Does Chat GPT have a word limit?
You’re deep in conversation with your AI chatbot for a content automation project, but suddenly it stops responding, and you wonder if you reached a word limit of some sort.
The answer is yes, you did… There is indeed a character limit for ChatGPT.
Let’s explore the practical limitations of ChatGPT for long texts and how OpenAI’s token system impacts word count.
I’ll go into strategies for character limit workarounds and encouraging longer responses from GPT models. I’ll include issues and challenges with current language models.
Lastly, I’ll say a few things about how supercomputers are revolutionizing data processing. I hope you’ve invested in Nvidia stock!
Does Chat GPT Have a Word Limit
For the question, does chat GPT have a word limit? Let’s clear things up.
Technically, this advanced language model doesn’t have a hard word limit but uses a token system instead.
Tokens can be thought of as word fragments. OpenAI forms these by chopping up your prompt to Chat GPT before the API starts working on it. Because of this, tokens don’t usually correspond precisely to whole words. They can include trailing spaces and even portions of words.
Here are some thumb rules straight from OpenAI regarding typical token-to-word conversions:
- 1 token roughly equals 4 English characters.
- 1 token roughly equals 75% of an English word.
- 100 tokens is about 75 English words.
Interesting, but why should we care?
Token Limitations for Long Text
As I said earlier, tokens can be characters or subwords, depending on the complexity of your language use. This naturally brings us back to the question, “Does Chat GPT have a word limit?”
When dealing with longer texts, you might face some challenges due to the high perplexity and increased randomness associated with using a limited number of tokens.
It’s like stuffing a huge suitcase for a vacation but having a weight limit. In this case, the weight limit is the number of tokens you can use. As your ‘suitcase’ gets fuller, things can get a bit messy – that’s the high perplexity and randomness I’m talking about.
OpenAI Max Token Limits
- GPT 3.5 Turbo: 4,096 tokens (ChatGPT word limit is ~3,000 words).
- GPT 4: 8,192 tokens (~6,000 words).
- GPT 4 32K: 32,768 tokens (~24,000 words).
Note: Keep in mind the token limits include your prompt and the GPT model response.
Stay current with the latest GPT releases and token counts here.
Bypass Word Count Limitations
So, you’re finding yourself still wondering, “Does Chat GPT have a word limit?” as you grapple with the word count constraints in OpenAI’s ChatGPT models?
The good news is – there are a few ingenious ways to navigate around the seemingly pesky word count ceilings of OpenAI’s ChatGPT models to get longer responses. It’s not about the limits but how you play within them.
Let’s dive into some of the strategies I use.
1. Break Text into Smaller Chunks
If you’re dealing with a lot of text, break it into smaller chunks to make it more manageable and avoid exceeding the model’s maximum token limit.
For example, if you’re analyzing a large podcast script for new content in your headless CMS, break it down into multiple sections and analyze them as separate prompts.
There are a bunch of free chunkers and splitters. Here is the one I use: https://conturata.com/ai/chunker
2. Use Precision and Brevity
Just as a poet carefully selects each word to convey a deep meaning in a few lines, you can do the same with your prompts.
Make your prompts short, precise, and straight to the point. Remember, your prompt counts as part of the tokens expended in the combined prompt and response.
That’s on the prompt side. You can also ask GPT to respond precisely with brevity and conciseness.
3. Establish an Upper Limit on Your API Call
If you use the OpenAi API feature, set the limit for “max tokens” to a number high enough to communicate with your application without exceeding the max token limit.
I understand this doesn’t ‘bypass’ the max limit per see, but it’s important to mention because I’ve seen this get overlooked and cause problems with API calls.
4. Sequence Your API Calls
Regarding API calls, suppose you have long text exceeding the token limit. In that case, you can divide it into smaller chunks and process each in separate, sequenced API calls.
Send one chunk, wait for the model to process it, send the next, and so on.
Issues and Challenges With Current Language Models
AI language models like ChatGPT are powerful, but they have limitations that we need to acknowledge.
One concern is that these models plagiarize. I can confidently say you shouldn’t worry about ChatGPT plagiarizing due to the nature of its content creation and the plagiarism safeguards I describe in this post.
Another major concern is social bias, which can perpetuate harmful stereotypes and affect how users interact with technology.
OpenAI is working to reduce biases in ChatGPT’s responses, but users can also provide feedback to improve future iterations.
Social Bias Concerns Within Current Language Models
Continuous research and engineering improvements are underway to reduce biases in AI language models like ChatGPT.
Users can play an active role in combating social bias by providing feedback on problematic outputs via the UI.
Hallucination Phenomena During Interaction
When AI chatbots seem to be dreaming up things out of nowhere, we deal with a curious phenomenon known as ‘hallucinations.‘ These are times when AI conjures up details that weren’t in its original training data, and they can be quite a puzzle.
Sure, these hallucinations can spark some pretty out-of-the-box ideas – it’s like having an imaginative storyteller inside your computer. But remember, sometimes these stories can be just that – stories, not facts.
That’s why you should always look closely and fact-check for accuracy before publishing or making big decisions based on them.
Think of it as walking a tightrope. On one side, there’s the creative potential of AI, and on the other, the risk of misinformation.
As we move forward in this exciting AI journey, we must take balanced, proactive steps to minimize the risks and make the most of what AI can offer us responsibly.
Future Developments and Improvements in Generative Conversational AIs
Get ready for the next level of AI with OpenAI’s upcoming GPT-4 32K release, promising to process up to 24k words accurately.
Expect advanced comprehension, nuanced responses, and a greater understanding of human language nuances.
Nvidia’s new supercomputer DGX GH200 could be a game-changer for data processing, with profound implications for generative AI recommender systems.
This high-performance computing beast has one goal: transforming how we process massive amounts of data.
Developers can expect vast opportunities in dealing with complex datasets and advanced algorithms.
Wrap Up – Does Chat GPT Have a Word Limit?
Does Chat GPT have a word limit?
Yes. ChatGPT’s word limit can be a challenge for long texts, but there are ways to get the most out of these limitations by chunking text, using brevity, and using creative API calls.
However, social bias concerns and hallucination phenomena remain challenging for current language models.
GPT-4 and supercomputer advancements offer exciting opportunities for data processing, higher token limits, and reduced bias and hallucination.
The landscape is changing so fast. For new information not mentioned, check out OpenAI’s blog.