Researchers from Stanford University and Google DeepMind have unveiled Step-Wise Reinforcement Learning (SWiRL), a technique designed to enhance the ability of large language models (LLMs) to tackle ...

Deep Learning Prerequisites: The Numpy Stack in Python https://deeplearningcourses.com/c/deep-learning-prerequisites-the-numpy-stack-in-python Deep Learning ...

The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my ...

Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various ...

In EIS, Distributed Machine Learning (DML), which requires fewer computing ... Vehicles (IoV), one of the typical scenarios of EIS, and consider the DML-based High Definition (HD) mapping and ...

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

OpenAI announced the release of a pair of models, o3 and o4-mini. In announcing them, the company referred to them as “the ...

Apr. 23, 2025 — A new study by developmental scientists offers the first evidence that infants as young as 15 months can identify an object they have learned about from listening to language ...

Strong methods do exist for measuring animal movement in the context of energy expenditure, but these are limited by the physical size of the equipment used. Now, in a paper published in the Journal ...

Rule-based reinforcement learning (RL) or reinforcement fine-tuning (RFT) is a promising alternative, requiring only dozens to thousands of samples instead of massive datasets. Various approaches have ...