Language models seem to be more than stochastic parrots. Does this knowledge stop them from making mistakes, or do they need ...

1. Deep Semantic Reconstruction: Breaking Through the Limits of Surface Expression Many users tend to directly copy and paste the output results when using AI-generated content, which is a major ...

Wang, S. (2025) A Review of Agent Data Evaluation: Status, Challenges, and Future Prospects as of 2025. Journal of Software ...

Like all full-fat Mercedes-AMGs, the A45 S has a ‘race start’ launch control system that requires you to use Race driving ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

None of the most widely used large language models (LLMs) that are rapidly upending how humanity is acquiring knowledge has ...

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational ...

As Meta unveils its powerful on-device reasoner, a wider industry trend emerges where small, specialized models are solving enterprise challenges around cost, privacy, and control.

Thinking like a developer, and leading with those same principles, can help organizations move faster, stay aligned and build ...

As cloud adoption accelerates and systems grow more complex, traditional testing and monitoring approaches are no longer a match to preventing outages. Enterprises face increased pressure to ensure ...

With Magistral 1.2, Mistral continues its dual-path strategy: delivering open, efficient models for developers, while scaling enterprise-ready tools with measurable advantages in reasoning, ...

By implementing a proper data migration strategy, organizations can improve performance, reduce risk and lower spend.