The algorithms that form the heart of machine learning have been around for decades, but computers have only recently reached the level of processing power needed to use the techniques in practical scenarios.
AI programs today can learn to identify objects in images and video, translate between languages, and even master arcade and board games. In some cases, like DeepMind’s AlphaGo program, the AI even exceeds top humans at its task.
Wait, what the heck is machine learning?
Artificial intelligence (AI) refers to the field of emulating intelligence in general—anything from making a convincing opponent in a video game to an automated chatbot.
Machine learning is one of the biggest fields within AI, and refers only to AI programs that are designed to learn and improve at their tasks with minimal outside input from the programmer.
You’ll also hear the term “deep learning” in conversations about AI; this refers to a method of machine learning that uses layers of interconnected neurons (inspired by how human brains work) to help programs make decisions.
Deep learning was long neglected in AI research, as it was too time-consuming and lacked practical results, but advances in processor speed have enabled deep learning to retake the limelight, leading to some of the massive leaps forward we’re seeing in recent AI research.
Download our 2018 brochure to learn more about getting your child started in machine learning. Or, continue reading for more info!
So, what can machine learning do?
One of the main categories of machine learning problems is supervised learning. These problems are ones where there’s available training data so the program can get feedback on its performance as it learns.
Tasks, like playing games and identifying objects, would fall under supervised learning because the computer is getting feedback as it learns. Did it guess what the object in the image was correctly? Did it get a high score on the game or lose 10 seconds into playing? Feedback allows it to adjust its decision-making process so it can do better next time.
To go a little deeper, two of the most common sub-categories of supervised learning problems are classification and reinforcement learning.
In a classification problem, the program is given a set of inputs and has to learn to classify those inputs correctly, like a spam email filter or image recognition program.
In reinforcement learning, a program (the “agent”) interacts with an environment dynamically, making choices for its next course of action. Based on the current state of the environment, the positive and negative rewards, and actions taken, the agent must learn the best method to accomplish the task.
Reinforcement learning agents can learn to play Ms. Pac-Man, master the games of Go and Chess, compete against pros at Dota 2, and even have started learning to play more complex strategy games like Starcraft 2.
But are companies hiring?
So, machine learning is one of the coolest emerging fields in tech, but why should your child hop in and start learning about it?
In the coming years, many companies like DeepMind and OpenAI (whose work I’ve linked in some of the examples above) hope to solve general artificial intelligence, which is a term for an AI that can learn and perform any task put in front of it. This breakthrough is likely still years in the future, but it has the potential to revolutionize how human beings interact with technology, the job market, and society in general.
In the shorter term, machine learning has practical business applications like analyzing large volumes of data, powering self-driving vehicles, and assisting medical diagnoses. As AI research advances, the number of tasks it can perform will only increase. Companies are already desperate for AI experts and are hiring anyone who’s got expertise in the field.
Students can take their first steps towards revolutionizing technology and society, with our summer machine learning programs, described below.
Artificial Intelligence and Machine Learning | iD Tech Camps | Ages 13-18
Dive into this developing field using data sets, probability, statistics and more, with tools like Python and TensorFlow to turn yesterday's dreams into reality.
Machine Learning and Deep Neural Networks | iD Coding & Engineering Academy | Ages 13-18
Start with Python, TensorFlow, and a lot of data to begin coding desired behaviors and reward your computer for doing well! Tweak your reward schemes and adjust your data sets so your computer gets better at different tasks.