What is AI? AI is short for artificial intelligence. It means machines and computer programs that can imitate smart human behavior, such as making predictions and decisions. AI helps phones understand the words that people say out loud. It is also used in translation apps that change words from one language into another. Computers can be good at some tasks that are hard for people, such as looking through huge amounts of data very fast. Even so, an AI does not think the way a person does.
How does AI learn? Many AI programs learn by looking at lots of examples. Some are pictures that people have labeled as dogs. People usually give an AI the examples that it learns from. This information is called training data. To work well, an AI usually needs a very large amount of training data. In unsupervised learning, a program looks for patterns in data that has no labels. Machine learning is one way to make AI. The computer finds patterns in data.
A neural network is a kind of AI program. It is made of many simple parts, called nodes, joined together. It is modeled loosely on the human brain. Most of today's neural networks are organized into layers of nodes. When a neural network is trained, the numbers that set how strongly its parts connect are adjusted. They change until it gives the right answers for the training examples. Even after training, it can be hard to find out why an AI gave a certain answer.
In May 1997 a computer called Deep Blue beat the world chess champion in a six-game match, 3½ to 2½. Some game-playing programs work by brute force. They try a huge number of possible moves and replies. Deep Blue could examine about 200 million moves each second. In March 2016 a Go-playing program called AlphaGo beat a top Go player four games to one. Before AlphaGo, many people thought it would be about a decade before computers could challenge skilled Go players. AlphaGo fine-tuned itself by playing games against slightly changed copies of itself.
A large language model is the kind of AI behind many chatbots. It works by predicting which word is likely to come next. A language AI works a bit like autocomplete, but on a much larger scale. It breaks what you type into small pieces called tokens. Because a language AI picks words by probability, it can produce a false statement that sounds right. AI mistakes are sometimes called hallucinations. AI chatbots can make up facts and even make up the sources they name.
AI can make mistakes and can say things that are not true. If the examples an AI learns from leave some people out, the AI can work worse for those people. A spam filter sorts out the junk email from the email that you want. A spam filter can wrongly flag a good email as spam. This is called a false positive. A chatbot may also not know about very recent events. It can only use the information it learned from.
AI can be wrong even when it sounds sure, so a confident answer is not proof. People should check what an AI tells them before they trust it. A good way to check is to open a new tab and look the facts up on other reliable pages. This is called lateral reading. If a chatbot names a book or article, a person should search to confirm that it really exists. An AI should not be asked to check its own work: a person should look for outside sources.
Words to know
- hallucinations: AI mistakes
- tokens: small word pieces
- nodes: simple parts
- autocomplete: word guesser
- lateral: sideways checking
