Pattern Recognition
Glossary page
Pattern recognition is a field of study within artificial intelligence and machine learning that focuses on the identification and analysis of patterns or regularities in data. It involves developing algorithms and models that can recognize and classify patterns in various types of data, such as images, text, sound, or numerical data. Pattern recognition techniques are widely used in applications like image recognition, speech recognition, data mining, and predictive analytics. The goal of pattern recognition is to enable computers to automatically identify and understand patterns, leading to automated decision-making and intelligent data analysis.
https://www.arm.com/glossary/pattern-recognition#:~:text=Pattern%20recognition%20is%20a%20data,familiar%20patterns%20quickly%20and%20accurately.
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Connect & Integrate: Simplifying certificate management with AI
Connect & Integrate brings the T-Systems AI power within the solution to support organizations scale up and become efficient in their business workflows within Catena-X. The cross-use-case AI layer sits at the intersection of data preparation and exchange as a business enabler directly within the workflows.
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Tushar Yadav
Aug 03, 2026
IDSA’s Dataspaces and AI: Our input from applied Physial AI in RoX with dataspaces
The IDSA position paper "Data Spaces and AI" argues that the coordination problems facing agentic AI — identity, trust, access control, governance and provenance across organizational boundaries — are the same ones dataspaces already solve for cross-company data sharing. Rather than reinventing them for autonomous agents, the peer-to-peer logic behind standards like ISO/IEC 20151 can transfer directly to agent-to-agent interaction. T-Systems contributes a concrete proof point: RoX, a German consortium where competing robotics players and institutes such as DFKI and DLR share a sovereign data foundation for AI-based robotics. Built on Tractus-X and aligned with IDSA and Gaia-X, it already powers live robotic cells and is now extending that governed data supply to an agentic layer — showing in practice what the paper argues in principle.
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Chris S. Langdon
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First Korea–Europe peer-to-peer dataspace transaction: L&F and EU Tier 1
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Chris S. Langdon
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