The operation teams of capital markets face many hurdles in post-trade lifecycle, such as errors in booking, delays in trade settlements and inaccurate regulatory reports. Artificial intelligence and machine learning (AI/ML) technologies like Intelligent Document Processing (IDP), which automate data extraction from documents, can be of great assistance in overcoming these obstacles. This offers potential…
Unstructured, a major innovator in data transformation, has launched the Unstructured Serverless API, a breakthrough solution designed to streamline the processing and preparation of enterprise-level data for artificial intelligence (AI) applications. Not only does this offer a more straightforward approach, but it significantly accelerates the process and reduces costs. The Unstructured Serverless API is a…
Artificial Analysis has launched the Artificial Analysis Text to Image Leaderboard & Arena, an initiative aimed at evaluating the effectiveness of AI image models. The initiative compares open-source and proprietary models, seeking to rate their effectiveness and accuracy based on the preferences of humans. The leaderboard, updated with ELO scores compiled from over 45,000 human…
Researchers from the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Clinical Center, and National Center for Biotechnology Information have introduced a new method for creating synthetic X-ray images using data from computed tomography (CT) scans. The method, called Digitally Reconstructed Radiography (DRR), uses ray tracing techniques to simulate the path of X-rays through CT volumes. Unlike…
MARS5 TTS, an open-source text-to-speech system, has been released by the team at Camb AI, offering game-changing levels of precision and control in the field of speech synthesis. This innovative system can clone voices and provide nuanced control of prosody using less than 5 seconds of audio input.
MARS5 TTS utilises a two-step process involving a…
The use of large language models (LLMs), such as ChatGPT, has significantly increased in academic writing, resulting in observable shifts in writing style and vocabulary, particularly in biomedical research. Concerns have risen around the authenticity and originality of scientific content and its implications for research integrity and the evaluation of academic contributions.
Traditional methods for detecting…
Scientists from MIT have developed a technique that helps to fine-tune predictive models for extreme weather events by combining machine learning and dynamical systems theory. Currently, climate models are run decades and even centuries in advance to assess a community's risk to extreme weather but these generally operate at a rough resolution. As a result,…
AI21 Labs has made its Jamba-Instruct large language model (LLM) available in Amazon Bedrock. Among its remarkable attributes, Jamba-Instruct supports a 256,000-token context window, making it suitable for handling large documents and complex Retrieval Augmented Generation (RAG) applications.
This language model is the instructional version of the Jamba base model. It merges Structured State Space (SSM)…
Sleep monitoring is a crucial part of maintaining overall health, yet accurately assessing sleep and diagnosing disorders is a complex task due to the need for multi-modal data interpretation typically obtained through polysomnography (PSG). Current methods often depend on extensive manual evaluation by trained technicians, making them time-consuming and susceptible to variability. To address these…
The technological world is advancing at a rapid pace, making the management of complex tasks more challenging. The difficulty lies in breaking down extensive objectives into manageable parts and coordinating multiple processes to achieve a unified result, a challenge that becomes more significant when using AI models, which can sometimes yield fragmented or incomplete results.
Traditional…
Retrieval-Augmented Generation (RAG) methods improve the ability of large language models (LLMs) by incorporating external knowledge gleaned from vast data sets. These methods are particularly useful for open-domain question answering where detailed and accurate answers are needed. RAG systems can utilize external information to complement the inherent knowledge built into LLMs, making them more effective…