Favorite This post is cowritten by Paul Burchard and Igor Halperin from Artificial Genius. The proliferation of large language models (LLMs) presents a significant paradox for highly regulated industries like financial services and healthcare. The ability of these models to process complex, unstructured information offers transformative potential for analytics, compliance,
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Shared by AWS Machine Learning March 28, 2026
Favorite Integrating Amazon Bedrock AgentCore with Slack brings AI agents directly into your workspace. Your teams can interact with agents without jumping between applications, losing conversation history, or re-authenticating. The integration handles three technical requirements: validating Slack event requests for security, maintaining conversation context across threads, and managing responses that
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Shared by AWS Machine Learning March 28, 2026
Favorite This post is cowritten by Tal Shapira and Tamir Friedman from Reco. Reco helps organizations strengthen the security of their software as a service (SaaS) applications and accelerate business without compromise. Using Anthropic Claude in Amazon Bedrock, Reco tackles the challenge of machine-readable security alerts that SOC teams struggle
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Shared by AWS Machine Learning March 28, 2026
Favorite Businesses across industries face a common challenge: how to efficiently extract valuable information from vast amounts of unstructured data. Traditional approaches often involve resource-intensive processes and inflexible models. This post introduces a game-changing solution: Claude Tool use in Amazon Bedrock which uses the power of large language models (LLMs)
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Shared by AWS Machine Learning March 28, 2026
Favorite Deploying large language models (LLMs) for inference requires reliable GPU capacity, especially during critical evaluation periods, limited-duration production testing, or burst workloads. Capacity constraints can delay deployments and impact application performance. Customers can use Amazon SageMaker AI training plans to reserve compute capacity for specified time periods. Originally designed
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Shared by AWS Machine Learning March 28, 2026
Favorite In December 2025, we announced the availability of Reinforcement fine-tuning (RFT) on Amazon Bedrock starting with support for Nova models. This was followed by extended support for Open weight models such as OpenAI GPT OSS 20B and Qwen 3 32B in February 2026. RFT in Amazon Bedrock automates the
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Shared by AWS Machine Learning March 28, 2026
Favorite This post is a collaboration between AWS and Pipecat. Deploying intelligent voice agents that maintain natural, human-like conversations requires streaming to users where they are, across web, mobile, and phone channels, even under heavy traffic and unreliable network conditions. Even small delays can break the conversational flow, causing users
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Shared by AWS Machine Learning March 28, 2026
Favorite Video content is now everywhere, from security surveillance and media production to social platforms and enterprise communications. However, extracting meaningful insights from large volumes of video remains a major challenge. Organizations need solutions that can understand not only what appears in a video, but also the context, narrative, and
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Shared by AWS Machine Learning March 28, 2026
Favorite Building natural conversational experiences requires speech synthesis that keeps pace with real-time interactions. Today, we’re excited to announce the new Bidirectional Streaming API for Amazon Polly, enabling streamlined real-time text-to-speech (TTS) synthesis where you can start sending text and receiving audio simultaneously. This new API is built for conversational
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Shared by AWS Machine Learning March 28, 2026
Favorite Last year, AWS announced an integration between Amazon SageMaker Unified Studio and Amazon S3 general purpose buckets. This integration makes it straightforward for teams to use unstructured data stored in Amazon Simple Storage Service (Amazon S3) for machine learning (ML) and data analytics use cases. In this post, we
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Shared by AWS Machine Learning March 28, 2026
Shared by AWS Machine Learning March 28, 2026
