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Tools to understand how content was created and edited

As generative media becomes more advanced and accessible, it’s helpful to know where content comes from, and whether it’s been altered. Today, we’re expanding our content transparency and verification tools in Search, Gemini, Chrome, Pixel and Cloud, and deepening our partnership with the broader industry. ContentsScaling our technologyProviding more ways to verify content Scaling our …

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Code Is Cheap. Engineering Judgement Is Now the Scarce Resource

underlying society is changing.  That was one of the ideas from Max Buckley’s talk at AI Engineer Singapore, and it has stuck with me ever since. For decades, software engineering was organised around scarcity. Code was expensive to write, engineers were scarce and features took time. This assumption shaped how teams worked. We prioritised carefully …

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Mocking a Year of IoT Sensor Time Series Data with Mimesis

  Contents# Introduction# Step-by-Step Guide# Final Remarks # Introduction  Mocking Internet of Things (IoT) sensor data that would be otherwise difficult to gather at scale can constitute a valuable approach to facilitate experimental analyses, projects, and studies. However, it requires much more than random value generation: it necessitates a chronological timeline, device metadata, and a need to reflect natural …

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New AI Tools for the Future of Science

For centuries, the scientific method has been the greatest engine of human progress. At Google, our mission is deeply rooted in building tools to accelerate it. We believe that a new era of discovery won’t come from narrow, specialized models, but general agents that empower researchers across every scientific field. That’s why we are introducing …

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Meta-Cognitive Regulation Might Be the Most Important AI Skill Nobody Is Talking About

into the world of generative AI adoption for almost the past three years now. We’ve spent the last three years learning how to talk to AI, but what if I told you that the next big shift will be learning how not to let AI think for us?! With the growing exposure of AI in …

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Practical NLP in the Browser with Transformers.js

  Contents# Introduction# What Transformers.js Actually Is# The pipeline() API# Task 1: Text Classification// Full Working Example# Task 2: Zero-Shot Classification// How It Works Under the Hood// Full Working Example # Introduction  For a long time, running transformer models meant maintaining a Python server, paying for GPU time, and routing every inference request through an API. The user typed something, it left their machine, …

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How to Effectively Run Many Claude Code Sessions in Parallel

coding agents sequentially and not in multiple runs in parallel, you’re losing out. One of the key benefits of coding agents is that you can start completing work in parallel, something that was never really possible before when working on software engineering tasks. However, when I start running a lot of parallel coding sessions, it’s …

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Visual Debugging Tools for Machine Learning Workflows

  Contents# Introduction# Visualizing Gradients, Losses, and Embeddings# TensorBoard and Its Alternatives# Using Breakpoints and Hooks for Machine Learning Computations# Conclusion # Introduction  Training a machine learning model and observing the loss decrease is a feeling of progress, until the validation accuracy reaches a plateau or the loss begins to spike, and you’re not sure what caused it. At that point, …

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