Tag: ai/ml

About this Series Frontend engineering at Palantir goes far beyond building standard web apps. Our engineers design interfaces for mission-critical decision-making, build operational applications that translate insight to action, and create systems that handle massive datasets — thinking not just about what the user needs, but what they need when the network is unreliable, the stakes are high, …

Read more “Frontend Engineering at Palantir: Polar Scaled Tiles in Zodiac”

Amazon Quick Sight, the business intelligence (BI) capability of Amazon Quick, is a unified BI service. It provides modern interactive dashboards, natural language querying, pixel-perfect reports, machine learning (ML) insights, and embedded analytics at scale. Amazon Quick brings together AI agents for business insights, research, and automation in one integrated experience, helping you work smarter …

Read more “Create rich, custom tooltips in Amazon Quick Sight”

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”