Micro1 is building the evaluation layer for AI agents providing contextual, human-led tests that decide when models are ready ...

A duplex speech-to-speech model changes the premise: The intelligence layer consumes audio and produces audio directly. The model can attend to what was said and how it was said—content and delivery ...

Enter large language model (LLM) evaluation. The purpose of LLM evaluation is to analyze and refine GenAI outputs to improve their accuracy and reliability while avoiding bias. The evaluation process ...

Anthropic and OpenAI ran their own tests on each other's models. The two labs published findings in separate reports. The goal was to identify gaps in order to build better and safer models. The AI ...

Databricks Inc. today announced a series of updates to its flagship artificial intelligence product, Agent Bricks, aimed at improving governance, accuracy and model flexibility for enterprise AI ...

A new study published by TELUS Digital, The Robustness Paradox: Why Better Actors Make Riskier Agents, finds that the use of ...

For cross-provider support, it is critical that evaluation benchmarks can be defined once and reused across multiple models, despite differences in their APIs. To this end, LMEval uses LiteLLM, a ...

In the context of global decarbonization, reducing energy consumption in the building sector is an urgent issue. Researchers have developed a next-generation building energy evaluation model that ...

The authors discuss multiple challenges to the production of policy-relevant results from evaluation of Medicare accountable care organizations (ACOs). Objectives: To explain key challenges to ...