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Curated links from external sources — not 360Softy original articles.

ExternalAI
AWS Machine Learning Blog

Beyond the price per token: Choosing the right OpenAI model on Amazon Bedrock for your workload

Comparing models on dollars per million tokens misses what production workloads actually pay for: outcomes. This post shares an open-source benchmarking harness that measures cost per correct answer, agent trajectory cost, and rubric-graded deliverable quality across OpenAI models on Amazon Bedrock.

Advanced (300)Amazon BedrockTechnical How-to
AWS Machine Learning BlogRead original
ExternalAI
AWS Machine Learning Blog

Build interactive MCP Apps using Amazon Bedrock AgentCore

Learn how to build and deploy an MCP App with interactive HTML widgets on Amazon Bedrock AgentCore. Because MCP Apps is a host-agnostic standard, the same server delivers the same rich experience across AI hosts like ChatGPT and Claude that support the extension.

Amazon Bedrock AgentCoreIntermediate (200)Technical How-to
AWS Machine Learning BlogRead original
ExternalCybersecurity
Dark Reading

Why AI Is So Good at Scamming Humans

Fred Heiding of Menlo Park Intelligence talks with the Dark Reading News Desk about his research on frontier models, and their ability to influence human behavior and create emotional dependency.

Dark ReadingRead original
ExternalSoftware Engineering
DZone

When TypeScript Types Meet Untrusted AI: Building Type-Safe LLM Pipelines With Runtime Validation

TypeScript can make an LLM integration look safer than it is. A function may promise Promise<Classification> and every branch may compile under strict settings, yet none of those guarantees prove that a model returned a valid Classification. TypeScript annotations are erased during compilation and do not alter runtime behavior, so data crossing an AI boundary remains untrusted until executable validation proves otherwise.  The practical goal is a pipeline in which model output becomes domain dat

DZoneRead original

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