AI, machine learning, and language models
- AI
- Machine learning
- Language models
- Machine learning
Distinguish a broad field from one kind of .
From an elementary-school level all the way to
Here, we mean : the kind of you chat with in writing. Let's explore how they produce a reply using an everyday sentence.
What would you put in the blank? Tap an example.
This morning, I __________. This morning, I ate breakfast. This morning, I went for a walk. This morning, I read a book.
These choices are prepared examples. Tap your selected example again to bring back the blank.
Yes, predicting what comes next is the basic idea! A language model uses patterns learned during , your input, and the text so far to calculate what could come next. It chooses a small piece of text called a , which can be a word or part of one, then repeats the process to build a reply.
Filling a blank is an analogy. In a chat reply, the usually keeps adding tokens at the end. It doesn't always choose the most likely one: it can also sample from several candidates according to their .
People use these words when AI works through a problem in steps. Underneath, it runs calculations using learned patterns and its input. Fluent language alone is no reason to treat it as a person with feelings or intentions.
A plausible continuation can still be wrong. Check important answers.
Distinguish a broad field from one kind of .
State the task, useful , constraints, and a way to check the result.
Separate text pieces from their numeric identifiers.