Google Unveils New Tool To Detect AI-Generated Scam Calls

Enhanced Call Security To Protect Users

Google has unveiled an innovative fake call detection feature aimed at thwarting sophisticated deepfake impersonation scams. Targeting Android 12+ devices, this new measure is set to safeguard users by automatically validating incoming calls through a secure, behind-the-scenes verification process.

Digital Handshake Authentication In Action

Built into the Phone by Google app, now available on Pixel devices and beyond, the feature operates like a digital handshake between devices. When a verified contact places a call, a silent confirmation signal is exchanged. Absence of this signal triggers an immediate alert, advising the recipient to disconnect the call.

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Broad Impact Across The Android Ecosystem

This development coincides with a suite of upgrades across the Android platform. Google Photos introduces a wardrobe feature that lets users virtually mix and match outfits, while Google Play Books debuts a “Catch Me Up” functionality to help readers seamlessly resume their favorite stories. Furthermore, Android 14+ devices now benefit from enhanced outfit searches via the updated Circle to Search feature, underscoring the company’s commitment to a robust, interconnected digital experience.

Strengthening Trust In Mobile Communications

By integrating this advanced authentication protocol, Google reinforces its position as a leader in mobile security innovation. The use of Rich Communication Services (RCS) underlines the potential for broader industry adoption, paving the way for more secure communication channels. In an era where AI-driven scams are evolving rapidly, such proactive measures are indispensable for protecting users from emerging threats.

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Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

by News Editor

August 6, 2026

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

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Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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