Ep 47: Chief AI Scientist of Databricks Jonathan Frankle on Why New Model Architectures are Unlikely, When to Pre-Train or Fine Tune, and Hopes for Future AI Policy
Unsupervised Learning
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Creating Effective Evaluation Benchmarks for AI Models
This chapter focuses on the significance of establishing effective evaluation benchmarks for AI models, highlighting the role of human testers in creating realistic assessments. It also unveils a new product designed to assist users in generating their own evaluation datasets more efficiently, emphasizing its importance in the model development process.
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