Future of ML DevOps
Tim discusses the potential of human-supervised machine teaching to enhance training efficiency. Sameer emphasizes the importance of interactive testing using language models like GPT-3 for diverse phrasings. Active learning frameworks and robust testing are key for evolving models in a changing landscape.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#73 - YASAMAN RAZEGHI & Prof. SAMEER SINGH - NLP benchmarks
Related Questions
Is there anyone taking a different approach to prompt engineering for large language models that makes the process more accessible to a wider audience?
Is there anyone taking a different approach to prompt engineering for large language models that makes the process more accessible to a wider audience, as discussed in the episode Collaboration & evaluation for LLM apps and the clip Fine Tuning Insights?