Why do you call TabPFN a revolution for data science?

Prof. Dr. Frank Hutter and his team presented a "radically new
approach" to tabular classification. It is a new tabular data
classification method that takes < 1 second & yields SOTA
performance (competitive with the best AutoML pipelines in an
hour). So far, it is limited in scale, though: it can only tackle
problems up to 1000 training examples, 100 features and 10 classes.
It works best when all features are numerical and there are no
missing values (but we believe when we focus on those cases we’ll
also improve performance for them). The podcast is growing and we
want to keep growing. That's why our German-language podcast is now
available in English. We are happy about new listeners. We thank
our new partner [Siemens
](https://new.siemens.com/global/en/products/automation/topic-areas/artificial-intelligence-in-industry.html)
News: Facebooks Language Model:
https://github.com/facebookresearch/llama Arduino and ML:
https://hackaday.com/2023/02/24/tiny-machine-learning-on-as-little-as-2-kb-of-ram/
Our guest: Prof. Dr. Frank [Hutter
](https://www.linkedin.com/in/frank-hutter-9190b24b/) The TabPFN
Paper: https://arxiv.org/abs/2207.01848 The Summary:
https://www.automl.org/tabpfn-a-transformer-that-solves-small-tabular-classification-problems-in-a-second/