​[[{“value”:” Generative modeling, particularly diffusion models (DMs), has significantly advanced in recent years, playing a crucial role in generating high-quality images, videos, and audio. Diffusion models operate by introducing noise into the data and then gradually reversing this process to generate data from noise. They… Read More »This AI Paper Introduces Data-Free Knowledge Distillation for Diffusion Models: A Method for Improving Efficiency and Scalability Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Hebrew University Researchers addressed the challenge of understanding how information flows through different layers of decoder-based large language models (LLMs). Specifically, it investigates whether the hidden states of previous tokens in higher layers are as crucial as believed. Current LLMs, such as transformer-based models, use… Read More »Understanding the Hidden Layers in Large Language Models LLMs Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Reconstructing high-fidelity surfaces from multi-view images, especially with sparse inputs, is a critical challenge in computer vision. This task is essential for various applications, including autonomous driving, robotics, and virtual reality, where accurate 3D models are necessary for effective decision-making and interaction with real-world… Read More »SuRF: An Unsupervised Surface-Centric Framework for High-Fidelity 3D Reconstruction with Region Sparsification Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” We are thrilled to introduce Amazon Elastic Kubernetes Service (Amazon EKS) support in Amazon SageMaker HyperPod, a purpose-built infrastructure engineered with resilience at its core. This capability allows for the seamless addition of SageMaker HyperPod managed compute to EKS clusters, using automated node and… Read More »Introducing Amazon EKS support in Amazon SageMaker HyperPod Keita Watanabe AWS Machine Learning Blog

​[[{“value”:” IBM’s release of PowerLM-3B and PowerMoE-3B signifies a significant leap in effort to improve the efficiency and scalability of language model training. IBM has introduced these models based on innovative methodologies that address some of the key challenges researchers and developers face in training… Read More »PowerLM-3B and PowerMoE-3B Released by IBM: Revolutionizing Language Models with 3 Billion Parameters and Advanced Power Scheduler for Efficient Large-Scale AI Training Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Data contains information, and information can be used to predict future behaviors, from the buying habits of customers to securities returns. Businesses are seeking a competitive advantage by being able to use the data they hold, apply it to their unique understanding of their… Read More »A review of purpose-built accelerators for financial services Hugh Christensen AWS Machine Learning Blog

​[[{“value”:” Time series data is a distinct category that incorporates time as a fundamental element in its structure. In a time series, data points are collected sequentially, often at regular intervals, and they typically exhibit certain patterns, such as trends, seasonal variations, or cyclical behaviors.… Read More »Anomaly detection in streaming time series data with online learning using Amazon Managed Service for Apache Flink Noah Soprala AWS Machine Learning Blog

​[[{“value”:” Technology operations (TechOps) refers to the set of processes and activities involved in managing and maintaining an organization’s IT infrastructure and services. There are several terminologies used with reference to managing information technology operations, including ITOps, SRE, AIOps, DevOps, and SysOps. For the context… Read More »Generative AI-powered technology operations Raman Pujani AWS Machine Learning Blog

​[[{“value”:” Machine learning operations (MLOps) are a set of practices that automate and simplify machine learning (ML) workflows and deployments. What is MLOps provides a detailed description of this concept. As ML workloads become increasingly complex and consume more energy and resources, a growing number… Read More »Optimizing MLOps for Sustainability Archana Srinivasan AWS Machine Learning Blog

​[[{“value”:” End-to-end (E2E) neural networks have emerged as flexible and accurate models for multilingual automatic speech recognition (ASR). However, as the number of supported languages increases, particularly those with large character sets like Chinese, Japanese, and Korean (CJK), the output layer size grows substantially. This… Read More »Apple Researchers Propose a Novel AI Algorithm to Optimize a Byte-Level Representation for Automatic Speech Recognition ASR and Compare it with UTF-8 Representation Mohammad Asjad Artificial Intelligence Category – MarkTechPost