Category: FAANG

Generative AI is reshaping how organizations approach productivity, customer experiences, and operational capabilities. Across industries, teams are experimenting with generative AI to unlock new ways of working. Many of these efforts produce compelling proofs of concept (POC) that demonstrate technical feasibility. The real challenge begins after those early wins. Although POCs frequently demonstrate technical feasibility, …

Read more “Navigating the generative AI journey: The Path-to-Value framework from AWS”

Building effective reward functions can help you customize Amazon Nova models to your specific needs, with AWS Lambda providing the scalable, cost-effective foundation. Lambda’s serverless architecture lets you focus on defining quality criteria while it handles the computational infrastructure. Amazon Nova offers multiple customization approaches, with Reinforcement fine-tuning (RFT) standing out for its ability to teach …

Read more “How to build effective reward functions with AWS Lambda for Amazon Nova model customization”

At Google Cloud, we often see customers asking themselves: “How can we manage our generative AI costs effectively without sacrificing the performance and availability our applications demand?”  This is the million-dollar question — or, perhaps more accurately, the “tokens-per-minute” question. The key isn’t just about choosing the cheapest option, but about finding the right recipe …

Read more “How to find the sweet spot between cost and performance”

by Gabriela Alessio, Cameron Taylor, and Cameron R. Wolfe Introduction When members log into Netflix, one of the hardest choices is what to watch. The challenge isn’t a lack of options — there are thousands of titles — but finding the most intriguing one is complex and deeply personal. To help, we surface personalized promotional assets, especially the show synopsis — a …

Read more “Evaluating Netflix Show Synopses with LLM-as-a-Judge”

For decades, expense automation relied on a simple premise: If the machine can read the text, it can do the work. But anyone who has ever tried to scan a crumpled, smudged, or sun-bleached receipt from their pocket knows that reading isn’t enough. When key data is missing, such as a city name or a …

Read more “How SAP Concur automates expense reporting with agentic AI”

Amazon Bedrock regularly releases new foundation model (FM) versions with better capabilities, accuracy, and safety. Understanding the model lifecycle is essential for effective planning and management of AI applications built on Amazon Bedrock. Before migrating your applications, you can test these models through the Amazon Bedrock console or API to evaluate their performance and compatibility. …

Read more “Understanding Amazon Bedrock model lifecycle”

Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models handle increasingly sensitive data, they introduce unique AI-driven attack vectors — from prompt injection to sensitive data leakage — that traditional firewalls aren’t designed to catch. Prompt injection …

Read more “Guardrails at the gateway: Securing AI inference on GKE with Model Armor”