A Guidepost for Navigating the GenAI Landscape – Intel & OPEA

Organizations are increasingly turning to AI to meet the demands of a fast-paced, data-driven environment that requires speed, efficiency, and reliability. With AI, businesses aim to achieve real-time insights that enhance decision-making, customer experiences, data security, and remote monitoring.

Open-source projects have significantly accelerated AI innovation, leading to the rapid development of generative AI (GenAI). However, this fast-paced progress has resulted in a fragmentation of techniques and tools, creating challenges for businesses trying to adopt GenAI. Developers aiming to harness its potential need to navigate a wide array of options, which can be overwhelming. At this early stage, collaboration within the open-source community is crucial for building a solid framework to guide the creation and evaluation of flexible GenAI solutions. Open-source methodologies are tried and proven to deliver better solutions and more choice to the enterprise and Intel aims for the same with GenAI.

Open Platform for Enterprise AI (OPEA) provides a comprehensive and easy-to-understand overview of a GenAI workflow, which includes retrieval augmented generation (RAG) and other necessary functionalities. The workflow is built on various open and proprietary components, such as GenAI models—including large language models (LLMs), large vision models (LVMs), and multimodal models. It also encompasses data ingestion and processing, embedding models and services, indexing and vector/graph data stores, retrieval and ranking mechanisms, prompt engines, guardrails, and memory systems.

Intel and OPEA

OPEA, a Sandbox Project for streamlining secure and cost-effective generative AI (GenAI) deployments for businesses, focuses on enhancing interoperability within the diverse and evolving ecosystem of retrieval-augmented generation (RAG) technology. Enterprises face challenges due to the lack of standardization across RAG components, making it difficult to deploy open and interoperable solutions efficiently. OPEA seeks to address these challenges by collaborating with the industry to standardize components such as frameworks, architecture blueprints, and reference solutions, thereby promoting the adoption of RAG solutions and fostering innovation within an open ecosystem. Intel, in collaboration with other OPEA partners, will lead the creation of open, resilient, and modular GenAI systems that are adaptable, scalable, and designed to meet enterprise-level requirements.

The composable framework is just one aspect of what OPEA offers to developers. It works alongside an assessment framework that Intel has already shared in the OPEA GitHub repository. This setup provides a standardized way to evaluate and grade GenAI workflows on key factors like performance, trustworthiness, scalability, and resilience, ensuring they are ready for enterprise use. Intel aims to add pre-built reference implementations to the OPEA Github repository, ready for immediate use. Intel further plans to:

• Publish a technical framework that outlines key concepts.
• Provide reference implementations for GenAI pipelines using secure solutions powered by Intel Xeon Scalable Processors and Intel Gaudi AI Accelerators.
• Expand infrastructure in the Intel Tiber Developer Cloud to support ecosystem development, AI acceleration, and the validation of current and future pipelines, including RAG.

Intel’s approach is grounded in the principle of an open ecosystem. By fostering a collaborative environment, the company enables various players to work together, driving innovation more rapidly and effectively. Computing in the datacenter and enterprise client is buouyed by a rich open source software ecosystem. Recognizing the importance of open source in AI software development as well, Intel shares this platform with the open-source community and collaborates with the community to enhance and expand the platform, helping developers meet their needs and accelerate the business value of GenAI.