Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Patronus AI unveiled “Generative Simulators,” adaptive “practice worlds” that replace static benchmarks with dynamic reinforcement-learning environments to train more reliable AI agents for complex, ...

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Crucially, detection and response must be unified across identity and data layers. An alert about unusual data access is meaningless if it is not correlated with identity risk signals. Autonomous ...

When a blog post by Andrej Karpathy lands in your feed, you pay close attention, simply because few voices in the field of ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

In 2025, large language models moved beyond benchmarks to efficiency, reliability, and integration, reshaping how AI is ...

Nemotron-3 Nano (available now): A highly efficient and accurate model. Though it’s a 30 billion-parameter model, only 3 ...

The rise of the AI gig workforce has driven an important shift from commodity task execution to first-tier crowd contribution ...

Grocery code of conduct comes into effect January 1st Ravens’ Lamar Jackson leaves against Patriots with back injury Ed ...