ML Model
topic on 3 shows · 3 statements across 3 episodes
3 statements about ML Model, every show
Kulik: Machine Learning Can Select Optimal Quantum Mechanical Approximations
“Not all quantum mechanical approximations are equal, and you can actually use ML models to kind of predict what the best approximation to use is, depending on the material studied.”
Ramade: Machine Learning Models Cannot Learn Physics Probabilistically
“There are certain rules of the world that we've learned over time that need to be true. It's like gravity is 9.8 meters per second square. You can't probabilistically learn that by watching stuff fall in air and being like, yeah, my ML. No, no. I mean, there's…”
Biewald: Yahoo Search Success Depended Entirely On Local Training Data Quality
“The model that I'm building is like the same for each country. It's the training data though is different. So some countries would take the training data collection process really seriously and they'd get a great model. And some would just like really half-ass…”