Generative AI infrastructure software provides the foundational tools and platforms necessary for developing, deploying, and managing AI models. Here are seven leading solutions in this domain:
Databricks Lakehouse Platform: Combining the capabilities of data warehouses and data lakes, Databricks offers a unified platform for data engineering, machine learning, and analytics. It supports the development of generative AI models by providing scalable computing resources and collaborative tools.
IBM Watsonx: IBM's AI and data platform, Watsonx, includes a suite of tools for building and fine-tuning large language models. It offers a studio for AI development, a data store, and governance tools, facilitating the creation of customized generative AI solutions.
Microsoft Azure AI: Part of the Microsoft Azure cloud platform, Azure AI provides a comprehensive set of services, including machine learning, cognitive services, and AI infrastructure. It supports the development and deployment of generative AI models with robust tools and frameworks.
SAS Viya: An AI, analytics, and data management platform, SAS Viya integrates with major large language models like GPT-4 and Gemini Pro. It offers tools for predictive modeling, econometrics, and algorithmic bias detection, supporting the development of generative AI applications.
Dynatrace: Specializing in software intelligence, Dynatrace provides an observability platform powered by AI. It offers infrastructure monitoring, application performance management, and digital experience monitoring, essential for managing the performance and reliability of generative AI applications.
VAST Data Platform: Designed for AI and deep learning workloads, VAST Data offers a data computing platform that enables organizations to store, manage, and process large amounts of data efficiently. Its architecture supports the high-performance requirements of generative AI model training and inference.
Amazon Web Services (AWS) AI Services: AWS provides a broad range of AI services and infrastructure, including machine learning platforms, pre-trained AI services, and customizable AI models. It supports the development of generative AI applications with scalable computing resources and specialized tools.
These platforms offer diverse capabilities to support the development and deployment of generative AI models, catering to various organizational needs and technical requirements.