🛜 How the internet took a long nap this week
Plus: YouTube wants to stop your AI doppelganger before it goes viral; major U.S. AI infrastructure companies bet big on Uniphore; and why women still earn less than men in 2025.
This week, Amazon’s cloud arm, AWS, went offline, taking hundreds of apps and websites down with it. For about 15 long hours, users couldn’t access everything from Canva and Snapchat to Fortnite and Ring. More than 11 million people reported issues across the globe, a reminder of just how much of the internet depends on a handful of cloud giants. While everything’s finally back online, it’s another wake-up call about the fragility of modern digital life.
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LEARN MORE🛂 Can YouTube save you from your fake self?

AI deepfakes have gotten far too real. From fake brand endorsements to AI clones of creators saying things they never said, YouTube has become the front line of digital identity theft. Now, the platform is fighting back with a new likeness detection system. It scans videos, spots fakes, and lets verified creators pull them down before they go viral.
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LEARN MOREđź’µ A powerful cohort of major U.S. AI infrastructure companies bet big on Uniphore
U.S. tech heavyweights NVIDIA, AMD, Snowflake, and Databricks backed India-founded enterprise automation platform Uniphore in a $260 million funding round, showing how they plan to control AI deployment. The move beyond their core offerings (chips, data clouds, and processing frameworks) will help them tighten control over the full AI value chain that delivers AI-driven business solutions worldwide.
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LEARN MORE🤷🏼‍♀️ It’s 2025, and women still earn less

You’d think by now the gender pay gap would be history. But new data from the U.S., Brazil, and India says otherwise: women still earn less than men across nearly every industry. In the U.S., the number’s stuck at 83 cents to the dollar. In Brazil, it’s about 19% less. In India, it’s as wide as 30%, depending on the job. Technology was supposed to fix this, but all it’s really done is digitize the same old biases.
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