A Technology Broker and Management Company Specializing in KM Systems
Favorite With ComfyUI workflows on Amazon SageMaker AI processing jobs, you can automate content generation at scale. For enterprises, every delay or misstep in creating compelling multimedia assets can mean lost sales, faded brand relevance, or missed marketing deadlines. When a product launch deadline looms or a seasonal promotion needs
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Shared by AWS Machine Learning June 22, 2026
Favorite Turning a library of aerial imagery into a natural-language-searchable knowledge base is a problem that touches every industry that relies on geospatial data — insurance, real estate, government, infrastructure, and agriculture. The traditional path requires either manual tile-by-tile inspection or training a bespoke computer vision model for each new
Read More Shared by AWS Machine Learning June 22, 2026
Favorite This post was co-written with Kevin Jones from Ampersend (Edge & Node) and Chethan Shriyan from the Amazon Bedrock AgentCore Payments team. Ampersend and Amazon Bedrock AgentCore Payments are addressing one of the hardest problems in agentic AI. How do autonomous agents pay for services without developers building bespoke
Read More Shared by AWS Machine Learning June 22, 2026
Favorite Amazon Quick and Adobe Marketing Agent help marketing teams access campaign insights within governed conversations in seconds. Marketers can ask questions about campaign performance, audiences, journeys, campaign conflicts, and content performance in natural language. Amazon Quick provides the chat experience and action orchestration. Adobe provides marketing-domain analysis to the
Read More Shared by AWS Machine Learning June 19, 2026
Favorite AI agents are changing how organizations find and act on information, but they share one structural limitation: their knowledge is frozen at training time. When you ask an agent that relies only on its training data about today’s stock price, a sports score, or a release that shipped an
Read More Shared by AWS Machine Learning June 19, 2026
Favorite A year ago, Simon Willison wrote one of the cleanest definitions of an agent that has stuck around: An LLM agent runs tools in a loop to achieve a goal. That definition stuck because it describes what every production agent actually does. Kiro, Amazon Q Developer, Quick Agents, Codex,
Read More Shared by AWS Machine Learning June 18, 2026
Favorite Monitoring and troubleshooting generative AI inference endpoints operating at scale is challenging. When your large language model (LLM) endpoint’s P99 latency spikes, you must determine in minutes whether the root cause is GPU memory pressure, a saturated KV cache, unbalanced traffic across Availability Zones, or an auto scaling policy
Read More Shared by AWS Machine Learning June 18, 2026
Favorite The Open Source Initiative (OSI) recently submitted comments to Brazil’s National Data Protection Authority (ANPD) regarding its draft guidance on technology providers under the ECA Digital framework, a law to protect children and teenagers in digital environments. Our contribution focused on ensuring that implementation of the law recognizes the
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Shared by voicesofopensource June 18, 2026
Favorite The models powering today’s agents are remarkably capable. They can reason across complex problems, plan multi-step workflows, and generate nuanced responses. But most agents are operating well below that potential. The gap isn’t intelligence. It’s access to the right context and feedback. A customer service agent tasked with answering
Read More Shared by AWS Machine Learning June 17, 2026
Favorite Agents are only as intelligent as the context they can reason over. Today, that context is scattered across data lakes, data warehouses, lakehouses, databases, and streams, and in institutional knowledge that has never been written down. You want to trust the decisions made by your AI agents, but that
Read More Shared by AWS Machine Learning June 17, 2026