2021-06

Data from the real world are never perfectly balanced. In this episode I explain a simple yet effective trick to train models with very unbalanced data. Enjoy the show!
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References
Leo Breiman, Random Forests, 2001
C. Chen, A. Liaw, L. Breiman, Using Random Forest to Learn Imbalanced Data (2004)
 

In this episode I am with Gilbert Hill, head of strategy at https://tapmydata.com/
We speak about personal data, blockchain and the ability to control it and monetize with another simple yet effective app in the ecosystem.
 
 
References
https://tapmydata.com/
https://medium.com/@tholder/we-dont-want-your-data-pushing-boundaries-in-data-collection-and-end-to-end-encryption-for-apps-ebd1d5f79df5

In this episode I have a really interesting conversation with Karan Grewal, member of the research staff at Numenta where he investigates how biological principles of intelligence can be translated into silicon.We speak about the thousand brains theory and why neural networks forget.
 
 
References
Main paper on the Thousand Brains Theory: https://www.frontiersin.org/articles/10.3389/fncir.2018.00121/full
Blog post on Thousand Brains Theory: https://numenta.com/blog/2019/01/16/the-thousand-brains-theory-of-intelligence/
GLOM paper by Geoff Hinton: https://arxiv.org/pdf/2102.12627.pdf
Why neural networks forget? https://numenta.com/blog/2021/02/04/why-neural-networks-forget-and-lessons-from-the-brain