Model Optimization Concerns
The discussion delves into the potential pitfalls of relying solely on automated model selection. Concerns arise about the risk of settling for a local optimum, suggesting that manual optimization might yield superior results in certain scenarios. This highlights the importance of balancing automated processes with human expertise in the pursuit of optimal machine learning models.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
AutoML for Natural Language Processing with Abhishek Thakur - #475
Related Questions
Have you seen any good techniques for automatically optimizing few-shot examples for large language models (LLMs) in the episode Deep Learning with Letitia Parcalabescu - Weaviate Podcast #96! and the clip Language Space Optimization?
Have you seen any good techniques for automatically optimizing few-shot examples for large language models (LLMs)?
Have you seen any good techniques for automatically optimizing few-shot examples for large language models (LLMs) in the episode ARCHIVE: GPT-3 Hype and the clip Neural Network Complexity?