It’s hard to overestimate the importance of function calling within the ChatGPT realm, though not a lot of people are aware of its concept. Let’s change that.

History

Before the advent of function calling, there were two main methods to enhance GPT language models:

  • Fine-Tuning: This involved additional training of the model with specific example responses to tailor it for certain tasks or contexts.
  • Embeddings: This method enriched the input prompt with contextual data, helping the model to generate more accurate and relevant responses.

Function calling was released in early 2023 with the GPT-4 model. This feature greatly expanded ChatGPT’s capabilities, allowing it to perform tasks beyond just generating text, such as browsing the internet or creating images.

Take aways:

  1. Boosting AI’s Abilities: Earlier, AI got better through fine-tuning and embeddings. But function calling is a whole new ball game, letting chatbots pull in live data from the outside world.
  2. How It Works: Chatbots use the Chat Completions API to decide whether to answer on their own or ask for help from an external function. It’s like having a secret helper on standby.
  3. AI Chatbots’ New Skills: With function calling, chatbots aren’t just limited to chatting. They can now help you with real-world tasks like making reservations or keeping you up-to-date with the latest news.
  4. Customized Conversations: Thanks to function calling, chatbots can give you more tailored information, making them more helpful in various situations.
  5. The Future of AI Chatbots: With function calling, AI chatbots are evolving into more helpful, intelligent companions. They’re getting better at understanding and helping us in real-time.

Overview Function Calling:

Example of added value function calling:

ChatGPT (GPT 3.5) without function calling (plugins):

ChatGPT (GPT-4) WITH function calling (Bing Search function):

References:

Function Calls in a Nutshell:

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