​[[{“value”:” Concept-based learning (CBL) in machine learning emphasizes using high-level concepts from raw features for predictions, enhancing model interpretability and efficiency. A prominent type, the concept-based bottleneck model (CBM), compresses input features into a low-dimensional space to capture essential data while discarding non-essential information. This… Read More »FI-CBL: A Probabilistic Method for Concept-Based Machine Learning with Expert Rules Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have gained significant attention in recent years, but ensuring their safe and ethical use remains a critical challenge. Researchers are focused on developing effective alignment procedures to calibrate these models to adhere to human values and safely follow human intentions.… Read More »45 Shades of AI Safety: SORRY-Bench’s Innovative Taxonomy for LLM Refusal Behavior Analysis Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Originally PyTorch used an eager mode where each PyTorch operation that forms the model is run independently as soon as it’s reached. PyTorch 2.0 introduced torch.compile to speed up PyTorch code over the default eager mode. In contrast to eager mode, the torch.compile pre-compiles the entire… Read More »Accelerated PyTorch inference with torch.compile on AWS Graviton processors Sunita Nadampalli AWS Machine Learning Blog

​[[{“value”:” In November 2023, we announced Knowledge Bases for Amazon Bedrock as generally available. Knowledge bases allow Amazon Bedrock users to unlock the full potential of Retrieval Augmented Generation (RAG) by seamlessly integrating their company data into the language model’s generation process. This feature allows… Read More »Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock Dani Mitchell AWS Machine Learning Blog

​[[{“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”:” 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