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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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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 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 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 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 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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Yaakov BelchYaakov Belch is an AI researcher with strong ideas about the role of humans in AI systems. Instead of "human in the loop," he argues, we should put "humans in control."Yaakov's research looks at business contracts and how knowledge graphs and AI systems can both capture their meaning more accurately and help managers make better busines…
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Michael IantoscaWhere content, knowledge management, and AI converge, you'll find Michael Iantosca.As many in the AI world flock to probabilistic models like LLMs, Michael takes a deterministic approach to content management and knowledge engineering, using ontologies and knowledge graphs to ground content in a concrete facts.This approach embodies…
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Fran AlexanderWhen Fran Alexander looks at the current AI landscape she sees some interesting parallels between the Alien vs Predator science fiction franchise and the way RAG and other architectures are combining LLMs and knowledge graphs.We talked about: the analogy she draws between the Alien and Predator science fiction franchise with LLMs and …
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Andreas BlumauerEvery enterprise nowadays is awash in data, content, and knowledge, the understanding of which is all too often available only in employees' heads.Forward-thinking businesses are moving to knowledge graphs to capture that tacit knowledge so that they can better understand and use it.Andreas Blumauer shows how those graphs work best …
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Jessica TalismanJessica Talisman is a seasoned information architect with decades of experience across a variety of domains.She's done a lot of education and outreach around her semantic and and information architecture practices. One of the most important lessons she's learned is the crucial role of standards like the W3C SKOS model to bring struc…
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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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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 !Di Boris Shalumov
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