ClearML
ClearML is an AI Infrastructure Platform that enhances AI performance and scalability through an Infrastructure Control Plane, an AI Development Centre, and a GenAI App Engine, thereby easing AI processes from development to production and optimising resource utilisation.
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Description for ClearML
ClearML is an AI Infrastructure Platform engineered to optimise AI performance and scalability for organisations with a three-tier solution that enhances AI workflows from development to production. It offers an Infrastructure Control Plane for the administration of GPU clusters, an AI Development Centre for model creation and evaluation, and a GenAI App Engine for the deployment of Large Language Models (LLMs) onto clusters.
Features of ClearML
- Infrastructure Control Plane: Enables users to connect and administer GPU clusters (on-premises, cloud, or hybrid) with integrated security, streamlined Kubernetes deployment, and GPU-as-a-Service (GPUaaS).
- AI Development Centre: Delivers a comprehensive environment for the development, training, and evaluation of AI models, featuring a cloud-like experience with one-click infrastructure access and integrated tools for data management, monitoring, automation, and pipelines.
- GenAI App Engine: Seamlessly distributes Large Language Models (LLMs) onto clusters, managing networking, authentication, and security, facilitating swift GenAI deployment and iteration at scale.
- Optimised AI Workflows: Integrates and enhances the complete AI workflow from experimental to production.
- Cost Optimisation: Seeks to enhance GPU utilisation while minimising computational and human resource expenses.
Use Cases for ClearML
- Oversee and enhance GPU resource allocation across various scenarios to ensure optimal performance and cost-effectiveness.
- Expedite the creation and deployment of AI/ML models from inception to production.
- Streamline the implementation of Generative AI (GenAI) workloads with customisable workflows and controlled access.
- Enhance resource efficiency and maximise return on investment by optimising GPU utilisation and expediting the time-to-market for models and applications.
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