Tools and Topics

AI Copilots: Enterprise Use Cases and Key Considerations

AI copilots are digital assistants using AI, often large language models (LLMs), to help with tasks like code generation, creative writing, and decision making.

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Working with Gemini API: Text Gen, Doc Processing & Code Execution

What Is the Google Gemini API? Google Gemini is a multi-modal large language model (LLM). It provides natural language and image processing capabilities to enable text generation, sentiment analysis, document processing, image and video analysis, and more. Using the Gemini API, developers can integrate AI functionalities into their applications without needing deep expertise in machine […]

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Top 10 RAG Tutorials in 2024 + Bonus LangChain Tutorial

What Is Retrieval Augmented Generation (RAG)? Retrieval-augmented generation (RAG) combines large language models (LLMs) with external knowledge retrieval. Traditional LLMs generate responses based solely on pre-trained data. With RAG, the model can access updated and specific information at the time of inference, providing more accurate and context-rich responses. This method leverages repositories of external data, […]

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8 Prompt Engineering Examples for Common NLP Tasks

What Is Prompt Engineering? Prompt engineering involves crafting specific instructions or queries for large language models (LLMs) to get desired outputs. It plays a crucial role in fine-tuning the capabilities of models like OpenAI’s GPT-4o, Google Gemini, and Anthropic Claude, ensuring they deliver accurate, relevant, and contextually appropriate responses. Instead of merely providing a broad […]

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Prompt Engineering in ChatGPT: 9 Proven Techniques

What Is Prompt Engineering in ChatGPT? Prompt engineering involves crafting inputs (prompts) that guide a large language model (LLM) to generate desired outputs. It’s a skill that combines understanding of natural language processing, creativity, and strategic thinking to communicate with the model. Prompt engineering can transform vague requests into precise commands that the AI interprets […]

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LLM Application Development: Tutorial & 7 Steps to Production Apps

LLM application development involves creating software applications that leverage LLMs like OpenAI GPT or Meta LLaMA to generate, or manipulate natural language.

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LLM Security: Top 10 Risks, Impact, and Defensive Measures

What Is LLM Security? LLM security focuses on safeguarding large language models against various threats that can compromise their functionality, integrity, and the data they process. This involves implementing measures to protect the model itself, the data it uses, and the infrastructure supporting it. The goal is to ensure that these models operate as intended […]

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RAG vs. LLM Fine-Tuning: 4 Key Differences and How to Choose

What Is RAG (Retrieval-Augmented Generation)? Retrieval-Augmented Generation (RAG) merges large language models (LLMs), typically based on the Transformer deep learning architecture, with retrieval systems to enhance the model’s output quality. RAG operates by fetching relevant information from large collections of texts (e.g., Wikipedia, a search engine index, or a proprietary dataset) and fuses this external […]

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Prompt Engineering: Techniques, Uses & Advanced Approaches

Explore the essentials of prompt engineering to optimize interactions with AI and improve output quality from language models.

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