Create Custom GPTs & 10x Your Productivity: A Tutorial for Everyone
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ChatGPT was yesterday. GPTs are the future. In case you missed last week’s “OpenAI Dev Day” and have not yet played around with GPTs, this post is for you. I’ll summarize the difference between ChatGPT and the new GPTs, and provide a step-by-step guide to creating your personal ecosystem of customized chatbots - without coding skills or prior knowledge. Let’s jump right in.
The Difference Between ChatGPT and GPTs
ChatGPT is a chat interface on top of OpenAI’s large language models (LLMs) such as GPT-3.5 or GPT-4. It was released on 30th Nov 2022 and allows you to interact with LLMs by prompting (=instructing) them with natural language. No coding skills required. The power of OpenAI LLMs compared to other options is mainly their broad applicability. They have been achieving this by training their models with heavy computing resources and extensive datasets containing information about anything you can imagine.
While the versatility and “one-stop-shop” value proposition is a big plus for users dealing with a variety of use cases, we often require a deeper understanding of specific contexts to solve more complex problems. This can either be achieved through fine-tuning (=improve model capabilities and context understanding with additional training data) or customization via advanced prompting and retrieval-augmented generation (RAG) frameworks.
Fine-tuning typically involves taking a pre-trained LLM (or any other neural network) and adjusting its parameters or architecture to adapt it to a specific task or dataset. It requires technical expertise, training resources, domain-specific data, and “original LLM” access. While the resulting model performs on an expert level and can be used by/shared with anyone, the training process comes with high entry barriers.
Customizing pre-trained models through advanced prompting and RAG frameworks (=grounding them with external, up-to-date sources of knowledge) achieves comparable results to pre-trained models, yet with significantly lower entry barriers. On the flip side, customized LLMs were difficult to share and needed to be replicated by copying & pasting the exact sequence of prompts and input data. Until last week. At “Dev Day” on 6th Nov 2023, OpenAI launched GPTs (see 20-minute summary video below), a way to customize chatbots/LLMs and share them with the world.
According to OpenAI, GPTs are custom versions of ChatGPT that combine instructions, extra knowledge, and any combination of skills. You can make them for yourself, just for your company’s internal use, or for everyone. Creating one is as easy as starting a conversation, giving it instructions and extra knowledge, and picking what it can do, like searching the web, making images, or analyzing data.
So in short, ChatGPT is a simple chat interface to interact with generic LLMs and GPTs are customized chatbots that have improved for specific tasks and contexts. With this in mind, let’s create your first customized GPT!
Creating Customized GPTs In Less Than 3 Minutes
1. Sign up to ChatGPT+ for $20/month and log in
2. Click on “Explore” at the top left
3. Click “Create a GPT” at the top
4. Click on “Configure” to set the basics straight: Name, Description, Instructions & more
Before you start “creating”, think about what you want these GPTs to be good at. Write down your most tedious tasks or anything that you’d like to automate. Subsequently, create one GPT at a time.
5. Click on “Create” to set up your first customized chatbot
(!) Note of Caution - Prevent Your GPTs From Being Cracked (!)
Only a few days live and already the first users shared ways to crack GPTs. To prevent others from jailbreaking your GPTs, follow these two simple steps: