FAQs
Tokens can be thought of as pieces of words. Before the API processes the request, the input is broken down into tokens. These tokens are not cut up exactly where the words start or end - tokens can include trailing spaces and even sub-words.
What are tokens in generative AI? ›
In the field of AI, a token is a fundamental unit of data that is processed by algorithms, especially in natural language processing (NLP) and machine learning services. A token is essentially a component of a larger data set, which may represent words, characters, or phrases.
What is token in prompt engineering? ›
Prompt tokens are the tokens that you input into the model. This is the number of tokens in your prompt. Completion tokens are any tokens that the model generates in response to your input. For a standard request, this is the number of tokens in the completion.
What is prompt engineering in generative AI? ›
Prompt engineering makes it easy for users to obtain relevant results in the first prompt. It helps mitigate bias that may be present from existing human bias in the large language models' training data. Further, it enhances the user-AI interaction so the AI understands the user's intention even with minimal input.
What is the difference between token and word? ›
These tokens are often loosely referred to as terms or words, but it is sometimes important to make a type/token distinction. A token is an instance of a sequence of characters in some particular document that are grouped together as a useful semantic unit for processing.
What is the difference between word and token in NLP? ›
Most words (“apple”, “banana”, “zebra”) are also tokens when written. Punctuation marks such as the exclamation mark “!” are tokens but not words, because you can't utter them in isolation. Word and token are often used interchangeably in NLP.
What is a token example? ›
In general, a token is an object that represents something else, such as another object (either physical or virtual), or an abstract concept as, for example, a gift is sometimes referred to as a token of the giver's esteem for the recipient.
What is a token in ChatGPT? ›
Tokens are the basic unit that OpenAI GPT models (including ChatGPT) use to compute the length of a text. They are groups of characters, which sometimes align with words, but not always. In particular, it depends on the number of characters and includes punctuation signs or emojis.
What is an example of a token in NLP? ›
For example, consider the sentence: “Never give up”. The most common way of forming tokens is based on space. Assuming space as a delimiter, the tokenization of the sentence results in 3 tokens – Never-give-up. As each token is a word, it becomes an example of Word tokenization.
How much do AI prompt engineers make? ›
The estimated total pay for a AI Prompt Engineer is $183,299 per year in the United States area, with an average salary of $127,710 per year. These numbers represent the median, which is the midpoint of the ranges from our proprietary Total Pay Estimate model and based on salaries collected from our users.
They transcend industries, spanning art, medicine, sports, tech, sustainable development, and beyond. The future of work is AI-powered, and Prompt Engineers are at the forefront of this transformation. Are you ready to prepare for the jobs of the future? Look no further.
What is the difference between tokens and keywords? ›
Tokens are used to build the structure of a C program and to specify the actions that the program should take. Keywords: In C programming, keywords are a set of reserved words that have a specific meaning and are used to build the structure of the language.
What is the difference between tokens and vocabulary? ›
In NLP tokens refers to the total number of "words" in your corpus. I put words in quotes because the definition varies by task. The vocab is the number of unique "words". It should be the case that vocab <= tokens.
What do tokens refer to in AI? ›
Tokenization, in the realm of Artificial Intelligence (AI), refers to the process of converting input text into smaller units or 'tokens' such as words or subwords. This is foundational for Natural Language Processing (NLP) tasks, enabling AI to analyze and understand human language.
Are tokens words or letters? ›
Tokens are the building blocks of Natural Language. Tokenization is a way of separating a piece of text into smaller units called tokens. Here, tokens can be either words, characters, or subwords.
