Cognitive Computing

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Cognitive Computing refers to the simulation of human thought processes through a computerized model. This involves self-learning systems that use techniques such as data mining, pattern recognition, and natural language processing to imitate the functioning of the human brain. The ultimate goal of cognitive computing is to create automated IT systems capable of independently solving problems without human intervention. Machine learning algorithms are used by cognitive computing systems to continuously acquire knowledge from the data fed into them. The systems refine their approach to pattern recognition and data processing to become capable of anticipating new problems and generating possible solutions.

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First Korea–Europe peer-to-peer dataspace transaction: L&F and EU Tier 1

In November 2025, the first peer-to-peer dataspace transaction between Korea and Europe was completed, with L&F (Korea) sharing product carbon footprint data with the automotive division of a major European Tier 1. Orchestrated by Prof. Chaisung Lim of Konkuk University and enabled by T-Systems' Dataspace-as-a-Service, the exchange ran on the Eclipse Tractus-X stack with the IDSA protocol and Gaia-X trust framework — the same standards underpinning Catena-X. The transaction proves that sovereign, governed data sharing can now travel across regions and regulatory environments without centralising data or surrendering control. Beyond secure, trusted file transfer, it points to a strategic foundation for AI-ready data and new value-creation scenarios, including controlled collaboration across ecosystems and even between competitors.

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Chris S. Langdon

Jun 29, 2026

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AIAG-Catena-X-SOD-Detroit 2026: AIAG conference & Supplier onboarding day

This article highlights the transition of Catena-X (CX) in North America from pilot initiatives to large-scale adoption within the automotive industry. It positions CX as a decentralized data ecosystem—an “Internet for data”—that addresses critical challenges such as quality management, sustainability compliance, and battery passport reporting. Drawing on insights from the AIAG Catena-X Conference and Supplier Onboarding Day in Detroit, the article emphasizes that digital transformation and AI initiatives are fundamentally data challenges, often hindered by fragmentation across organizations and supply chains. Catena-X provides a practical, business-oriented approach by combining trusted data-sharing infrastructure, ready-to-deploy use cases, and a scalable onboarding model for suppliers. The experiences shared by industry leaders demonstrate how CX accelerates time-to-value, enabling companies to transform fragmented data into interoperable, trusted data flows that underpin generative AI, digital twins, and future digital business models.

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Chris S. Langdon

Jun 01, 2026

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Hannover Messe 2026: Physical AI meets data ecosystems and the enterprise dataspace

Hannover Messe 2026 highlighted the convergence of Physical AI, data ecosystems, and industrial policy. The article shows how dataspace technology enables both global data ecosystems and enterprise dataspaces, forming the foundation for AI-data readiness and the extended enterprise.

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Chris S. Langdon

May 21, 2026