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​[[{“value”:” Large Language Models (LLMs) have advanced significantly, but a key limitation remains their inability to process long-context sequences effectively. While models like GPT-4o and LLaMA3.1 support context windows up to 128K tokens, maintaining high performance at extended lengths is challenging. Rotary Positional Embeddings (RoPE)… Read More »Microsoft AI Released LongRoPE2: A Near-Lossless Method to Extend Large Language Model Context Windows to 128K Tokens While Retaining Over 97% Short-Context Accuracy Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Unleashing a more efficient approach to fine-tuning reasoning in large language models, recent work by researchers at Tencent AI Lab and The Chinese University of Hong Kong introduces Unsupervised Prefix Fine-Tuning (UPFT). This method refines a model’s reasoning abilities by focusing solely on the… Read More »Tencent AI Lab Introduces Unsupervised Prefix Fine-Tuning (UPFT): An Efficient Method that Trains Models on only the First 8-32 Tokens of Single Self-Generated Solutions Aswin Ak Artificial Intelligence Category – MarkTechPost

​This tutorial is in four parts; they are: • The Core Text Generation Implementation • Contrastive Search: What are the Parameters in Text Generation? • Batch Processing and Padding • Tips for Better Generation Results Let’s start with a basic implementation that demonstrates the fundamental… Read More »Text Generation with GPT-2 Model Muhammad Asad Iqbal Khan MachineLearningMastery.com

​[[{“value”:” With researchers aiming to unify visual generation and understanding into a single framework, multimodal artificial intelligence is evolving rapidly. Traditionally, these two domains have been treated separately due to their distinct requirements. Generative models focus on producing fine-grained image details while understanding models prioritize… Read More »This AI Paper Introduces UniTok: A Unified Visual Tokenizer for Enhancing Multimodal Generation and Understanding Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) leverage deep learning techniques to understand and generate human-like text, making them invaluable for various applications such as text generation, question answering, summarization, and retrieval. While early LLMs demonstrated remarkable capabilities, their high computational demands and inefficiencies made them impractical… Read More »IBM AI Releases Granite 3.2 8B Instruct and Granite 3.2 2B Instruct Models: Offering Experimental Chain-of-Thought Reasoning Capabilities Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) rely on reinforcement learning techniques to enhance response generation capabilities. One critical aspect of their development is reward modeling, which helps in training models to align better with human expectations. Reward models assess responses based on human preferences, but existing… Read More »This AI Paper Introduces Agentic Reward Modeling (ARM) and REWARDAGENT: A Hybrid AI Approach Combining Human Preferences and Verifiable Correctness for Reliable LLM Training Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models have made remarkable strides in natural language processing, yet they still encounter difficulties when addressing complex planning and reasoning tasks. Traditional methods often rely on static templates or single-agent systems that fall short in capturing the subtleties of real-world problems. This… Read More »Google AI Introduces PlanGEN: A Multi-Agent AI Framework Designed to Enhance Planning and Reasoning in LLMs through Constraint-Guided Iterative Verification and Adaptive Algorithm Selection Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have progressed beyond basic natural language processing to tackle complex problem-solving tasks. While scaling model size, data, and compute has enabled the development of richer internal representations and emergent capabilities in larger models, significant challenges remain in their reasoning abilities.… Read More »Thinking Harder, Not Longer: Evaluating Reasoning Efficiency in Advanced Language Models Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Amazon Q Business is a fully managed, generative AI–powered assistant that empowers enterprises to unlock the full potential of their data and organizational knowledge. With Amazon Q Business, you can quickly access answers to questions, generate summaries and content, and complete tasks by using… Read More »Streamline work insights with the Amazon Q Business connector for Smartsheet Brandon Seiter AWS Machine Learning Blog

​[[{“value”:” Organizations across many industries are harnessing the power of foundation models (FMs) and large language models (LLMs) to build generative AI applications to deliver new customer experiences, boost employee productivity, and drive innovation. Amazon Bedrock, a fully managed service that offers a choice of… Read More »Level up your problem-solving and strategic thinking skills with Amazon Bedrock Senaka Ariyasinghe AWS Machine Learning Blog