Self-learning AI releases NFL picks, score predictions every 2026 NFL Wild Card Weekend game

The 2026 NFL Wild Card Weekend schedule features two games on Saturday, three on Sunday and one 'Monday Night Football' ...
GitHub

verl: Volcano Engine Reinforcement Learning for LLMs

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.
IEEE

MAGECODE: Machine-Generated Code Detection Method Using Large Language Models

Abstract: The widespread use of virtual assistants (e.g., GPT4 and Gemini, etc.) by students in their academic assignments raises concerns about academic integrity. Consequently, various ...
IEEE

Integrating Convolution and Sparse Coding for Learning Low-Dimensional Discriminative Image Representations

Abstract: This work investigates the problem of efficiently learning discriminative low-dimensional (LD) representations of multiclass image objects. We propose a generic end-to-end approach that ...

Children and parents given opportunity to try their hand at AI

Families explored the world of artificial intelligence at a hands-on workshop. Code Ninjas in High Wycombe opened its doors ...
Community Impact Newspaper

Code Ninjas now offering coding lessons in Spring

Code Ninjas offers classes in computer programming, game coding and robotics for children ages 5-14. Families can join the waitlist for classes online via the business’s website. Daily news about your ...
AOL

Ex-Meta staffer nicknamed 'coding machine' says the best engineers aren't on LinkedIn — but they're special cases

Michael Novati, a former Meta principal software engineer, said that the best engineers' names are "nowhere" online. "The $100 million engineer is not on LinkedIn with a tagline that's like, ...
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...