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Interviews with experts on semantic technology, ontology design and engineering, linked data, and the semantic web.
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In just a few years Knowledge Graphs have exploded in usage, as has their impact in the world of Artificial Intelligence. Semantic AI has become a significant part of text analytics, search engines, chat-bots and more. And yet, few people outside of niche tech communities are fully aware of how semantic knowledge graphs can be leveraged.In the Podcast "Chaos Orchestra" we will explore how Knowledge Graphs can be applied over the next decade to boost many areas of Artifical Intelligence and a ...
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Andrea Volpini: The Role of Memory in Digital Branding for AI – Episode 27
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Andrea VolpiniYour organization's brand is what people say about you after you've left the room. It's the memories you create that determine how people think about you later.Andrea Volpini says that the same dynamic applies in marketing to AI systems. Modern brand managers, he argues, need to understand how both human and machine memory work and th…
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Jacobus Geluk: Use-Case Trees for the Data-Product Marketplace – Episode 26
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Jacobus GelukThe arrival of AI agents creates urgency around the need to guide and govern them.Drawing on his 15-year history in building reliable AI solutions for banks and other enterprises, Jacobus Geluk sees a standards-based data-product marketplace as the key to creating the thriving data economy that will enable AI agents to succeed at scale…
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Rebecca Schneider: Knowledge Graphs and Enterprise Content Strategy – Episode 25
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Rebecca SchneiderSkills that Rebecca Schneider learned in library science school - taxonomy, ontology, and semantic modeling - have only become more valuable with the arrival of AI technologies like LLMs and the growing interest in knowledge graphs.Two things have stayed constant across her library and enterprise content strategy work: organization…
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Ashleigh Faith: Knowledge Graph Modeling and AI Architectures – Episode 24
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Ashleigh FaithWith her 15-year history in the knowledge graph industry and her popular YouTube channel, Ashleigh Faith has informed and inspired a generation of graph practitioners and enthusiasts.She's an expert on semantic modeling, knowledge graph construction, and AI architectures and talks about those concepts in ways that resonate both with h…
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Panos Alexopoulos: Semantic Modeling for Data – Episode 23
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Panos AlexopoulosAny knowledge graph or other semantic artifact must be modeled before it's built.Panos Alexopoulos has been building semantic models since 2006. In 2020, O'Reilly published his book on the subject, "Semantic Modeling for Data."The book covers the craft of semantic data modeling, the pitfalls practitioners are likely to encounter, a…
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Mike Pool: Is it time for a moratorium on the word “semantics”? – Episode 22
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Mike PoolMike Pool sees irony in the fact that semantic-technology practitioners struggle to use the word "semantics" in ways that meaningfully advance conversations about their knowlege-representation work.In a recent LinkedIn post, Mike even proposed a moratorium on the use of the word.We talked about: his multi-decade career in knowledge represe…
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Margaret Warren: Image Metadata for Knowledge Graphs and People – Episode 21
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Margaret WarrenAs a 10-year-old photographer, Margaret Warren would jot down on the back of each printed photo metadata about who took the picture, who was in it, and where it was taken.Her interest in image metadata continued into her adult life, culminating the creation of ImageSnippets, a service that lets anyone add linked open data description…
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Jans Aasman: Knowledge Graphs in Modern Hybrid AI Architectures – Episode 20
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Jans AasmanHybrid AI architectures get more complex every day. For Jans Aasman, large language models and generative AI are just the newest additions to his toolkit.Jans has been building advanced hybrid AI systems for more than 15 years, using knowledge graphs, symbolic logic, and machine learning - and now LLMs and gen AI - to build advanced AI s…
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Juan Sequeda: LLMs as a Critical Enabler for Knowledge Graph Adoption – Episode 19
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Juan SequedaKnowledge graph technology has been around for decades. The benefits so far accruing to only a few big enterprises and tech companies.Juan Sequeda sees large language models as a critical enabler for the broader adoption of KGs. With their capacity to accelerate the acquisition and use of valuable business knowledge, LLMs offer a path t…
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Jesús Barrasa: Pragmatic Advice for Graph Technology Adoption – Episode 18
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Jesús BarrasaOver his 20-year career, Jesús Barrasa has spanned the worlds of object-oriented property graphs and assertion-based knowledge graphs.He knows as much about these two foundational technologies as anyone and offers pragmatic advice to help architects and engineers decide which approach will work best for their needs.We talked about: hi…
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#10 - The Future of Data Management - Sean Martin
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Knowledge Graphs revolutionise the way companies make use of their data. The technology has the potential to turn every digitised piece of knowledge in a company into actionable insights. You can exceed even Google’s Search capabilities by creating an intelligent platform with knowledge graph. Many of us can imagine our idealistic future data dream…
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Can Knowledge Graphs help to build better Cognitive Models? How will Knowledge Graphs look like in the future and how will we interact with them? Why didn't Knowledge Graphs solve COVID-19-related data problems? How far away are Technocracy and Digital Immortality? Extrapolating from 40 years of Knowledge Graphs and cognitive models with Dr. Jans A…
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Graph Neural Networks are very effective in dealing with complex network data structures to perform label and link predictions. They can process typological and structural information from social networks to protein pathways. But can they also work with multi-dimensional and dynamic data models of Semantic Graphs? What information loss does one hav…
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We have never been closer to knowledge democratisation and collective intelligence. However, the enabling technology is a blessing and a curse at the same time. Fake News and Filter Bubbles dominate the spread of information in social networks and search engines, influencing our personal trust chains and constantly directing our perspective on the …
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#06 - Knowledge democratization & Abstract Wikipedia - Denny Vrandečić
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Wikipedia, Google and social networks transformed the way of knoweldge aggregation and spread - but can we make all of humanty's knoweldge machine-readable? Are Knoweldge Graphs enough to achieve that? What technological and social challenges come with Knoweldge democratization? Inspiring and thought provoking conversation with Denny Vrandečić, Hea…
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#05 - Ontologies, Knowledge & Human-Machine Interfaces - Panos Alexopoulos
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Ontologies are a way to represent and communicate knowledge, understandable to both - machines and humans. But what level of expressivity is needed to be able to convey human thoughts and human understanding of the world to machines? Are current graph representation models sufficient for generalisation and reasoning? How many ontology engineers wou…
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It is nearly impossible for a scientist to process all relevant information to one's field of research. Due to “antique”, document-based knowledge transmission methods, scientists are deriving hypotheses from a smaller and smaller fraction of our collective knowledge. It seems that science has outgrown the human mind and its limited capacities. But…
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Deep Learning has proven to be the primary technique to address a number of problems. But each application of AI inevitably encounters unexpected scenarios (edge cases) in which the system does not perform as required. Knowledge-infused learning uses commonsense knowledge encoded in Knowledge Graphs in order to provide capabilities like generalisat…
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#02 - Intelligence & NLU, the ultimate test for AI - Walid Saba
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Despite huge investments into Deep Learning we did not get close to making machines understand natural language (NLU). Can semantic approaches make up for weaknesses of Deep Learning like for example abstraction and generalization ? If humans would need to touch hundreds of hot ovens before they being able to extrapolate and generalize - our lives …
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Can we build a #google for enterprise data? How can #KnowledgeGraphs & #HybridAI help executives make better business decisions, and accelerate the evolution towards enterprise collective intelligence? “The direction is very clear and you can’t stop it” - Inspiring talk with Dan McCreary !저자 Boris Shalumov
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