​[[{“value”:” Large Language Models (LLMs) have made significant progress in following instructions and responding to user queries. However, the current instruction tuning process faces major challenges. Acquiring human-generated data for training these models is expensive and time-consuming. Moreover, the quality of such data is limited… Read More »Meta-Rewarding LLMs: A Self-Improving Alignment Technique Where the LLM Judges Its Own Judgements and Uses the Feedback to Improve Its Judgment Skills Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Artificial Intelligence (AI) has rapidly advanced, revolutionizing various sectors by performing tasks that require human intelligence, such as learning, reasoning, and problem-solving. Improvements in machine learning algorithms, computational capabilities, and the availability of large datasets drive these advancements. Despite the progress, the field faces… Read More »Model Openness Framework (MOF): Enhancing AI Transparency with 17 Essential Components for Full Lifecycle Openness and Reproducibility Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Open-source libraries facilitated RAG pipeline creation but lacked comprehensive training and evaluation capabilities. Proposed frameworks for RAG-based large language models (LLMs) omitted crucial training components. Novel approaches, such as treating LLM prompting as a programming language, emerged but introduced complexity. Evaluation methodologies using synthetic… Read More »Intel Labs Introduce RAG Foundry: An Open-Source Python Framework for Augmenting Large Language Models LLMs for RAG Use Cases Shoaib Nazir Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AI chatbots and virtual assistants have become increasingly popular in recent years thanks the breakthroughs of large language models (LLMs). Trained on a large volume of datasets, these models incorporate memory components in their architectural design, allowing them to understand and comprehend textual context.… Read More »Improve AI assistant response accuracy using Knowledge Bases for Amazon Bedrock and a reranking model Wei Teh AWS Machine Learning Blog

​[[{“value”:” Innovations in artificial intelligence (AI) and machine learning (ML) are causing organizations to take a fresh look at the possibilities these technologies can offer. As you aim to bring your proofs of concept to production at an enterprise scale, you may experience challenges aligning… Read More »Automate the machine learning model approval process with Amazon SageMaker Model Registry and Amazon SageMaker Pipelines Jason Sizer McIntosh AWS Machine Learning Blog

​[[{“value”:” Taipy and Streamlit have garnered significant attention among data scientists & machine learning engineers in Python-based web application frameworks. Both platforms offer unique functionalities tailored to different development needs. Let’s compare Taipy’s callback functionalities and Streamlit’s caching mechanisms and how Taipy beats Streamlit in… Read More »Comparing Taipy’s Callbacks and Streamlit’s Caching: A Detailed Technical Analysis Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The Role of Explainable AI in In Vitro Diagnostics Under European Regulations: AI is increasingly critical in healthcare, especially in vitro diagnostics (IVD). The European IVDR recognizes software, including AI and ML algorithms, as part of IVDs. This regulatory framework presents significant challenges for… Read More »Navigating Explainable AI in In Vitro Diagnostics: Compliance and Transparency Under European Regulations Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rapid advancements in AI have led to the development of increasingly powerful and efficient language models. Among the most notable recent releases are Mistral NeMo, developed by Mistral in partnership with Nvidia, and Meta’s Llama 3.1 8B model. Both are top-tier small language… Read More »Mistral NeMo vs Llama 3.1 8B: A Comparative Analysis Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” MiniCPM-V 2.6 represents the latest and most advanced iteration in the MiniCPM-V series, constructed on the SigLip-400M and Qwen2-7B frameworks, boasting a total of 8 billion parameters. This model introduces significant enhancements in performance and new features tailored for multi-image and video understanding, achieving… Read More »MiniCPM-V 2.6: A GPT-4V Level Multimodal LLMs for Single Image, Multi-Image, and Video on Your Phone Aswin Ak Artificial Intelligence Category – MarkTechPost