Large language models (LLMs) are increasingly interacting with external tools and generating structured outputs. This shift requires a robust method for defining and validating the data exchanged between the LLM, the tool, and the user. JSON Schema provides a standardized way to describe and enforce the structure of data passed
The rapid evolution of artificial intelligence (AI) has brought forth a new and exciting field: prompt engineering. As large language models (LLMs) become increasingly sophisticated, the ability to effectively communicate with them is paramount. This article provides a comprehensive overview of prompt engineering, covering what it is, why it'
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Table of contents: * How to Use Claude to Summarize Reports * How to Use ChatGPT to Summarize Reports * How to Use Gemini to Summarize Reports * Prompt Templates for Summarizing Reports * Types of Reports and Summarization Approaches Using AI Summarizing long reports takes a lot of time and energy. Luckily, artificial intelligence
Table of contents: * What is an Assistant Prompt? * What is a Tool / Function Prompt? * Assistant Prompt vs. Tool / Function Prompt: Key Differences In artificial intelligence (AI), the ability to communicate clearly with applications is important to fully leverage an LLM's capabilities. Prompt engineering is an important skill that
ChatGPT, developed by OpenAI, has changed how we work with its ability to generate human-like text. Beyond the hype, ChatGPT offers many practical applications for professionals. We've researched and broken down the top 5 compelling use cases that demonstrate how ChatGPT can increase productivity, enhance creativity, and streamline
Table of contents: * What is a System Prompt? * What is a User Prompt? * Examples of System and User Prompts * System and User Prompt Best Practices * System Prompts in Applications In artificial intelligence (AI), the ability to communicate clearly with applications is important to fully leverage an LLM's capabilities.
Evaluating complex datasets—whether textual, numerical, or multimodal—is a challenge in data science. Many evaluation metrics and human-annotation methods struggle to capture subtle quality issues, contextual relationships, or emerging patterns within large-scale and heterogeneous data. As a result, organizations often rely on time-consuming manual checks or oversimplified metrics that
Mistral and Meta have both staked their claims to open-source AI development, each pushing the boundaries of accessibility, scalability, and performance in large language models. The latest models in their respective lineups, Mistral Large 2 and Llama 3.1, are prime examples of this ambition, offering great alternatives to closed-source
Meta has consistently pushed the envelope in open-source AI development, with a focus on making powerful LLMs more accessible, scalable, and efficient. The Llama series is Meta's frontier LLM that offers an open alternative to proprietary models. With the introduction of Llama 3.1, Meta has built on
What is an LLM (Large Language Model)? A Large Language Model (LLM) is an advanced AI system trained to understand and generate human-like text based on large datasets. Understanding LLM architecture is crucial for creating efficient, scalable, and task-specific AI applications that meet user needs effectively. LLM architecture diagrams for
It’s been almost three months since OpenAI announced its groundbreaking o1 series, featuring the o1 preview and o1 mini models. These two models represent a leap forward in specialized reasoning and problem-solving, each designed with a specific set of use cases in mind. The o1 preview excels in deep
Large Language Model (LLM) agents have rapidly evolved, becoming one of the hot topics in the tech industry. Initially designed for natural language processing tasks, LLMs can now serve as autonomous agents capable of complex decision-making and task execution. In this guide, we’ll explore the basics of LLM Agents,