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Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI…

ODSC - Open Data Science

Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices Editor’s note: Jayachandran Ramachandran and Rohit Sroch are speakers for ODSC APAC this August 22–23. Various prompting techniques, such as Zero/Few Shot, Chain-of-Thought (CoT)/Self-Consistency, ReAct, etc.

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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.

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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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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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AI and coding: How Seattle tech companies are using generative AI for programming

Flipboard

Redfin Photo) “We’ve already found a number of places where AI tools are making our engineers more efficient. The auto-complete and auto-suggestions in Visual Studio Code are pretty good, too, without being annoying. ” We’ve also found ways to use these tools to help us serve customers more efficiently.

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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.

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Future of Data-Centric AI day 1: LLMs changed the world

Snorkel AI

Foundation models, Alex said, yield results that are “nothing short of breathtaking,” but they’re not a complete answer for enterprises who aim to solve challenges using machine learning. “We We are, in our view, in a bit of a hype cycle,” he said.