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

On SWE-Bench Verified, the model achieved a score of 70.6%. This performance is notably competitive when placed alongside ...
DMR News

Physical Intelligence Bets On General-Purpose Robot Learning Over Commercial Timelines

Physical Intelligence, a two-year-old robotics startup based in San Francisco, is pursuing a research-first approach to general-purpose robotic intelligence, ...

Arcee's U.S.-made, open source Trinity Large and 10T-checkpoint offer rare look at raw model intelligence

San Francisco-based AI lab Arcee made waves last year for being one of the only U.S. companies to train large language models (LLMs) from scratch and release them under open or partially open source ...

AI systems learn better when trained with inner speech like humans

Talking to yourself feels deeply human. Inner speech helps you plan, reflect, and solve problems without saying a word.

Physics-constrained AI boosts satellite weather accuracy

FAYETTEVILLE, GA, UNITED STATES, January 29, 2026 /EINPresswire.com/ -- Accurate atmospheric temperature profiles are ...
Frontiers

Machine Learning for Hydrological Modeling in Water Resource Management in Data-Scarce Regions

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...
IEEE

Sparse-FCL: Sparse Federated Continual Learning for Evolving Mobile Edge Computing Environments

Abstract: Mobile Edge Computing (MEC) leverages embedded devices to deliver low-latency and cost-effective intelligent services, such as autonomous driving. Federated learning allows MEC devices to ...
IEEE

Performance Enhancement on Sparse Federated Learning Supported by RIS-Aided Communication in the Finite Blocklength Regime

Abstract: Federated learning (FL) has been considered as a promising way to train distributed wireless systems in a privacy-preserving manner. However, the significant communications overheads caused ...
Frontiers

A sparse tensor generator with efficient feature extraction

Sparse tensor operations are increasingly important in diverse applications such as social networks, deep learning, diagnosis, crime, and review analysis. However, a major obstacle in sparse tensor ...
Forbes

Enhancing Your Leadership With Continuous Learning

When I started my first degree fresh out of high school, I was flooded with advice about what to study and what career path to follow. The most significant piece of guidance was from one of my ...