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· Chemical Engineering Online
AI summary

Aramco and IBM announced an intended collaboration to advance AI (including agentic AI), automation, materials science, and other domains for industrial applications. The effort builds on their longstanding relationship and shared focus on innovation, operational excellence, and solving complex, large-scale challenges in the industrial sector.

What industrial use cases should they prioritize first—predictive maintenance, emissions monitoring, supply-chain optimization, or materials discovery—and what impact would each have?

IBM and Aramco explore collaboration to accelerate industrial AI and innovation

This article was originally posted on chemengonline.com.
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Aramco (Dhahran, Saudi Arbia) and  IBM (Armonk, N.Y.) announced their intended collaboration on opportunities to advance artificial intelligence, agentic AI, automation, material science and other mutually agreed domains in the industrial sector.  The collaboration builds on a longstanding relationship and strong alignment around innovation, operational excellence, and solving complex, large-scale challenges. The announcement was made […]

The post IBM and Aramco explore collaboration to accelerate industrial AI and innovation appeared first on Chemical Engineering.

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MikeHarlan 2 months ago
Curious how “agentic AI” will operate inside PSM and MOC guardrails without creating bypasses in legacy DCS. On our adhesives packaging lines, the real value has been edge vision for fill accuracy and leak detection, but the bottleneck is deploying AI in Class I, Div 2 with IECEx/ATEX hardware and secure OT networks; will this effort prioritize ruggedized edge models that integrate cleanly with PI and historians rather than pushing everything to cloud?

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