​[[{“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

​[[{“value”:” Large Language Models (LLMs) have revolutionized software engineering, demonstrating remarkable capabilities in various coding tasks. While recent efforts have produced autonomous software agents based on LLMs for end-to-end development tasks, these systems are typically designed for specific Software Engineering (SE) tasks. Researchers from FPT… Read More »FPT Software AI Center Introduces HyperAgent: A Groundbreaking Generalist Agent System to Resolve Various Software Engineering Tasks at Scale, Achieving SOTA Performance on SWE-Bench and Defects4J Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In June, I started a series of posts that highlight the key factors that are driving customers to choose Amazon Bedrock. The first covered building generative AI apps securely with Amazon Bedrock, while the second explored building custom generative AI applications with Amazon Bedrock.… Read More »Enabling complex generative AI applications with Amazon Bedrock Agents Vasi Philomin AWS Machine Learning Blog

​[[{“value”:” Understanding multi-page documents and news videos is a common task in human daily life. To tackle such scenarios, Multimodal Large Language Models (MLLMs) should be equipped with the ability to understand multiple images with rich visually-situated text information. However, comprehending document images is more… Read More »Optimizing Document Understanding with DocOwl2: A Novel High-Resolution Compression Architecture Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AI has seen significant progress in coding, mathematics, and reasoning tasks. These advancements are driven largely by the increased use of large language models (LLMs), essential for automating complex problem-solving tasks. These models are increasingly used to handle highly specialized and structured problems in… Read More »Stanford Researchers Explore Inference Compute Scaling in Language Models: Achieving Enhanced Performance and Cost Efficiency through Repeated Sampling Nikhil Artificial Intelligence Category – MarkTechPost