The Bitcoin community is rallying behind a petition demanding the proposal of a Bitcoin emoji. The movement, termed 'Bitcoin Emoji', started in March and has so far garnered close to 7,500 signatures. The goal, however, is to reach 1.35 million signatures. The campaign is lagging in momentum despite the support of 25 large crypto organizations.…
Large language models (LLMs) have made significant strides in the field of artificial intelligence, paving the way for machines that understand and generate human-like text. However, these models face the inherent challenge of their knowledge being fixed at the point of their training, limiting their adaptability and ability to incorporate new information post-training. This proves…
Large Vision Language Models (LVLMs) have been successful in text and image comprehension tasks, including Referring Expression Comprehension (REC). Notably, models like Griffon have made significant progress in areas such as object detection, denoting a key improvement in perception within LVLMs. Unfortunately, known challenges with LVLMs include their inability to match task-specific experts in intricate…
In a recent AI research paper, Google researchers have developed a new pre-trained scorer model, named Cappy, which has been designed to improve and surpass the capabilities of large multi-task language models (LLMs). This new development aims to tackle the primary issues related to LLMs. While they demonstrate remarkable performance and compatibility with numerous natural…
Medical image segmentation is a key component in diagnosis and treatment, with UNet's symmetrical architecture often used to outline organs and lesions accurately. However, its convolutional nature requires assistance to capture global semantic information, thereby limiting its effectiveness in complex medical tasks. There have been attempts to integrate Transformer architectures to address this, but these…
Artificial intelligence (AI) researchers from Stanford University and Notbad AI Inc are striving to improve language models' AI capabilities in interpreting and generating nuanced, human-like text. Their project, called Quiet Self-Taught Reasoner (Quiet-STaR), embeds reasoning capabilities directly into language models. Unlike previous methods, which focused on training models using specific datasets for particular tasks, Quiet-STaR…
A new study by Google is aiming to teach powerful large language models (LLMs) how to reason better with graph information. In computer science, the term 'graph' refers to the connections between entities - with nodes being the objects and edges being the links that signify their relationships. This type of information, which is inherent…
Researchers from Capital Normal University and the School of Artificial Intelligence at Beijing University of Posts and Telecommunications have developed RealNet, a new feature reconstruction framework for industrial image anomaly detection. This approach addresses ongoing issues with generating diverse, realistic anomalies that align with natural distributions, as well as challenges around feature redundancy and pre-training…
GitHub Actions is a powerful feature of the GitHub platform that allows for automating software development workflows, enabling developers to streamline their development process. In this tutorial, we demonstrate how to use GitHub Actions for a beginner Machine Learning (ML) project, and cover everything from setting up our ML project on GitHub to creating a…
The DIGITOUR system is an end-to-end pipeline for creating digital tours of real-estate properties. It involves capturing 360-degree images in each area of a property, tagging each of these areas with bi-colored paper tags, and using machine learning algorithms to stitch together a coherent tour.
To create a tour, an operator places paper tags at various…