Skip to content
AI News HubLIVE

Live AI News Intelligence

Live monitoring

The most important shift in AI today

105 sources in the directory · Latest publication in this list: 2026-06-17 21:45 UTC.

Live monitoring

Live updates

Trusted sources, attribution, rights, and in-site reading distilled into a signal-first AI brief.

Live updates

Reset

2026-06-17

Payment Fraud Detection: How Banks and Businesses Stop Fraudulent Transactions

Payment fraud detection combines rule-based systems, machine learning, and real-time monitoring to block unauthorized transactions. Learn about major fraud types, detection techniques, and prevention strategies.

Databricks BlogAgents / ResearchIn-site articlePayment Fraud Detection: How Banks and Businesses Stop Fraudulent Transactions
What is an AI agent harness?

An AI agent harness is the software infrastructure that wraps around a large language model (LLM) and enables it to act on tasks, not just respond to prompts. This article explains the core components—tools, memory, sandboxes, and guardrails—and how they enable reliable action through a reason-act-observe loop. It covers eight building blocks, common failure modes, and why harness design is critical for enterprise AI strategy.

Databricks BlogModels / Agents / PolicyIn-site articleWhat is an AI agent harness?
Amazon SageMaker AI Async Inference now supports inline request payloads

Today, we’re announcing inline payload support for Amazon SageMaker AI Async Inference. Customers can now send inference payloads directly in the request body of the InvokeEndpointAsync API, removing the need to upload input data to Amazon Simple Storage Service (Amazon S3) before each invocation.

AWS Machine Learning BlogAgentsIn-site articleAmazon SageMaker AI Async Inference now supports inline request payloads
Get back hours every day with autonomous agents in Amazon Quick

Amazon Quick introduces autonomous agents that work continuously, a prioritized activity feed, and cross-data source insights from a single question, helping users reclaim hours daily.

AWS Machine Learning BlogAgents / Policy / ResearchIn-site articleGet back hours every day with autonomous agents in Amazon Quick
Databricks and NVIDIA: Building for the Agentic Era

Databricks and NVIDIA are expanding their collaboration to deliver an end-to-end AI platform that accelerates model training, inference, and agentic AI development on governed enterprise data. New capabilities include Multinode training in AI Runtime, GPU support in Databricks Free Edition, Model Serving Enhancements, and support for NVIDIA technologies such as NVIDIA Agent Toolkit. Customers can leverage NVIDIA’s industry-specific AI frameworks directly within Databricks to accelerate use cases across healthcare, life sciences, supply chain, robotics, digital twins, and document intelligence.

Databricks BlogModels / Agents / ChipsIn-site articleDatabricks and NVIDIA: Building for the Agentic Era
Getting more from each token: How Copilot improves context handling and model routing

GitHub Copilot is improving efficiency by reducing redundant context through prompt caching and deferred tool loading, and by introducing Auto model selection that routes tasks to the best-fit model based on intent and real-time health, saving credits without sacrificing quality.

GitHub AI & MLAgents / ResearchIn-site articleGetting more from each token: How Copilot improves context handling and model routing
Bringing more agent harnesses and frameworks to Cloudflare, starting with Flue

Cloudflare is opening up its Agents SDK primitives for any agent framework to build on, with Flue as the first open-source framework targeting the SDK. Flue, built on the Pi harness, leverages Durable Objects for durable execution, dynamic code execution via Code Mode, and a virtual filesystem via @cloudflare/shell, enabling production-grade agent deployment.

Cloudflare AI BlogAgentsIn-site articleBringing more agent harnesses and frameworks to Cloudflare, starting with Flue