The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production.

Learn how XAI and LLM observability are transforming GenAI deployments, ensuring trust and reliability in AI-driven insights.

LLM-as-a-judge is exactly what it sounds like: using one language model to evaluate the outputs of another. Your first ...

Some predict that by 2028, more people will discover products and information through large language models (LLMs) like ChatGPT and Gemini than through traditional search engines. But based on ...

There is a quiet assumption running through most enterprise GenAI deployments: if the output looks right, it is right. In low-stakes environments, that is a reasonable shortcut. In regulated ...

LLM-assisted manuscripts exhibit more complexity of the written word but are lower in research quality, according to a Policy Article by Keigo Kusumegi, Paul Ginsparg, and colleagues that sought to ...

Erman Ayday, Co-Faculty Director, xLab; Associate Professor, Computer and Data Science The rapid expansion of artificial intelligence (AI) and natural language processing (NLP) in recent years has ...

A consistent media flood of sensational hallucinations from the big AI chatbots. Widespread fear of job loss, especially due to lack of proper communication from leadership - and relentless overhyping ...

Benchmarking four compact LLMs on a Raspberry Pi 500+ shows that smaller models such as TinyLlama are far more practical for local edge workloads, while reasoning-focused models trade latency for ...