How AI is transforming modern cloud security on AWS; Latest AI-driven threat detection & prevention techniques; Real-world use cases of GenAI enhancing cloud defense; Strategies to prepare your organization for the AI-first security era.

A 120-minute live masterclass exploring how AI and Generative AI are revolutionizing cloud protection, reshaping security operations, and helping businesses build a more resilient AWS ecosystem. Learn how AI is transforming modern cloud security on AWS, AI-driven threat detection and prevention techniques, real-world GenAI use cases, and strategies to prepare your organization for the AI-first security era.

Comparison of generative vs discriminative AI and semi-supervised learning concepts.

An introduction to AI-DLC, a transformative approach to software development that integrates AI as a central collaborator, with three core phases: Inception, Construction, and Operations.

Overview of Generative AI lifecycle operational excellence on AWS.

Postgres and the Artificial Intelligence Landscape, artificial intelligence use has exploded, with much anticipation about its future. This talk explores many of the advances that has fueled this explosion, including multi-dimensional vectors, text embeddings, semantic/vector search, transformers, generative AI, and Retrieval-Augmented Generation (RAG). The talk includes semantic/vector search and RAG examples. It covers how the valuable data stored in databases can be used to enhance AI usage.

This presentation introduces Gene.AI’s dual virtual assistant ecosystem - the Service Virtual Assistant (SVA) and the Commercial Virtual Assistant (CVA). They built to transform enterprise operations through Generative AI and data intelligence.

An expert talk on AI agent design and real-world use cases.

explores how GenAI is transforming how we access and interact with online content.

In this talk, you will learn about GraphRAG, a technique that combines graph databases with generative AI to improve the quality of LLM-generated content. We will explore the terms Retrieval-Augmented Generation (RAG) and Context Engineering, and how GraphRAG can be used in both scenarios. The topic is aimed at Generative AI practitioners who are familiar with vector-based Retrieval-Augmented Generation (RAG) and would like to understand how the approach of GraphRAG can improve the quality of LLM-generated content.

DORA metrics are the gold standard for measuring software delivery performance and stability. However, conventional methods of capturing these metrics are increasingly challenged by siloed DevOps toolchains, manual data collection, and the growing prevalence of AI-generated code in production. Enterprise delivery pipelines demand resilience and accuracy, but today's measurement systems struggle with both integration complexity and the specialized expertise required to operate in large, distributed environments. This talk will discuss these challenges in detail and show how Generative AI can elevate DORA from static, descriptive dashboards to dynamic diagnostic, prescriptive, and predictive insights—unlocking a new era of actionable intelligence.

Offers strategies for preparing people, processes, and governance to adopt GenAI-enabled DevOps at scale.

Showcases real-world use cases of Generative AI for developers and operations teams to improve productivity, reliability, and speed.

Exploration of practical GenAI use cases for developers and operations teams in DevOps workflows.

Discussion on how Amazon Q changes the DevOps workflow by enabling AI-powered automation and orchestration in the development lifecycle.

Explores how Amazon Q accelerates DevOps workflows by enabling AI-powered automation and improved orchestration within the DevOps lifecycle.

A generative AI gateway is a design pattern popular in enterprise settings which establishes a central gateway where developers can access foundation models from multiple providers. It includes features for access control, quota management, cost control, governance, and observability. This session will dive deep on a recommended architecture for building an AI gateway on AWS and provide a demo of the final result.