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Ray jobs on Amazon SageMaker HyperPod: scalable and resilient distributed AI Mark Vinciguerra AWS Machine Learning Blog

​[[{“value”:” Foundation model (FM) training and inference has led to a significant increase in computational needs across the industry. These models require massive amounts of accelerated compute to train and operate effectively, pushing the boundaries of traditional computing infrastructure. They require efficient systems for distributing… Read More »Ray jobs on Amazon SageMaker HyperPod: scalable and resilient distributed AI Mark Vinciguerra AWS Machine Learning Blog

Using Large Language Models on Amazon Bedrock for multi-step task execution Bruno Klein AWS Machine Learning Blog

​[[{“value”:” The goal of this blog post is to show you how a large language model (LLM) can be used to perform tasks that require multi-step dynamic reasoning and execution. Examples of tasks that require dynamic reasoning and execution are answering questions of the form… Read More »Using Large Language Models on Amazon Bedrock for multi-step task execution Bruno Klein AWS Machine Learning Blog

The Roadmap for Mastering MLOps in 2025 Iván Palomares Carrascosa MachineLearningMastery.com

​Organizations increasingly adopt machine learning solutions into their daily operations and long-term strategies, and, as a result, the need for effective standards for deploying and maintaining machine learning systems has become critical. Organizations increasingly adopt machine learning solutions into their daily operations and long-term strategies, and,… Read More »The Roadmap for Mastering MLOps in 2025 Iván Palomares Carrascosa MachineLearningMastery.com

Taking a responsible path to AGI Google DeepMind Blog

​We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community. We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community.  Read More  

Mutual Reinforcement of LLM Dialogue Synthesis and Summarization Capabilities for Few-Shot Dialogue Summarization Apple Machine Learning Research

​In this work, we propose Mutual Reinforcing Data Synthesis (MRDS) within LLMs to improve few-shot dialogue summarization task. Unlike prior methods that require external knowledge, we mutually reinforce the LLM’s dialogue synthesis and summarization capabilities, allowing them to complement each other during training and enhance… Read More »Mutual Reinforcement of LLM Dialogue Synthesis and Summarization Capabilities for Few-Shot Dialogue Summarization Apple Machine Learning Research

Universally Instance-Optimal Mechanisms for Private Statistical Estimation Apple Machine Learning Research

​[[{“value”:”We consider the problem of instance-optimal statistical estimation under the constraint of differential privacy where mechanisms must adapt to the difficulty of the input dataset. We prove a new instance specific lower bound using a new divergence and show it characterizes the local minimax optimal… Read More »Universally Instance-Optimal Mechanisms for Private Statistical Estimation Apple Machine Learning Research

The Role of Prosody in Spoken Question Answering Apple Machine Learning Research

​Spoken language understanding research to date has generally carried a heavy text perspective. Most datasets are derived from text, which is then subsequently synthesized into speech, and most models typically rely on automatic transcriptions of speech. This is to the detriment of prosody–additional information carried… Read More »The Role of Prosody in Spoken Question Answering Apple Machine Learning Research

Modeling Speech Emotion With Label Variance and Analyzing Performance Across Speakers and Unseen Acoustic Conditions Apple Machine Learning Research

​Spontaneous speech emotion data usually contain perceptual grades where graders assign emotion score after listening to the speech files. Such perceptual grades introduce uncertainty in labels due to grader opinion variation. Grader variation is addressed by using consensus grades as groundtruth, where the emotion with… Read More »Modeling Speech Emotion With Label Variance and Analyzing Performance Across Speakers and Unseen Acoustic Conditions Apple Machine Learning Research