​ Singing voice conversion (SVC) is a fascinating domain within audio processing, aiming to transform one singer’s voice into another’s while keeping the song’s content and melody intact. This technology has broad applications, from enhancing musical entertainment to artistic creation. A significant challenge in this… Read More »This AI Paper Proposes CoMoSVC: A Consistency Model-based SVC Method that Aims to Achieve both High-Quality Generation and High-Speed Sampling Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​ Language modeling is important for natural language processing tasks like machine translation and text summarization. The core of this development revolves around constructing LLMs that can process and generate human-like text which transforms how we interact with technology. A significant challenge in language modeling… Read More »This Paper Explores Efficient Large Language Model Architectures – Introducing PanGu-π with Superior Performance and Speed Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ BERT is a language model which was released by Google in 2018. It is based on the transformer architecture and is known for its significant improvement over previous state-of-the-art models. As such, it has been the powerhouse of numerous natural language processing (NLP) applications… Read More »Meet MosaicBERT: A BERT-Style Encoder Architecture and Training Recipe that is Empirically Optimized for Fast Pretraining Asif Razzaq Artificial Intelligence Category – MarkTechPost

​ This post is co-written with Jayadeep Pabbisetty, Sr. Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. Model developers… Read More »Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention Tom Kim AWS Machine Learning Blog

​ Meta Research introduced Retrieval-Augmented Generation (RAG) models, a method for refining knowledge manipulation. RAG combines pre-trained parametric-memory generation models with a non-parametric memory, creating a versatile fine-tuning approach. In simple terms, RAG is a natural language processing (NLP) approach that blends retrieval and generation… Read More »8 Open-Source Tools for Retrieval-Augmented Generation (RAG) Implementation Manya Goyal Artificial Intelligence Category – MarkTechPost

​ Studying animal behavior is crucial for understanding how different species and individuals interact with their surroundings. Video coding is preferred for collecting detailed behavioral data, but manually extracting information from extensive video footage is time-consuming. Likewise, manually coding animal behavior demands significant training for… Read More »This Paper Unveils How Machine Learning Revolutionizes Wild Primate Behavior Analysis with DeepLabCut Mahmoud Ghorbel Artificial Intelligence Category – MarkTechPost

​ The prevalence of osteoporosis, a condition that weakens bones due to decreased bone mass, is a significant concern due to the increasing global population. The current methods used to diagnose osteoporosis, primarily relying on central dual-energy X-ray absorptiometry (DXA), have limitations contributing to the… Read More »This Paper Explores How Deep Learning Enhances Osteoporosis Screening with Routine CT Scans Madhur Garg Artificial Intelligence Category – MarkTechPost

​ Large language models have shown notable achievements in executing instructions, multi-turn conversations, and image-based question-answering tasks. These models include Flamingo, GPT-4V, and Gemini. The fast development of open-source Large Language Models, such as LLaMA and Vicuna, has greatly accelerated the evolution of open-source vision… Read More »This AI Research from China Introduces LLaVA-Phi: A Vision Language Assistant Developed Using the Compact Language Model Phi-2 Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ Light is studied in two essential components:  amplitude and phase. However, optical detectors that rely on photon-to-electron conversion face problems capturing the phase due to their restricted sampling frequency. The limitation they face is that while they can easily measure the amplitude, they struggle… Read More »Can Deep Learning Revolutionize Phase Recovery? This Review Paper Explores Its Impact and Future in Computational Imaging Rachit Ranjan Artificial Intelligence Category – MarkTechPost

​ Multimodal learning involves creating systems capable of interpreting and processing diverse data inputs like visual and textual information. Integrating different data types in AI presents unique challenges and opens doors to a more nuanced understanding and processing of complex data. One significant challenge in… Read More »Researchers from Microsoft and NU Singapore Introduce Cosmo: A Fully Open-Source Pre-Training AI Framework Meticulously Crafted for Image and Video Processing Adnan Hassan Artificial Intelligence Category – MarkTechPost