When I started looking for alternatives, I wasn’t searching for a better chatbot. I was searching for one that can simply work on my machine while being useful for me. Most AI apps on Android are just front-ends. You type something. It leaves your phone. A server processes it. A reply comes back. That's not what I call Private AI. MNN Chat does something different. It is an Open Source Android App that runs LLMs directly on your device. You download a model inside the app, and your phone handles the rest. The prompts don’t leave or gets processed by any server. It’s just your device doing the work. Under the hood it uses an engine optimized for CPU inference, which matters more than people think. Phones don’t have desktop GPUs sitting around waiting for 70B models. Efficiency is the difference between “interesting demo” and “actually usable.”

I can say that the plugins I'm about to share with you guys are proven to be a game changer for me especially if you use Adobe After Effects to edit your videos.

Websites that let you generate the exact kind of images you want just by typing a few words of Prompt. The best part? They’re all completely free to use!

If you’ve been playing with AI music tools lately, here’s some genuinely good news. Heartmula has released an open-source AI music foundation model that’s surprisingly close to what tools like Suno AI can do but with a very different philosophy. It gives you something many creators actually want: full control. With this model, you can generate music directly on your own PC, offline, with no usage limits. What you run, you own & once it’s set up, you can generate as much music as your hardware allows. In this guide, I’ll show you exactly how to run Heartmula on your PC, step by step, without skipping the confusing parts.

Developers are making a strategic shift, embracing open-source tools that offer something far more valuable: genuine control and transparency. As we approach 2026, clear patterns are emerging across developer communities, open-source repositories, and day-to-day workflows. Tools that prioritize local-first development, privacy, performance, and community ownership are gaining steady traction, especially among independent developers & teams

Imagine You’re standing in line for coffee. Someone looks at you & their glasses quickly pull up your name and maybe your Instagram. You never gave permission & never even knew it was possible. That’s the idea behind "Name Tag," a feature being tested by Meta for its Ray-Ban smart glasses. According to The New York Times, the glasses would scan faces and match them to social profiles in real time. I’ll be honest. Part of me thinks the tech is impressive. The other part finds it deeply uncomfortable. Because once facial recognition moves from your phone into everyday glasses, the rules change. Your face stops being just your face. It becomes searchable. Meta says this kind of tech would have limits. There would be controls. But here’s what keeps bothering people: most of us did not sign up to be identified by strangers in public. That’s the tension. The company frames it as innovation. Critics call it surveillance. The truth probably sits somewhere in between.

MiMo V2 Flash is Xiaomi’s latest open source foundation language model, built with a strong emphasis on reasoning, coding, and agent based workflows. Xiaomi has focused on efficiency, deployment readiness, and real world usability.