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 chatbot is more humanlike and aware than it actually is, like believing it's ...

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.

Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...

Abstract: Due to its property of not requiring prior knowledge of the environment, reinforcement learning (RL) has significant potential for solving quantum control problems. In this work, we ...

Agentic Context Engine learns from your agent's successes and failures. Just plug in and watch your agents improve.

Department of Curriculum and Instruction, Education College, Umm Al-Qura University, Makkah, Saudi Arabia This mixed-method experimental study investigates the effectiveness and typology of ...

Thor Sawin has received funding for teacher development projects through the State Department Fulbright Specialist and English Language Specialist program, as well as the US Air Force and LCC ...

Inquiry-based learning has been gaining more attention in classrooms across the world. Teachers often ask, What does it look like in practice? How does it differ from more traditional approaches? At ...