The AI Monthly Top 3 — March 2021

Here are the 3 most interesting research papers of the month, in case you missed any of them. It is a curated list of the latest breakthroughs in AI and Data Science by release date with a clear video explanation, link to a more in-depth article, and code (if applicable). Enjoy the read, and let me know if I missed any important papers in the comments, or by contacting me directly on LinkedIn!

Paper #1:

Brain-computer interface for generating personally attractive images [1]

Can an AI understand what beauty is to us? This one reads your brain to generate personally attractive faces! Michiel Spapé and his team from the University of Helsinki attempted to understand what attractiveness is to us in their most recent paper “Brain-computer interface for generating personally attractive images” [1] using Electroencephalography or EEG and GANs. EEG is a monitoring method used to record electrical brain activity using electrodes placed along the scalp…

Watch the video

A short read version

Can an AI understand what beauty is to us?

I think you will all agree that when you look at someone and find the person attractive, you cannot explain why. There may be many reasons involved in this decision. Plus, some of these reasons may…

Towards AILouis (What’s AI) Bouchard

Code they used to train the GAN models: https://github.com/tkarras/progressive_growing_of_gans

Paper #2:

We Asked Artificial Intelligence to Create Dating Profiles. Would You Swipe Right? [2]

Would you swipe right on an AI profile? Can you distinguish an actual human from a machine? This is what this study reveals using AI-made-up people on dating apps.

Watch the video

A short read version

Would You Swipe Right on an AI Profile?

As we discussed in a previous post, it is now possible to train artificial intelligence (AI) to model beauty. Within a couple of years, the famous saying “Beauty is in the eye of the beholder” may…

Towards AILouis (What’s AI) Bouchard

Code used for the text generative model: https://colab.research.google.com/drive/1VLG8e7YSEwypxU-noRNhsv5dW4NfTGce#forceEdit=true&sandboxMode=true&scrollTo=aeXshJM-Cuaf

Paper #3:

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows [3]

Will Transformers Replace CNNs in Computer Vision? In less than 5 minutes, you will know how the transformer architecture can be applied to computer vision with a new paper called the Swin Transformer.

Watch the video

A short read version

Will Transformers Replace CNNs in Computer Vision?

This article is about most probably the next generation of neural networks for all computer vision applications: The transformer architecture. You’ve certainly already heard about this architecture…

Towards AILouis (What’s AI) Bouchard

Code: https://github.com/microsoft/Swin-Transformer

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References

[1] M. Spape, K. Davis, L. Kangassalo, N. Ravaja, Z. Sovijarvi-Spape and T. Ruotsalo, “Brain-computer interface for generating personally attractive images,” in IEEE Transactions on Affective Computing, doi: 10.1109/TAFFC.2021.3059043.

[2] Sandra Bryant et al., “We Asked Artificial Intelligence to Create Dating Profiles. Would You Swipe Right?”, (2021), UNSW Sydney blog.

[3] Liu, Z. et al., 2021, “Swin Transformer: Hierarchical Vision Transformer using Shifted Windows”, arXiv preprint https://arxiv.org/abs/2103.14030v1