Remove Auto-complete Remove LLM Remove Prompt Engineering
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ChatGPT & Advanced Prompt Engineering: Driving the AI Evolution

Unite.AI

GPT-4: Prompt Engineering ChatGPT has transformed the chatbot landscape, offering human-like responses to user inputs and expanding its applications across domains – from software development and testing to business communication, and even the creation of poetry. Imagine you're trying to translate English to French.

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Latest Modern Advances in Prompt Engineering: A Comprehensive Guide

Unite.AI

Prompt engineering , the art and science of crafting prompts that elicit desired responses from LLMs, has become a crucial area of research and development. In this comprehensive technical blog, we'll delve into the latest cutting-edge techniques and strategies that are shaping the future of prompt engineering.

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Beyond ChatGPT; AI Agent: A New World of Workers

Unite.AI

Current Landscape of AI Agents AI agents, including Auto-GPT, AgentGPT, and BabyAGI, are heralding a new era in the expansive AI universe. AI Agents vs. ChatGPT Many advanced AI agents, such as Auto-GPT and BabyAGI, utilize the GPT architecture. Their primary focus is to minimize the need for human intervention in AI task completion.

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MetaGPT: Complete Guide to the Best AI Agent Available Right Now

Unite.AI

Last time we delved into AutoGPT and GPT-Engineering , the early mainstream open-source LLM-based AI agents designed to automate complex tasks. Enter MetaGPT — a Multi-agent system that utilizes Large Language models by Sirui Hong fuses Standardized Operating Procedures (SOPs) with LLM-based multi-agent systems.

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MAGPIE: A Self-Synthesis Method for Generating Large-Scale Alignment Data by Prompting Aligned LLMs with Nothing

Marktechpost

This limitation hinders the advancement of LLM capabilities and their application in diverse, real-world scenarios. Existing methods for generating instruction datasets fall into two categories: human-curated data and synthetic data produced by LLMs. The model then generates diverse user queries based on these templates.

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Going Beyond Zero/Few-Shot: Chain of Thought Prompting for Complex LLM Tasks

Towards AI

Instead of formalized code syntax, you provide natural language “prompts” to the models When we pass a prompt to the model, it predicts the next words (tokens) and generates a completion. 2022 where, instead of adding examples for Few Shot CoT, we just add “Let’s think step by step” to the prompt. Source : Wei et al.

LLM 76
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Top LangChain Books to Read in 2024

Marktechpost

LangChain is an open-source framework that allows developers to build LLM-based applications easily. It provides for easily connecting LLMs with external data sources to augment the capabilities of these models and achieve better results. It teaches how to build LLM-powered applications using LangChain using hands-on exercises.