A Technology Broker and Management Company Specializing in KM Systems
Favorite 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
Read More
Shared by AWS Machine Learning May 29, 2026
Favorite 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
Read More Shared by AWS Machine Learning May 29, 2026
Favorite 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
Read More Shared by AWS Machine Learning May 29, 2026
Favorite 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
Read More Shared by AWS Machine Learning May 29, 2026
Favorite 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
Read More Shared by AWS Machine Learning May 29, 2026
Favorite 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
Read More Shared by AWS Machine Learning May 29, 2026
Favorite 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
Read More Shared by AWS Machine Learning May 29, 2026
Favorite Here are 12 of the biggest Google I/O 2026 keynote moments, including news about Gemini Omni, Gemini 3.5 Flash and more. View Original Source (blog.google/technology/ai/) Here.
Favorite As agent adoption scaled, we saw a common pattern emerge across enterprises, including our own sales organization: specialized agents deliver value, but without orchestration, users carry the cognitive load of choosing between them. At AWS Sales, this meant more than 20 domain-specific agents deployed across the global organization, with
Read More Shared by AWS Machine Learning May 28, 2026
Favorite AWS leaders manage complex data across multiple hierarchies while making time-sensitive decisions that impact global operations. Traditional business intelligence relies on static dashboards and manual reports, which creates delays and limits organizational agility. NarrateAI, our intelligent conversational solution, addresses this through conversational agentic AI powered by our data lake
Read More Shared by AWS Machine Learning May 28, 2026