AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

With LLMs increasingly working multimodally, there are exciting developments for more performance and leaner sizes.

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.

Google’s Diffusion Gemma introduces a bold shift in AI language modeling by adopting a diffusion-based architecture that processes tokens in parallel, rather than sequentially. As explained by Prompt ...

Abstract: Pavement cracks pose a direct threat to the safety of transportation systems. ConditionCrack Segmentation (CCS), a pavement crack segmentation model based on conditional diffusion, is ...

Figure | Schematics of inverse design methods. a, Optimization-based inverse design methods usually model only the forward prediction process and execute iterative optimization algorithms to obtain an ...

In the study titled MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer, a team of nearly 30 Apple researchers details a novel unified approach that enables both ...

Abstract: Multimodal medical image fusion (MMIF) extracts the most meaningful information from multiple source images, enabling a more comprehensive and accurate diagnosis. Achieving high-quality ...

While AI generators are far from the largest contributor to climate change, their carbon footprint is steadily growing as more people use these platforms. Designed by scientists at the University of ...

An AI image generator that uses light to produce images, rather than conventional computing hardware, could consume hundreds of times less energy. When an artificial intelligence model produces an ...