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Organizations are increasingly seeking to enhance customer experiences through natural, responsive voice interactions across their telephony systems. Amazon Nova Sonic addresses this need as a speech-to-speech generative AI model that delivers real-time voice conversations with low latency and natural turn-taking. It understands speech across different accents and speaking styles, responds with expressive voices in multiple …

Building AI-Powered Voice Applications: Amazon Nova Sonic Telephony Integration Guide Read More »

This post was co-written with Andrew Browning, Anthony Doolan, Jerome Ronquillo, Jeff Burke, Chiheb Boussema, and Naisha Agarwal from UCLA. The University of California, Los Angeles (UCLA) is home to 16 Nobel Laureates and has been ranked the #1 public university in the United States for 8 consecutive years. The Office of Advanced Research Computing …

University of California Los Angeles delivers an immersive theater experience with AWS generative AI services Read More »

This post is written by Chaim Rand, Principal Engineer, Pini Reisman, Software Senior Principal Engineer, and Eliyah Weinberg, Performance and Technology Innovation Engineer, at Mobileye. The Mobileye team would like to thank Sunita Nadampalli and Guy Almog from AWS for their contributions to this solution and this post. Mobileye is driving the global evolution toward …

Optimizing Mobileye’s REM™ with AWS Graviton: A focus on ML inference and Triton integration Read More »

This blog post introduces the new Amazon Nova model evaluation features in Amazon SageMaker AI. This release adds custom metrics support, LLM-based preference testing, log probability capture, metadata analysis, and multi-node scaling for large evaluations. The new features include: Custom metrics use the bring your own metrics (BYOM) functions to control evaluation criteria for your …

Evaluate models with the Amazon Nova evaluation container using Amazon SageMaker AI Read More »

Workplaces are increasingly integrating AI tools into daily operations, with AI assistants supporting teams, predictive analytics informing strategies, and automation streamlining workflows. AI has moved from experimental technology to standard business practice, changing how work gets done. Organizations need to understand what AI can do and how it affects their workforce to implement it successfully. …

Beyond the technology: Workforce changes for AI Read More »

You can now achieve significant performance improvements when using Amazon Bedrock Custom Model Import, with reduced end-to-end latency, faster time-to-first-token, and improved throughput through advanced PyTorch compilation and CUDA graph optimizations. With Amazon Bedrock Custom Model Import you can to bring your own foundation models to Amazon Bedrock for deployment and inference at scale. These …

Enhanced performance for Amazon Bedrock Custom Model Import Read More »

Generative AI models continue to expand in scale and capability, increasing the demand for faster and more efficient inference. Applications need low latency and consistent performance without compromising output quality. Amazon SageMaker AI introduces new enhancements to its inference optimization toolkit that bring EAGLE based adaptive speculative decoding to more model architectures. These updates make …

Amazon SageMaker AI introduces EAGLE based adaptive speculative decoding to accelerate generative AI inference Read More »

Sundar Pichai sits down with Logan Kilpatrick to discuss Gemini 3 on the Google AI: Release Notes podcast. ​ 

On October 10, 2024, Amazon announced the discontinuation of the Amazon Lookout for Vision service, with a scheduled shut down date of October 31, 2025 (see Exploring alternatives and seamlessly migrating data from Amazon Lookout for Vision blog post). As part of our transition guidance for customers, we recommend the use of Amazon SageMaker AI tools …

Train custom computer vision defect detection model using Amazon SageMaker Read More »

Artificial Intelligence (AI) is changing how businesses operate. Gartner® predicts at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028. And 92% of companies are boosting their AI spending, according to McKinsey. But here’s the problem: most companies are yet to realize a positive impact of AI on their …

Practical implementation considerations to close the AI value gap Read More »