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Cloud CISO Perspectives: How Google + Wiz changes multicloud strategy for CISOs

Welcome to the first Cloud CISO Perspectives for May 2026. Today, Vinod D’Souza, director, Office of the CISO, shares highlights from his RSA Conference fireside chat with Anthony Belfiore, chief strategy officer, Wiz. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog. If you’re reading this …

Why I disappeared for 3 Months & What’s Next

I’ve been quiet since November because I’ve been building. Over the past few months, AI has moved so quickly that the barrier between an idea and a high-powered system has essentially vanished. Even as a non-developer, I’ve found that working with AI is like having a small team of A-level developers who work for $40 …

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Build financial document processing with Pulse AI and Amazon Bedrock

Financial institutions process thousands of complex documents daily. Optical Character Recognition (OCR) errors in financial data can propagate through interconnected calculations, affecting analytical accuracy. While a single OCR error in a standard legal document might require only a quick manual correction, the same mistake in financial data can cascade through interconnected calculations, leading to systematic …

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How Amazon Finance streamlines regulatory inquiries by using generative AI on AWS

Amazon’s Finance Technology (FinTech) teams build and operate systems for Amazon teams to manage regulatory inquiries in compliance with different jurisdictions. These teams process regulatory inquiries from authorities, each presenting different requirements, document formats, and complexity levels. Processing these regulatory inquiries involves reviewing documentation, extracting relevant information, retrieving supporting data from multiple systems within Amazon’s …

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Beyond source code: The files AI coding agents trust — and attackers exploit

As AI coding agents become deeply embedded in developer workflows, defenders must evolve their definition of malicious files and rethink how to protect against them.  Autonomous AI agents operate across integrated development environments (IDEs), editors, terminals, and extension runtimes, and they often have access to local files, command execution, and external services. As a result, …

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Building web search-enabled agents with Strands and Exa

This post is co written by Ishan Goswami and Nitya Sridhar from Exa. If you are building web search-enabled AI agents for research, fact-checking, or competitive intelligence, access to current and reliable information is critical. Most general-purpose search APIs are not designed for agent workflows. They return HTML-heavy pages and short snippets optimized for human …

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Cloud Storage Rapid: Turbocharged object storage for AI and analytics

At Google Cloud Next ’26 we announced Cloud Storage Rapid, a family of object storage capabilities for data-intensive workloads like AI and analytics. Out of the gate, Cloud Storage Rapid consists of Rapid Bucket (formerly Rapid Storage), a high-performance zonal object storage offering, and Rapid Cache (formerly Anywhere Cache), which accelerates reads on-demand and colocates …

Scaling ArchUnit with Nebula ArchRules

By John Burns and Emily Yuan Introduction At Netflix, we operate using a polyrepo strategy with tens of thousands of Java repositories. This means that we need to have ways of sharing common build logic across these repositories. On the JVM Ecosystem team within Java Platform, we build tooling such as the Nebula suite of Gradle …

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Halliburton enhances seismic workflow creation with Amazon Bedrock and Generative AI

Seismic data analysis is an essential component of energy exploration, but configuring complex processing workflows has traditionally been a time-consuming and error-prone challenge. Halliburton’s Seismic Engine, a cloud-native application for seismic data processing, is a powerful tool that previously required manual configuration of approximately 100 specialized tools to create workflows. This process was not only …

What Matters in Practical Learned Image Compression

One of the major differentiators unlocked by learned codecs relative to their hard-coded traditional counterparts is their ability to be optimized directly to appeal to the human visual system. Despite this potential, a perceptual yet practical image codec is yet to be proposed. In this work, we aim to close this gap. We conduct a …