Tootfinder

Gemoddete Hardware: Nintendo soll 2 Millionen US-Dollar bekommen
Nintendo hat sich mit dem Betreiber einer Plattform für Mod-Hardware auf eine Strafzahlung von 2 Millionen US-Dollar geeinigt. Der Anbieter hatte keinen Anwalt.

Qi2.2: Schnelleres Laden dank iOS 26 mit passender Hardware
Erste Geräte mit Qi2.2 drehen von 15 auf 25 Watt induktive Stromversorgung auf. Beim iPhone 16 geht es mit iOS 26 los.
https://www.

PSA (i don't use Chrome so haven't tested)
https://www.neowin.net/news/chrome-140-make-is-it-harder-to-install-ublock-origin-but-it-is-still-possible/

Chrome 140 makes it harder to install uBlock Origin, but it is still possible
Google recently released Chrome 140, and with it, made it harder to use MV2-based extensions, such as uBlock Origin. Fortunately, you can still make it work. Here is how.

Bit-Flip Fault Attack: Crushing Graph Neural Networks via Gradual Bit Search
Sanaz Kazemi Abharian, Sai Manoj Pudukotai Dinakarrao
https://arxiv.org/abs/2507.05531

Bit-Flip Fault Attack: Crushing Graph Neural Networks via Gradual Bit Search
Graph Neural Networks (GNNs) have emerged as a powerful machine learning method for graph-structured data. A plethora of hardware accelerators has been introduced to meet the performance demands of GNNs in real-world applications. However, security challenges of hardware-based attacks have been generally overlooked. In this paper, we investigate the vulnerability of GNN models to hardware-based fault attack, wherein an attacker attempts to misclassify output by modifying trained weight paramete…

Hardware Acceleration in Portable MRIs: State of the Art and Future Prospects
Omar Al Habsi, Safa Mohammed Sali, Anis Meribout, Mahmoud Meribout, Saif Almazrouei, Mohamed Seghier
https://arxiv.org/abs/2509.06365

Hardware Acceleration in Portable MRIs: State of the Art and Future Prospects
There is a growing interest in portable MRI (pMRI) systems for point-of-care imaging, particularly in remote or resource-constrained environments. However, the computational complexity of pMRI, especially in image reconstruction and machine learning (ML) algorithms for enhanced imaging, presents significant challenges. Such challenges can be potentially addressed by harnessing hardware application solutions, though there is little focus in the current pMRI literature on hardware acceleration. T…

Tiny but Mighty: A Software-Hardware Co-Design Approach for Efficient Multimodal Inference on Battery-Powered Small Devices
Yilong Li, Shuai Zhang, Yijing Zeng, Hao Zhang, Xinmiao Xiong, Jingyu Liu, Pan Hu, Suman Banerjee
https://arxiv.org/abs/2510.05109

Tiny but Mighty: A Software-Hardware Co-Design Approach for Efficient Multimodal Inference on Battery-Powered Small Devices
Large Multimodal Models (LMMs) are inherently modular, consisting of vision and audio encoders, projectors, and large language models. Yet, they are almost always executed monolithically, which underutilizes the heterogeneous accelerators (NPUs, GPUs, DSPs) in modern SoCs and leads to high end-to-end latency. In this paper, we present NANOMIND, a hardware--software co-design inference framework for Large Multimodal Models (LMMs) that breaks large models into modular ``bricks'' (vision, language…

MedMambaLite: Hardware-Aware Mamba for Medical Image Classification
Romina Aalishah, Mozhgan Navardi, Tinoosh Mohsenin
https://arxiv.org/abs/2508.05049 https://

MedMambaLite: Hardware-Aware Mamba for Medical Image Classification
AI-powered medical devices have driven the need for real-time, on-device inference such as biomedical image classification. Deployment of deep learning models at the edge is now used for applications such as anomaly detection and classification in medical images. However, achieving this level of performance on edge devices remains challenging due to limitations in model size and computational capacity. To address this, we present MedMambaLite, a hardware-aware Mamba-based model optimized throug…

OpenAI und Jony Ive: Neue Details zur Arbeit an erster eigener KI-Hardware
Zusammen mit Jony Ive arbeitet OpenAI an KI-Hardware, noch gibt es aber Hürden. Ein Zeitungsbericht legt nun nahe, dass der angepeilte Markt schwierig ist.

AirPods Pro 3: Zwei Versionen – und nicht viel besserer Klang?
Apple plant wohl mindestens zwei Versionen der AirPods Pro 3, jedoch nicht gleichzeitig. Die neue Hardware ist interessant – nicht in Sachen Audio.
h…

Drohnenzeugnisse: KI beaufsichtigt theoretische Online-Prüfungen
Eine KI ersetzt den beaufsichtigenden Prüfer bei OPEs von Drohnenzeugnissen. Der Prüfling profitiert von geringeren Hardwareanforderungen und günstigen Preisen.