The researchers from Huazhong University of Science and Technology, the University of New South Wales, and Nanyang Technological University have unveiled a novel framework named HalluVault, aimed at enhancing the efficiency and accuracy of data processing in machine learning and data science fields. The framework is designed to detect Fact-Conflicting Hallucinations (FCH) in Large Language…
Neuromorphic Computing, Quantum Computing for AI, Explainable AI (XAI), AI-augmented Design and Creativity, Autonomous Vehicles and Robotics, AI in Cybersecurity, and AI for Environmental Sustainability are the seven key areas where AI advancements are considerably changing several sectors.
Neuromorphic Computing is a technology that is designed to mirror the structure and functioning of the human brain.…
Language models play a crucial role in advancing artificial intelligence (AI) technologies, revolutionizing how machines interpret and generate text. As these models grow more intricate, they employ vast data quantities and advanced structures to improve performance and effectiveness. However, the use of such models in large scale applications is challenged by the need to balance…
"Finetuned adapters" play a crucial role in generative image models, permitting custom image generation and reducing storage needs. Open-source platforms that provide these adapters have grown considerably, leading to a boom in AI art. Currently, over 100,000 adapters are available, with the Low-Rank Adaptation (LoRA) method standing out as the most common finetuning process. These…
AI21 Labs has launched a new model, the Jamba-Instruct, which is designed to revolutionize natural language processing tasks for businesses. It does this by improving upon the limitations of traditional models, particularly their limited context capabilities. These limitations affect model effectiveness in tasks such as summarization and conversation continuation.
The Jamba-Instruct model significantly enhances this capability…
AI21 Labs has unveiled its Jamba-Instruct model, a solution designed to tackle the challenge of using large context windows in natural language processing for business applications. Traditional models usually have constraints in their context capabilities, impacting their effectiveness in tasks such as summarising lengthy documents or continuing conversations. In contrast, Jamba-Instruct overcomes these barriers by…
In the rapidly evolving domain of Artificial Intelligence, Natural Language Processing (NLP), and Information Retrieval, the advent of advanced models like Retrieval Augmented Generation (RAG) has stirred considerable interest. Despite this, many data science experts advise against jumping into complex RAG models until the evaluation pipeline is fully reliable and robust.
Performing comprehensive assessments of RAG…
Retrieval Augmented Generation (RAG) models have become increasingly important in the fields of Artificial Intelligence, Natural Language Processing (NLP), and Information Retrieval. Despite this, there's a cautionary note from data science experts advising against a rush into using sophisticated RAG models until the evaluation pipeline is reliable and robust.
Emphasising the importance of examining RAG…
The challenge of efficiently determining a user's preferences through natural language dialogues, specifically in the context of conversational recommender systems, is a focus of recent research. Traditional methods require users to rate or compare options, but this approach fails when the user is unfamiliar with the majority of potential choices. Solving this problem through Large…
Continual learning (CL), the capability of systems to adapt over time without losing prior knowledge, presents a significant challenge. Neural networks, while adept at processing large amounts of data, can often suffer from catastrophic forgetting, when learning new information may erase what was previously learned. This becomes extremely problematic in scenarios with limited data retention…