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Agentic AI Meets Quantum – ORCA Computing Featured in GEN News Article

Juliet McGinnis
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A July 2025 collaboration highlights how agentic AI and quantum computing are revolutionizing biomanufacturing, with ORCA Computing leading alongside Novo Nordisk, Henkel, and BCG. Hybrid quantum-classical systems now enable real-time optimization in biologics production, merging AI’s adaptability with quantum’s computational power for faster, smarter manufacturing processes. ORCA’s CCO Per Nyberg emphasizes quantum’s edge: its ability to generate non-uniform, correlated data that mirrors molecular interactions, improving AI model accuracy for complex biological systems. The SIC (Sense, Infer, Control) platform exemplifies this shift, using hybrid architectures to tackle biological challenges more efficiently than classical methods alone. Industry giants and researchers are adopting these technologies to cut costs, reduce errors, and accelerate drug development through precise, data-driven quantum-enhanced AI solutions.
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NEWS NEWS PODCASTS & VIDEOS REPORTS & PUBLICATIONS EVENTS CALENDAR Search for: Agentic AI Meets Quantum – ORCA Computing Featured in GEN News Article JUL 23 2025 Agentic AI is poised to transform biomanufacturing, and quantum computing is playing a pivotal role. In the recent GEN article: Agentic AI is poised to transform biomanufacturing, ORCA Computing is featured alongside SiC Systems, DTU, Novo Nordisk, Henkel, and Boston Consulting Group (BCG), exploring how agentic AI platforms are combining with hybrid quantum–classical systems to enable real-time optimization and smarter biologics production. ORCA’s CCO Per Nyberg highlights the quantum advantage: “The strength of…quantum systems…stems from their ability to produce strongly correlated, non-uniform data that enable the models to learn natural correlations found in molecular distributions and bond formation dynamics.” Our work in the SIC (Sense, Infer, Control) platform reflects a growing shift toward hybrid architectures that can solve complex biological problems faster and more efficiently. READ THE ARTICLE PREVIOUS ARTICLE NEXT ARTICLE

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Source: Orca Computing

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