GenAI

Listen to the podcast on this blog In past blogs, we discussed data science, artificial intelligence, and how they affect business and technology. We covered the changes in data platforms,…

Large Language Models (LLMs) like GPT have transformed how we interact with and leverage AI. While these models have shown impressive capabilities across various tasks, the need for industry-specific LLMs…

This cross-region inference capability in Amazon Bedrock enables customers to build highly scalable, resilient, and cost-effective generative AI applications that can adapt to dynamic usage patterns and regional variations, all while leveraging the consistency and simplicity of the Bedrock API.

As I have frequently written on this blog, the telecom industry is on the cusp of major changes (as are other industry verticals), but a new report suggests many telco leaders may not be adequately prepared.

Pretraining financial services workloads for Large Language Models (LLMs) and Generative AI (Gen AI) is a complex and challenging task due to the unique requirements of the financial industry. The…

 This blog explores the lifecycle of LLMs, from development to deployment, with real-world examples from industry leaders.

Join my team at AWS for an enlightening event that explores the intersection of GenAI development and inclusivity. Experience real-life demos of GenAI applications created by diverse builders. Engage in…

The Generative AI (GenAI) landscape is rapidly evolving, and the cloud-native GenAI stack is the foundation for building, deploying, and scaling these powerful AI models. This blog dives into the…

The rise of Generative AI models is fueling a surge in building multi-tenant chatbots. These chatbots can be customized for each client (tenant) with their specific needs and data, while still running efficiently on familiar, cost-effective infrastructure.

Containerization is a software deployment method that packages an application’s code with all the files and libraries it needs to run on any infrastructure