SciShow
Can You Make A Computer Out Of Food?
Could an edible computer be in your future? Researchers are currently working on several of the components you find in them, from batteries to circuit boards to logic gates.
TED Talks
TED: How AI and democracy can fix each other | Divya Siddarth
We don't have to sacrifice our freedom for the sake of technological progress, says social technologist Divya Siddarth. She shares how a group of people helped retrain one of the world's most powerful AI models on a constitution they...
PBS
Will Constructor Theory REWRITE Physics?
The people behind the greatest leaps in physics - Einstein, Newton, Heisenberg, all had the uncanny ability to see the fundamentals - see the deepest, underlying facts about the world, and from simple statements about reality they built...
SciShow
Why Is ChatGPT Bad At Math?
Sometimes, you ask ChatGPT to do a math problem that an arithmetically-inclined grade schooler can do with ease. And sometimes, ChatGPT can confidently state the wrong answer. It's all due to its nature as a large language model, and the...
SciShow
The Crabs That Revolutionized Neuroscience
We used to think neural circuits were rigid and robotic, but now we know that's not true -- thanks to crab stomachs.
PBS
Use Of Artificial Intelligence Generates Questions About The Future Of Art
Artificial intelligence is everywhere and part of our conversations about education, politics and social media. It's also a hot topic in the arts world as programs that generate art using AI are widely available to the public. But what...
SciShow
8 Mind-Blowing Optical Illusions
Your brain does its best to inform you about the world around you, but sometimes it gets tricked. Enjoy eight optical illusions to test your brain’s sensory input.
Bozeman Science
Environmental Systems
In this video Paul Andersen explains how matter and energy are conserved within the Earth's system. Matter is a closed system and Energy is open to the surroundings. In natural systems steady state is maintained through feedback loops...
3Blue1Brown
Visualizing the chain rule and product rule: Essence of Calculus - Part 4 of 11
The product rule and chain rule in calculus can feel like they were pulled out of thin air, but is there an intuitive way to think about them?
3Blue1Brown
Visualizing the chain rule and product rule | Essence of calculus, chapter 4
The product rule and chain rule in calculus can feel like they were pulled out of thin air, but is there an intuitive way to think about them?
Crash Course
Keyboards & Command Line Interfaces: Crash Course Computer Science
Today, we are going to start our discussion on user experience. We've talked a lot in this series about how computers move data around within the computer, but not so much about our role in the process. So today, we're going to look at...
PBS
What are Numbers Made of?
In the physical world, many seemingly basic things turn out to be built from even more basic things. Molecules are made of atoms, atoms are made of protons, neutrons, and electrons. So what are numbers made of?
3Blue1Brown
Winding numbers and domain coloring
An algorithm for solving continuous 2d equations using winding numbers.
3Blue1Brown
Solving 2D equations using color, a story of winding numbers and composition
An algorithm for numerically solving certain 2d equations. Even though we described how winding numbers can be used to solve 2d equations at a high level, it's worth pointing out that there are a few details missing for if you wanted to...
3Blue1Brown
Gradient descent, how neural networks learn | Deep learning, chapter 2
An overview of gradient descent in the context of neural networks. This is a method used widely throughout machine learning for optimizing how a computer performs on certain tasks.
3Blue1Brown
But what *is* a Neural Network? | Chapter 1, deep learning
An overview of what a neural network is, introduced in the context of recognizing hand-written digits.
3Blue1Brown
What they won't teach you in calculus
A visual for derivatives which generalizes more nicely to topics beyond calculus. Thinking of a function as a transformation, the derivative measure how much that function locally stretches or squishes a given region.
Crash Course
Cats Vs Dogs? Let's make an AI to settle this (LAB)
Today, in our final lab, Jabril tries to make an AI to settle the question once and for all, "Will a cat or a dog make us happier?" But in building this AI, Jabril will accidentally incorporate the very bias he was trying to avoid. So...
SciShow
How Science Is Trying to Understand Consciousness
Figuring out exactly what consciousness is and whether or not it could emerge in non-human things has stumped us for centuries. Now, analyzing it from a scientific perspective might not just be possible, but necessary.
SciShow
Why You Can’t Listen to Music While You Work
Some people are capable of concentrating in a storm of noise and motion, and some get distracted by the slightest squeak of a classmate’s chair. This has to do with our brain’s ability to filter, and not only are both entirely natural,...
Crash Course
Neural Networks - Crash Course Statistics
Today we're going to talk big picture about what Neural Networks are and how they work. Neural Networks, which are computer models that act like neurons in the human brain, are really popular right now - they're being used in everything...
3Blue1Brown
Gradient descent, how neural networks learn: Deep learning - Part 2 of 4
An overview of gradient descent in the context of neural networks. This is a method used widely throughout machine learning for optimizing how a computer performs on certain tasks.
3Blue1Brown
Gradient descent, how neural networks learn | Chapter 2, deep learning
An overview of gradient descent in the context of neural networks. This is a method used widely throughout machine learning for optimizing how a computer performs on certain tasks.
TED-Ed
TED-Ed: The greatest mathematician that never lived | Pratik Aghor
When Nicolas Bourbaki applied to the American Mathematical Society in the 1950s, he was already one of the most influential mathematicians of his time. He'd published articles in international journals and his textbooks were required...