​[[{“value”:” Traditionally, finding relevant information from documents has been a time-consuming and often frustrating process. Manually sifting through pages upon pages of text, searching for specific details, and synthesizing the information into coherent summaries can be a daunting task. This inefficiency not only hinders productivity… Read More »Accenture creates a custom memory-persistent conversational user experience using Amazon Q Business Dominik Juran AWS Machine Learning Blog

​[[{“value”:” With the rise of generative artificial intelligence (AI), an increasing number of organizations use digital assistants to have their end-users ask domain-specific questions, using Retrieval Augmented Generation (RAG) over their enterprise data sources. As organizations transition from proofs of concept to production workloads, they… Read More »Create an end-to-end serverless digital assistant for semantic search with Amazon Bedrock Mehdi Amrane AWS Machine Learning Blog

​[[{“value”:” The field of research focuses on optimizing algorithms for training large language models (LLMs), which are essential for understanding and generating human language. These models are critical for various applications, including natural language processing and artificial intelligence. Training LLMs requires significant computational resources and… Read More »Adam-mini: A Memory-Efficient Optimizer Revolutionizing Large Language Model Training with Reduced Memory Usage and Enhanced Performance Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Using machine learning to solve real-world problems is exciting. But most eager beginners jump straight to model building—overlooking the fundamentals—resulting in models that aren’t very helpful. From understanding the data to choosing the best machine learning model for the problem, there are some common… Read More »5 Common Mistakes in Machine Learning and How to Avoid Them Bala Priya C MachineLearningMastery.com

​[[{“value”:” Frontier AI systems, including LLMs, increasingly shape human beliefs and values by serving as personal assistants, educators, and authors. These systems, trained on vast amounts of human data, often reflect and propagate existing societal biases. This phenomenon, known as value lock-in, can entrench misguided… Read More »ProgressGym: A Machine Learning Framework for Dynamic Ethical Alignment in Frontier AI Systems Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rise of Generative AI (GenAI) has revolutionized various industries, from healthcare and finance to entertainment and customer service. The effectiveness of GenAI systems hinges on the seamless integration of four critical components: Human, Interface, Data, and large language models (LLMs). Understanding these elements… Read More »The Four Components of a Generative AI Workflow: Human, Interface, Data, and LLM Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have shown impressive performance in a range of tasks in recent years, especially classification tasks. These models demonstrate amazing performance when given gold labels or options that include the right answer. A significant limitation is that if these gold labels… Read More »Understanding the Limitations of Large Language Models (LLMs): New Benchmarks and Metrics for Classification Tasks Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multi-modal Large Language Models (MLLMs) have various applications in visual tasks. MLLMs rely on the visual features extracted from an image to understand its content. When a low-resolution image containing fewer pixels is provided as input, it translates less information to these models to… Read More »MG-LLaVA: An Advanced Multi-Modal Model Adept at Processing Visual Inputs of Multiple Granularities, Including Object-Level Features, Original-Resolution Images, and High-Resolution Data Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In various fields, data comes in many forms. Be it documents, images, or video/audio files, managing and making sense of this unstructured data can be overwhelming. The challenge lies in converting this diverse data into a structured format that is easy to work with,… Read More »OmniParse: An AI Platform that Ingests/Parses Any Unstructured Data into Structured, Actionable Data Optimized for GenAI (LLM) Applications Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Language models have become increasingly complex, making it challenging to interpret their inner workings. Researchers are attempting to solve this problem through mechanistic interpretability, which involves identifying and analyzing circuits – sparse computational subgraphs that capture specific aspects of a model’s behavior.  Current methodologies… Read More »Researchers at Princeton University Proposes Edge Pruning: An Effective and Scalable Method for Automated Circuit Finding Mohammad Asjad Artificial Intelligence Category – MarkTechPost