Infosys and LFN Partner to Promote AI Adoption in Global Networks
Infosys and Linux Foundation Networking (LFN) partner to promote the adoption of domain-specific artificial Intelligence (AI) across global networks. As part of this initiative, Infosys has contributed its Responsible AI Toolkit and AI application development framework, which are a part of Infosys’ Topaz AI offerings, to two new networking projects: Salus and Essedum.
Salus, the responsible AI Toolkit by Infosys offers advanced technical protection to detect and reduce AI risks like bias, privacy breaches, and harmful content, while enhancing model transparency.
Essedum. developed on Infosys' code and existing AI networking solutions, maximizes its AI application development framework to accelerate the integration of AI data, models, and applications within the networking industry.
The CTO of Infosys, Mohammed Rafee Tarafdar stated, “At Infosys, we are deeply committed to advancing innovation that solves complex challenges while upholding transparency, fairness, and trust. Our collaboration with the Linux Foundation is a testament to our shared vision of embedding Responsible AI principles into actionable solutions. Linux Foundations efforts in driving excellence in open-source networking projects have been remarkable.
With our strong AI capabilities, powered by Infosys Topaz, we actively support this endeavor, helping organizations harness domain-specific AI responsibly and effectively across global networks.”
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Arpit Joshipura, GM, networking, Edge and IoT at the Linux Foundation, stated, “Our efforts to further domain-specific AI are coming to fruition with the addition of these new projects, and we are incredibly grateful to Infosys for their contributions, creating combined, open and unified frameworks will only accelerate AI-driven innovation. By introducing accessible solutions for Responsible AI and integrating data sharing, domain-specific AI tools, and application development under one roof, we are enabling the industry to build smarter, more efficient networks.”