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.

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

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

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AI bots told to act as trading agents in simulated markets engaged in pervasive collusion, raising new questions about how ...

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

Here is the AI research roadmap for 2026: how agents that learn, self-correct, and simulate the real world will redefine ...

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