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​[[{“value”:” The growth of data in the digital age presents both opportunities and challenges. An immense volume of text, images, audio, and video is generated daily across platforms. Traditional machine learning models, while effective in many scenarios, often struggle to process high-dimensional and unstructured data… Read More »What is Deep Learning? Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Generative Large Multimodal Models (LMMs), such as LLaVA and Qwen-VL, excel in vision-language (VL) tasks like image captioning and visual question answering (VQA). However, these models face challenges when applied to foundational discriminative VL tasks, such as image classification or multiple-choice VQA, which require… Read More »Revolutionizing Vision-Language Tasks with Sparse Attention Vectors: A Lightweight Approach to Discriminative Classification Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post introduces HCLTech’s AutoWise Companion, a transformative generative AI solution designed to enhance customers’ vehicle purchasing journey. By tailoring recommendations based on individuals’ preferences, the solution guides customers toward the best vehicle model for them. Simultaneously, it empowers vehicle manufacturers (original equipment manufacturers… Read More »HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design Bhajandeep Singh AWS Machine Learning Blog

​[[{“value”:” Large Language Models (LLMs) and Vision-Language Models (VLMs) transform natural language understanding, multimodal integration, and complex reasoning tasks. Yet, one critical limitation remains: current models cannot efficiently handle extremely large contexts. This challenge has prompted researchers to explore new methods and architectures to improve… Read More »MiniMax-Text-01 and MiniMax-VL-01 Released: Scalable Models with Lightning Attention, 456B Parameters, 4B Token Contexts, and State-of-the-Art Accuracy Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The AWS global backbone network is the critical foundation enabling reliable and secure service delivery across AWS Regions. It connects our 34 launched Regions (with 108 Availability Zones), our more than 600 Amazon CloudFront POPs, and 41 Local Zones and 29 Wavelength Zones, providing… Read More »Mitigating risk: AWS backbone network traffic prediction using GraphStorm Jian Zhang AWS Machine Learning Blog

​[[{“value”:” Advances in large language and multimodal speech-text models have laid a foundation for seamless, real-time, natural, and human-like voice interactions. Achieving this requires systems to process speech content, emotional tones, and audio cues while giving accurate and coherent responses. However, challenges remain in overcoming… Read More »MinMo: A Multimodal Large Language Model with Approximately 8B Parameters for Seamless Voice Interaction Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Speech processing systems often struggle to deliver clear audio in noisy environments. This challenge impacts applications such as hearing aids, automatic speech recognition (ASR), and speaker verification. Conventional single-channel speech enhancement (SE) systems use neural network architectures like LSTMs, CNNs, and GANs, but they… Read More »Redefining Single-Channel Speech Enhancement: The xLSTM-SENet Approach Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Blockchain systems face significant challenges in efficiently managing and updating state storage due to high write amplification (WA) and extensive I/O operations. In traditional architecture, such as Merkle Patricia Tries (MPT), frequent and expensive disk interactions incur inefficiencies that restrict throughput and scalability. Such… Read More »Efficient Blockchain State Management with Quick Merkle Database (QMDB) Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Mathematical reasoning has long been a significant challenge for Large Language Models (LLMs). Errors in intermediate reasoning steps can undermine both the accuracy and reliability of final outputs, which is particularly problematic for applications requiring precision, such as education and scientific computation. Traditional evaluation… Read More »Alibaba Qwen Team just Released ‘Lessons of Developing Process Reward Models in Mathematical Reasoning’ along with a State-of-the-Art 7B and 72B PRMs Asif Razzaq Artificial Intelligence Category – MarkTechPost