​[[{“value”:” Bilevel optimization (BO) is a growing field of research, gaining attention for its success in various machine learning tasks like hyperparameter optimization, meta-learning, and reinforcement learning. BO involves a two-level structure where the solution to the outer problem depends on the solution to the… Read More »ScaleBiO: A Novel Machine Learning Based Bilevel Optimization Method Capable of Scaling to 34B LLMs on Data Reweighting Tasks Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Business data analysis is a field that focuses on extracting actionable insights from extensive datasets, crucial for informed decision-making and maintaining a competitive edge. Traditional rule-based systems, while precise, need help with the complexity and dynamism of modern business data. On the other hand,… Read More »This AI Paper by Narrative BI Introduces a Hybrid Approach to Business Data Analysis with LLMs and Rule-Based Systems Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Ensuring the safety and moderation of user interactions with modern Language Models (LLMs) is a crucial challenge in AI. These models, if not properly safeguarded, can produce harmful content, fall victim to adversarial prompts (jailbreaks), and inadequately refuse inappropriate requests. Effective moderation tools are… Read More »WildGuard: A Light-weight, Multi-Purpose Moderation Tool for Assessing the Safety of User-LLM Interactions Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” It is observed that LLMs often struggle to retrieve relevant information from the middle of long input contexts, exhibiting a “lost-in-the-middle” behavior. The research paper addresses the critical issue of the performance of large language models (LLMs) when handling longer-context inputs. Specifically, LLMs like… Read More »Researchers at the University of Wisconsin-Madison Propose a Finetuning Approach Utilizing a Carefully Designed Synthetic Dataset Comprising Numerical Key-Value Retrieval Tasks Shreya Maji Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and extract insights directly from the content in digital as well as scanned PDF documents in your enterprise data sources without needing to extract the text first. Customers across… Read More »Improve productivity when processing scanned PDFs using Amazon Q Business Sonali Sahu AWS Machine Learning Blog

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​[[{“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