​[[{“value”:” Large language models (LLMs) have advanced significantly in recent years. However, its real-world applications are restricted due to substantial processing power and memory requirements. The need to make LLMs more accessible on smaller and resource-limited devices drives the development of more efficient frameworks for… Read More »LightLLM: A Lightweight, Scalable, and High-Speed Python Framework for LLM Inference and Serving Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have made significant strides in various Natural Language Processing tasks, yet they still struggle with mathematics and complex logical reasoning. Chain-of-Thought (CoT) prompting has emerged as a promising approach to enhance reasoning capabilities by incorporating intermediate steps. However, LLMs often… Read More »Logic-of-Thought: Enhancing Logical Reasoning in Large Language Models through Propositional Logic Augmentation Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Instruction-tuned LMs have shown remarkable zero-shot generalization but often fail on tasks outside their training data. These LMs, built on large datasets and billions of parameters, excel in In-Context Learning (ICL), generating responses based on a few examples without re-training. However, the training dataset’s… Read More »Instructive Decoding (ID): A Novel AI Method that Enhances the Attention of Instruction-Tuned LLMs Towards Provided Instructions during the Generation Phase without Any Parameter Updates Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have gained significant attention due to their advanced capabilities in processing and generating text. However, the increasing demand for multimodal input processing has led to the development of vision language models. These models combine the strengths of LLMs with image… Read More »Self-Training on Image Comprehension (STIC): A Novel Self-Training Approach Designed to Enhance the Image Comprehension Capabilities of Large Vision Language Models (LVLMs) Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Over the last 18 months, AWS has announced more than twice as many machine learning (ML) and generative artificial intelligence (AI) features into general availability than the other major cloud providers combined. This accelerated innovation is enabling organizations of all sizes, from disruptive AI… Read More »AWS recognized as a first-time Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms Susanne Seitinger AWS Machine Learning Blog

​[[{“value”:” At Amazon and AWS, we are always finding innovative ways to build inclusive technology. With voice assistants like Amazon Alexa, we are enabling more people to ask questions and get answers on the spot without having to type. Whether you’re a person with a… Read More »Build a serverless voice-based contextual chatbot for people with disabilities using Amazon Bedrock Michael Shapira AWS Machine Learning Blog

​[[{“value”:” Amazon Monitron, the Amazon Web Services (AWS) machine learning (ML) service for industrial equipment condition monitoring, will no longer be available to new customers effective October 31, 2024. Existing customers of Amazon Monitron will be able to purchase devices and use the service as… Read More »Maintain access and consider alternatives for Amazon Monitron Stuart Gillen AWS Machine Learning Blog

​[[{“value”:” LightGBM is a highly efficient gradient boosting framework. It has gained traction for its speed and performance, particularly with large and complex datasets. Developed by Microsoft, this powerful algorithm is known for its unique ability to handle large volumes of data with significant ease… Read More »Exploring LightGBM: Leaf-Wise Growth with GBDT and GOSS Vinod Chugani MachineLearningMastery.com

​[[{“value”:” Retrieval-augmented generation (RAG) has been a transformative approach in natural language processing, combining retrieval mechanisms with generative models to enhance factual accuracy and reasoning capabilities. RAG systems excel in generating complex responses by leveraging external sources and synthesizing the retrieved information into coherent narratives.… Read More »Google Releases FRAMES: A Comprehensive Evaluation Dataset Designed to Test Retrieval-Augmented Generation (RAG) Applications on Factuality, Retrieval Accuracy, and Reasoning Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Generating versatile and high-quality text embeddings across various tasks is a significant challenge in natural language processing (NLP). Current embedding models, despite advancements, often struggle to handle unseen tasks and complex retrieval operations effectively. These limitations hinder their ability to adapt dynamically to diverse… Read More »‘bge-en-icl’: A Novel AI Model that Employs Few-Shot Examples to Produce High-Quality Text Embeddings Aswin Ak Artificial Intelligence Category – MarkTechPost