feat(ai): added concept

Author: tgenaitay

ai-data/managed-inference/concepts.mdx

@@ -42,6 +42,10 @@ Fine-tuning involves further training a pre-trained language model on domain-spe
 Few-shot prompting uses the power of language models to generate responses with minimal input, relying on just a handful of examples or prompts.
 It demonstrates the model's ability to generalize from limited training data to produce coherent and contextually relevant outputs.
 
+## Function calling
+
+Function calling allows a language model (LLM) to interact with external tools or APIs, executing specific tasks based on user requests. The LLM identifies the appropriate function, extracts needed parameters, and returns the results as structured data, typically in JSON format.
+
 ## Hallucinations
 
 Hallucinations in LLMs refer to instances where generative AI models generate responses that, while grammatically coherent, contain inaccuracies or nonsensical information. These inaccuracies are termed "hallucinations" because the models create false or misleading content. Hallucinations can occur because of constraints in the training data, biases embedded within the models, or the complex nature of language itself.