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Gen AI News Talk

Build an agentic multimodal AI assistant with Amazon Nova and Amazon Bedrock Data Automation

Modern enterprises are rich in data that spans multiple modalities—from text documents and PDFs to presentation slides, images, audio recordings, and more. Imagine asking an AI assistant about your company’s quarterly earnings call: the assistant should not only read the transcript but also “see”...

No-code data preparation for time series forecasting using Amazon SageMaker Canvas

Time series forecasting helps businesses predict future trends based on historical data patterns, whether it’s for sales projections, inventory management, or demand forecasting. Traditional approaches require extensive knowledge of statistical methods and data science methods to process raw time series data. Amazon SageMaker Canvas offers...

Build a scalable AI video generator using Amazon SageMaker AI and CogVideoX

In recent years, the rapid advancement of artificial intelligence and machine learning (AI/ML) technologies has revolutionized various aspects of digital content creation. One particularly exciting development is the emergence of video generation capabilities, which offer unprecedented opportunities for companies across diverse industries. This technology...

Building trust in AI: The AWS approach to the EU AI Act

As AI adoption accelerates and reshapes our future, organizations are adapting to evolving regulatory frameworks. In our report commissioned to Strand Partners, Unlocking Europe’s AI Potential in the Digital Decade 2025, 68% of European businesses surveyed underlined that they struggle to understand their responsibilities...

Update on the AWS DeepRacer Student Portal

The AWS DeepRacer Student Portal will no longer be available starting September 15, 2025. This change comes as part of the broader transition of AWS DeepRacer from a service to an AWS Solution, representing an evolution in how we deliver AI & ML education....

Accelerate foundation model training and inference with Amazon SageMaker HyperPod and Amazon SageMaker Studio

Modern generative AI model providers require unprecedented computational scale, with pre-training often involving thousands of accelerators running continuously for days, and sometimes months. Foundation Models (FMs) demand distributed training clusters — coordinated groups of accelerated compute instances, using frameworks like PyTorch — to parallelize...