According to Telefónica's Alex Harmand, agentic AI changes how network APIs generate revenue by shifting pricing away from individual API calls toward outcome-based consumption.

A reinforcement learning environment is a fail-safe digital practice room where an agent can afford to make mistakes and learn from them without real-world consequences.

Central to Collate’s new capabilities is the launch of AI Studio , which enables enterprises to build, deploy, customize, and tune AI agents to their unique data environments. AI Studio provides a ...

As the access and autonomy of AI agents expand, organizations must rethink identity, access and governance models before agent-driven risk scales beyond control.

They can shop, book flights, and control your apps—at least in theory. In practice, today’s AI agents are slow, error-prone, ...

As companies rush to roll out “helpful” AI bots, they’re inadvertently giving those agents broad access to sensitive data.

Many teams are approaching agentic AI with a mixture of interest and unease. Senior leaders see clear potential for efficiency and scale. Builders see an opportunity to remove friction from repetitive ...

This desktop app for hosting and running LLMs locally is rough in a few spots, but still useful right out of the box.

Weights & Biases is a helpful tool to analyze experiments, while Optuna is an effective tool for hyperparameter tuning. To use either of these tools, make sure to check out the notebooks in the ...

Abstract: In this paper, we present an agent-based modeling framework for Unmanned Aerial Vehicle (UAV) operational risk assessment to support large-scale unmanned flights at low altitudes. The main ...

Abstract: Functional integration is a growing trend in vehicle control, often involving the coordination of multiple controllers to achieve various objectives simultaneously. The need for flexibility ...

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