Tag: faang

Authors: Divya Gadde, Ko-Jen Hsiao, Dhaval Patel and Moumita Bhattacharya The motivation for building the Netflix Foundation Model for personalization was laid out in this previous blog post. The Netflix homepage is powered by several specialized models and it requires significant time and resources to maintain and continue innovating on these individual models. Therefore, we …

Read more “Integrating Netflix’s Foundation Model into Personalization applications”

IDC research shows that document-related challenges cost organizations $19,732 for each information worker annually and reduce productivity by 21.3 percent. Organizations receiving invoices from hundreds of suppliers often face layouts that vary by issuer and change without notice. Template-based systems require constant maintenance at this scale. Staff can spend up to 30 percent of their …

Read more “Build self-improving document processing using Amazon Bedrock AgentCore”

The generative AI functions in BigQuery (AI.GENERATE, AI.IF, AI.CLASSIFY, AI.SCORE, and more) bring large language models (LLMs) directly into your SQL, so a single query can classify millions of support tickets or score each product review for sentiment. However, because these functions are billed by the token, scaling them across massive datasets highlights the importance …

Read more “Predictable AI spend in BigQuery: Introducing cost management for generative AI functions”

AI agents increasingly need to access web resources that are priced per request. For example, premium datasets charge by the query, research APIs meter by the call, and paywalled publishers gate content behind payment. When an AI agent encounters one of these resources, the server returns HTTP 402 Payment Required. The agent has no built-in …

Read more “Building agents that transact with Anchor Browser and AgentCore payments”

Last week we announced that Gemini Enterprise has evolved to make it even simpler to get work done, and introduced the Gemini agent, your new universal agent for work. It’s always on and ready to answer your questions. It will write code, complete longer and more complex tasks, or perform whatever you need to get …

Read more “Gemini 4 Argon available on Google Cloud, built to help solve your business’ hardest problems”

Single-Region inference can throttle when demand exceeds local capacity. Teams in Thailand, Malaysia, Singapore, Indonesia, and Taiwan need access to the newest OpenAI models beyond that capacity. Amazon Bedrock offers OpenAI GPT-6 Sol and GPT-6 Luna through global cross-Region inference from all five AWS Regions, and GPT-6 Astra from Asia Pacific (Singapore). This post shows …

Read more “Accessing OpenAI GPT models on Amazon Bedrock with global cross-Region inference in Thailand, Malaysia, Singapore, Indonesia, and Taiwan”

A recap of the latest Amazon Bedrock, Amazon Bedrock AgentCore, and Strands updates from September 2026 At AWS, we believe the fastest path to enterprise AI is giving builders real choice at every layer: model, runtime, and tooling. That belief shapes how we invest across Amazon Bedrock, AgentCore, and Strands. Amazon Bedrock continues expanding access …

Read more “ICYMI: What landed for AI builders in September 2026”

Editor’s note: This article is adapted from Thomas Kurian’s keynote address at Gemini at Work 2026. It includes a number of announcements: Gemini, a single, universal agent for work that answers your questions, handles your knowledge work, creates your images and media, and writes and runs code.  Inline in Workspace, Gemini works directly inside Gmail, …

Read more “Welcome to Gemini at Work 2026: Introducing the Gemini agent”