Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

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 ...

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

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

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, ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

With over a decade of experience architecting and operating large-scale cloud environments across AWS, Azure, and Google ...

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

Nemotron-3 Nano (available now): A highly efficient and accurate model. Though it’s a 30 billion-parameter model, only 3 billion parameters are active at any time, allowing it to fit onto smaller form ...

Research reveals why AI systems can't become conscious—and what radically different computing substrates would be needed to ...

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