Figure 1: Pure Reinforcement Learning. A simpler abstraction of the RL problem is the Multi-armed bandit problem. A multi-armed bandit problem does not account for the environment and its state ...

Yann LeCun proposed the World Model in paper in June 2022, which uses a “cost module” in its architecture that measures the energy-cost of an action by the machine. When reinforcement learning is ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

The rapid advancement of quantum computing (QC) and machine learning (ML) has given rise to the burgeoning field of quantum machine learning (QML), aiming to capitalize on the strengths of quantum ...

Deep Learning and Reinforcement Learning are two of the most popular subsets of Artificial intelligence. The AI market was about $120 billion in 2022 and is increasing at a mind-boggling CAGR above 38 ...

Reinforcement learning is one form of machine learning based on this concept, but let's not get ahead of ourselves. "Machine Learning is the study of computer algorithms that improve automatically ...

This project is based on the paper: EvoPrompting: Language Models for Code-Level Neural Architecture Search by Angelica Chen, David M. Dohan, and David R. So. The authors successfully demonstrate the ...

Supervised machine learning is a branch of AI. This article covers the relevant concepts, importance in various fields, practical use in investing, and CAPTCHA applications.

Unsupervised machine learning discovers patterns in unstructured data without specific goals. It's utilized in various sectors, enhancing services like streaming and social media suggestions ...