The Connected Data Podcast

Welcome to the Welcome to the Connected Data Podcast. Connecting Data, People and Ideas since 2016. Community, Events, Thought Leadership. For those who use the Relationships, Meaning and Context in Data to achieve Great things. Bringing together Leaders and Innovators in Knowledge Graphs Graph Databases Graph Analytics / Data Science / AI Semantic Technology Stay tuned and dive into our diverse content. Engage, network, learn and share ideas and best practices. Presentations, Masterclasses, Workshops, Panels, Networking. 👉 https://connecteddataworld.com/ 👉 https://www.meetup.com/Connected-Data-London

The Connected Data Podcast is a technology podcast hosted by Connected Data World, with 41 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Connected Data World hosts The Connected Data Podcast, a technology show with 41 episodes published.

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  Episode #1

  Graph-Based Data Science: Hybrid AI meets data science process | Paco Nathan

  Jan 6, 202536 minS5

  <p>Python offers excellent libraries for working with graphs: semantic technologies, graph queries, interactive visualizations, graph algorithms, probabilistic graph inference, as well as embedding and other integrations with deep learning.</p> <p>However, most of these approaches share little common ground, nor do many of them integrate effectively with popular data science tools (pandas, scikit-learn, spacy, pytorch), nor efficiently with popular data engineering infrastructure such as Spark, RAPIDS, Ray, Parquet, fsspect, etc.</p> <p>In this podcast episode, Paco Nathan reviews kglab – an open source project that integrates most all of the above, and moreover provides ways to leverage disparate te...

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  Episode #12

  Enterprise Knowledge Graphs: Breaking Through Organizational Inertia to Reimagine Data Management | Panel Discussion

  Dec 2, 202439 minS4

  <p>Industry leaders from Accenture, Johnson & Johnson, and the Enterprise Knowledge Graph Foundation dive deep into the transformative potential of knowledge graphs, exploring how these semantic technologies are revolutionizing enterprise data management. </p> <p>Featuring Mike Atkin, Laurent Alquier and Teresa Tung.</p> <p>The conversation reveals a critical shift from traditional data processing to a more nuanced, context-rich approach that prioritizes data meaning and reusability. Participants discuss how organizations are moving beyond experimental pilots to enterprise-wide implementations, driven by a growing recognition that data incongruence is a significant liability in today's data-driven business landscape.</p> <p>The discussion unveils t...

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  Episode #11

  Rebooting AI: Adding Knowledge to Deep Learning | Gary Marcus

  Nov 2, 202439 minS4

  <p>Gary Marcus argues for a shift in research priorities, towards four cognitive prerequisites for building robust artificial intelligence:</p> Hybrid architectures that combine large-scale learning with the representational and computational powers of symbol-manipulationLarge-scale knowledge bases—likely leveraging innate frameworks—that incorporate symbolic knowledge along with other forms of knowledgeReasoning mechanisms capable of leveraging those knowledge bases in tractable waysAnd rich cognitive models that work together with those mechanisms and knowledge bases. <p>Although there are real problems to be solved here, and a great deal of effort must go into constraining symbolic search well enough to work in real time...

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  Episode #10

  The Enterprise Knowledge Graph | Omar Khan and David Newman

  Oct 7, 202433 minS4

  <p>Join Omar Khan and David Newman as they canvas the Enterprise Knowledge Graph, and how you can apply it using its cornerstones of:</p> Foundational building blocksInformation model expressivityMachine understandable representationsTranscending the relational modelHow an EKG expands on a graph and a knowledge graphProvides an infrastructure for Machine LearningContrasting an unlinked with linked data environmentQuestion and answering model emergenceSemantic similarity & embeddingFocused UI <p>---</p> <p>David Newman provides leadership and expertise for the advancement of knowledge graph solutions at Wells Fargo. His team develops innovations that employ key knowledge graph capabilities, including ontology models, semantic and property graph...

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  Episode #9

  Deep Learning on Graphs: Past, Present, And Future | Michael Bronstein

  Sep 2, 202430 minS4

  <p>Graph representation learning has recently become one of the hottest topics in machine learning.</p> <p>One particular instance, graph neural networks, is being used in a broad spectrum of applications ranging from 3D computer vision and graphics to high energy physics and drug design.</p> <p>Despite the promise and a series of success stories of graph deep learning methods, we have not witnessed so far anything close to the smashing success convolutional networks have had in computer vision.</p> <p>In this Michael Bronstein outlines his views on the possible reasons and how the field could progress...

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