The Thesis Review [39] Burr Settles - Curious Machines: Active Learning with Structured Instances
Feb 2, 2022
Burr Settles, who leads machine learning research at Duolingo, discusses his fascinating journey from studying art and math to focusing on language education through AI. He dives into how active learning methodologies can enhance language acquisition, overcoming motivation barriers with personalized educational experiences. Burr shares innovative strategies in translation, the integration of generative AI like GPT-3, and the evolution of success metrics from academia to meaningful real-world applications in tech.
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Motivation in Language Learning
- The hardest part of learning a language is staying motivated due to its long, continuous nature.
- Personalized learning experiences, adjusting for prior knowledge, can improve motivation.
Biomedical Text Processing
- Burr Settles's initial work involved using machine learning (CRFs) for biomedical text processing.
- The goal was to extract information from literature to build gene regulatory networks and aid drug discovery.
Active Learning
- In active learning, the model actively participates in data labeling by querying an 'oracle' (human annotator).
- This aims to minimize the cost of data annotation by selecting the most informative instances.