By making big research bets, the prolific Meta Senior Research Director Dr. Laurens van der Maaten has devised or supported countless world-changing machine-learning innovations across healthcare, climate change, privacy and more.
Laurens:
• Is a Senior Research Director at Meta, overseeing swathes of their high-risk, high-reward A.I. projects with application areas as diverse as augmented reality, biological protein synthesis and tackling climate change.
• Developed the "CrypTen" privacy-preserving ML framework.
• Pioneered web-scale weakly supervised training of image-recognition models.
• Along with the iconic Geoff Hinton, created the t-SNE dimensionality reduction technique (this paper alone has been cited over 36,000 times).
• In aggregate, his works have been cited nearly 100,000 times!
• Holds a PhD in machine learning from Tilburg University in the Netherlands.
Today’s episode will probably appeal primarily to hands-on data science practitioners, but there is tons of content in this episode for anyone who’d like to appreciate the state of the art in A.I. across a broad range of socially impactful, super-cool applications.
In this episode, Laurens details:
• How he pioneered learning across billions of weakly labeled images to create a state-of-the-art machine-vision model.
• How A.I. can be applied to the synthesis of new biological proteins with implications for both medicine and agriculture.
• Specific ways A.I. is being used to tackle climate change as well as to simulate wearable materials for enhancing augmented-reality interactivity.
• A library just like PyTorch but where all the computations are encrypted.
• The wide range of applications of his ubiquitous dimensionality-reduction approach.
• His vision for the impact of A.I. on society in the coming decades.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.