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Run MiniMax models on Amazon Bedrock

Favorite Organizations are increasingly adopting open-weight foundation models (FMs) to power production AI workloads, from agentic coding assistants to long-context document analysis. As these workloads move from experimentation to enterprise deployment, two requirements shape every model selection decision: the model must deliver the capabilities the workload demands, and the inference

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Shared by AWS Machine Learning July 7, 2026

Teaching models to forget: Selective unlearning with Amazon Nova

Favorite Organizations deploying foundation models (FMs) often encounter a common challenge: model safeguards designed for content moderation can also prevent legitimate, business-critical use cases. A media company summarizing scripts with mature language, a cyber security firm simulating real-world threats, or a legal team processing sensitive evidence may all find that

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Shared by AWS Machine Learning July 7, 2026

From Hugging Face to Amazon SageMaker Studio in one click

Favorite Today, we’re excited to announce a deep-link integration between Hugging Face and Amazon SageMaker AI. Developers can now go from model discovery to hands-on experimentation in SageMaker Studio with a single selection. Whether you fine-tune a foundation model (FM) from Amazon SageMaker JumpStart or deploy it to an Amazon

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Shared by AWS Machine Learning July 7, 2026

How Amazon Bedrock catches AI-generated phishing

Favorite Social engineering through phishing remains one of the most common tactics for launching cyberattacks. AI-generated phishing email messages now pose a new challenge for security teams managing email systems, significantly raising the risk because of their advanced sophistication. Modern social engineers use generative AI and open source intelligence (OSINT)

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Shared by AWS Machine Learning July 2, 2026

Safely Releasing Frontier Models to Customers

Favorite It’s our goal for AWS to be the most secure place to run any workload, and in support of that we’ve been deeply investing in security across our services since AWS’s inception more than two decades ago.  Our AI services like Amazon Bedrock are built on this foundation and with the

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Shared by AWS Machine Learning July 1, 2026

Accelerate protein design with BoltzGen on Amazon SageMaker AI

Favorite BoltzGen on Amazon SageMaker AI accelerates protein binder design by managing GPU compute infrastructure end to end. BoltzGen is a diffusion-based generative model that designs proteins and peptides capable of binding to specific biomolecular targets. A typical design campaign involves multiple GPU-intensive steps: backbone generation, inverse folding, structural validation,

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Shared by AWS Machine Learning July 1, 2026

HippoRAG: Neurobiologically inspired RAG using Amazon Bedrock, Amazon Neptune, and personalized PageRank

Favorite Large language models (LLMs) have transformed how we process and generate information, but they still struggle with effectively integrating knowledge across multiple sources. Standard Retrieval Augmented Generation (RAG) methods, although helpful, often fall short when tackling multi-hop reasoning tasks that require connecting information from separate documents. To address these

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Shared by AWS Machine Learning July 1, 2026