highlighted by Dr. Moria Levy, combining knowledge engineering with AI analytics reduces bias, improves model training, and enables early detection of weak signals-strengthening decision-making and organizational resilience. Aug 3rd. Session 19 of our KMGN Knowledge-Management-Artificial-Intelligence course. Art Murray speaks about implementin

Knowledge engineering connects business challenges with AI systems by structuring expert knowledge into data, models, and rules. As outlined by Dr. Moria Levy, this iterative process combines human insight, taxonomies, and machine learning to improve decision quality, accelerate learning, and ensure AI solutions deliver sustainable organizational value. KMGN: KM-AI course Session 17, July 27th. Today Art opens a window to the fabulous world of knowledge engineering. We are pa

Leveraging AI through knowledge management means aligning content services, classification, and lessons learned with machine learning initiatives. As emphasized by Dr. Moria Levy, KM professionals add value by structuring data, improving quality, and supporting knowledge engineering- ensuring AI projects are reliable, scalable, and aligned with real organizational needs. Hi all. Today I am excited. In our AI KM course, we reached today the set of sessions dealing with the one