faang - Robotic Content

Pioneering AI-assisted code migration: How Google achieved 6x faster migration from TensorFlow to JAX

by AI Generated Robotic ContentFAANG May 7, 2026Comments are Disabled

AI coding agents are rapidly becoming ubiquitous across the software industry, fundamentally changing how developers write, test, and debug daily code. While these tools excel at localized, self-contained tasks, applying them to massive, systemic codebase migrations requires an entirely new approach. Google is already addressing this challenge by incorporating AI into many migration workflows: x86 …

Stochastic KV Routing: Enabling Adaptive Depth-Wise Cache Sharing

by AI Generated Robotic ContentFAANG May 6, 2026Comments are Disabled

Serving transformer language models with high throughput requires caching Key-Values (KVs) to avoid redundant computation during autoregressive generation. The memory footprint of KV caching is significant and heavily impacts serving costs. This work proposes to lessen these memory requirements. While recent work has largely addressed KV cache reduction via compression and eviction along the temporal …

How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

by AI Generated Robotic ContentFAANG May 6, 2026Comments are Disabled

Hapag-Lloyd stands as one of the world’s leading liner shipping companies, operating a modern fleet of 313 container ships with a total transport capacity of 2.5 million TEU (Twenty-foot Equivalent Unit—a standard unit of measurement for cargo capacity in container shipping). The company maintains a container capacity of 3.7 million TEU, which includes one of …

Five must-have guides to move agents into production with Gemini Enterprise Agent Platform

by AI Generated Robotic ContentFAANG May 6, 2026Comments are Disabled

Building AI agents that work well in a demo is one thing, but running them in production requires serious infrastructure. At Google Cloud Next ’26, we introduced Gemini Enterprise Agent Platform to help developers build, deploy, scale, govern, and optimize autonomous AI agents. From managing long-running state and enforcing security with the Agent Governance Stack, …

PORTool: Importance-Aware Policy Optimization with Rewarded Tree for Multi-Tool-Integrated Reasoning

by AI Generated Robotic ContentFAANG May 5, 2026Comments are Disabled

Multi-tool-integrated reasoning enables LLM-empowered tool-use agents to solve complex tasks by interleaving natural-language reasoning with calls to external tools. However, training such agents using outcome-only rewards suffers from credit-assignment ambiguity, obscuring which intermediate steps (or tool-use decisions) lead to success or failure. In this paper, we propose PORTool, an importance-aware policy-optimization algorithm that reinforces agents’ …

Democratizing Machine Learning at Netflix: Building the Model Lifecycle Graph

by AI Generated Robotic ContentFAANG May 5, 2026Comments are Disabled

Saish Sali, Nipun Kumar, Sura Elamurugu Introduction As Netflix has grown, machine learning continues to support our ability to deliver value to members and drive excellence across multiple areas of our business. When Netflix began investing in machine learning over a decade ago, it was primarily focused on a single domain: personalization. Scala was the …

Beyond BI: How the Dataset Q&A feature of Amazon Quick powers the next generation of data decisions

by AI Generated Robotic ContentFAANG May 5, 2026Comments are Disabled

Business leaders across industries rely on operational dashboards as the shared source of truth that their teams execute against daily. But dashboards are built to answer known questions. When teams need to explore further, ad-hoc, multi-dimensional, or unforeseen questions, they hit a bottleneck. They wait hours or days for BI teams to build new views …

Reinforced Agent: Inference-Time Feedback for Tool-Calling Agents

by AI Generated Robotic ContentFAANG May 2, 2026Comments are Disabled

This paper was accepted at the Fifth Workshop on Natural Language Generation, Evaluation, and Metrics at ACL 2026. Tool-calling agents are evaluated on tool selection, parameter accuracy, and scope recognition, yet LLM trajectory assessments remain inherently post-hoc. Disconnected from the active execution loop, such assessments identify errors that are usually addressed through prompt-tuning or retraining, …

State of Routing in Model Serving

by AI Generated Robotic ContentFAANG May 2, 2026Comments are Disabled

By Nipun Kumar, Rajat Shah, Peter Chng Introduction This is the first blog post in a multi-part series that shares technical insights into how our ML model serving infrastructure powers several personalized experiences at scale across various domains (e.g., title recommendations, commerce). In this introductory blog post, we will dive into our domain-independent API abstraction and …

AWS Transform now automates BI migration to Amazon Quick in days

by AI Generated Robotic ContentFAANG May 2, 2026Comments are Disabled

Migrating to Amazon Quick doesn’t have to mean starting from scratch. Your dashboards encode hard-won domain knowledge: calculated fields your analysts perfected, layouts your executives rely on every Monday morning, security rules tuned to your org chart. You want AI-powered insights and serverless scale, but you’re staring at hundreds of dashboards and a migration estimate …