How do AI coding agents work? We look under the hood.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...
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 ...
The Mobile Rundown on MSN

He built a learning game at 16 that millions of students now use

He launched a learning game at 16 that now reaches millions of students worldwide. Here’s what we can learn from this young ...

Google explains JavaScript execution on non-200 HTTP status codes

Google noted that if the HTTP status code is non-200 (for example, on error pages with 404 status code), rendering might be ...

Frontend Future Announces AI-Integrated Curriculum for Frontend Mentorship Program.

Frontend Future, a mentorship program for working professionals who want to learn to code and transition into a frontend ...

JetBrains Junie IDE Agent : Plans, Acts, Verifies & Refines Your App Code

Discover Junie inside JetBrains IDEs, with Ask mode plus Brave mode to confirm actions, so you ship safer updates with less ...

Google says don’t use JavaScript to generate a noindex tag in the original page code

Google updated its JavaScript SEO basics documentation to clarify that may skip rendering and JavaScript execution.

Google Warns Noindex Can Block JavaScript From Running

Google updated its JavaScript SEO documentation to clarify that noindex tags may prevent rendering and JavaScript execution, ...
IEEE

Coding-Aware Routing for Maximum Throughput and Coding Opportunities by Deep Reinforcement Learning in FANET

Abstract: Coding-Aware routing algorithm improves the performance of Network Coding (NC) by selecting the paths with more coding opportunities, thus increasing the throughput of network transmission.
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.