CGG unveils AI Cloud solution powered by NVIDIA for optimized AI and HPC workloads
PARIS: CGG, a renowned leader in technology and high-performance computing (HPC), has unveiled its innovative AI Cloud solution. This advanced platform is engineered to cater to the burgeoning needs of data-heavy sectors such as life sciences, digital media, manufacturing, and geoscience. The AI Cloud is poised to transform how these industries manage their complex and resource-intensive AI workloads.
The newly launched AI Cloud by CGG is a fusion of the latest high-performance architecture and state-of-the-art NVIDIA H100 Tensor Core GPUs, meticulously configured for AI fine-tuning and inference. This robust solution is complemented by a customizable software environment, pre-installed to meet the unique requirements of each client. With the expertise of CGG’s specialists, clients are liberated from the intricacies of cloud computing and infrastructure management, allowing them to concentrate on enhancing their production, advancing insights, and making more informed decisions.
Furthermore, the AI Cloud integrates CGG’s seven decades of pioneering contributions to scientific computing, thereby optimizing energy-efficient, industrial-scale production for its clientele. In an industry characterized by rapid technological advancements, CGG pledges to continuously upgrade its AI Cloud ecosystem with optimized hardware and breakthrough software solutions, in collaboration with its partners.
Agnès Boudot, the Executive Vice President of HPC & Cloud Solutions at CGG, emphasized the escalating demand for AI, data science, and HPC workloads. She noted that progressive companies are eager to leverage deep learning, large language models, and large-scale intelligent data processing. These technologies are instrumental in automating and revolutionizing complex business operations, fostering innovation, and maintaining a competitive edge. In response to this demand, CGG’s AI Cloud offering emerges as a comprehensive solution, enabling clients to streamline their workloads efficiently while adhering to sustainability commitments.
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