Category: FAANG

Agents have evolved from simple chat applications to autonomous, long-running systems that dynamically discover and compose dozens of tools per task without human oversight. On the other side, service and content providers are moving from human-centric subscription-based, one-size-fits-all pricing to pay-per-use, per-execution models where costs are often a few cents. Today, agents are doing a …

Read more “Amazon Bedrock AgentCore payments is now generally available: Enabling agents to transact safely and autonomously at scale”

Real-time streaming pipelines are the operational backbone of modern enterprises, continuously processing everything from customer support interactions to transaction logs. Traditionally, streaming DAGs are static; once deployed, their processing logic and execution paths are fixed. However, by integrating generative AI agents, we can move beyond static logic to adaptive execution. This allows streaming workflows to …

Read more “Building cost-effective, high-throughput gen AI workflows in Google Dataflow”

NVIDIA Nemotron 3.5 Lightning is designed for the fast, specialized model execution required by high-volume agentic workloads. With NVIDIA Nemotron 3.5 Lightning on Amazon SageMaker JumpStart, you can access an open model designed for high-volume agentic workloads. With this launch, you can deploy Nemotron 3.5 Lightning from Amazon SageMaker JumpStart without configuring the serving infrastructure …

Read more “NVIDIA Nemotron 3.5 Lightning now available in Amazon SageMaker JumpStart”

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”