Prompt Engineering

The Controversial Trademark of "Prompt Engineering" - A Call to Action for the AI Community

The controversial "Prompt Engineering" trademark, and its impact on the AI community.

Introduction

In the rapidly growing field of artificial intelligence (AI), it's crucial to maintain an open and collaborative environment for innovation. However, recent events have raised concerns within the AI community, once such is the battle for the GPT trademark last month, read about it here.

But another flew under the radar it seems, that is the term "Prompt Engineering" has been trademarked in February 2023, potentially

What is a Prompt Engineer: The Developing and Essential Role of Prompt Engineers in AI Powered Systems Featured Post

Ever wondered what a prompt engineer actually does? Learn about the roles, responsibilities and activities of a professional Prompt Engineer.

Introduction

As AI systems, such as large language models, become increasingly sophisticated, prompt engineers play a critical role in ensuring that these systems generate outputs that are relevant, accurate, and in line with desired outcomes. In this article, we will explore the key roles and responsibilities of a prompt engineer, the skills required for success in the field, potential employment opportunities and take a detailed walkthrough on what it's like to be a prompt engineer on a specific project.

What is a Prompt Engineer

A "Prompt Engineer" is a professional who specializes in designing, optimizing, and refining prompts or inputs

Master Prompting Techniques: Self-Consistency Prompting Featured Post

Learn about self-consistency prompting and its place in prompt engineering

Introduction to Self-Consistency in LLMs

Self-consistency is an advanced prompting technique that builds on COT prompting. The aim here is to improve the naive greedy decoding using COT prompting by sampling multiple diverse reasoning paths and selecting the most consistent answers.

This can help boost the performance of COT prompting on tasks involving arithmetic and common sense reasoning. By utilizing a majority voting system, the AI model can arrive at more accurate and reliable answers.

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In this approach, you supply the language model with several question-answer or input-output pairs, illustrating the thought process in the provided answers or outputs. You

Master Prompting Techniques: Knowledge Generation Prompting Featured Post

Master AI-driven problem-solving with knowledge generation prompting techniques. Learn how to combine AI models & external sources for optimal results.

Knowledge generation prompting is a technique that utilizes the AI model's ability to generate knowledge for solving specific tasks. By providing the model with demonstrations and guiding it towards a particular problem, the AI can generate knowledge that is then used to answer the task at hand.

This technique can be combined with external sources, such as APIs or databases, to further enhance the AI's problem-solving abilities.

Knowledge generation prompting has two core steps:

Knowledge generation - evaluate what the LLM already knows about the topic/subtopic as well as related ones
Knowledge integration at inference time (during prompting via

Master Prompting Concepts: Chain of Thought Prompting Featured Post

Learn about Chain of Thought Prompting - Learn tips, techniques, and applications for enhanced problem-solving.

Introduction to Chain of Thought (CoT) Prompting

Chain of Thought Prompting is a novel method developed by researchers at Google to enhance the reasoning capabilities of large language models. This approach breaks down multi-step problems into intermediate steps, allowing language models to tackle complex reasoning tasks that cannot be solved with standard prompting techniques. In this essay, we will discuss the benefits of Chain of Thought Prompting and review the experimental results obtained from its application.

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

We explore how generating a chain of thought -- a series of intermediatereasoning steps -- significantly

Master Prompt Engineering: LLM Embedding and Fine-tuning Featured Post

In this lesson, we cover fine-tuning for structured output & semantic embeddings for knowledge retrieval. Unleash AI's full potential! 🧠

Fine-tuning and embedding LLMs (GPT-3/3.5/4) have become a popular topic of discussion as people seek to leverage the power of this advanced language model for various applications, such as question-answering (QA) and information retrieval.

While both semantic embeddings and fine-tuning are techniques employed to adapt LLMs to specific tasks, they serve different purposes and offer unique benefits.

We will explore these two concepts together as they are related and there is often much confusion about which to use and when.

Core Concepts

LLM Transfer Learning

Transfer learning is a machine learning technique that allows a model to

The Controversial Trademark of "Prompt Engineering" - A Call to Action for the AI Community

Introduction

What is a Prompt Engineer: The Developing and Essential Role of Prompt Engineers in AI Powered Systems Featured Post

Introduction

What is a Prompt Engineer

Master Prompting Techniques: Self-Consistency Prompting Featured Post

Introduction to Self-Consistency in LLMs

Master Prompting Techniques: Knowledge Generation Prompting Featured Post

Master Prompting Concepts: Chain of Thought Prompting Featured Post

Introduction to Chain of Thought (CoT) Prompting

Master Prompt Engineering: LLM Embedding and Fine-tuning Featured Post

Core Concepts

LLM Transfer Learning

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Reasoners - A New Approach to Smarter AI

Generative AI - The New Compiler

How Prompt Keywords (Magic Words) Optimize Language Model Performance

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