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.

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 ...

AI guys love talking about “vibes.” There’s “vibe coding,” a term coined by OpenAI co-founder Andrej Karpathy to describe ...

Fake band exposed by hoax spokesman, turning ChatGPT evil, and a vending machine calls the FBI over $2. The weirdest AI Eye ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

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

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...