Question: Can you recommend a data platform that can handle large-scale AI and HPC workloads with high performance and sustainability?

If you need a powerful data platform for large-scale AI and HPC workloads with high performance and sustainability, WEKA is a good option. This platform is optimized for high-performance workloads like AI and HPC, delivering up to 10M IOPS in the cloud and 10-100x better performance than traditional data infrastructure. It can scale up to 10 exabytes of data and includes sustainability features to minimize energy usage and carbon footprint.

Another good option is NVIDIA, a major player in AI computing. NVIDIA offers a variety of solutions to help accelerate AI adoption and optimize data center energy efficiency. Its platforms include NVIDIA Omniverse for synthetic data generation, RTX AI Toolkit for AI model deployment, and the EGX Platform for accelerated computing. NVIDIA's solutions are geared for data scientists, developers, and content creators who want to accelerate AI application development and deployment.

If you're looking for a cloud-based option, Scaleway offers a full platform to develop, train and deploy AI models. It offers a resilient and sustainable cloud environment with options like bare metal, high-performance computing and predictable pricing. Scaleway's focus on sustainability and GDPR compliance means it's a good option for companies that want to minimize their environmental impact while keeping data private.

Last, Cloudera offers a hybrid data platform for ingesting, processing and analyzing data in the cloud and on-premise environments. The platform aggregates large data sources into a single trusted system for insights and AI model training, and it's well suited for industries like financial services and healthcare. Cloudera's platform is built on Apache Iceberg, which provides data reliability and flexibility for managing data lakehouses across multiple clouds.