A Technology Broker and Management Company Specializing in KM Systems
Favorite As data collection and data generation accelerate, the gap between our ability to produce raw data and our capacity to standardize it continues to widen. Without automation, this gap becomes a critical bottleneck that delays analysis, complicates interpretation, and limits the global value of shared datasets. Metadata harmonization (standardizing
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Shared by AWS Machine Learning August 25, 2026
Favorite At many restaurants, a large share of orders still arrive by phone, and those calls usually land on a staff member who is already taking care of customers at the counter. Callers wait on hold, orders get written down by hand, and busy periods make both worse. Adding an
Read More Shared by AWS Machine Learning August 25, 2026
Favorite How AWS Agent Registry and the Agentic Resource Discovery (ARD) specification enable cross-environment discovery for your agents As organizations scale their use of artificial intelligence (AI) agents and tools, finding the right resource becomes the hard part. Teams build Model Context Protocol (MCP) servers, deploy agents, and create specialized
Read More Shared by AWS Machine Learning August 25, 2026
Favorite Organizations across industries struggle with managing institutional knowledge, the collective wisdom and experience accumulated over years of operations. This “tribal knowledge” often disappears when key personnel leave, creating knowledge gaps that impact efficiency and innovation. Traditional documentation methods have proven inadequate, often resulting in outdated or inaccessible information when
Read More Shared by AWS Machine Learning August 25, 2026
Favorite Today, we are announcing new Ray capabilities on Amazon SageMaker HyperPod that integrate Ray with the HyperPod purpose-built infrastructure for foundation model training and serving. Ray is an open-source framework that data scientists use to scale distributed Python workloads across clusters of GPUs, from distributed training with Ray Train
Read More Shared by AWS Machine Learning August 25, 2026
Favorite Panasonic Avionics Corporation provides in-flight entertainment and connectivity (IFEC) systems across a large global fleet serving hundreds of airlines and billions of passengers annually. When a system issue affects passenger experience at this scale, engineers must diagnose the root cause quickly across thousands of unique deployment configurations. Doing this
Read More Shared by AWS Machine Learning August 22, 2026
Favorite Input tokens sent to the foundation model (FM) on every call are often a meaningful part of the cost of running Retrieval Augmented Generation (RAG) at scale. Query-aware compression offers one way to reduce how many of them reach the model. Amazon Bedrock provides the foundation models and features
Read More Shared by AWS Machine Learning August 22, 2026
Favorite In our conversations with customers over the past months, one pattern keeps recurring. Whether they work with coding agents, autonomous agents, or human-interactive ones, and regardless of workload maturity, we start with the same question: “Which AI agents have access to customer data, who granted it, and what would
Read More Shared by AWS Machine Learning August 22, 2026
Favorite Data engineering teams routinely spend weeks standing up a single new data source: writing ETL, hand-writing quality checks, updating semantic models, and validating compliance. The Agentic Data Operations Platform (ADOP) on AWS is designed to significantly accelerate that timeline. It’s a reference architecture built on Amazon Bedrock and your
Read More Shared by AWS Machine Learning August 22, 2026
Favorite KnowledgeForge is about mining gold from the IT Service Management (ITSM) ticket graveyard: the resolved incident tickets whose knowledge never reaches a knowledge base article. Enterprise IT support teams resolve thousands of tickets every month, and each one holds something useful: a symptom, a root cause, and the fix
Read More Shared by AWS Machine Learning August 21, 2026