The computing community has largely treated AI hallucinations as a model problem. The default path to reliability has been model improvement: better training data, larger context windows, retrieval ...

A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...

Entity Component System (ECS) architectures have become a standard approach for scaling modern games. They offer predictable performance, efficient memory usage, and a clean way to extend gameplay ...

Ten AI concepts to know in 2026, including LLM tokens, context windows, agents, RAG, and MCP, for building reliable AI apps.

Many engineering challenges come down to the same headache—too many knobs to turn and too few chances to test them. Whether tuning a power grid or designing a safer vehicle, each evaluation can be ...

Spec-driven development doesn’t just change how we work with AI; it fundamentally improves the quality and sustainability of the software we build.

Managing complex medical conditions often requires the simultaneous use of multiple different drugs, referred to as polypharmacy. While necessary, this significantly increases the risk of drug-drug ...

AI-native platform adds enterprise SSO capabilities across 25+ identity providers to existing authentication infrastructure without migration. SAN FRANCISCO, CA, UNITED STATES, Ma ...

New delivery model applies AI across engineering, testing, DevOps, and analytics to improve speed, transparency, and ...

Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on ...

Dyad AI from JuliaHub is bringing an AI-for-Science environment to product development. Users can model and interrogate ...

AI protein function prediction uses machine learning models trained on sequence and structural data to infer protein roles at ...