​[[{“value”:” Recent advancements in large language models (LLMs) have significantly enhanced their ability to handle long contexts, making them highly effective in various tasks, from answering questions to complex reasoning. However, a critical bottleneck has emerged: the memory requirements for storing key-value (KV) caches escalate… Read More »SimLayerKV: An Efficient Solution to KV Cache Challenges in Large Language Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have demonstrated significant reasoning capabilities, yet they face issues like hallucinations and the inability to conduct faithful reasoning. These challenges stem from knowledge gaps, leading to factual errors during complex tasks. While knowledge graphs (KGs) are increasingly used to bolster… Read More »Graph-Constrained Reasoning (GCR): A Novel AI Framework that Bridges Structured Knowledge in Knowledge Graphs with Unstructured Reasoning in LLMs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Training and deploying large-scale language models (LLMs) is complex, requiring significant computational resources, technical expertise, and access to high-performance infrastructure. These barriers limit reproducibility, increase development time, and make experimentation challenging, particularly for academia and smaller research institutions. Addressing these issues requires a lightweight,… Read More »Meta AI Releases Meta Lingua: A Minimal and Fast LLM Training and Inference Library for Research Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Deep neural networks are powerful tools that excel in learning complex patterns, but understanding how they efficiently compress input data into meaningful representations remains a challenging research problem. Researchers from the University of California, Los Angeles, and New York University propose a new metric,… Read More »Understanding Local Rank and Information Compression in Deep Neural Networks Shobha Kakkar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advancements in Large Language Models (LLMs) have reshaped the Artificial intelligence (AI)landscape, paving the way for the creation of Multimodal Large Language Models (MLLMs). These advanced models expand AI capabilities beyond text, allowing understanding and generation of content like images, audio, and video,… Read More »Baichuan-Omni: An Open-Source 7B Multimodal Large Language Model for Image, Video, Audio, and Text Processing Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Agentic systems have evolved rapidly in recent years, showing potential to solve complex tasks that mimic human-like decision-making processes. These systems are designed to act step-by-step, analyzing intermediate stages in tasks like humans do. However, one of the biggest challenges in this field is… Read More »Agent-as-a-Judge: An Advanced AI Framework for Scalable and Accurate Evaluation of AI Systems Through Continuous Feedback and Human-level Judgments Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” One of the primary challenges in developing advanced text-to-speech (TTS) systems is the lack of expressivity when transcribing and generating speech. Traditionally, large language models (LLMs) used for building TTS pipelines convert speech to text using automatic speech recognition (ASR), process it using an… Read More »Meta AI Releases Meta Spirit LM: An Open Source Multimodal Language Model Mixing Text and Speech Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rapid growth of large language models (LLMs) has brought impressive capabilities, but it has also highlighted significant challenges related to resource consumption and scalability. LLMs often require extensive GPU infrastructure and enormous amounts of power, making them costly to deploy and maintain. This… Read More »Microsoft Open-Sources bitnet.cpp: A Super-Efficient 1-bit LLM Inference Framework that Runs Directly on CPUs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post is co-written Rodrigo Amaral, Ashwin Murthy and Meghan Stronach from Qualcomm. In this post, we introduce an innovative solution for end-to-end model customization and deployment at the edge using Amazon SageMaker and Qualcomm AI Hub. This seamless cloud-to-edge AI development experience will… Read More »Train, optimize, and deploy models on edge devices using Amazon SageMaker and Qualcomm AI Hub Rodrigo Amaral AWS Machine Learning Blog

​[[{“value”:” The study investigates the emergence of intelligent behavior in artificial systems by examining how the complexity of rule-based systems influences the capabilities of models trained to predict those rules. Traditionally, AI development has focused on training models using datasets that reflect human intelligence, such… Read More »Emergence of Intelligence in LLMs: The Role of Complexity in Rule-Based Systems Sana Hassan Artificial Intelligence Category – MarkTechPost