Introduction “Cognitive Surrender” is a new phrase coined in a recent paper by Steven Shaw and Gideon Nave at the Wharton School (UPenn) called “Thinking, Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning…

🤖 The Robin Script API Every script gets resilient superpowers: Robin.click, Robin.fill, Robin.waitFor with multi-signal targeting (role, label, text) — plus in-script AI via Robin.ai() and your connected tools via Rob…

Groundbreaker Aug 20, 2026 Nothing looked wrong in the summer of 2006. Home prices had risen for the better part of a decade. Delinquencies were near historic lows. Credit spreads were tight, the ratings held, and the s…

The company used an open-weight model as the base for its own model.

Amazon SageMaker HyperPod now offers managed Ray support on Amazon EKS. Create and monitor Ray clusters, connect JupyterLab and Code Editor notebooks to live clusters, get out-of-the-box observability, and run resilient distributed training and accelerated inference from SageMaker Studio, all with open-source KubeRay and standard Ray APIs.

Only 15% of US-based organizations have reached scaled, orchestrated, multi-agent adoption, according to the latest Deloitte research.

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Verify 837P claims against clinical evidence Product identity PrismClaim is Zero-trust 837P professional claim verification middleware. Insight IT Solutions LLC (Insight ITS) makes it. Category: Research — 837P claim ve…

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Learn how to build a customizable, smart-caching knowledge management system on AWS that captures and delivers institutional (tribal) knowledge through a voice-first AI avatar. The accelerator uses Amazon Bedrock Knowledge Bases for retrieval-augmented generation and deploys in hours with AWS CloudFormation.

Labor Day is just around the corner, and there are already some great deals available at Amazon, Best Buy, Walmart, and more.

Kodamai, an enterprise AI startup, is addressing the growing concerns around the explainability and governance of AI systems by applying mathematically grounded theories.

London and Kyiv in deal to help stop protesters and hostile states targeting military bases and critical infrastructure AI models trained on Ukrainian battlefield data will be used to stop protesters and foreign states targeting UK defence sites, railways and energy plants under a deal struck between London and Kyiv. Private companies will also be given access to the vast trove of data from Ukraine’s Avengers AI lab to help build new systems, the first agreement of its kind in the UK. Continue reading...

A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.

The Blink Outdoor 2K+ security camera and Blink Battery Doorbell 2K+ are on sale in this bundle deal, but not for long.

See how Toyota North America uses Deep Agents and LangSmith to run 50+ production agents, cut delivery from 6 months to 4 days, and track AI ROI.

Physical artificial intelligence is emerging as the next major phase of AI. These systems not only generate content or analyze data but also perceive, reason about and act in the physical world. The opportunity is massive, but so are the operational, data, latency and lifecycle-management challenges. That is why Amazon Web Services Inc. last month […] The post Physical AI’s moment has arrived – but moving from demo to deployment is the hard part. AWS wants to fix that appeared first on SiliconANGLE.

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You can now code your own mini games and 'gizmos' with no experience. Creating is just half the fun.

The Databricks workspace is purposefully built for data analysis and data engineering. However...

In our previous blog post, we shared how Databricks uses AI to debug thousands of...

Choosing between relational and non-relational databases is one of the most consequential...

Transactional Vs Analytical Database: Choosing OLTP, OLAP, or HybridTransactional...

Release: llm-anthropic 0.27 This release of the Anthropic plugin for LLM mainly provides compatibility with the recently released anthropic v1.0.0 Python library, which switches from httpx to httpx2. OpenAI made the same change in their v3.0.0 release two weeks ago. Anthropic provide this migration guide for upgrading to 1.0, so I prompted Fable 5 in Claude Code with: Upgrade to anthropic>=1 - read https://raw.githubusercontent.com/anthropics/anthropic-sdk-python/refs/heads/main/MIGRATION.md and get the tests passing Here's the resulting PR. Tags: python, httpx, llm, anthropic, claude

AWS Agent Registry gives your organization a centralized, searchable catalog for agents, tools, and skills. It works with the open Agentic Resource Discovery (ARD) standard to enable cross-environment discovery and governance at scale.

Learn how to build a voice ordering system for restaurants that answers a phone call and takes an order end to end, with no app, no website, and no sign-in. It uses Amazon Connect for telephony, Amazon Connect Agentic Voice for real-time speech, an Amazon Connect AI agent for reasoning, and Amazon Bedrock AgentCore Gateway to reach backend tools through MCP.

To keep pace with modern business, data strategy is shifting toward more autonomous real-time systems that deliver intelligence at the moment decisions are made. Driven by agentic AI, modern data teams are moving beyond simply looking at what happened. Now they’re automating complex workflows that analyze what’s happening, anticipate what might happen next, and recommend […]

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Metadata harmonization (standardizing labels, identifiers, and formats so datasets can work together) is still largely manual. This post shows how AI-powered metadata correction works in practice, covering two approaches, human-in-the-loop validation and autonomous agent-driven workflows, plus governance considerations for production deployment.

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore. The idea of letting a machine do the driving for you may put a lot of people off autonomous vehicles. But research could make it possible to backseat-drive an autonomous vehicle just as you might with a human driver. Self-driving cars carefully balance a host of parameters to ensure a smooth ride, including things like speed, acceleration, and the smoothness of turns. But human driving preferences can often vary depending on how much of a rush they’re in, whether they’re feeling carsick, or how busy the traffic is. These cars have a software component called the motion planner, which is responsible for choosing a safe and efficient path through traffic. The motion planner is normally tuned by…