AI

Creating AI that matters

When it comes to artificial intelligence, MIT and IBM were there at the beginning: laying foundational work and creating some of the first programs — AI predecessors — and theorizing how machine “intelligence” might come to be. Today, collaborations like the MIT-IBM Watson AI Lab, which launched eight years ago, are continuing to deliver expertise

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Serverless deployment for your Amazon SageMaker Canvas models

Deploying machine learning (ML) models into production can often be a complex and resource-intensive task, especially for customers without deep ML and DevOps expertise. Amazon SageMaker Canvas simplifies model building by offering a no-code interface, so you can create highly accurate ML models using your existing data sources and without writing a single line of

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Building a multi-agent voice assistant with Amazon Nova Sonic and Amazon Bedrock AgentCore

Amazon Nova Sonic is a foundation model that creates natural, human-like speech-to-speech conversations for generative AI applications, allowing users to interact with AI through voice in real-time, with capabilities for understanding tone, enabling natural flow, and performing actions. Multi-agent architecture offers a modular, robust, and scalable design pattern for production-level voice assistants. This blog post

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Accelerate large-scale AI training with Amazon SageMaker HyperPod training operator 

Large-scale AI model training faces significant challenges with failure recovery and monitoring. Traditional training requires complete job restarts when even a single training process fails, resulting in additional downtime and increased costs. As training clusters expand, identifying and resolving critical issues like stalled GPUs and numerical instabilities typically requires complex custom monitoring code. With Amazon SageMaker

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