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Pick a Card and Our Fellow Nour’s AI Device Will Know What It Is

Nour's mind-reading device prototype
My mind-reading device prototype

***Written by Nour Chahine***

Can you use a brain-computer interface to perform magic tricks? Guess what card someone is thinking of?

That is exactly what my TinyML project, Pick a Card, is all about. 

I will develop a small screen to show a set of playing cards while measuring EEGs. The subject chooses a card, and an AI algorithm would determine which one it was. 

But before I get into the specifics, let me tell you how this project came about.


Dreaming With Your Eyes Open: Can Tiny ML Help You Deal with FOMO?

tinyml fomo glasses
Wearing an EOG setup on your person

—Written by Ari Miri—

How much do you notice throughout your day? Are you paying attention to your surroundings? Are you present in every moment of your life? Odds are, the answer is no. As most adults know, the more we grow up, the more we seem to live on autopilot. We’ve got places to be and things to do, and no time to sit around marveling at the world around us. 

This is the problem I’m hoping to solve with the help of Tiny ML and a 3D printer. 


FOMO Glasses!

The concept behind FOMO glasses is to capture an image of what you would be seeing every time you blink. If you do the math (which I did), the average human spends anywhere from 2.7 to 4 years blinking. That’s years of your awake life spent with your eyes closed! This makes blinking an ideal metric for recording ALL the snapshots of your day you’re missing out on.


Building a Poker Bot You Can’t Bluff: TinyML Gets All In!

poker bot you can't bluff
Skin galvanic sensor setup. Edit: you CAN play poker with these on!

—Written by Sachin Pillai—

This summer at Backyard Brains, I’m developing a Poker Bot trained via machine learning that can detect when players bluff and predict how risky a player’s hand is based on internal physiological reactions during the game.

A full month into the fellowship, I’ve already had substantial progress with my project! The first week of the program consisted of learning foundational theory and skills from experts in fields of neuroscience and computer science, and here’s a peek into everything I got from it:

  • Lessons that not only brought me up to speed on all the progress in these fields but were applicable later as I ran into challenges and began developing my project
  • I gained valuable insight into how to convert my ideas into actionable plans (this is MORE important than it sounds!)
  • I learned about soldering techniques, collecting my own EKG/EEG/EMG data, using Edge Impulse (software that records galvanic skin response) and SpikerBox (a tool I suspect you’re already familiar with).