Artificial Intelligence (AI) has brought significant transformation in healthcare by improving diagnostic and treatment planning efficiency. However, the accuracy and reliability of AI-driven predictions remain a challenge, due to the scarcity of data, which is common in healthcare. The specialized nature of medical data and privacy concerns often restrict the information available for training AI…
On-Device Intelligence (ODI) is a promising technology bridging mobile computing and artificial intelligence (AI) for real-time personalized services without reliance on the network. While the technology shows promise in applications like medical diagnostics and AI-enhanced tracking, it faces challenges due to decentralized user data and privacy concerns.
Traditional methods such as cloud-based computing raise privacy issues…
Apple Vision Pro, a new technology platform from Apple, is set to significantly reshape the biomedical landscape. The innovative toolset is designed specifically for biomedical imaging and analysis, leveraging the high-quality camera and computation power of Apple devices. It allows users to capture highly detailed images to aid in disease diagnosis and treatment planning, which…
Researchers from the University of Pennsylvania, University of Washington, Allen Institute for AI, University of California, and Columbia University have developed a novel benchmark study for evaluating core visual perception abilities in multimodal large language models (LLMs), called 'Blink.' The study suggests that current methods of evaluating LLMs conflate perception with linguistic understanding and reasoning.…
Generative models are key tools in various sectors, such as computer vision and natural language processing, due to their ability to generate samples from learning data distributions. Among these, Diffusion Models (DMs) and particularly Latent Diffusion Models (LDMs) are favored for their high-quality image output, speed of generation, and reduced computational cost. Despite these advantages,…
