Understanding AI Tokens and Their Importance
Arunabh Satpathy- October 31, 2024
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.
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1. What are Tokens in AI?
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 4o mini is ideal for developers, BAs, QAs, project managers, and product owners. GPT4o is the highest performance model, but it consumes more tokens.
The above example was generated on GPT 4o.
You can further explore AI token consumption on the ChatGPT Tokenizer tool.
2. AI Token Limits and Costs
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 |
|---|---|---|
|
GPT-4o Mini |
16k tokens |
Input: 1800 tokens, Output: 1600 tokens, Total: 3400 tokens |
|
GPT-4o |
128k tokens |
Input: 4000 tokens, Output: 4200 tokens, Total: 8200 tokens
|
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
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 :
- Elicit: Elicit high quality output from work items, including requirements, bugs, test cases, and other work items, ensuring comprehensive coverage.
- Analyze: Analyze work item data for quality using the 6Cs method, INVEST model, PABLO Criteria, MoSCoW method, or SWOT method.
- Impact Assessment: Evaluate the impact of specific work items on other work items or based on explanation. Identify impact details and tasks, categorized by severity.
- Q&A Assistant: Ask questions to the assistant to elicit insightful questions and detailed requirements. Enhance clarity and ensure comprehensive coverage of stakeholder needs.
- Convert: Express requirements in different formats like user story, use case, or Gherkin language. Enable better alignment between technical and non-technical stakeholders.
- Dynamic Prompt: Create and manage your own prompts on selected queries, enhancing flexibility and efficiency in generating results.
- Transform: Modify and enhance requirements by summarizing or paraphrasing them for better understanding.
Elaborate them to add detail and increase requirement coverage.
Translate them to other languages to empower distributed teams.
Generate: Translate requirements into algorithmic steps using Pseudocode or Test Scripts.
Create high-quality pseudocode from work items in multiple languages like Javascript, C++, or natural language.
Create high quality test scripts from work items in common scripting languages like Selenium, Python, and more. - Create Codeless App: Create custom applications without code, enabling rapid deployment and easy customization.
- Token Quota Status: Monitor monthly token consumption.
- Custom Instructions: Refine your interactions within Copilot4DevOps Plus by picking the GPT model (4o or 4o Mini), response type, and modifying instructions.
- 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 4o and GPT 4o mini 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 10 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 Best Practices: 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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