Generative AI

A research report  conducted just prior to the passing of US tariffs ) from the Boston Consulting Group (BCG) points to a notable increase in IT budgets for 2025, with…

As organizations navigate the convergence of Edge AI, GenAI, and IoT, understanding proven architectural patterns becomes crucial for building robust, scalable solutions that deliver real business value. The integration of…

In Part 1 of our series –https://www.vamsitalkstech.com/ai/engineering-the-ai-factory-blueprint-for-industrial-scale-ai-infrastructure/ , we explored the foundational concepts of AI factories and their critical infrastructure components. I intend to do a series of blogs on…

The evolution of Radio Access Networks (RAN) towards AI-native architectures represents a fundamental shift in telecommunications infrastructure. This blog explores the eight key architectural principles that define AI-Native RAN, examining…

The advancement of artificial intelligence and machine learning has made it necessary to significantly transform data center architecture. Traditional data centers, which were mainly designed for data storage and retrieval,…

The rising number of connected devices and data demands are putting a significant strain on network infrastructure. AI-native networks, especially those using agentic AI, are addressing these challenges by implementing…

This post delves into the key technical innovations, challenges, and emerging trends, providing a deeper understanding for a technical audience.

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.

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