​ The introduction of Large Language Models (LLMs) has captured the world by storm. These models are famous for imitating humans by generating unique and creative content and answering questions like humans would. These models are also capable of summarizing long paragraphs of text, translating… Read More »This AI Paper Explains How Programming Languages Can Enhance Each Other Through Instruction Tuning Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ A significant challenge in evaluating the text comprehension abilities of multilingual models is the lack of high-quality, simultaneous evaluation standards. There are high-coverage natural language processing datasets like FLORES-200, although they are mostly used for machine translation. Although 100+ languages use understanding and generative… Read More »Meta AI Releases BELEBELE: The First Parallel Reading Comprehension Evaluation Benchmark for 122 Languages Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ The evolution of artificial intelligence (AI) models and hardware accelerators has brought about unique challenges for compilers. These challenges stem from the constantly evolving architecture of AI models, such as the transition from RNNs and CNNs to more recent models like Transformers, alongside rapid… Read More »Microsoft Research Releases the ‘Heavy-Metal Quartet’ of AI Compilers: Rammer, Roller, Welder, and Grinder Niharika Singh Artificial Intelligence Category – MarkTechPost

​ With the growing advancements in the field of Artificial Intelligence, its sub-fields, including Natural Language Processing, Natural Language Generation, Computer Vision, etc., have rapidly gained a lot of popularity due to their extensive use cases. Optical Character Recognition (OCR) is a well-established and heavily… Read More »Meta AI Releases Nougat: A Visual Transformer Model that Performs OCR for Processing Scientific Documents into a Markup Language Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ The paper introduces VITS2, a single-stage text-to-speech model that synthesizes more natural speech by improving various aspects of previous models. The model addresses issues like intermittent unnaturalness, computational efficiency, and dependence on phoneme conversion. The proposed methods enhance naturalness, speech characteristic similarity in multi-speaker… Read More »Researchers from South Korea Propose VITS2: A Breakthrough in Single-Stage Text-to-Speech Models for Enhanced Naturalness and Efficiency Mahitha Sannala Artificial Intelligence Category – MarkTechPost

​ Recent advancements in deep neural networks have enabled new approaches to address anatomical segmentation. For instance, state-of-the-art performance in the anatomical segmentation of biomedical images has been attained by deep convolutional neural networks (CNNs). Conventional strategies adopt standard encoder-decoder CNN architectures to predict pixel-level… Read More »Unveil The Secrets Of Anatomical Segmentation With HybridGNet: An AI Encoder-Decoder For Plausible Anatomical Structures Decoding Daniele Lorenzi Artificial Intelligence Category – MarkTechPost

​ The MongoDB distinct() is used to get the list of distinct/unique values from a specified field within a collection. Finding distinct values is frequently required to figure out the number of distinct values for particular fields or keys within a collection. In this write-up,… Read More »MongoDB distinct() – Get Unique values from field AQSA Spark By {Examples}

​ MongoDB uses the $match stage in the aggregation pipeline to filter documents according to predetermined criteria. The $match stage in MongoDB is usually the first stage in an aggregation pipeline as it filters the documents before any other stages are executed. You can use… Read More »MongoDB $match Usage AQSA Spark By {Examples}