These universal truths form the shared foundation upon which a great deal of rigorous and robust merit-based inquiry is ...

In 2026, here's what you can expect from the AI industry: new architectures, smaller models, world models, reliable agents, ...

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

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.

Abstract: The rise of e-commerce demands greater efficiency in warehouses, requiring dynamic task allocation among humans and robots. Traditional methods often fail in such complex environments. This ...

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a ...

Abstract: This paper addresses the dynamic task assignment problem for multiple uncrewed aerial vehicles (UAVs) operating under weak communication. Existing learning-based methods face two primary ...