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NVIDIA has introduced over twenty-five new microservices tailored for healthcare enterprises globally, providing access to cutting-edge generative AI advancements from any location and across various cloud platforms.

This latest suite of NVIDIA healthcare microservices encompasses optimized NVIDIA NIM™ AI models and workflows equipped with industry-standard APIs, facilitating the creation and deployment of cloud-native applications. These microservices offer sophisticated capabilities in imaging, natural language processing, speech recognition, and digital biology for prediction, simulation, and generation.

Moreover, NVIDIA has made available accelerated software development kits and tools, including Parabricks®, MONAI, NeMo™, Riva, and Metropolis, now accessible as NVIDIA CUDA-X™ microservices. These resources aim to expedite healthcare workflows in areas such as drug discovery, medical imaging, and genomics analysis.

The launch of these twenty-five microservices marks a significant step forward for healthcare organizations, leveraging the potential of generative AI to revolutionize processes for pharmaceutical companies, medical professionals, and hospitals. Possibilities include screening vast numbers of drug compounds, enhancing patient data collection for early disease detection, and deploying intelligent digital assistants.

Researchers, developers, and practitioners can seamlessly integrate these microservices into both new and existing applications, leveraging their copilot capabilities to augment life-saving endeavors across various environments, from cloud-based solutions to on-premises systems.

Kimberly Powell, Vice President of Healthcare at NVIDIA, emphasized the transformative impact of these developments, stating, “For the first time in history, we can represent the world of biology and chemistry in a computer, making computer-aided drug discovery possible. By facilitating the easy construction and management of AI solutions for healthcare enterprises, we’re empowering them to fully harness the potential of generative AI.