Machine Learning
Machine learning is a subset of artificial intelligence (AI) that enables systems to learn from data, identify patterns, and make decisions without explicit programming. ML algorithms build models by processing input data and using statistical methods to improve their performance...
LLM Safety
LLM Safety refers to the practices and methodologies designed to ensure that Large Language Models (LLMs) operate responsibly, ethically, and without causing harm. It involves aligning LLMs with societal values, reducing biases, and mitigating risks like harmful content, misinformation, or...
LLM Observability
LLM Observability refers to the practice of gaining in-depth visibility into the behavior, performance, and decision-making processes of Large Language Models (LLMs). It focuses on understanding how and why LLMs produce certain outputs, enabling developers to identify issues, optimize performance,...
LLM Monitoring
LLM Monitoring is the process of continuously tracking the performance, behavior, and outputs of Large Language Models (LLMs) during real-world deployment. This practice ensures that the models maintain reliability, relevance, and alignment with user expectations, while also detecting and addressing...
LLM Evaluation
LLM Evaluation refers to the systematic assessment of Large Language Models (LLMs) to measure their performance, reliability, and alignment with desired objectives. This process employs a variety of metrics and methodologies to evaluate the quality of outputs, identify limitations, and...