​[[{“value”:” Quantization, a method integral to computational linguistics, is essential for managing the vast computational demands of deploying large language models (LLMs). It simplifies data, thereby facilitating quicker computations and more efficient model performance. However, deploying LLMs is inherently complex due to their colossal size… Read More »QoQ and QServe: A New Frontier in Model Quantization Transforming Large Language Model Deployment Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Mixture-of-experts (MoE) architectures use sparse activation to initial the scaling of model sizes while preserving high training and inference efficiency. However, training the router network creates the challenge of optimizing a non-differentiable, discrete objective despite the efficient scaling by MoE models. Recently, an MoE… Read More »Researchers from Princeton and Meta AI Introduce ‘Lory’: A Fully-Differentiable MoE Model Designed for Autoregressive Language Model Pre-Training Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Understanding and mitigating hallucinations in vision-language models (VLVMs) is an emerging field of research that addresses the generation of coherent but factually incorrect responses by these advanced AI systems. As VLVMs increasingly integrate text and visual inputs to generate responses, the accuracy of these… Read More »THRONE: Advancing the Evaluation of Hallucinations in Vision-Language Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Maritime transportation has always been pivotal for global trade and travel, but navigating the vast and often unpredictable waters presents significant challenges. The advent of autonomous ships promises to revolutionize this domain, leveraging advanced sensors and Artificial Intelligence (AI) to enhance situational awareness and… Read More »Safe Marine Navigation Using Vision AI: Enhancing Maritime Safety and Efficiency Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The power of LLMs to generate coherent and contextually appropriate text is impressive and valuable. However, these models sometimes produce content that appears accurate but is incorrect or irrelevant—a problem known as “hallucination.” This issue can be particularly problematic in fields requiring high factual… Read More »KnowHalu: A Novel AI Approach for Detecting Hallucinations in Text Generated by Large Language Models (LLMs) Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Discover the best AI Fraud Prevention Tools and Software for detecting payment fraud, identifying identity theft, preventing insurance fraud, addressing cybersecurity threats, combating e-commerce fraud, and reducing banking and financial fraud. Greip Greip is an AI-powered fraud protection tool that assists developers in protecting… Read More »Top AI Tools Enhancing Fraud Detection and Financial Forecasting Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Structured commonsense reasoning in natural language processing involves automated generating and manipulating reasoning graphs from textual inputs. This domain focuses on enabling machines to understand and reason about everyday situations as humans would, translating natural language into interconnected concepts that mirror human logical processes.… Read More »This AI Paper by the University of Michigan Introduces MIDGARD: Advancing AI Reasoning with Minimum Description Length Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Information extraction (IE) is a pivotal area of artificial intelligence that transforms unstructured text into structured, actionable data. Despite their expansive capacities, traditional large language models (LLMs) often fail to comprehend and execute the nuanced directives required for precise IE. These challenges primarily manifest… Read More »Tsinghua University Researchers Propose ADELIE: Enhancing Information Extraction with Aligned Large Language Models Around Human-Centric Tasks Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The robotics field has historically vacillated between two primary architectural paradigms: modular hierarchical policies and end-to-end policies. Modular hierarchies employ rigid layers such as symbolic planning, trajectory generation, and tracking, while end-to-end policies utilize high-capacity neural networks to map sensory input directly to actions.… Read More »UC Berkeley Researchers Introduce Learnable Latent Codes as Bridges (LCB): A Novel AI Approach that Combines the Abstract Reasoning Capabilities of Large Language Models with Low-Level Action Policies Mohammad Asjad Artificial Intelligence Category – MarkTechPost