SIGNAL
Tracking the global AI frontier — labs · research · agents · policy
Frontier Signal

Practice

How AI actually ships: enterprise case studies, engineering lessons from production, adoption data and ROI evidence.

How AI actually ships: enterprise case studies, engineering lessons from production, adoption data and ROI evidence.

Latest in Practice

30 stories
The future of Ohio: Playing to win in the next economy
Practice

The future of Ohio: Playing to win in the next economy

Ohio has a proud legacy as a strong builder economy, but playing to win in the new arenas of competition requires a fresh and more diverse approach.…

From AI potential to agentic reality: Driving the UK’s next chapter
Practice

From AI potential to agentic reality: Driving the UK’s next chapter

The United Kingdom, and London in particular, continues to be one of the great hubs for AI development in Europe and the world. We’re home to Google DeepMind, o…

How growing UK midsize businesses are building in the AI era
Practice

How growing UK midsize businesses are building in the AI era

The UK’s 5-million-plus small and midsize businesses and enterprises (SMBs) are the backbone of our economy. Today, we’re seeing these critical businesses begin…

The symbiotic enterprise
Practice

The symbiotic enterprise

How cognitive and physical AI are reinventing enterprise execution…

Safeguard your agentic AI applications with the Amazon Bedrock Guardrails InvokeGuardrailChecks API
Practice

Safeguard your agentic AI applications with the Amazon Bedrock Guardrails InvokeGuardrailChecks API

Today, we’re announcing a new API with Amazon Bedrock Guardrails. With this API, you can apply individual safeguards, also referred to as safety checks, at any …

Introducing container caching in Amazon SageMaker AI for faster model scaling
Practice

Introducing container caching in Amazon SageMaker AI for faster model scaling

Today, we’re excited to announce container image caching for Amazon SageMaker AI inference, the next major advancement in our faster scaling optimization journe…

Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI
Practice

Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI

This post walks you through how to use P-EAGLE directly within Amazon SageMaker AI. It will demonstrate how to select a compatible model from the SageMaker Jump…

As America turns 250, unlocking the next generation's potential is key
Practice

As America turns 250, unlocking the next generation's potential is key

As America prepares to celebrate its 250th birthday, I've been reflecting on the generations that built the country's success and what it will take to prepare t…

Prompt Hungary: The impact of AI on the competitiveness of the economy
Practice

Prompt Hungary: The impact of AI on the competitiveness of the economy

AI could become a powerful growth engine for the country by helping overcome the economy’s challenges and limitations, and generating improved productivity and …

The agentic advertising economy: From attention to action
Practice

The agentic advertising economy: From attention to action

As AI changes how consumers discover products and impact is measured, advertising value will shift to the players that can shape what is seen, selected, and pur…

How Siemens "slices the elephant," advancing agentic workflows for industrial software development
Practice

How Siemens "slices the elephant," advancing agentic workflows for industrial software development

For technology companies like Siemens, software is the nervous system of factories, energy grids, and transportation networks worldwide. As a global leader in i…

Introducing Gemma 4 models on Amazon Bedrock
Practice

Introducing Gemma 4 models on Amazon Bedrock

Today, we are announcing the availability of the Gemma 4 family on Amazon Bedrock. Built by Google DeepMind and released under the Apache 2.0 license, Gemma 4 i…

AI Agent Failure Detection and Root Cause Analysis with Strands Evals
Practice

AI Agent Failure Detection and Root Cause Analysis with Strands Evals

In this post, we walk you through calling the detector functions to diagnose real agent failures. You learn how to interpret their structured output: categorize…

Build context-rich research agents with Deep Agents and Bedrock AgentCore
Practice

Build context-rich research agents with Deep Agents and Bedrock AgentCore

In this post, you'll build a competitive research agent that demonstrates this pattern end to end. This walkthrough targets developers building multi-step AI wo…

Cloud CISO Perspectives: The 4 lessons that guided AI Threat Defense
Practice

Cloud CISO Perspectives: The 4 lessons that guided AI Threat Defense

Welcome to the first Cloud CISO Perspectives for June 2026. Today, we introduce Chris Betz as the new CISO of Google Cloud. For his first Cloud CISO Perspective…

Phil Ozuah on enhancing ambulatory care and accessibility
Practice

Phil Ozuah on enhancing ambulatory care and accessibility

The president and CEO of Montefiore Einstein talks about technology in healthcare, opportunities to close gaps in patient access, and his own path to leadership…

Collective action, collective success: A CEO’s role in transformations
Practice

Collective action, collective success: A CEO’s role in transformations

Successful transformations require everyone in the organization to move in the same direction. That can only happen when CEOs directly address collective-action…

The health system CEO imperative: Turning AI’s promise into performance
Practice

The health system CEO imperative: Turning AI’s promise into performance

Health systems aren’t short on AI, they’re short on impact from AI. Capturing real value requires CEO-led transformation and a fundamental rethink of how care a…

From silicon to softmax: Inside the Ironwood AI stack
Practice

From silicon to softmax: Inside the Ironwood AI stack

As machine learning models continue to scale, a specialized, co-designed hardware and software stack is no longer optional, it’s critical. Ironwood, our latest …

Announcing Ironwood TPUs General Availability and new Axion VMs to power the age of inference
Practice

Announcing Ironwood TPUs General Availability and new Axion VMs to power the age of inference

Today’s frontier models, including Google’s Gemini, Veo, Imagen, and Anthropic’s Claude train and serve on Tensor Processing Units (TPUs). For many organization…

ADK architecture: When to use sub-agents versus agents as tools
Practice

ADK architecture: When to use sub-agents versus agents as tools

At its simplest, an agent is an application that reasons on how to best achieve a goal based on inputs and tools at its disposal. As you build sophisticated mul…

Easy AI workflow automation: Deploy n8n on Cloud Run
Practice

Easy AI workflow automation: Deploy n8n on Cloud Run

n8n is a powerful yet easy-to-use workflow and automation tool for multi-step AI agents, and many teams want a simple, scalable, and cost-effective way to self-…

Achieve better AI-powered code reviews using new memory capabilities on Gemini Code Assist
Practice

Achieve better AI-powered code reviews using new memory capabilities on Gemini Code Assist

The best feedback during a code review is specific, consistent, and understands the history of a project. However, AI code review agents today are often statele…

Running high-scale reinforcement learning (RL) for LLMs on GKE
Practice

Running high-scale reinforcement learning (RL) for LLMs on GKE

As Large Language Models (LLMs) evolve, Reinforcement Learning (RL) is becoming the crucial technique for aligning powerful models with human preferences and co…

Supporting Viksit Bharat: Announcing our newest AI investments in India
Practice

Supporting Viksit Bharat: Announcing our newest AI investments in India

Editor's note: This blog has been translated into Bengali, Hindi, Marathi, Tamil, and Telugu. India’s developer community, vibrant startup ecosystem, and leadin…

Introducing Agent Sandbox: Strong guardrails for agentic AI on Kubernetes and GKE
Practice

Introducing Agent Sandbox: Strong guardrails for agentic AI on Kubernetes and GKE

Google and the cloud-native community have consistently strengthened Kubernetes to support modern applications. At KubeCon EU 2025 earlier this year, we announc…

How Lightricks trains video diffusion models at scale with JAX on TPU
Practice

How Lightricks trains video diffusion models at scale with JAX on TPU

Training large video diffusion models at scale isn't just computationally expensive — it can become impossible when your framework can't keep pace with your amb…

BigQuery under the hood: How Google brought embeddings to analytics
Practice

BigQuery under the hood: How Google brought embeddings to analytics

Embeddings are a crucial component at the intersection of data and AI. As data structures, they encode the inherent meaning of the data they represent, and thei…

Building Supercharger: How Rocket Close optimized title operations with agentic AI
Practice

Building Supercharger: How Rocket Close optimized title operations with agentic AI

In this post, we explore how Rocket Close built a solution using Strands Agents, large language models (LLMs), Amazon Bedrock, Amazon Bedrock Knowledge Bases, a…

From PDFs to insights: Architecting an intelligent document processing pipeline with AWS generative AI services
Practice

From PDFs to insights: Architecting an intelligent document processing pipeline with AWS generative AI services

This post outlines the development of a cost-effective and scalable intelligent document processing pipeline on AWS, powered by Amazon Bedrock and its features.…