Hate Windows 11? Here's how you can make it work more like Windows 10

ZDNet - Artificial Intelligence
Jul 17, 2025 03:12
1 views
aibusinessenterprisetechnology

Summary

The article discusses user frustrations with Windows 11 and offers solutions to make its interface resemble Windows 10. While not directly focused on AI, these customization options may improve user experience and productivity, which could indirectly benefit AI workflows and adoption on Windows platforms.

Every new Windows version comes with its own set of annoyances, but for some people, Windows 11 seems even more annoying than its predecessors. Fortunately, there are some solutions available.

Related Articles

PEPE Price Projection: $0.00005 by 2025 as Ozak AI Rockets to New Highs

Analytics InsightJul 17

The article discusses the projected rise of PEPE's price to $0.00005 by 2025, highlighting growing investor interest in AI-driven cryptocurrencies. It also notes that Ozak AI has reached new performance highs, signaling increased momentum and innovation in the AI sector. These trends suggest that AI integration is playing a significant role in shaping the future of digital assets and investment strategies.

Don't Fall for AI: Reasons for Writers to Reject Slop

Hacker News - AIJul 17

The article argues that writers should reject low-quality, AI-generated content ("slop") because it often lacks originality, depth, and emotional resonance. It warns that widespread use of such content could degrade creative standards and undermine the value of human authorship. This highlights ongoing concerns in the AI field about balancing technological advancement with the preservation of authentic, high-quality writing.

A £3.93/mo Nomad‑backed learning lab: Next.js · .NET · Postgres on a budget

Hacker News - AIJul 17

The article details how to set up a cost-effective learning lab for web development technologies like Next.js, .NET, and Postgres using Nomad, all for just £3.93 per month. While not directly focused on AI, this affordable infrastructure can support AI experimentation and learning by providing accessible backend resources for developers and students. The approach highlights the growing accessibility of robust development environments, which can accelerate AI prototyping and education.