#storage

Google Chrome may be taking up more of your storage than expected thanks to a large on-device AI model file that, in some cases, is being automatically downloaded to the browser's system folders. Users who have noticed unexplained drops in their available desktop device storage are now discovering that Chrome is installing a 4GB weights.bin file inside their browser directory when certain AI features are enabled. The weights.bin file in question is connected to Google's Gemini Nano AI model, which powers Chrome AI tools like scam detection, writing assistance, autofill, and suggestion features. As the Gemini Nano model is designed to run lo … Read the full story at The Verge.

In 2021, I was developing software for an aerospace manufacturer and met with our machine learning team to discuss innovative approaches for tracking FOD (free-orbiting debris), a major security and operational concern in the industry. What struck me wasn’t the algorithms or tracking equipment, but the terabytes of data (up to petabytes) that were being produced. Old-school problems of limited hardware resources and inefficient data compression were bottlenecking cutting-edge visual learning models and traditional tracking solutions alike. The team was smart and could fine-tune quickly, but the real challenge was making sure our infrastructure could scale with them. In aerospace, performance hinges on how fast systems can absorb and interpret massive telemetry streams, and storage is often the silent limiter. When you’re generating terabytes to petabytes of data in a single test cycle, even a brief stall in the storage layer becomes a bottleneck. A few milliseconds of delay between wha

Let’s be honest about what’s happening in the market: Public cloud has become the easy button for AI. It offers immediate access to compute, storage, managed services, foundation model ecosystems, automation tools, and global reach. For enterprises that want to launch quickly, it is hard to argue against it. You do not need to spend years standing up infrastructure, hiring specialized operations teams, or engineering your own scalable environment before you can test your first use case. This is exactly why adoption continues even as confidence in cloud resilience becomes more complicated. This article about the expanding cloud market makes the point clearly. Enterprises are not pulling back from hyperscale clouds despite numerous outages. They continue to move forward because the benefits of agility, scalability, and rapid deployment are too valuable to ignore. The cloud remains deeply embedded in business operations, and for many organizations, stepping away would undo years, often de