Tag: prompt
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The Death of the “Everything Prompt”: Google’s Move Toward Structured AI
The Death of the “Everything Prompt”: Google’s Move Toward Structured AI How the new Interactions API enables deep-reasoning, stateful, agentic workflows. The post The Death of the “Everything Prompt”: Google’s Move Toward Structured AI appeared first on Towards Data Science. Thomas Reid Go to original source
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Why the Sophistication of Your Prompt Correlates Almost Perfectly with the Sophistication of the Response, as Research by Anthropic Found
Why the Sophistication of Your Prompt Correlates Almost Perfectly with the Sophistication of the Response, as Research by Anthropic Found How prompt engineering has evolved, examined scientifically; and implications for the future of conversational AI tools The post Why the Sophistication of Your Prompt Correlates Almost Perfectly with the Sophistication of the Response, as Research…
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Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example
Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example Walkthrough using open-source prompt optimization algorithms in Python to improve the accuracy of an autonomous vehicle car safety agent running on OpenAI’s GPT 5.2 The post Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example appeared first on Towards Data Science. Vincent Koc Go to…
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Prompt Engineering vs RAG for Editing Resumes
Prompt Engineering vs RAG for Editing Resumes Running a code-free comparison in Azure The post Prompt Engineering vs RAG for Editing Resumes appeared first on Towards Data Science. Robert Etter Go to original source
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Prompt Engineering for Time-Series Analysis with Large Language Models
Prompt Engineering for Time-Series Analysis with Large Language Models Part 1: Prompts for Core Strategies in Time-Series The post Prompt Engineering for Time-Series Analysis with Large Language Models appeared first on Towards Data Science. Sara Nobrega Go to original source
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Systematic LLM Prompt Engineering Using DSPy Optimization
Systematic LLM Prompt Engineering Using DSPy Optimization This article is a journey into the fascinating and rapidly evolving science of LLM prompt iteration, which is a fundamental part of Large Language Model Operations (LLMOPs). We’ll use the example of generating customer service responses with a real-world dataset to show how both generator and LLM-judge prompts…
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Advanced Prompt Engineering for Data Science Projects
Advanced Prompt Engineering for Data Science Projects Part 2: Prompt Engineering for Features, Modeling, and Evaluation The post Advanced Prompt Engineering for Data Science Projects appeared first on Towards Data Science. Sara Nobrega Go to original source
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Declarative and Imperative Prompt Engineering for Generative AI
Declarative and Imperative Prompt Engineering for Generative AI Conceptual overview and practical considerations The post Declarative and Imperative Prompt Engineering for Generative AI appeared first on Towards Data Science. Chinmay Kakatkar Go to original source
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Exploring Prompt Learning: Using English Feedback to Optimize LLM Systems
Exploring Prompt Learning: Using English Feedback to Optimize LLM Systems Prompt learning presents a compelling approach for continuous improvement of AI applications The post Exploring Prompt Learning: Using English Feedback to Optimize LLM Systems appeared first on Towards Data Science. Aparna Dhinakaran Go to original source
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Become a Better Data Scientist with These Prompt Engineering Tips and Tricks
Become a Better Data Scientist with These Prompt Engineering Tips and Tricks Part 1: prompt engineering for planning, cleaning, and EDA The post Become a Better Data Scientist with These Prompt Engineering Tips and Tricks appeared first on Towards Data Science. Sara Nobrega Go to original source
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Mastering Prompt Engineering with Functional Testing: A Systematic Guide to Reliable LLM Outputs
Mastering Prompt Engineering with Functional Testing: A Systematic Guide to Reliable LLM Outputs Creating efficient prompts for large language models often starts as a simple task… but it doesn’t always stay that way. Initially, following basic best practices seems sufficient: adopt the persona of a specialist, write clear instructions, require a specific response format, and…