If you're looking for a cloud computing foundation that can power high-performance computing and AI workloads, Google Cloud is a great option. It's got a rich set of developer tools, including generative AI models, prepackaged solutions and Vertex AI for training and deploying AI agents and generative AI services. Compute services include customizable virtual machines, containerized computing and storage, and data analytics tools like BigQuery, real-time data processing and Looker. Google Cloud also has a range of security tools like Cloud Armor and Cloud CDN, so it's a good option for companies trying to modernize their businesses.
Another good option is Lambda, a cloud computing foundation geared for AI developers. It lets you provision on-demand and reserved NVIDIA GPU instances and clusters for training and inferencing AI. It's got preconfigured ML environments for popular frameworks, scalable file systems and pay-by-the-second pricing, which makes it a good option for developers who need fast and cheap ways to tackle big AI jobs.
If you need a foundation for high-performance computing and AI that's got a more accessible interface, Bitdeer is a good option. It's got an AI cloud instance for fast setup, a powerful data center management interface and support for complex AI workloads with custom NVIDIA software stacks and high-speed networking. It's also got flexible pricing options and cloud mining support, so it's good for people who need high-end computing power.
Last, Anyscale is a foundation for developing, deploying and scaling AI applications. It's got the highest performance and efficiency with features like workload scheduling, heterogeneous node control and GPU and CPU fractioning to get the most out of your resources. It's based on the open-source Ray framework, so it supports a broad range of AI models, and it's got strong security and governance features, too, which makes it a good option for big businesses that need high-end AI.