Understanding AI Tokens and Their Importance

illustration of one unit of AI input with several tokens.

When talking about AI, it’s important to grasp the concept of “tokens.” Tokens are the fundamental building blocks of input and output that Large Language Models (LLMs) use. AI tokens are the smallest units of data used by a language model to process and generate text. Tokenization is how these LLMs break down your input to understand it and generate an output in human language so that it can be useful to you. This blog covers what tokens are in AI language models, their limits, and how the latest AI requirements management tools use them.

1. What are Tokens in AI?

AI Tokens are like pieces of words in natural language processing.  As a user, you consume tokens based on the length of your input and output. One token can include characters, spaces, and punctuation marks.

In English, input and output tokens may break down the following ways:

  • 1 token ~= 4 chars in English
  • 1 token ~= ¾ words
  • 100 tokens ~= 75 words

A typical interaction in ChatGPT may have the following ChatGPT token consumption:

The number of tokens you consume depends on the AI model you are using. For OpenAI products, GPT 4 and GPT 3.5-turbo are ideal for developers, BAs, QAs, project managers, and product owners. GPT-4 is the highest performance model. Conversely, GPT-3.5-turbo gives you faster outputs and a lower cost per token. 

The above example was generated on GPT 3.5.

You can further explore AI token consumption on the ChatGPT Tokenizer tool.

2. AI Token Limits and Costs
Multicolor display of how LLMs process AI tokens.
The cutting edge of current generative AI technology has certain token limits.

The forefront of current technology and the model you choose limits your token consumption. The maximum number of tokens you can consume is called your context window. Here’s how it works for different GPTs with examples:

Model Context Windows Token Consumption Example
2048 tokens
Input: 1000 tokens
Output: 800 tokens
Consumption = 1800 tokens
4096 tokens
Input: 2000 tokens
Output: 1500 tokens
Consumption = 3500 tokens
8192 tokens
Input: 4000 tokens
Output: 4192 tokens
Consumption = 8192 tokens (At the limit)

Typically, you will also see the number of tokens referred to as 4k, 8k, or 32k ChatGPT tokens available. These refer to the maximum number of tokens a model can handle in a single interaction or conversation.

In the case of 250,000 4k tokens, its breakdown is as follows:

  • 250,000 is the total amount of tokens you can consume
  • 4000 tokens are the limit per interaction
  • If you use 1000 tokens per interaction, you can have 250 interactions with the AI.
3. Token usage in AI requirements management with Copilot4DevOps Plus
UI of Copilot4DevOps displayed showing analysis, translation, elicitation and other features
Copilot4DevOps is part of an award-winning product lineup by Modern Requirements

Copilot4DevOps Plus is a work item and requirements management solution to revolutionize the DevOps lifecycle. It’s also available as an upgrade to Modern Requirements4DevOps, an award-winning requirements management tool built into Azure DevOps. Using Copilot4DevOps Plus, your teams can save time, unload manual work, handle project complexity, and maintain top-tier security. It offers you the following features:

  • AI elicitation: Generate high-quality, editable requirements from raw data.
  • AI analysis: Analyze work item data for quality.
  • Gherkin conversion: Automatically convert work items to Gherkin language.
  • Use case conversion: Generate use cases from elicited requirements.
  • Dynamic prompting: Give outputs based on unique queries using keywords, phrases, or sentences.
  • Elaborate: Add more detail to existing requirements.
  • Summarize: Create a brief abstract or reframe requirements in different terms.
  • Pseudocode Generation: Automatically generate pseudocode in multiple programming languages, aiding developers and analysts to conceptualize solutions faster.
  • Test Script Creation: Effortlessly create test scripts in various languages, significantly reducing test preparation time.
  • Custom Instructions: Refine your interactions within Copilot4DevOps Plus by picking the GPT model, response type, and modifying instructions.
  • Token Quota Status: Monitor monthly token consumption.
  • Translate: Translate work item data to multiple languages with high accuracy.
  • Security: Copilot4DevOps inherits the top-tier security features and upgrades from the OpenAI and Azure OpenAI Service

Copilot4DevOps Plus allows you to choose between GPT 3.5 turbo and GPT 4 models, with corresponding token usage. The model you choose will determine how you give it inputs and what outputs you will get.

Copilot4DevOps Plus gives you 7 million tokens per month but higher token counts are available upon request in Enterprise applications.

4. Strategies to Optimize AI Token Usage

So, you already have access to your preferred Copilot4DevOps Plus model. How do you optimize your output? In this case, optimize means balancing the best output and maximum token conservation. Here’s how to do it:

  • Follow : Knowing how to use an AI means the difference between a good and an excellent result.
  • Learn prompt engineering: Your “ask” from the AI should be concise and focused. Use as few words as possible to conserve tokens and get the best possible result. Large text blocks may introduce noise into the AI output and consume tokens.
  • Don’t summarize previous conversations: Within the context of a chat, the AI already knows what you are talking about. Avoiding summarizing previous parts of a conversation reduces time spent and tokens consumed, ensuring efficient communication.
  • Request multiple outputs: With an efficiently worded prompt, you can request multiple outputs with one prompt. This consumes fewer output tokens.

Request more efficient output formats: An AI may often respond in paragraphs. But if you request short bullets or tables, you are likely to get a more efficient answer.

5. Understand What AI Tokens are to Get Better Results

By understanding what tokens in AI are, you can choose the right AI model for your organization. AI requirements management tools like Copilot4DevOps Plus are a powerful new technology shaking up work item and requirements management. Companies that don’t follow these trends will fall behind.  

Maximizing token efficiency involves concise prompts, judicious summarization, and strategic output formats. Elevate your AI interactions by grasping token dynamics and leveraging Copilot4DevOps Plus for seamless requirements management.

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