English 
IBM Japan has launched a new service called IBM Material DX, aimed squarely at fixing how materials research actually works inside manufacturing firms. The core problem is familiar. Data sits in silos, material design depends heavily on expert intuition, and progress comes through slow trial and error. That model does not survive regulatory pressure, cost constraints, or faster product cycles.
Material DX brings together アイビーエム Research technology, consulting, and infrastructure to cover the full materials workflow. Discovery, design, and implementation sit in one loop. At the center is an AI platform pre trained on data covering billions of compounds. This model is used to speed up candidate screening, structural design, and synthesis planning, cutting development time by multiples rather than small gains.
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The service also includes integrated data management that connects internal material data with large public research databases. A conversational interface lets non specialists query material insights directly, lowering dependence on scarce experts. Flexible deployment across on premise, hybrid, and multi cloud setups keeps sensitive data contained.
An added focus is ESG risk. Tools like Safer Material Advisor flag regulated substances such as PFAS early. The move reflects a broader industry shift where AI is no longer experimental in R&D, but operational and increasingly unavoidable.
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