Learn how to inject domain-specific knowledge into LLMs for medicine, law, finance & more. Explore two powerful frameworks: fine-tuning + prompting and prompt engineering with examples.
Time's Secrets: The Temporal Knowledge Graph Prompt Engineering (TKGP) framework empowers language models to analyze time-dependent data in legal, medical, financial, and historical domains, uncovering hidden connections and generating deeper insights.
Discover how carefully chosen prompt keywords enhance the effectiveness of language models. Learn how to craft precise prompts to improve the reliability and usefulness of AI responses.
Discover the role of the prompt engineering layer in generative AI, optimizing interactions and workflows. See how Make.com and Zapier simplify integration, enabling scalable AI solutions with GPT-4 and Claude. Learn more at PromptEngineering.org.
Make AI interactions smoother and more effective. Learn how role-play lets AI agents adapt to your needs, offering better customer service, education, and more.
Discover the power of prompt templates and recipes in AI prompt engineering. Learn how these tools enable scalable, efficient, and effective AI solutions across industries and domains.
Explore our innovative framework that utilizes LLMs for educational storytelling, designed to simplify complex concepts for non-experts.
Discover the power of intention-aligned prompting to unlock the full potential of AI language models. Learn how to craft prompts that empower AI's problem-solving and creative capabilities for optimal results.
Goal-oriented prompts unlock more powerful results from AI language models compared to process-oriented prompts. Learn why and see examples and tips for effective prompting.
Discover a prompt engineering framework that leverages large language models (LLMs) to generate effective heuristics dynamically, enhancing decision-making and problem-solving capabilities across various domains.
Following up on the intriguing abilities of LLMs to decode and ideas and thoughts in symbols and emojis, here are a few brief case studies using ChatGPT and Claude.
A discussion on how emotional prompting can create more engaging, empathetic, and human-like interactions with AI & ChatBots. Learn about the key considerations, ethical implications, and future directions of this cutting-edge technology.
Discover how the Emotional Intelligence (EI) Graph provides a structured approach to developing and regulating emotional intelligence skills. Learn about EI Clusters, Cognitive Chains, and Nodes, and how they work together to support personal growth and well-being.
The OPUS Framework enables the creation of high-quality, relevant AI-generated content through a structured approach to crafting effective prompts from initial observations.
Discover how prompt engineering techniques can help language models overcome memory limitations and deliver more accurate, context-rich responses.
Retrieval-Augmented Generation (RAG) offers promise for grounding large language models, but remains an imperfect science. Learn about the challenges, innovations, and future directions in RAG research and development.
Discover how the techniques used to optimize AI prompts can also supercharge your human communication skills. From crafting clear requests to embracing iterative dialogue, learn to apply the core principles of prompt engineering to your everyday interactions.
Many-Shot Jailbreaking (MSJ) attacks exploit language models' expanded context windows to induce harmful outputs. Current alignment techniques like supervised fine-tuning and reinforcement learning fail to fully mitigate MSJ risks.
A groundbreaking study reveals ChatGPT-4's surprising prowess in clinical reasoning, outperforming physicians but with notable pitfalls. Exploring AI's potential as a collaborative tool in healthcare.
Discover the persuasive power of AI language models in human conversations and the impact of personalization in this randomized controlled trial.
Can a machine learn how people perceive public figures? A new study suggests AI can predict personality traits with surprising accuracy, just by analyzing text. We explore the implications and what it means for the future.
So you want to be a prompt engineer? Let's peek into the world of these AI wranglers, exploring their experiences, the tools they use, and why you might not need a coding degree to become one.
Explore the inner workings of Large Language Models (LLMs) and learn how their memory limitations, context windows, and cognitive processes shape their responses. Discover strategies to optimize your interactions with LLMs and harness their potential for nuanced, context-aware outputs.
This paper introduces a novel method to bypass the filters of Large Language Models (LLMs) like GPT4 and Claude Sonnet through induced hallucinations, revealing a significant vulnerability in their reinforcement learning from human feedback (RLHF) fine-tuning process.
