JuliaHub Announces Dyad 3.0 General Availability, Bringing Agentic AI to Physics-Based Engineering

Apple is being re-rated as an AI winner on the back of “agentic” iPhone and Mac ecosystems rather than frontier models, and the next question is whether on-device agents eventually plug into tokenized payments and assets. Apple’s perceived AI weakness,…

Demonstrating how agentic AI can empower the federal workforce illustrates the art of what's possible, according to Chris Kraft, Secret Service CIO.

AI factories are token factories, converting power into intelligence in real time. And as agentic AI scales and autonomous, always-on special agents are deployed in the enterprise, performance per watt and cost per token become the economics that matter.

With the rise of agentic AI, developers need secure but also lightweight solutions for running their agents. The agent should be able to do all the things a human developer could do with containers — build them, install software into them, and modify files they have access to — but in a way that protects the host system from the agent doing something destructive. Docker offers several different levels of isolation for running containers. Each comes with its own trade-offs. Some are faster, but less inherently secure; others are slower, but better protected against attack or egress. In April, Docker introduced a new kind of isolation for containers, one specifically designed to run AI agents: Docker Sandboxes. Docker Sandboxes explained Docker Sandboxes use what is called a “microVM” to isolate containers. A microVM is a virtual machine that runs on the native hypervisor of the host operating system for isolation. The “micro” comes from the design of the VM, which is specifically for ru

The shift to agentic AI creates a new CPU requirement for the AI factory: fast cores, massive memory bandwidth and the ability to sustain high performance when all cores are active. Initial benchmark results published by Phoronix today show that the NVIDIA Vera CPU meets this need. For this first public look, the benchmark scope […]

Amid rapidly growing adoption of enterprise-level AI agents, there’s a disconnect emerging between ambition and execution.  Although 85% of organizations say they want to be agentic within the next three years, 76% say their current operations and infrastructure can’t support that change. They cite a lack of readiness across people, processes, and workflows.  The sticky…

In many agentic AI workflows, tools ask for permission before they act. A prompt appears, you click approve, the action runs. It feels like control. But by the time that prompt shows up, the tool may already have access to your email, files, or credentials. In Herbert’s view, that approval may not mean much if access was already handed over when the user connected the integration.

This post demonstrates how Agentic AI and SAS Viya can modernize SME loan origination by combining OCR, LLMs, governed decisioning, and interactive dashboards to accelerate transparent, explainable, and scalable credit decisions. The post How Agentic AI Accelerates SME Credit Decisions with SAS Viya appeared first on SAS Blogs.