AI
Model alignment protects against accidental harms, n...
The hand wringing about failures of model alignment is misguided
What the executive order means for openness in AI
Good news on paper, but the devil is in the details
How Transparent Are Foundation Model Developers?
Introducing the Foundation Model Transparency Index
Is the future of AI open or closed? Watch today’s Pr...
By Sayash Kapoor, Rishi Bommasani, Percy Liang, Arvind Narayanan Perhaps the ...
Reinforcement Learning From Human Feedback (RLHF) Fo...
Reinforcement Learning from Human Feedback (RLHF) has turned out to be the ke...
LLM For Structured Data
It is estimated that 80% to 90% of the data worldwide is unstructured. Howeve...
Strategies For Effective Prompt Engineering
When I first delved into machine learning, prompt engineering seemed like a n...
LLM Evaluation For Text Summarization
Text summarization is a prime use case of LLMs (Large Language Models). It ai...
Observability in LLMOps: Different Levels of Scale
Observability is invaluable in LLMOps. Whether we’re talking about pretrainin...
LLM Observability: Fundamentals, Practices, and Tools
Large Language Models (LLMs) have become the driving force behind AI-powered ...
3 Takes on End-to-End For the MLOps Stack: Was It Wo...
As machine learning (ML) drives innovation across industries, organizations s...
Adversarial Machine Learning: Defense Strategies
The growing prevalence of ML models in business-critical applications results...
