Prompt engineering makes it possible to optimize the results obtained by acting only on what is provided to the LLMs. In recent years, several techniques have been proposed to appropriately structure prompts to solve even complex tasks without having to retrain the initial model. We will look at some simple techniques such as zero-shoot, few-shoot and Chain-of-Thought (CoT).
Creating prompts for LLM models, such as ChatGPT, can be considered a new art. From structuring prompts to using context, it is possible to improve the conversational experience and extract maximum value from interactions with LLMs. Through practical examples, we will see how to best structure prompts to generate engaging and meaningful conversations with AI based on the set task.
The advent of ChatGPT and LLM (Large Language Models) has revolutionized the world. Almost every industry has undergone a revolution and is adopting these powerful means of artificial intelligence to build new tools and services. But how do we build the prompts, i.e., the instructions, to make these models generate what we are interested in? Prompt engineering is the discipline that addresses this very issue. Let’s discover some tips for improving our prompts to artificial intelligence tools.
Clustering algorithms allow data to be grouped according to their inherent characteristics. There are many algorithms that have been developed over the years. Hierarchical clustering, thanks to a graphical representation called a dendogram, makes it possible to visualize at a glance the composition of clusters and interpret their characteristics. Let us find out, step by step, how it works and how to interpret the results obtained.
Clustering algorithms allow data to be grouped according to their inherent characteristics. There are many algorithms that have been developed over the years. K-Means is certainly the most popular and simple one. Let’s find out, step by step, how this method succeeds in identifying clusters of data using only the number of groups that need to be extracted.
Clustering algorithms allow data to be grouped according to their inherent characteristics. There are many algorithms that have been developed over the years. Among the most famous ones, we cannot forget DBSCAN. Let’s find out, step by step, how this method succeeds in identifying clusters of data of any shape and size thanks to only two parameters.
ChatGPT is OpenAI’s flagship product. This chatbot, which is completely free, allows us to interact with artificial intelligence to generate ideas, articles, code, and more. Let’s discover its features and some possible application areas.
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