The Changing Role of Mathematics in Machine Learning Research
Published:Nov 16, 2024 16:46
•1 min read
•The Gradient
Analysis
The article discusses the evolving importance of mathematics in machine learning, contrasting mathematically-driven research with compute-intensive approaches. It suggests a shift in the field's focus.
Key Takeaways
- •Machine learning research is shifting from mathematically-principled approaches to compute-intensive methods.
- •Engineering-first efforts are gaining prominence due to their ability to scale with larger datasets.
Reference
“Research involving carefully designed and mathematically principled architectures result in only marginal improvements while compute-intensive and engineering-first efforts that scale to ever larger training sets”