Large language models like ChatGPT have the potential to transform various fields but integrating them into real-world products poses challenges. A powerful strategy called retrieval-augmented generation (RAG) has emerged, allowing connection to external information sources for more accurate outputs. Several articles explore the intricacies and practical considerations of working with RAG, helpful for those in…

AI-driven apps are becoming popular for enhancing professional online images. Apps like Remini, Try It On AI, and AI Suit Up use artificial intelligence to create polished profile photos. While some users find these images to be genuine and professional, others believe they appear noticeably artificial. Cost is a driving factor, as professional photo sessions…

Researchers from Microsoft and ETH Zurich have released a dataset called “HoloAssist” to address the challenges of developing AI assistants for real-world tasks. The dataset contains extensive recordings of participants collaborating on physical manipulation tasks, capturing various sensor modalities and annotations. The dataset enables the development of anticipatory and proactive AI assistants for real-world scenarios,…

Predictive policing uses advanced analytics and machine learning to anticipate crimes before they happen. By analyzing historical crime data and other relevant information, algorithms can identify patterns and hotspots of criminal activity. However, recent investigations have revealed failures and ethical concerns, highlighting biases and the potential for inaccurate predictions. The efficacy of predictive policing software,…

MedARC has developed MindEye, an AI model that can analyze fMRI scans and retrieve the exact original image the person was looking at, even if the images are similar. The model can also identify similar images from a large image database. While impressive, the fMRI data collection process and limited training data are challenges. Nevertheless,…

Text-to-image diffusion models have dominated generative tasks by producing high-quality outcomes. Recently, image-to-image transformation tasks have been guided by diffusion models with external image conditions. However, the iterative and time-consuming nature of diffusion models limits their practical use. Recent research proposes distillation techniques to speed up sampling and condense the models. A single-stage distillation method…

Discover the quick and simple method for running Nougat using only a few lines of code.

Diffusion models have gained attention in the AI community for their ability to reverse the process of turning data into noise and understand complex data distributions. While they excel in some areas, they have limitations in tasks like picture translation. To address this, researchers have introduced Denoising Diffusion Bridge Models (DDBMs), which use diffusion bridges…

KOSMOS-G is an AI model developed by researchers at Microsoft Research, New York University, and the University of Waterloo. It can generate detailed images from text descriptions and multiple pictures. It uses a combination of pre-training and fine-tuning stages to align text and images and generate accurate pictures. KOSMOS-G has the capability to replace CLIP…