In this video, Cami explains in layman’s terms what a neural network is, it’s related components, so that by the end your interest in ML is hopefully piqued, and you can go explore deeper into other resources on how to implement a neural network.
In the last video in this series we discussed the ancient origins of artificial intelligence progressing forward to the beginnings of the development of modern computing based artificial intelligence, encompassing the philosophies, theories and inventions of many talented individuals and groups. The focus of this video will continue right were the last one left off, so sit back, relax and join me on an exploration on the official birth of modern artificial intelligence leading to present day!
When 20 years ago, a computer beat a human at chess, it marked the dawn of Artificial Intelligence, as we know it.
These days, neural networks, deep learning and all types of sensors allow AI to be used in healthcare, to operate self-driving cars and to tweak our photos on Instagram.
In the future, the ability to learn, to emulate the creative process and to self-organize may give rise to previously unimagined opportunities and unprecedented threats.
By: Two Minute Papers.
Should we be afraid of AI? Afraid of robots terminating the human race? Afraid of our daily devices slowly gaining consciousness? Okay maybe these scenarios sound very far fetched, but according to estimates by Oxford Economics, 47 percent of all jobs across the United States are at risk of becoming automated. And Elon Musk thinks we’re all doomed. Is this the beginning of the singularity? Do you know what is the singularity is? We’ll explain that in a bit. Artificial Intelligence has been around for quite some time now and even when it wasn’t around it was making guest appearances in our favorite sci-fi shows and movies. Since the dawn of technology, humans have wondered, “Could we create a machine that works like — or even better than — us?” The answer to this question seems to be a resounding yes. Machine learning is happening all around us: tablets, cellphones, computers, not to mention YouTube, the platform you’re watching this video on right now — they’re all rigged with it. There are many questions that arise when we think of A.I. How far are we from going from an r2d2 to a c3po? Or maybe you believe a Terminator-esque scenario is more likely? How possible is it to create a machine with a conscience? Will the rise of A.I. be the beginning of the end for humans? And how will the evolution of A.I. actually affect our day to day lives? You’re watching Explore Mode and today we are diving into the rise of artificial intelligence.
This video on “What is Deep Learning” provides a fun and simple introduction to its concepts. We learn about where Deep Learning is implemented and move on to how it is different from machine learning and artificial intelligence. We will also look at what neural networks are and how they are trained to recognize digits written by hand. We further look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.
Neural network training for animation.
Artificial Intelligence is the branch of computer science that deal with writing computer programs that can solve problems creatively
Machine learning is a subset of AI that provides statistical tools to explore the data.
The three primary types of Machine learning are:
1) Supervised machine learning (past labeled data)
2) Unsupervised machine learning (solve clustering problems)
3) and semi-supervised machine learning (aka reinforcement; combination of previous)
Deep learning is multi neural network archictecture. The idea is to mimic the human brain.
Data Science uses these tools and more, such as math and statistics, to learn.