From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
Frontiers

Adaptive multi-mode locomotion for bipedal wheel-legged robots via sparse mixture-of-experts deep reinforcement learning

The bipedal wheel-legged robot combines the high energy efficiency of wheeled movement with the terrain adaptability of legged locomotion. However, achieving a smooth transition between these two ...
VentureBeat

Qwen3-Coder-Next offers vibe coders a powerful open source, ultra-sparse model with 10x higher throughput for repo tasks

Chinese e-commerce giant Alibaba's Qwen team of AI researchers has emerged in the last year as one of the global leaders of open source AI development, releasing a host of powerful large language ...
IEEE

Effective Input Projection for Updating Dictionary Atoms in Sparse Coding-Based Image Denoising

Abstract: Adaptive dictionary learning algorithms jointly optimize sparse representations and dictionary atoms to enhance performance. However, this alternating minimization process is complex, and ...
InfoWorld

Which development platforms and tools should you learn now?

Software development used to be simpler, with fewer choices about which platforms and languages to learn. You were either a Java, .NET, or LAMP developer. You focused on AWS, Azure, or Google Cloud.
Frontiers

Augmenting sparse spaceflight mass spectra datasets for machine learning applications

Relationship between artificial intelligence (AI), machine learning (ML), deep learning (DL), and data science and basic definitions. Representation of the Rosalind Franklin ExoMars rover (credits: ...
marktechpost

OpenAI Researchers Train Weight Sparse Transformers to Expose Interpretable Circuits

If neural networks are now making decisions everywhere from code editors to safety systems, how can we actually see the specific circuits inside that drive each behavior? OpenAI has introduced a new ...
GitHub

Consider "light" use of sparse user-supplied MIP solution

Taking a sparse user-supplied MIP solution, fixing the corresponding variables, and solving the resulting MIP to optimality may be very expensive, and not worth the investment. Introduce a "light" ...
IEEE

A deep dictionary learning framework for device-free localization based on nonconvex sparse regularization and DC programming

Abstract: Received signal strength (RSS) based device-free localization (DFL) is commonly used in the Internet of Things (IoT) field. However, the current DFL algorithms have limitations in terms of ...