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University of Waterloo students develop AI prototypes like sign language tutors to reshape the future of education and work. ​ 

This solution builds on open source tools including PyTorch, Hugging Face Transformers, and Liger Kernels. The authors would also like to thank Aiham Taleb, Arefeh Ghahvechi, Manav Choudhary, Rohit Thekkanal, Daz Akbarov, Jamila Jamilova, Ross Povelikin, Almas Moldakanov, Christelle Xu, and Ivan Khvostishkov for their contributions in making this project possible. Azercell Telecom LLC, Azerbaijan’s …

Training Azerbaijani language models on Amazon SageMaker AI Read More »

As ML teams grow, embedding Amazon SageMaker AI MLflow Apps into a custom portal requires a scalable approach to access management. Distributing presigned URLs doesn’t scale for teams with dozens of data scientists, and granting individual AWS Management Console access adds operational overhead for administrators managing access controls. Teams who rely on SSO-integrated internal portals …

Build a custom portal with embedded Amazon SageMaker AI MLflow Apps Read More »

Machine learning (ML) teams use MLflow to manage their ML lifecycle effectively. Amazon SageMaker MLflow provides comprehensive ML experiment tracking and model management capabilities. However, many enterprises have existing infrastructure requirements that need HTTPS-based integrations rather than direct SDK usage. Many organizations need to integrate Amazon SageMaker MLflow with their established systems while maintaining their …

Streamline external access to Amazon SageMaker MLflow using a REST API proxy Read More »

This post was co-authored with Karan Singh, Head of Partnerships at LangChain Validating AI agent behavior before production is one of the hardest problems in applied AI. Agents are non-deterministic, multi-step where errors in early steps can affect downstream results. A single bad tool call can cascade through an entire workflow. LangSmith on AWS gives …

Evaluating Deep Agents using LangSmith on AWS Read More »

Agent evaluation is most powerful when you combine fast-moving online signals with stable offline baselines. To understand whether your agent is truly improving over time, you need a fixed benchmark alongside your changing real-world traffic. Managing test cases for evaluation baselines as a dataset in Amazon Bedrock AgentCore brings the discipline of versioned test fixtures …

Build a test suite that grows with your agent with dataset management in Amazon Bedrock AgentCore Read More »

Today, we’re excited to announce the availability of Anthropic’s most advanced Opus model, Claude Opus 4.8, on Amazon Bedrock and the Claude Platform on AWS. Claude Opus 4.8 represents a meaningful step forward, delivering improvements across the workflows teams run in production, from agentic coding and deep knowledge work to multi-stage autonomous tasks that span …

Claude Opus 4.8 is now available on AWS Read More »

Financial institutions running on AWS and Snowflake benefit from a deeply integrated framework that combines Snowflake’s AI Data Cloud with AWS cloud infrastructure, including integrations with AWS services such as Amazon Simple Storage Service (Amazon S3), AWS Glue, Amazon SageMaker, and Amazon Bedrock. With over 50 native integrations between AWS services and Snowflake, organizations can …

Automate AML alert triage with Amazon Quick and Snowflake Cortex AI Read More »

Here are 12 of the biggest Google I/O 2026 keynote moments, including news about Gemini Omni, Gemini 3.5 Flash and more. ​ 

Financial institutions process thousands of documents daily, including tax forms, loan statements, and purchase orders. Each has a unique format, structure, and field names, making it challenging to create automation workflows using optical character recognition (OCR) software. Amazon Bedrock Data Automation (BDA) helps solve these challenges by automating the extraction, validation, and analysis of data …

Process financial documents using Amazon Bedrock Data Automation Read More »