I asked ChatGPT to help me learn coding in a 12-Sunday upskilling plan: AI gives me structured routine

I am a software engineer. But, there is one thing still missing from my profile: coding. I asked ChatGPT to prepare a ...
marktechpost

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

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 ...
Beebom

What Is ChatGPT and How Does It Work? Everything You Need to Know (2026)

ChatGPT is an AI chatbot developed by OpenAI and it uses a large language model (LLM) to generate human-like responses. It can also generate images, videos, interact in real-time using audio, and ...
Forbes

Leadership Amid Uncertainty: CEOs Can Learn Effective Decision Making From Reinforcement Learning

Leaders, whether in boardrooms or garages, constantly face an unchanging force: uncertainty. For a CEO, making a good decision always involves factoring in as much data as possible, and then trusting ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
GitHub

Deep Reinforcement Learning in Robotics

In this tutorial, we'll be creating artificially intelligent agents that learn from interacting with their environment, gathering experience, and a system of rewards with deep reinforcement learning ...
GitHub

SCOPE-RL: A Python library for offline reinforcement learning, off-policy evaluation, and selection

SCOPE-RL is an open-source Python Software for implementing the end-to-end procedure regarding offline Reinforcement Learning (offline RL), from data collection to offline policy learning, off-policy ...
marktechpost

Weak-for-Strong (W4S): A Novel Reinforcement Learning Algorithm that Trains a weak Meta Agent to Design Agentic Workflows with Stronger LLMs

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
IEEE

Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

Abstract: Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across ...
the-decoder

Go read this to learn how reinforcement learning makes LLMs better at reasoning

AI researcher Sebastian Raschka has published a new analysis that looks at how reinforcement learning is used to improve reasoning in large language models (LRMs). In a blog post, he describes how ...