There is undeniable potential in generative AI and large language models, but these tools alone come with significant gaps and challenges. AI often needs additional technologies to create guardrails around data security and response accuracy.
Matthew Payne //
04 Nov 2024
AllegroGraph is designed to seamlessly integrate with LLMs, providing the most secure and scalable AI solution for enterprises. AllegroGraph offers a comprehensive solution platform including Large Language Models (LLMs), Vector generation and storage, Graph Neural Networks, Graph Virtualization, GraphQL, Apache Spark graph analytics, and Kafka streaming graph pipelines.
Jans Aasman //
04 Nov 2024
The ability to centralize the knowledge found in the distributed tools, repositories, and databases for KM practitioners is the defining characteristic of today's technologies. Generative machine learning models not only play pivotal roles in managing that knowledge to make it meaningful to users, but also in enabling them to interface with it on-demand, for ad-hoc use cases.
Jelani Harper //
04 Nov 2024
It's clear from the increase in new and exciting products designed for KM practitioners that KM is gaining in importance within organizations and being recognized as critical to the success of enterprises. The ability of technology to streamline information flows, summarize lengthy documents, surface hidden information from existing data, and make search results relevant and actionable gives companies a competitive advantage.
Marydee Ojala //
09 Sep 2024
The need for comprehensive data management will always be important, and there are many other benefits of digital transformation, but CIOs don't need to delay GenAI projects until the completion of a giant data centralization effort. By adopting a more flexible approach that incorporates GenAI and next-generation BI tools, businesses can navigate the complexities of modern data ecosystems while driving innovation and maintaining a competitive edge in an AI-driven world.
Saurabh Abhyankar //
09 Sep 2024
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.
Scott Francis, Technology Evangelist, PFU America, Inc. //
08 Jul 2024
A strong AI governance program is essential to ensuring compliance and reducing risk. An equally important benefit is that by developing the governance program at the same time the AI application is being developed, issues can be identified early, thus avoiding system redesign or rework on the tail end.
Mark Diamond //
02 May 2024
Multinational companies are generally aware of data transfer laws, but smaller ones just embarking on looking beyond country borders may not be.
Carlos Melendez //
08 Jan 2024
Today's AI has many different flavors and architectures, along with massive amounts of memory and processing capacity. We could probably make better use of this computational power by looking at how we can improve the quality of our queries and, as a result, make better quality decisions.
Art Murray, D.Sc. //
04 Nov 2024
While process mining started years ago as a mainly data-driven exercise, its stated goal is to be knowledge-driven. Given KM's multidisciplinary scope, we can play a major role in achieving that goal. Any process, no matter how simple, has the potential to reach across an entire business ecosystem, including all stakeholders. This seems like a perfect match for collaborative workflow, AI/ML, knowledge graphs, human sensemaking, and many of the other arrows in our KM quiver.
Art Murray, D.Sc. //
09 Sep 2024
The citizen developer movement was heralded as a revolution. Like most revolutions, things have sometimes gone differently than planned. The logic is sound, empowering those who know the business best to build the tools and systems needed to do their job. Ah, if only things were that simple …
Alan Pelz-Sharpe //
09 Sep 2024
The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.
Alan Pelz-Sharpe //
02 May 2024