Oracle's Palanivel Saravanan on How AI Can Transform Indian Businesses

AI is reshaping industries worldwide, and India is no exception. As businesses grapple with the increasing complexity of data, the need for innovative solutions has never been greater. Saravanan discusses how HeatWave GenAI can revolutionize data analytics for Indian businesses. Excerpts:

How will HeatWave GenAI's capabilities specifically benefit Indian companies in data analytics?

HeatWave GenAI will benefit Indian companies by enabling them to leverage generative AI directly within their existing databases, eliminating the need for separate AI expertise or additional data movement. This integration simplifies the development process and reduces costs.

Companies can create vector stores for enterprise unstructured content with a single SQL command, perform natural language searches efficiently, and utilise in-database large language models (LLMs) for advanced analytics. This ensures enhanced performance, lower costs, and increased data security, empowering companies to drive digital transformation and accelerate innovation in AI and analytics.

How does HeatWave GenAI's in-database approach address data security concerns in the Indian market?

HeatWave GenAI's in-database approach enhances data security by ensuring data does not leave the database, all processes – AI & Analytics are conducted within the database This reduces the risk of data breaches and unauthorised access, addressing a major concern for Indian companies.

Oracle's robust cloud infrastructure, combined with HeatWave GenAI's integrated security features, provides a secure environment for managing and analysing enterprise data, ensuring that sensitive information remains within the enterprise's control.

Can HeatWave GenAI help Indian developers achieve more with less, considering cost-effectiveness? Are there any workshops planned to train developers in India?

Yes, definitely. HeatWave GenAI empowers Indian developers to achieve more with less through streamlining application complexity, enhancing performance, and reducing costs.

Developers can create advanced AI applications using in-database LLMs and automated vector store features without needing extensive AI knowledge or extra infrastructure. This cost-effective solution democratises access to generative AI, making it accessible to businesses of all sizes. Oracle plans to conduct workshops and training sessions in India to help developers understand and utilise the full potential of HeatWave GenAI, ensuring they can effectively leverage these innovative capabilities.

How can HeatWave GenAI address data silos and infrastructure limitations faced by Indian developers?

HeatWave GenAI provides an integrated, automated AI solution within the database. This approach eliminates the need for separate vector databases and complex data movement processes, enabling seamless access to all enterprise data. The scale-out vector processing and automated in-database vector store streamline the process of managing and analysing large volumes of data.

Indian developers can perform advanced AI and analytics tasks without facing infrastructure bottlenecks, ensuring faster, more accurate insights, fostering innovation and improved decision-making capabilities..

How will Oracle support HeatWave GenAI adoption within the vast Indian developer community?

We offer comprehensive training programs, workshops, and resources tailored to the needs of Indian developers. These include hands-on training sessions, online tutorials, and community events to help developers understand and utilise the full potential of HeatWave GenAI.

Our support team also provides ongoing assistance to ensure a smooth adoption process, enabling developers to integrate and leverage the advanced AI capabilities of HeatWave GenAI effectively.

What upcoming features of HeatWave GenAI would be valuable for Indian developers?

The newly added features are poised to empower Indian developers to innovate and create advanced AI applications more efficiently. We aim to revolutionise how Indian enterprises manage and analyse their rapidly growing data. Here are some of the features that would be valuable for developers:

● In-Database Large Language Models (LLMs): These models simplify the development of generative AI applications, enabling developers to integrate advanced AI capabilities directly within the database without needing external AI expertise.

Automated In-Database Vector Store: This feature allows developers to use generative AI with business documents without moving data to a separate vector database. It automates the process of creating vector stores and embeddings, making it easy to manage and search unstructured data.

● Scale-Out Vector Processing: This delivers very fast semantic search results with high accuracy, enabling developers to perform complex queries efficiently. This can significantly enhance the performance and capability of AI-driven applications.

● HeatWave Chat: This Visual Code plug-in for MySQL Shell provides a graphical interface that allows developers to interact with their data using natural language or SQL. This feature can streamline development processes and make data interaction more intuitive.

How does Exadata Exascale cater to the scalability and cost needs of small and medium-sized enterprises?

By reducing infrastructure costs by up to 95%, Exadata Exascale enables small businesses to take advantage of advanced database technology. It addresses the scalability and cost requirements of SMEs by offering an intelligent data architecture that delivers extreme performance for AI, analytics, and critical workloads.

The elastic, pay-per-use model of Exadata Exascale is especially advantageous for SMEs, allowing them to scale resources as needed without incurring unnecessary expenses. SMEs can specify the necessary number of database cores and storage capacity, ensuring high performance and availability without dedicated database and storage servers. This flexibility allows businesses to start small and expand their resources seamlessly as they grow.

Can you explain how AI Smart Scan enhances AI vector search operations in Exadata Exascale?

AI Smart Scan enhances AI vector search operations in Exadata Exascale by offloading data and compute-intensive tasks to the Exascale intelligent storage cloud. This unique capability allows key vector search operations to run up to thirty times faster, enabling customers to perform thousands of concurrent AI vector searches in multi-user environments.

By leveraging the Exascale intelligent storage cloud, AI Smart Scan optimises the processing of large and complex datasets, making it possible to handle extensive AI workloads efficiently. This seamless interaction between the AI Smart Scan and the intelligent storage cloud enables businesses to scale their AI capabilities effectively, supporting advanced analytics and decision-making processes without compromising on speed or efficiency.