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GPT-3 and Prompts: A quick primer

Summary

This article provides an introduction to GPT-3 and explains the importance of prompts in building applications with GPT-3. It outlines three key understandings for writing prompts for GPT-3: garbage in, garbage out; prompting with examples; and using easily query-able return types. It also provides an example of how to structure a prompt for building a chatbot, and how to ask GPT-3 to respond in JSON for easier parsing on the frontend. It concludes by encouraging readers to experiment and explore the possibilities of GPT-3 in creating unique applications.

Q&As

What is GPT-3?
GPT-3 is an open-source text generation model developed by OpenAI.

What is the key to creating complex, tailored behaviour with GPT-3?
The key to creating complex, tailored behaviour with GPT-3 is providing it with clear, unambiguous context and instructions.

How can one use the GPT-3 API to create a chatbot?
To use the GPT-3 API to create a chatbot, one must provide a prompt that instructs GPT-3 to behave like a chatbot and respond appropriately to user texts.

What are the benefits of using a few-shot prompt over a zero-shot prompt?
The benefits of using a few-shot prompt over a zero-shot prompt are that it can greatly improve the accuracy and coherence of the generated text.

What is prompt engineering and what can it be used for?
Prompt engineering is the process of providing GPT-3 with instructions and context to generate text. It can be used to generate text for applications in production, as well as to create AI-first applications such as a GPT-3 chess engine or a math tutor speaking in the uwu voice.

AI Comments

👍 This article provides an excellent primer on GPT-3 and Prompts. It is filled with key understandings, examples, and resources to help readers understand how to use GPT-3 and Prompts.

👎 The article is too long and could have been condensed into a shorter format. It also lacks any visual aids to help readers understand the content better.

AI Discussion

Me: It's about GPT-3 and Prompts, and how they work together to create powerful AI applications. It also gives an overview of how to use prompts to get the best results from GPT-3, such as using examples and structured return types.

Friend: Wow, that's really interesting. It's amazing how AI is advancing at such a rapid pace. What implications do you think this article has?

Me: Well, I think it's a sign of how powerful AI is becoming, and just how much potential it has for creating new and innovative applications. It also shows how important it is to understand the nuances of AI and how to use it properly, as it can be easy to misuse or misunderstand the power of AI. Finally, it's also a reminder of how important it is to keep learning and trying new things, as the possibilities are nearly endless.

Action items

Technical terms

GPT-3
Generative Pre-trained Transformer 3, an open-source language model developed by OpenAI.
Prompts
A set of instructions given to a machine learning model to generate a desired output.
ML/AI
Machine Learning/Artificial Intelligence.
DALL-E
A text-to-image model developed by OpenAI.
Midjourney
A text-to-image model developed by OpenAI.
Stable Diffusion
An open-source image generation model.
Meta-learner
A machine learning model that has been trained to learn how to learn.
JSON
JavaScript Object Notation, a data format used for exchanging information between a server and a web application.
PGN
Portable Game Notation, a standard for the representation of chess games.
ENS
Ethereum Name Service, a distributed, open, and extensible naming system based on the Ethereum blockchain.
Solidity
A programming language used for writing smart contracts on Ethereum.
NFT
Non-Fungible Token, a type of digital asset that is unique and not interchangeable.
DAO
Decentralized Autonomous Organization, a type of organization that is run by a set of rules encoded as computer programs called smart contracts.
Solana
A blockchain platform designed to scale to thousands of transactions per second.
Flow
A blockchain platform designed to enable developers to build and deploy decentralized applications.

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