mobile technology
-
Motorola’s Razr Fold and Signature Unveiled
Read Full Article: Motorola’s Razr Fold and Signature Unveiled
The Motorola Razr Fold, a new book-style foldable phone, is reportedly on the horizon, with limited details available beyond a marketing slide highlighting its camera system, display, and AI capabilities. Meanwhile, the upcoming Motorola Signature, previously known as the Motorola Edge 70 Ultra, will feature three 50-MP cameras, a Snapdragon 8 Gen 5 processor, and options for 12GB or 16GB RAM. It boasts a 6.8-inch "Extreme AMOLED" screen, a 5,200mAh battery, and advanced charging options, all in a slim profile. The Motorola Signature is set to launch on January 7th, promising to answer any remaining questions about its features. Why this matters: The introduction of new foldable and flagship smartphones by Motorola signifies advancements in mobile technology and provides consumers with more diverse options in the competitive smartphone market.
-
Guide: Running Llama.cpp on Android
Read Full Article: Guide: Running Llama.cpp on Android![Llama.cpp running on Android with Snapdragon 888 and 8GB of ram. Compiled/Built on device. [Guide/Tutorial]](https://www.tweakedgeek.com/wp-content/uploads/2026/01/featured-article-8272-300x171.png)
Running Llama.cpp on an Android device with a Snapdragon 888 and 8GB of RAM involves a series of steps beginning with downloading Termux from F-droid. After setting up Termux, the process includes cloning the Llama.cpp repository, installing necessary packages like cmake, and building the project. Users need to select a quantized model from HuggingFace, preferably a 4-bit version, and configure the server command in Termux to launch the model. Once the server is running, it can be accessed via a web browser by navigating to 'localhost:8080'. This guide is significant as it enables users to leverage advanced AI models on mobile devices, enhancing accessibility and flexibility for developers and enthusiasts.
-
Qbtech’s Mobile AI Revolutionizes ADHD Diagnosis
Read Full Article: Qbtech’s Mobile AI Revolutionizes ADHD DiagnosisQbtech, a Swedish company, is revolutionizing ADHD diagnosis by integrating objective measurements with clinical expertise through its smartphone-native assessment, QbMobile. Utilizing Amazon SageMaker AI and AWS Glue, Qbtech has developed a machine learning model that processes data from smartphone cameras and motion sensors to provide clinical-grade ADHD testing directly on patients' devices. This innovation reduces the feature engineering time from weeks to hours and maintains high clinical standards, democratizing access to ADHD assessments by enabling remote diagnostics. The approach not only improves diagnostic accuracy but also facilitates real-time clinical decision-making, reducing barriers to diagnosis and allowing for more frequent monitoring of treatment effectiveness. Why this matters: By leveraging AI and cloud computing, Qbtech's approach enhances accessibility to ADHD assessments, offering a scalable solution that could significantly improve patient outcomes and healthcare efficiency globally.