Schema Design

Just wrapped up an incredible two days at TEDAI San Francisco filled with discussion and insights into how AI is transforming a wide variety of areas, from science to the creative fields. A few highlights: - Theoretical physicist Carlo Rovelli gave a fascinating presentation on time’s fluidity and relativity and its implications for AI and physics. - Surya Ganguli of Andreessen Horowitz spoke about how AI mirrors the brain's predictive capabilities through synaptic networks, offering glimpses of future breakthroughs in explainable AI. - Max Jaderberg of Isomorphic Labs shared exciting developments with AlphaFold and in-silico open-ended discovery—a paradigm where AI models complex natural processes, experimenting in-silico to bring discoveries back to the real world. Day two shifted to practical applications, from AI agents to generative video. Omar Shaya of MultiOn discussed how AI agents are taking on increasingly complex tasks, while Joshua X. of HeyGen emphasized the growing importance of real-time video generation for personalized content. These discussions tied into a panel on Science and Creativity where I reflected on a concept I’ve been giving much thought to lately: Knowledge Interfaces. These are the next generation of tools that will enable the creation and dissemination of knowledge, combining the two pillars of Search and Learning which are key to AI’s ability to synthesize massive datasets. Steven Johnson's remarks on NotebookLM highlighted this potential, showing how AI can help us manage and process complex knowledge. Reflecting on the event, I’m excited about the future of multimodal AI and the opportunity for next-generation interfaces that can integrate both AI agents and Generative AI to reshape how we learn and interact. Thanks to Sam De Brouwer and Walter DE BROUWER for putting together this fantastic event – looking forward to next year. #TEDAI #ai #knowledgeinterfaces

It was an absolute pleasure teaching the Experiential Data Lab at MOME Budapest last week. The students were incredibly talented, and the workshop results didn't fail to impress. Among the projects: A media installation consisting of a Kinect and a projector, visualizing Spotify data via sensing the position of the user in space. Thanks to Mary Karyda, Ph.D. and Mihály Minkó for their support and participation, to the students for their enthusiasm and creativity, and to Peter Molnar for the opportunity. Looking forward to the next one! #datavisualization #experiencedata #design

The new The World Bank Group Scorecard provides a yardstick to measure how we deliver on our mission to end extreme poverty and boost shared prosperity on a livable planet, helping us be more transparent and accountable to strengthen the impact of our work. https://lnkd.in/e4TvVbXQ

Excited to announce that in less than two weeks I’ll be returning to MOME Budapest to co-teach a week-long, in-person workshop called the Experiential Data Lab. I’m thrilled to once again be collaborating with Mary Karyda, Ph.D. and Mihály Minkó from the Data Storytelling Hub at MOME. Together, we’ll be working with a multidisciplinary group of students to push the boundaries of data visualization, exploring how to envision data in dynamic, 3D physical and digital environments. Thanks to Peter Molnar and MOME for supporting this initiative, and looking forward to an inspiring week! #datavisualization #experientialdata #design #MOME

It was a privilege to be part of the panel discussion at #EES2024 in Rimini on Friday, “From Data to Decision: The Role of KM and Communication in Evidence-Based Policy Making.” One of the central themes we explored was Building Trust and how to establish and maintain trust when using data to inform policy and decision-making. Several key points that emerged from our conversation: 1. Integrity: Building trust begins with the fundamentals—data cleanliness, data accuracy, data provenance, and data transparency. Confidence in data begins with clean and accurate data, using and citing trustworthy sources, and clarifying how data was collected, processed, and presented. 2. Context: Building trust is also about conveying meaning. Integrating qualitative data around the human impact of the data is important to provide the sentiment, context, and narrative needed to connect with stakeholders on a human level. Without context, even the most precise data analysis can fall flat or be misinterpreted. 3. Empathy: Communicating data effectively is about connecting with people on an emotional level. Building trust through data integrity and context is not enough. People also want to trust an intermediary or messenger who conveys information in a relatable and understandable way. Empathy is also important for reaching audiences with limited time or attention. 4. Dialogue: Building trust is about facilitating an ongoing conversation, not dictating conclusions. We can use data to encourage open dialogue and explore issues in 360 degrees by highlighting the various diverse perspectives and collectively exploring how data can guide better decisions. My main takeaway: Building trust through communicating data is about creating relationships, conveying meaning, and being accountable to the people and communities impacted. A special thanks to Patrizia Cocca for organizing and to my fellow panelists—Cristian Crespo, Darlene Brady Christopher, CPTD, and Anne-Claire Luzot—for such an engaging discussion. #DataVisualization #DataViz #TrustInData