Tag: faang

In multi-turn reinforcement learning (RL), your custom reward function decides what the model actually learns. A subtly wrong reward can quietly teach the wrong thing while every training curve looks healthy. Designing a reward that holds up over multi-turn, agentic tasks is one of the hardest parts of customizing Amazon Nova models. For multi-turn training, …

Read more “Custom reward functions for multi-turn reinforcement learning with Amazon Nova Forge”

Part 1 introduced granular cost attribution for Amazon Bedrock. This feature automatically traces every inference request back to the IAM principal that made the call. It showed how the new line_item_iam_principal column can give you per-user and per-application visibility. With optional cost allocation tags, you can also aggregate spend by team, project, or tenant using …

Read more “Part 2: Amazon Bedrock cost attribution with Amazon Athena and CUDOS”

Cyber defenders have never had more capability at their fingertips, and they have never needed it more. Frontier models can now reason across an entire code base, trace a vulnerability to its root cause, and propose a fix in minutes. Those same capabilities are available to adversaries. This is why the window between a vulnerability …

Read more “Accelerate cyber defense with OpenAI and AWS: Daybreak Red & Daybreak Blue now available to eligible customers on Amazon Bedrock”

For organizations deploying AI agents at scale, there’s often a critical divide between structured and unstructured data. While large language models (LLMs) excel at parsing text documents, emails, and PDFs, they can struggle when presented with raw enterprise databases. Meanwhile, standard natural-language-to-SQL (NL2SQL) models often guess how database schemas fit together, which can lead to …

Read more “Looker’s semantic layer governs Gemini Enterprise data for user trust”

To power up AI workflows on Amazon Elastic Kubernetes Service (Amazon EKS), data scientists need interactive IDEs like JupyterLab and Code Editor. Yet running those IDEs usually means leaving the cluster that hosts their pipelines, moving to a standalone JupyterHub deployment or a local laptop. That switch leaves them without the GPU nodes, shared storage, …

Read more “Run interactive IDEs on Amazon EKS with SageMaker AI to power up your AI workflows”

Between chaotic levels of market fragmentation and economic volatility, marketing and communications agencies can no longer rely on the human intuition they’ve traditionally used to win clients and optimize their ad spend. WPP is replacing that guesswork with an AI-powered view of shifting market dynamics, giving brands predictive certainty that lets them invest with confidence …

Read more “How WPP operationalizes platform and data engineering for AI marketing”

How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC execution API Authors: Nilesh Mishra and Ajit Koti This is the third entry of a multi-part blog series describing how we built a Real-Time Distributed Graph (RDG). In Part 1, we discussed the motivation for creating the RDG and the architecture …

Read more “How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC…”