Generative AI (GenAI) has gained significant prominence in the last couple of years. This technology breakthrough has created the possibility of integrating various innovative use cases into applications across domains. Organisations and developer communities are exploring tools and frameworks that allow them to integrate GenAI use cases into their existing applications. The Spring AI framework is one such great open source tool that helps Java developers to rapidly adopt GenAI.
Rise of AI and generative AI (GenAI)
Creating AI models and solutions around AI has traditionally been very time consuming as well as resource- and costintensive. This has led to innovations around AI being limited to a few organisations with very deep pockets. But with tech advancements like the adoption of GPUs; and availability of foundational models from tech giants like Google, Meta, OpenAI, etc, building AI models has become cheaper and easier. Many of the popular foundation models are now available as services. Also, many open source models are being developed. Apart from the generic ones, various domain-specific models are also being built to address the needs of targeted domains. Prompt engineering and retrieval augmented generation (RAG) are helping make GenAI more usable for various innovative use cases. Developers can worry less about the model intricacies and can focus more on how to make best use of the models.
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This technical paper authored by Lokesh Chenta and Vijayabhaskar Reddy was published in Open Source For You magazine.