In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...

Derek's love of games came at an early age when his parents first brought home the Nintendo Entertainment System. From then on, countless nights were spent hunting ducks, stomping turtles, exploring ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...

After previewing at I/O 2025 in May, Google is now rolling out the Gemini 2.5 Deep Think mode to AI Ultra subscribers. Google says “Deep Think pushes the frontier of thinking capabilities by ...

A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...

This repository contains code for the RAL paper LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation. This environment setup is designed for Tensorflow 2.x with NVIDIA RTX ...

Abstract: The Deep Q-Network (DQN) has emerged as a robust deep reinforcement learning algorithm capable of learning optimal policies in complex, high-dimensional environments. The Snake game presents ...

Abstract: Non-orthogonal Multiple Access (NOMA) is a crucial technique in Cognitive Radio Networks (CRNs) that improves frequency band use efficiency. However, NOMA may encounter difficulties due to ...

Forbes contributors publish independent expert analyses and insights. Rachel Wells is a writer who covers leadership, AI, and upskilling. And no, in case you were wondering, python is not a snake in ...