​[[{“value”:” Recent advancements in text-to-speech (TTS) synthesis have struggled to achieve high-quality results due to the complexity of speech, which involves various attributes like content, prosody, timbre, and acoustic details. While scaling up dataset size and model complexity has shown promise for zero-shot TTS, issues… Read More »Revolutionizing Text-to-Speech Synthesis: Introducing NaturalSpeech-3 with Factorized Diffusion Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The evolution of artificial intelligence, particularly in the realm of neural networks, has significantly advanced our data processing and analysis capabilities. Among these advancements, the efficiency of training and deploying deep neural networks has become a paramount focus. Recent trends have shifted towards developing… Read More »Researchers from the University of Cambridge and Sussex AI Introduce Spyx: A Lightweight Spiking Neural Networks Simulation and Optimization Library designed in JAX Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In recent research, a team of researchers has introduced SynCode, a versatile and efficient approach for generating syntactically accurate code across various programming languages. SynCode works with a variety of Large Language Model (LLM) decoding algorithms, including beam search, sampling, and greedy.  The primary… Read More »Meet SynCode: A Novel Machine Learning Framework for Efficient and General Syntactical Decoding of Code with Large Language Models (LLMs) Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Neural text embeddings play a foundational role in many modern natural language processing (NLP) applications. These embeddings are like digital fingerprints for words and sentences that enable tasks like judging similarity or finding related documents. Traditionally, masked language models (MLMs) have dominated in generating… Read More »CMU Researchers Present ‘Echo Embeddings’: An Embedding Strategy Designed to Address an Architectural Limitation of Autoregressive Models Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Inflection AI presents a new advancement in the field of large language models (LLMs), Inflection-2.5, to address the challenges faced in creating highly efficient and competitive LLMs that can power various applications, including personal AI assistants like Pi. The challenge lies in creating such… Read More »Inflection AI presents Inflection-2.5: An Upgraded AI Model that is Competitive with all the World’s Leading LLMs like GPT-4 and Gemini Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In recent years, machine learning has significantly shifted away from the assumption that training and testing data come from the same distribution. Researchers have identified that models perform better when handling data from multiple distributions. This adaptability is often achieved through what’s known as… Read More »This AI Paper from NYU and Meta Reveals ‘Machine Learning Beyond Boundaries – How Fine-Tuning with High Dropout Rates Outshines Ensemble and Weight Averaging Methods’ Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models, predominantly based on transformer architectures, have reshaped natural language processing. The LLaMA family of models has emerged as a prominent example. However, a fundamental question arises: can the same transformer architecture be effectively applied to process 2D images? This paper introduces… Read More »Bridging Modalities with VisionLLaMA: A Unified Architecture for Vision Tasks Vibhanshu Patidar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The relentless advancement in natural language processing (NLP) has ushered in an era of large language models (LLMs) capable of performing various complex tasks with unprecedented accuracy. These models, however, come at the cost of extensive computational and memory requirements, limiting their deployment in… Read More »EasyQuant: Revolutionizing Large Language Model Quantization with Tencent’s Data-Free Algorithm Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Reinforcement Learning (RL) has become a cornerstone for enabling machines to tackle tasks that range from strategic gameplay to autonomous driving. Within this broad field, the challenge of developing algorithms that learn effectively and efficiently from limited interactions with their environment remains paramount. A… Read More »Advancing Sample Efficiency in Reinforcement Learning Across Diverse Domains with This Machine Learning Framework Called ‘EfficientZero V2’ Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Integrating APIs into Large Language Models (LLMs) represents a significant leap forward in the quest for highly functional AI systems capable of performing complex tasks such as hotel bookings or job requisitions through conversational interfaces. This advancement, however, hinges on the LLMs’ ability to… Read More »IBM AI Research Introduces API-BLEND: A Large Corpora for Training and Systematic Testing of Tool-Augmented LLMs Vineet Kumar Artificial Intelligence Category – MarkTechPost