prompt engineering
Prompt engineering for low-resource languages
Dive into innovative prompt engineering strategies for multilingual NLP to improve language tasks across low-resource languages, making AI more accessible worldwide
prompt engineering
prompt engineering
What is tree of thought prompting?
Large language models (LLMs) keep getting better, and so do the ways we work with them. Tree of thought prompting is a new technique that helps LLMs solve complex problems. It works by breaking down the model's thinking into clear steps, similar to how humans work through difficult
chain-of-thought prompting
Prompt engineering techniques for effective AI outputs
Remember when prompt engineering meant just asking ChatGPT to write your blog posts or answer a basic question? Those days are long gone. We're seeing companies hire dedicated prompt engineers now - it's become a real skill in getting large language models (LLMs) to do exactly
prompt engineering
Prompting Chatgpt vs Claude
Explore the key differences between Claude and ChatGPT, from their capabilities and use cases to their response speeds and unique features.
prompting
Prompt Security and Guardrails: How to Ensure Safe Outputs
Prompt security is an emerging and essential field within AI development making sure that AI-generated responses are safe, accurate, and aligned with the intended purpose. When prompts are not secured, the resulting outputs can unintentionally generate or amplify misinformation. Compliance risks are also a major concern. Enterprises deploying AI systems
prompt engineering
Using Prompt Chaining for Complex Tasks
Master prompt chaining to break down complex AI tasks into simple steps. Learn how to build reliable workflows that boost speed and cut errors in your language model applications.
prompting
Evaluating Prompt Effectiveness: Key Metrics and Tools
Learn how to evaluate prompt effectiveness for AI models. Discover essential metrics and tools that help refine prompts, enhance accuracy, and improve user experience in your AI applications.`
Few-shot prompting
Zero-Shot vs. Few-Shot Prompting: Choosing the Right Approach for Your AI Model
Explore the differences between zero-shot and few-shot prompting to optimize your AI model's performance. Learn when to use each technique for efficiency, accuracy, and cost-effectiveness.
prompt engineering
The Complete Guide to Prompt Engineering
What is Prompt Engineering? At its core, prompt engineering is about designing, refining, and optimizing the prompts that guide generative AI models. When working with large language models (LLMs), the way a prompt is written can significantly affect the output. Prompt engineering ensures that you create prompts that consistently generate
OpenAI
OpenAI’s Prompt Caching: A Deep Dive
This update is welcome news for developers who have been grappling with the challenges of managing API costs and response times. OpenAI's Prompt Caching introduces a mechanism to reuse recently seen input tokens, potentially slashing costs by up to 50% and dramatically reducing latency for repetitive tasks. In
prompt engineering
What is Automatic Prompt Engineering?
Learn how automatic prompt engineering optimizes prompt creation for AI models, saving time and resources. Discover key techniques, tools, and benefits for Gen AI teams in this comprehensive guide.
paper summaries
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance - Summary
The paper discusses the cost associated with querying large language models (LLMs) and proposes FrugalGPT, a framework that uses LLM APIs to process natural language queries within a budget constraint. The framework uses prompt adaptation, LLM approximation, and LLM cascade to reduce the inference