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

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

It has become one of the fastest ways to improve productivity, reduce workload, and give teams practical tools they can apply ...

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.

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 ...

We evaluate DeepCode on the PaperBench benchmark (released by OpenAI), a rigorous testbed requiring AI agents to independently reproduce 20 ICML 2024 papers from scratch. The benchmark comprises 8,316 ...

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.

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 ...