If you’ve been paying attention to the growing world of Artificial Intelligence (AI) models – a program that analyses datasets to find patterns and make predictions – and the number of companies currently providing their own models to the world, you may have heard the term ‘tokens’ being used. For those new to the technological world of AI, this can be a confusing concept to wrap your head around but plays a crucial role in the capabilities of each AI model. As a key functional element of AI technology, we are avid believers that understanding how tokens work, their positives and their limitations can help you better utilise AI systems and cater for AI in your everyday business world.

What Are Tokens?

So, what exactly are ‘tokens’? Simply put, a token is simply a unit of data that the AI system processes, whether input or output. Tokens are effectively a way for the language processing system to break down a query into manageable chunks, or building blocks, to produce the best possible answer. By breaking sentences and queries down into ‘tokens’, an AI can better process information provided, by analysing patterns, relationships between words and more, all to provide a more human-like response. 

Tokens could be and are broken down by: 

  • The words (e.g. “the” and “words” would both be an individual token) 
  • Parts of words (e.g. where words may be more complex, such as with other languages)
  • Punctuation (any commas, full stops, question marks and other punctuation count as individual tokens) 
  • Other ‘special’ tokens (e.g. any indication of beginnings or endings or sentences, or unknown words etc.)

A sentence such as “What is search engine optimisation?” would be broken down into “What”, “Is”, “search”, “engine”, “optimisation”, “?”. Some models may split words into further tokens, so ‘optimisation’ could be split down into shorter tokens. 

Why Are There Limits?

The token limits you will face will ultimately depend on which model you are using. While some of the leading AI platforms will provide insight into their token limitations, not all companies do and so it can be difficult to compare models using token limits. However, every AI model will have one, and this limit can vary drastically from model to model according to resources, architecture and more. 

Token limits exist for two key reasons, regardless of the model you use. These are: 

  • Memory Constraints – AI models are trained and improved through mass datasets. It is the core way that models can grow and adapt and learn from the people that use it, in order to provide better answers and responsiveness overall. However, token limits ensure that the model can’t be overloaded. This data needs to be stored somewhere, and token limits can help to better manage the amount of data stored and needed at any time. 
  • Performance – Token limits are a key way that AI models can ensure they are providing the best possible answers and responses at any time. Processing massive amounts of text and data can be an intense process, and so token limits can help to ensure the model runs smoothly and provides responses in a more timely and efficient manner.

What Are The Limits Of Different Models?

While not every AI model has advertised it’s token limits, some of the front runners have provided this data to it’s users. Not only is this useful for the average user, but for those utilising models within their businesses, it can be crucial information to have. Some key limits to note include: 

  • GPT-3.5 – 4,096
  • GPT-4 – 8,192
  • GPT-4-32k – 32,768
  • Llama2 – 2,048
  • Claude 2 – 100,000 
  • Claude 3 – 4,096
  • Gemini 1.0 – 16,384 
  • Gemini 1.5 Pro – 1,000,000 

Can Token Limits Affect Search Optimisation?

While tokens won’t necessarily have a direct impact on search optimisation for businesses, for companies looking to stand out among the rest, understanding how tokens work and how best to navigate AI models despite limitations can make a huge difference. Being able to utilise AI for content ideas, understanding data and getting a basis for content can be a great way to produce more informative and relevant content, but it’s important to understand that AI can have limits. 

Limits can mean that AI won’t produce content to the same level of human-like speech or search engine optimisation that you are seeking, so it’s important to take additional time to go through any content produced or check over information to ensure that it is all correct. This is particularly important for businesses, as a wrong answer or poor-quality content can have a negative impact on your online presence. 

For support with your search engine optimisation or web management, we are on hand to help. Our team are well-versed in not just AI, but in SEO as a whole, as well as other digital marketing to ensure your site remains relevant, optimised and user-friendly. Simply get in touch with our team to find out more.