What is machine learning?
Machine learning is a form of artificial intelligence that is able to learn without explicit programming by a human. For most of our history, we’ve thought that learning—the ability to adjust our behaviour based on collected information—was something only humans did. The past few decades have changed all that. We now know that animals of all kinds learn from experience, teaching, and even play. But it is not only animals that learn: there’s increasing evidence that plants do,too . And if you’ve ever unlocked a phone with facial recognition, or interacted with a virtual assistant, you’ve experienced firsthand that machines, too, are capable of learning. Machine learning is a form of artificial intelligence (AI) that can adapt to a wide range of inputs, including large data sets and human instruction. Some machine learning algorithms are specialised in training themselves to detect patterns; this is called deep learning. The term “machine learning” was first coined in 1959 by computer scientist Arthur Samuel, who defined it as “a computer’s ability to learn without being explicitly programmed.” It follows, then, that machine learning algorithms are able to detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data and experiences to improve over time. How did machine learning evolve into generative AI? Machine learning as a discipline was first introduced in 1959, building on formulas and hypotheses dating back to the 1930s. But it wasn’t until the late 1990s that machine learning truly flowered, as steady advances in digitisation, computing languages capable of greater nuance, and cheaper computing power and memory enabled data scientists to train machine learning models to independently learn from data sets rather than rely on rules written for them. The broad availability of inexpensive […]