As reported by 9to5Mac, Apple's research team, in partnership with Purdue University, has crafted an innovative AI model called DarkDiff. This model is specifically tailored to tackle the complexities of capturing photos in extremely dimly lit settings. By integrating a diffusion model into the camera's Image Signal Processing (ISP) workflow, DarkDiff is capable of directly retrieving lost details from the raw sensor data, resulting in a substantial improvement in image quality.

DarkDiff steps in at the initial phase of ISP processing for raw data, where it executes noise reduction and detail generation tasks. This approach effectively circumvents the detail degradation that often occurs due to over-smoothing in conventional algorithms. The research also highlights the introduction of the 'Local Image Patch Attention Mechanism' and 'Classifier-Free Guidance' techniques. These innovations ensure that the enhanced content stays true to the original scene, striking a perfect balance between smoothness and sharpness.

While DarkDiff excels over existing technologies in terms of color accuracy and detail sharpness, its sluggish processing speed and hefty computational requirements currently render it impractical for widespread commercial use. Looking ahead, its implementation might hinge on cloud computing solutions.