Microsoft criticized by The Guardian for AI-generated poll

A UC Berkeley research team has developed a novel LM pipeline, a retrieval-augmented language model system designed to improve forecasting accuracy. The system utilizes web-scale data and rapid parsing capabilities of language models, achieving a Brier…

AI hallucinations, seen in generative AI like ChatGPT and Google Bard, occur when large language models deviate from accurate information due to flawed training data or generation methods. The consequences include misinformation, bias amplification, and privacy…

The latest wave of generative AI, from ChatGPT to GPT4 to DALL-E 2/3 to Midjourney, has attracted global attention. These models exhibit superhuman capabilities but also make fundamental comprehension mistakes. Researchers propose the Generative AI Paradox…

Understanding Language Models and Their Challenges Language models (LMs) are essential tools used in areas like mathematics, coding, and reasoning to tackle complex tasks. They utilize deep learning to produce high-quality results, but their effectiveness can…

Enhancing Knowledge Retrieval Systems with AI Knowledge retrieval systems have been used for many years in various fields like healthcare, education, and finance. Today, they are improved by large language models (LLMs) that provide more accurate…

Valence Labs has introduced LOWE, an advanced LLM-Orchestrated Workflow Engine designed for executing complex drug discovery workflows using natural language commands. Integrated with Recursion’s OS, LOWE enables efficient use of proprietary data and computational tools. Its…

Part 2 of an article on Wave Data Feature Engineering focuses on spectral features. Techniques like FFT help convert time-domain signals into frequency-domain, providing insights on dominant frequencies and power distribution through features such as spectral…

Project Guideline is an innovative initiative aimed at enhancing the independence of individuals with visual impairments. It leverages on-device machine learning on Google Pixel phones to enable users to walk or run independently. The system includes…

USC researchers have developed DeLLMa, a machine learning framework aimed at improving decision-making in uncertain environments. It leverages large language models to address the complexities of decision-making, offering structured, transparent, and auditable methods. Rigorous testing demonstrated…

Practical Solutions and Value of Mobility VLA in AI Enhancing Robot Navigation with Mobility VLA Technological advancements in sensors, AI, and processing power have led to significant improvements in robot navigation. Mobility VLA enables robots to…

Understanding AI Pipelines Artificial intelligence (AI) has evolved from simple tasks to solving complex real-world problems by integrating various specialized models. This method, known as AI pipelines, allows different models to work together efficiently, enabling applications…

The text discusses the growing influence of large language models (LLMs) on information extraction (IE) in natural language processing (NLP). It highlights research on generative IE approaches utilizing LLMs, providing insights into their capabilities, performance, and…

Overcoming Challenges with Large Language Models Organizations often struggle to implement Large Language Models (LLMs) for complex workflows. Issues such as speed, flexibility, and scalability make it hard to automate processes that need coordination across different…

Phase-Field Models and Their Importance Phase-field models are essential for simulating material behavior by connecting atomic-level details to larger-scale effects. They help in understanding microstructural changes and phase transformations, which are important in various processes like…

Understanding Knowledge Graph Synthesis Knowledge Graph (KG) synthesis is an important area in artificial intelligence. It helps create organized knowledge from large amounts of unstructured text data. These structured graphs are useful for: Information Retrieval: Finding…

LEO is a generalized agent developed by researchers at the Beijing Institute for General Artificial Intelligence, CMU, Peking University, and Tsinghua University. It is trained in an LLM-based architecture and is capable of perceiving, reasoning, planning,…

Transforming Tabular Data with Deep Learning Understanding the Challenge Deep learning has revolutionized fields like finance, healthcare, and e-commerce by processing complex data. However, using deep learning for tabular data (data organized in rows and columns)…

Graph-based machine learning is undergoing a transformation driven by Graph Neural Networks (GNNs). Traditional GNNs face challenges with long-range dependencies in graphs. Graph Mamba Networks (GMNs) by Cornell University researchers integrate State Space Models to offer…

Practical Solutions for Vulnerability Detection Automated Tools for Detecting Vulnerabilities In software engineering, detecting vulnerabilities in code is crucial for ensuring the security and reliability of software systems. Automated tools have become increasingly important as software…