Securing their products is a challenge for businesses. Teams are inundated with false positives from current Static Application Security Testing (SAST) technologies, and those identifying vulnerabilities cannot be fixed. Meet ZeroPath, a GitHub app that detects, verifies, and issues pull requests for security vulnerabilities in your code. The ZeroPath tool not only automatically identifies vulnerabilities… →

On-call shifts can be very stressful for engineers. When something goes wrong in a system, the person on call has to figure out the problem and fix it quickly. This often means going through lots of logs and data, which takes time and can be challenging, especially during off-hours. Getting to the root cause of… →

AI and ML in Untargeted Metabolomics and Exposomics: Metabolomics employs a high-throughput approach to measure a variety of metabolites and small molecules in biological samples, providing crucial insights into human health and disease. One application, untargeted metabolomics, allows for an unbiased global analysis of the metabolome, identifying key metabolites that contribute to or indicate health… →

A major development in artificial intelligence, multimodal large language models (MLLMs) combine verbal and visual comprehension to produce more accurate representations of multimodal inputs. Through the integration of data from multiple sources, including text and images, these models improve understanding of intricate relationships between various modalities. Because of this integration, sophisticated tasks requiring a thorough… →

The recent development of large language models (LLMs) has transformed the field of Natural Language Processing (NLP). LLMs show human-level performance in many professional and academic fields, showing a great understanding of language rules and patterns. However, they often struggle with reasoning reliably and flexibly. This problem likely comes from the way transformers, the underlying… →

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has highlighted the critical need for large, diverse, and high-quality datasets to train and evaluate foundation models. However, acquiring such datasets presents significant challenges, including data scarcity, privacy concerns, and high data collection and annotation costs. Artificial (synthetic) data has emerged as a promising… →