A Technology Broker and Management Company Specializing in KM Systems
Favorite Agentic AI is changing how you work, and vector search powers the retrieval layer that makes agents accurate, contextual, and grounded in real data. Agents plan, reason, and take action across multi-step workflows, making fast, relevant access to your organization’s knowledge essential. That knowledge already has a home across
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Shared by AWS Machine Learning August 21, 2026
Favorite Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore starts with recognizing where large-scale migrations break down. Discovery consumes weeks per application. Engineers write infrastructure code from scratch for each workload. Post-migration operations devolve into reactive firefighting. Multiply those bottlenecks across over 300 applications and a fixed fiscal
Read More Shared by AWS Machine Learning August 21, 2026
Favorite Scaling agentic AI across an enterprise requires architectural patterns that preserve flexibility while avoiding vendor lock-in. This post is Part 2 of our series on multi-agent systems at scale. In this post, we examine how machine learning (ML) teams operate agentic AI systems across a “multi-everything” environment of frameworks,
Read More Shared by AWS Machine Learning August 21, 2026
Favorite AI agents can automate complex workflows but might take actions that don’t align with your organization’s policies or regulatory constraints if used without proper controls. To address this, we built Policy in Amazon Bedrock AgentCore so teams can implement controls that are applied across agents running in Amazon Bedrock
Read More Shared by AWS Machine Learning August 21, 2026
Favorite Part 1 covered the Snowflake database implementation setup and established the foundational infrastructure for our no-code machine learning (ML) workflow. Part 2 walked through the complete data preparation and model building workflow using Amazon SageMaker Canvas, demonstrating how to connect directly to Snowflake data sources, transform and prepare data
Read More Shared by AWS Machine Learning August 21, 2026
Favorite Part 1 covered the Snowflake database setup and established the foundational infrastructure for this no-code machine learning (ML) workflow. Part 2 of this blog series covers complete data preparation and model building workflow using Amazon SageMaker Canvas, demonstrating how to connect directly to Snowflake data sources, transform and prepare
Read More Shared by AWS Machine Learning August 21, 2026
Favorite Healthcare, retail, and life sciences organizations generate massive quantities of operational data in cloud data warehouses like Snowflake. While these systems store and scale information efficiently, transforming that data into meaningful predictions remains a challenge. Traditional machine learning (ML) approaches require specialized teams, long development cycles, and heavy engineering
Read More Shared by AWS Machine Learning August 21, 2026
Favorite This post is co-written with Chris Dickens from OpenAI. Amazon Bedrock now offers OpenAI GPT-5.6 models on Amazon Bedrock in more than 25 AWS Regions, with cross-Region inference. Three GPT-5.6 variants support cross-Region inference, Sol, Terra, and Luna, each tuned for a different balance of capability and cost. Cross-Region
Read More Shared by AWS Machine Learning August 21, 2026
Favorite When an AI agent uses Web Search to ground its answers on behalf of a customer, the organization behind that agent needs domain and date filters to control which sources the agent consults and how fresh those sources must be. A financial-services agent shouldn’t ground its answers in an
Read More Shared by AWS Machine Learning August 20, 2026
Favorite Here’s how you can use Google Search tools to study for classes and standardized tests. View Original Source (blog.google/technology/ai/) Here.