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.

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

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

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 ...

After more than two years of public fretting over AI models as future threats to human civilization or the seedlings of ...

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 ...