Prostate biopsy whole slide image dataset from an underrepresented Middle Eastern population

The rise of AI-generated videos has prompted concerns about misinformation, leading to a guide on how to distinguish between real and fake content. The article outlines six practical methods to identify AI videos, emphasizing the importance of vigilance in an era where digital content can easily be manipulated.

Autonomous Vehicles (AVs) are advancing rapidly, driven by improvements in intelligent perception and control systems, with a critical focus on reliable object detection in complex environments. Recent research highlights the integration of Vision-Language Models (VLMs) and Large Language Models (LLMs) as pivotal in overcoming existing challenges in multimodal perception and contextual reasoning.

The study on generative AI (GenAI) practices in Italy reveals significant adoption among Italian-speaking adults, with 1,906 participants reporting usage for both personal and professional tasks, including sensitive areas like emotional support and medical advice. Despite this widespread use, many users exhibit low digital literacy, raising concerns about their ability to identify misinformation.

A recent study highlights the implementation of an AI framework within Shriners Childrens, focusing on enhancing data quality in their Research Data Warehouse. The modernization to OMOP CDM v5.4 and the introduction of a Python-based data quality assessment tool aim to address existing challenges in AI system evaluations and clinical adoption.

The increasing use of wearable sensors has the potential to generate extensive time series data, which could enhance applications in human sensing through Artificial Intelligence. However, ethical regulations and privacy concerns are significantly limiting data collection, presenting challenges in the advancement of generative AI technologies, particularly in synthesizing this data effectively.

Recent advancements in artificial intelligence (AI) highlight significant progress in perception, language, reasoning, and multimodal capabilities. However, a new study identifies seven core deficiencies in current AI systems, including a lack of intrinsic self-monitoring and meta-cognitive awareness, which hinder their ability to self-regulate in dynamic environments. These limitations suggest that existing architectures, such as deep learning and transformer-based systems, are insufficient for achieving true cognitive autonomy.

A new explainable, few-shot AI4E framework has been developed, integrating physics and expert knowledge to enhance materials engineering, particularly in aerospace applications. This framework addresses critical challenges such as the scarcity of high-quality data and the interpretability of AI models, which are essential in safety-sensitive sectors. The framework was tested using a limited dataset of 32 experimental samples from K439B superalloy castings repair welding.