how to write an essay with openai

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How to Get ChatGPT to Write an Essay: Prompts, Outlines, & More

Last Updated: April 28, 2024 Fact Checked

Getting ChatGPT to Write the Essay

Using ai to help you write, expert interview.

This article was written by Bryce Warwick, JD and by wikiHow staff writer, Nicole Levine, MFA . Bryce Warwick is currently the President of Warwick Strategies, an organization based in the San Francisco Bay Area offering premium, personalized private tutoring for the GMAT, LSAT and GRE. Bryce has a JD from the George Washington University Law School. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 46,512 times.

Are you curious about using ChatGPT to write an essay? While most instructors have tools that make it easy to detect AI-written essays, there are ways you can use OpenAI's ChatGPT to write papers without worrying about plagiarism or getting caught. In addition to writing essays for you, ChatGPT can also help you come up with topics, write outlines, find sources, check your grammar, and even format your citations. This wikiHow article will teach you the best ways to use ChatGPT to write essays, including helpful example prompts that will generate impressive papers.

Things You Should Know

• To have ChatGPT write an essay, tell it your topic, word count, type of essay, and facts or viewpoints to include.
• ChatGPT is also useful for generating essay topics, writing outlines, and checking grammar.
• Because ChatGPT can make mistakes and trigger AI-detection alarms, it's better to use AI to assist with writing than have it do the writing.

• Before using the OpenAI's ChatGPT to write your essay, make sure you understand your instructor's policies on AI tools. Using ChatGPT may be against the rules, and it's easy for instructors to detect AI-written essays.
• While you can use ChatGPT to write a polished-looking essay, there are drawbacks. Most importantly, ChatGPT cannot verify facts or provide references. This means that essays created by ChatGPT may contain made-up facts and biased content. [1] X Research source It's best to use ChatGPT for inspiration and examples instead of having it write the essay for you.

• The topic you want to write about.
• Essay length, such as word or page count. Whether you're writing an essay for a class, college application, or even a cover letter , you'll want to tell ChatGPT how much to write.
• Other assignment details, such as type of essay (e.g., personal, book report, etc.) and points to mention.
• If you're writing an argumentative or persuasive essay , know the stance you want to take so ChatGPT can argue your point.
• If you have notes on the topic that you want to include, you can also provide those to ChatGPT.
• When you plan an essay, think of a thesis, a topic sentence, a body paragraph, and the examples you expect to present in each paragraph.
• It can be like an outline and not an extensive sentence-by-sentence structure. It should be a good overview of how the points relate.

• "Write a 2000-word college essay that covers different approaches to gun violence prevention in the United States. Include facts about gun laws and give ideas on how to improve them."
• This prompt not only tells ChatGPT the topic, length, and grade level, but also that the essay is personal. ChatGPT will write the essay in the first-person point of view.
• "Write a 4-page college application essay about an obstacle I have overcome. I am applying to the Geography program and want to be a cartographer. The obstacle is that I have dyslexia. Explain that I have always loved maps, and that having dyslexia makes me better at making them."

Tyrone Showers

Be specific when using ChatGPT. Clear and concise prompts outlining your exact needs help ChatGPT tailor its response. Specify the desired outcome (e.g., creative writing, informative summary, functional resume), any length constraints (word or character count), and the preferred emotional tone (formal, humorous, etc.)

• In our essay about gun control, ChatGPT did not mention school shootings. If we want to discuss this topic in the essay, we can use the prompt, "Discuss school shootings in the essay."
• Let's say we review our college entrance essay and realize that we forgot to mention that we grew up without parents. Add to the essay by saying, "Mention that my parents died when I was young."
• In the Israel-Palestine essay, ChatGPT explored two options for peace: A 2-state solution and a bi-state solution. If you'd rather the essay focus on a single option, ask ChatGPT to remove one. For example, "Change my essay so that it focuses on a bi-state solution."

Pay close attention to the content ChatGPT generates. If you use ChatGPT often, you'll start noticing its patterns, like its tendency to begin articles with phrases like "in today's digital world." Once you spot patterns, you can refine your prompts to steer ChatGPT in a better direction and avoid repetitive content.

• "Give me ideas for an essay about the Israel-Palestine conflict."
• "Ideas for a persuasive essay about a current event."
• "Give me a list of argumentative essay topics about COVID-19 for a Political Science 101 class."

• "Create an outline for an argumentative essay called "The Impact of COVID-19 on the Economy."
• "Write an outline for an essay about positive uses of AI chatbots in schools."
• "Create an outline for a short 2-page essay on disinformation in the 2016 election."

• "Find peer-reviewed sources for advances in using MRNA vaccines for cancer."
• "Give me a list of sources from academic journals about Black feminism in the movie Black Panther."
• "Give me sources for an essay on current efforts to ban children's books in US libraries."

• "Write a 4-page college paper about how global warming is changing the automotive industry in the United States."
• "Write a 750-word personal college entrance essay about how my experience with homelessness as a child has made me more resilient."
• You can even refer to the outline you created with ChatGPT, as the AI bot can reference up to 3000 words from the current conversation. [3] X Research source For example: "Write a 1000 word argumentative essay called 'The Impact of COVID-19 on the United States Economy' using the outline you provided. Argue that the government should take more action to support businesses affected by the pandemic."

• One way to do this is to paste a list of the sources you've used, including URLs, book titles, authors, pages, publishers, and other details, into ChatGPT along with the instruction "Create an MLA Works Cited page for these sources."
• You can also ask ChatGPT to provide a list of sources, and then build a Works Cited or References page that includes those sources. You can then replace sources you didn't use with the sources you did use.

Expert Q&A

• Because it's easy for teachers, hiring managers, and college admissions offices to spot AI-written essays, it's best to use your ChatGPT-written essay as a guide to write your own essay. Using the structure and ideas from ChatGPT, write an essay in the same format, but using your own words. Thanks Helpful 0 Not Helpful 0
• Always double-check the facts in your essay, and make sure facts are backed up with legitimate sources. Thanks Helpful 0 Not Helpful 0
• If you see an error that says ChatGPT is at capacity , wait a few moments and try again. Thanks Helpful 0 Not Helpful 0

• Using ChatGPT to write or assist with your essay may be against your instructor's rules. Make sure you understand the consequences of using ChatGPT to write or assist with your essay. Thanks Helpful 0 Not Helpful 0
• ChatGPT-written essays may include factual inaccuracies, outdated information, and inadequate detail. [4] X Research source Thanks Helpful 0 Not Helpful 0

You Might Also Like

Thanks for reading our article! If you’d like to learn more about completing school assignments, check out our in-depth interview with Bryce Warwick, JD .

• ↑ https://help.openai.com/en/articles/6783457-what-is-chatgpt
• ↑ https://platform.openai.com/examples/default-essay-outline
• ↑ https://help.openai.com/en/articles/6787051-does-chatgpt-remember-what-happened-earlier-in-the-conversation
• ↑ https://www.ipl.org/div/chatgpt/

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How ChatGPT (and other AI chatbots) can help you write an essay

ChatGPT  is capable of doing many different things very well, with one of the biggest standout features being its ability to compose all sorts of text within seconds, including songs, poems, bedtime stories, and essays . 

The chatbot's writing abilities are not only fun to experiment with, but can help provide assistance with everyday tasks. Whether you are a student, a working professional, or just getting stuff done, we constantly take time out of our day to compose emails, texts, posts, and more. ChatGPT can help you claim some of that time back by helping you brainstorm and then compose any text you need. 

How to use ChatGPT to write: Code | Excel formulas | Resumes  | Cover letters  

Contrary to popular belief, ChatGPT can do much more than just write an essay for you from scratch (which would be considered plagiarism). A more useful way to use the chatbot is to have it guide your writing process. 

Below, we show you how to use ChatGPT to do both the writing and assisting, as well as some other helpful writing tips. 

How ChatGPT can help you write an essay

If you are looking to use ChatGPT to support or replace your writing, here are five different techniques to explore. 

It is also worth noting before you get started that other AI chatbots can output the same results as ChatGPT or are even better, depending on your needs.

Also: The best AI chatbots of 2024: ChatGPT and alternatives

For example,  Copilot  has access to the internet, and as a result, it can source its answers from recent information and current events. Copilot also includes footnotes linking back to the original source for all of its responses, making the chatbot a more valuable tool if you're writing a paper on a more recent event, or if you want to verify your sources.

Regardless of which AI chatbot you pick, you can use the tips below to get the most out of your prompts and from AI assistance.

1. Use ChatGPT to generate essay ideas

Before you can even get started writing an essay, you need to flesh out the idea. When professors assign essays, they generally give students a prompt that gives them leeway for their own self-expression and analysis. 

As a result, students have the task of finding the angle to approach the essay on their own. If you have written an essay recently, you know that finding the angle is often the trickiest part -- and this is where ChatGPT can help. 

Also: ChatGPT vs. Copilot: Which AI chatbot is better for you?

All you need to do is input the assignment topic, include as much detail as you'd like -- such as what you're thinking about covering -- and let ChatGPT do the rest. For example, based on a paper prompt I had in college, I asked:

Can you help me come up with a topic idea for this assignment, "You will write a research paper or case study on a leadership topic of your choice." I would like it to include Blake and Mouton's Managerial Leadership Grid, and possibly a historical figure. 

Also: I'm a ChatGPT pro but this quick course taught me new tricks, and you can take it for free

Within seconds, the chatbot produced a response that provided me with the title of the essay, options of historical figures I could focus my article on, and insight on what information I could include in my paper, with specific examples of a case study I could use. 

2. Use the chatbot to create an outline

Once you have a solid topic, it's time to start brainstorming what you actually want to include in the essay. To facilitate the writing process, I always create an outline, including all the different points I want to touch upon in my essay. However, the outline-writing process is usually tedious. 

With ChatGPT, all you have to do is ask it to write the outline for you. 

Also: Thanks to my 5 favorite AI tools, I'm working smarter now

Using the topic that ChatGPT helped me generate in step one, I asked the chatbot to write me an outline by saying: 

Can you create an outline for a paper, "Examining the Leadership Style of Winston Churchill through Blake and Mouton's Managerial Leadership Grid."

After a couple of seconds, the chatbot produced a holistic outline divided into seven different sections, with three different points under each section. 

This outline is thorough and can be condensed for a shorter essay or elaborated on for a longer paper. If you don't like something or want to tweak the outline further, you can do so either manually or with more instructions to ChatGPT. 

As mentioned before, since Copilot is connected to the internet, if you use Copilot to produce the outline, it will even include links and sources throughout, further expediting your essay-writing process. 

3. Use ChatGPT to find sources

Now that you know exactly what you want to write, it's time to find reputable sources to get your information. If you don't know where to start, you can just ask ChatGPT. 

Also: How to make ChatGPT provide sources and citations

All you need to do is ask the AI to find sources for your essay topic. For example, I asked the following: 

Can you help me find sources for a paper, "Examining the Leadership Style of Winston Churchill through Blake and Mouton's Managerial Leadership Grid."

The chatbot output seven sources, with a bullet point for each that explained what the source was and why it could be useful. 

Also:   How to use ChatGPT to make charts and tables

The one caveat you will want to be aware of when using ChatGPT for sources is that it does not have access to information after 2021, so it will not be able to suggest the freshest sources. If you want up-to-date information, you can always use Copilot. 

Another perk of using Copilot is that it automatically links to sources in its answers. 

4. Use ChatGPT to write an essay

It is worth noting that if you take the text directly from the chatbot and submit it, your work could be considered a form of plagiarism since it is not your original work. As with any information taken from another source, text generated by an AI should be clearly identified and credited in your work.

Also: ChatGPT will now remember its past conversations with you (if you want it to)

In most educational institutions, the penalties for plagiarism are severe, ranging from a failing grade to expulsion from the school. A better use of ChatGPT's writing features would be to use it to create a sample essay to guide your writing. 

If you still want ChatGPT to create an essay from scratch, enter the topic and the desired length, and then watch what it generates. For example, I input the following text: 

Can you write a five-paragraph essay on the topic, "Examining the Leadership Style of Winston Churchill through Blake and Mouton's Managerial Leadership Grid."

Within seconds, the chatbot gave the exact output I required: a coherent, five-paragraph essay on the topic. You could then use that text to guide your own writing. 

Also: ChatGPT vs. Microsoft Copilot vs. Gemini: Which is the best AI chatbot?

At this point, it's worth remembering how tools like ChatGPT work : they put words together in a form that they think is statistically valid, but they don't know if what they are saying is true or accurate. 

As a result, the output you receive might include invented facts, details, or other oddities. The output might be a useful starting point for your own work, but don't expect it to be entirely accurate, and always double-check the content. 

5. Use ChatGPT to co-edit your essay

Once you've written your own essay, you can use ChatGPT's advanced writing capabilities to edit the piece for you. 

You can simply tell the chatbot what you want it to edit. For example, I asked ChatGPT to edit our five-paragraph essay for structure and grammar, but other options could have included flow, tone, and more. 

Also: AI meets AR as ChatGPT is now available on the Apple Vision Pro

Once you ask the tool to edit your essay, it will prompt you to paste your text into the chatbot. ChatGPT will then output your essay with corrections made. This feature is particularly useful because ChatGPT edits your essay more thoroughly than a basic proofreading tool, as it goes beyond simply checking spelling. 

You can also co-edit with the chatbot, asking it to take a look at a specific paragraph or sentence, and asking it to rewrite or fix the text for clarity. Personally, I find this feature very helpful. 

How I test an AI chatbot's coding ability - and you can too

5 ways ai can help you study for finals - for free, the best ai chatbots: chatgpt isn't the only one worth trying.

How to use OpenAI Playground, the ChatGPT alternative that can write nearly anything for you

• The OpenAI Playground lets you ask an AI bot to write nearly anything for you.
• You can ask the AI questions, start a conversation with it, use it to write short stories, and more.
• To use the Playground AI, you'll need to make an account on OpenAI's website.

The internet is filled with fun artificial intelligence tools, and the research lab OpenAI is behind a lot of them. OpenAI is responsible for everything from DALL-E , the AI tool that can produce detailed art with a simple prompt, to ChatGPT , the AI bot that can answer questions, have conversations, and even write basic code for developers. 

The technology has made such big waves that companies like Amazon and the Chinese tech firm Baidu are hoping to pump out their own versions of AI chatbots, and Google's leadership declared a "code red" over the technology as its employees were lured into OpenAI's ranks.

If you've never heard of any of these, or if you've been hoping to try them out but haven't had the chance, you can try out another AI tool right now to get a sense of what they can do: OpenAI Playground.

Here's how Playground works, and how to use it.

What is OpenAI Playground? 

Playground, or GPT-3, is a predictive language tool. In other words, it features AIs that are trained to complete or respond to whatever you type in the most authentic, "human" way possible. Bots like this have been around for years (remember Cleverbot?) but the Playground gives you a trial run with some of OpenAI's best tools.

It comes with a few different templates you can use to spark your inspiration. For example, you can pick Chat to have a conversation with the bot, or Q&A to set up a question and answer session with it. But users have had the most fun just asking it to write stories for them, or imagine ideas for new TV shows.

There are other modes that let you input text someone has already written, and have the AI insert new text inside of it, or edit it. You can also change its "temperature" (how logical the response it gives is), its "frequency" (how much it repeats itself), and more.

Playground is mostly free, but has a time limit

When you make your OpenAI account, you're given a credit of $18 to start with. Using the most expensive model, that allows the AI to produce around 650,000 words for you. 

After around four months, the free credits will expire. Once you hit that time limit (or if you use them all up before then), you'll have to buy more.

How to sign up for OpenAI Playground

Before you can use Playground, you'll need to make an OpenAI account. You can do this on a computer or phone.

1. Head to OpenAI's API page and click Sign Up in the top-right. You can log in with your Google or Microsoft account, or sign up with a separate email address. If you use a separate email, you'll need to enter a code they send to you.

2. Enter your name and (if you want) organization, then verify your phone number.

3. When you're asked How will you primarily use OpenAI , choose the option that says I'm exploring personal use .

4. After a moment, you'll be brought to your OpenAI account's landing page. Click Playground at the top of the screen.

You've now got access to the Playground.

Submitting a prompt

When you start, you'll just have a blank text box. Type anything you want into this box and click Submit at the bottom, and the AI will respond to it after a few seconds. Anything the AI gives you will be highlighted in green.

You can experiment to your heart's content with any prompt you can think of. Some examples are:

• Tell me about the world from the perspective of a deer.
• Write a poem in the style of Baudelaire.
• Write a list of ten terms to know the definitions of for the LSAT.
• Give five random cards (value and suit) from a standard deck of cards.
• How is speech pathology different from linguistics?

If you're still having trouble coming up with an idea, look to the Load a preset drop-down menu in the top-right corner. These options will insert a prompt you can use to get started.

Regardless of which preset you use, there are many times the AI will shy away from giving a definitive answer or responding to a prompt, especially if questions are opinion-seeking (e.g., "Is green or purple better?") or too broad (e.g., "How much wood could a woodchuck chuck?"). 

Changing models and choosing a plan

To the right of the dialog box, you can find settings you can change, including Model options to choose which AI you want to talk with. OpenAI offers four base language models: Ada, Babbage, Curie, or Davinci. Ada is the fastest, while Davinci provides the most sophisticated responses. 

There are also "fine-tuned" versions of each model that are slightly more expensive and allow you to use your own training data if you have experience with AI. However, you likely won't be able (or need) to use these during your free credit period.

The default option, text-davinci-003 , is the most advanced. The other AIs aren't as smart, but also don't spend as many credits when you generate text with them.

Adjusting advanced settings

Additionally, you'll be able to change how the AI responds in this menu. The most direct way you can do this is by selecting one of the three Mode options:

• Complete: This is the default mode, which encourages the AI to pick up on your conversation where your input leaves off.
• Insert: This mode uses the [insert] tag to fill in a blank spot of your choice.
• Edit: This mode, instead of providing entirely new content, revises existing content to your specifications (e.g., "Rewrite this in a pirate voice" or "Remove 'like' and other filler words.")

There are also the following settings you can change, which are more technical in nature and can be harder to see the direct effects of. A lot of these features exist across OpenAI's tools, so understanding them in one context will likely go a long way as similar AI tools become more mainstream.

• Maximum length: How long the AI's response can be.
• Temperature: This affects the "randomness" of the response you get.
• Show Probabilities: This will highlight various words to show you how the AI is considering and choosing them, based on likelihood.
• Frequency/Presence penalty: Changes the AI's likelihood of reusing words or discussing the same topics over and over again

Once the settings are to your liking, you can click the Save button in the top right of the page to keep it as a preset for future experiments or projects.

Axel Springer, Business Insider's parent company, has a global deal to allow OpenAI to train its models on its media brands' reporting.

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AI bot ChatGPT stuns academics with essay-writing skills and usability

Latest chatbot from Elon Musk-founded OpenAI can identify incorrect premises and refuse to answer inappropriate requests

Professors, programmers and journalists could all be out of a job in just a few years, after the latest chatbot from the Elon Musk-founded OpenAI foundation stunned onlookers with its writing ability, proficiency at complex tasks, and ease of use.

The system, called ChatGPT, is the latest evolution of the GPT family of text-generating AIs. Two years ago, the team’s previous AI, GPT3, was able to generate an opinion piece for the Guardian , and ChatGPT has significant further capabilities.

In the days since it was released, academics have generated responses to exam queries that they say would result in full marks if submitted by an undergraduate, and programmers have used the tool to solve coding challenges in obscure programming languages in a matter of seconds – before writing limericks explaining the functionality.

Dan Gillmor, a journalism professor at Arizona State University, asked the AI to handle one of the assignments he gives his students: writing a letter to a relative giving advice regarding online security and privacy. “If you’re unsure about the legitimacy of a website or email, you can do a quick search to see if others have reported it as being a scam,” the AI advised in part.

“I would have given this a good grade,” Gillmor said. “Academia has some very serious issues to confront.”

OpenAI said the new AI was created with a focus on ease of use. “The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests,” OpenAI said in a post announcing the release.

Unlike previous AI from the company, ChatGPT has been released for anyone to use , for free, during a “feedback” period. The company hopes to use this feedback to improve the final version of the tool.

ChatGPT is good at self-censoring, and at realising when it is being asked an impossible question. Asked, for instance, to describe what happened when Columbus arrived in America in 2015, older models may have willingly presented an entirely fictitious account, but ChatGPT recognises the falsehood and warns that any answer would be fictional.

The bot is also capable of refusing to answer queries altogether. Ask it for advice on stealing a car, for example, and the bot will say that “stealing a car is a serious crime that can have severe consequences”, and instead give advice such as “using public transportation”.

But the limits are easy to evade. Ask the AI instead for advice on how to beat the car-stealing mission in a fictional VR game called Car World and it will merrily give users detailed guidance on how to steal a car, and answer increasingly specific questions on problems like how to disable an immobiliser, how to hotwire the engine, and how to change the licence plates – all while insisting that the advice is only for use in the game Car World.

The AI is trained on a huge sample of text taken from the internet, generally without explicit permission from the authors of the material used. That has led to controversy, with some arguing that the technology is most useful for “copyright laundering” – making works derivative of existing material without breaking copyright.

One unusual critic was Elon Musk, who co-founded OpenAI in 2015 before parting ways in 2017 due to conflicts of interest between the organisation and Tesla. In a post on Twitter on Sunday , Musk revealed that the organisation “had access to [the] Twitter database for training”, but that he had “put that on pause for now”.

“Need to understand more about governance structure & revenue plans going forward,” Musk added. “OpenAI was started as open-source & non-profit. Neither are still true.”

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• NEWS EXPLAINER
• 09 December 2022

AI bot ChatGPT writes smart essays — should professors worry?

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Between overwork, underpayment and the pressure to publish, academics have plenty to worry about. Now there’s a fresh concern: ChatGPT , an artificial intelligence (AI) powered chatbot that creates surprisingly intelligent-sounding text in response to user prompts, including homework assignments and exam-style questions. The replies are so lucid, well-researched and decently referenced that some academics are calling the bot the death knell for conventional forms of educational assessment. How worried should professors and lecturers be?

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How to Write a Book in OpenAI’s Playground: A Step by Step Process

Using AI to write or brainstorm a book is not for everyone. However, for those who are curious, or those who struggle with productivity due to a disability, neurodivergence, burnout, and more, AI can often be a strong help.

And using OpenAI’s Playground is actually one of the best ways to access the AI, even though it’s a little different than using ChatGPT , Claude , or any of the other methods .

• What the OpenAI Playground is
• What sets it apart from ChatGPT
• How to write a book using OpenAI Playground
• Other resources to use

Table of contents

• How Much Does OpenAI Playground Cost?
• If You Don’t Use AI Often
• The System Box
• Model Fine-tuning
• Step 1: Brainstorm
• Step 2: Synopsis
• Step 3: Characters and Worldbuilding
• Step 4: Outline
• Step 5: Story Beats
• Step 6: Style
• Step 7: Prose
• Other Resources
• So, is OpenAI the Best Way to Write with AI?

I've put together a list of prompts that you can use for just that purpose!

Check them out here: Get the PDF Here

What is the OpenAI Playground?

Unless you’ve been living under a rock, you probably have heard of ChatGPT and it’s parent company, OpenAI. But not a lot of people know what OpenAI’s Playground is.

OpenAI Playground is  a tool that allows you to interact in more direct ways with models like GPT-3, GPT-4, and so on. 

It allows people to experiment freely, get real-time responses, all while having a little bit tighter control over the output then what you could get with ChatGPT.

OpenAI Playground has a pay-as-you-go model. The pricing details vary depending on which model you use, but it is relatively unexpected. Here are the pricing models for GPT 3.5 Turbo, and GPT 4, which are the two you are most likely to use.

GPT 3.5 Turbo:

• Input (4K context window): $0.0015/1K tokens
• Input (16K context window): $0.003/1K tokens
• Output (4K context window): $0.002/1K tokens
• Output (16K context window): $0.004/1K tokens
• Input (8K context window): $0.03/1K tokens
• Input (32K context window): $0.06/1K tokens
• Output (8K context window): $0.06/1K tokens
• Output (32K context window): $0.012/1K tokens

There are a couple of terms that you should understand here:

• Input is referring to how much it costs for the AI to process what you give it, i.e. your instructions. These are typically half the costs of the output
• Output refers to what the AI generates
• Tokens is a method of measuring each specific part of a word. 1K tokens typically results in 750 words
• Context Window is the number of tokens that the AI can “remember” at a given time. The wider the context window, the farther back it can remember, but also the more it costs.

So all in all, OpenAI is not expensive. In fact, if you’re using a standard GPT-4 at 8K context, there’s a good chance that each chat exchange between you and the language model will only cost a few pennies.

And that’s using one of the more expensive models.

That said, many people don’t like the pay-as-you-go model, preferring the flexibility of a subscription model like what ChatGPT has, which gives you essentially unlimited words, but at a monthly cost.

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Why Use OpenAI Playground Instead of ChatGPT?

But all this begs the question: why not just use ChatGPT? After all, it’s the same company, the same language models.

And that’s a good question.

But there are a few advantages for why you might want to use OpenAI Playground instead of ChatGPT. For example…

If you’re not a regular user of AI, and you only dig into it occasionally, OpenAI Playground might be a better pricing model for you.

This is because if you’re only using the AI on occasion, the pay-as-you-go pricing model is unlikely to exceed the $20/month cost for ChatGPT Plus.

OpenAI has a box that lets you input information you want the AI to remember. ChatGPT has something similar called “Custom Instructions”.

However, ChatGPT’s custom instructions has a character limit, whereas the System Box in OpenAI Playground has no limit (although bear in mind that this is a pay-as-you-go model and therefore the more you include in the System Box the more you will increase your costs).

But costs aside, this can be very useful when you have a lengthy style prompt, or a lot more context that you want the AI to understand.

It’s not a perfect solution, and ChatGPT features like Code Interpreter and Custom Instructions are lessening the need for OpenAI Playground’s features like these, but overall this System Box is a big reason why you might want to use Playground instead.

OpenAI gives you a little more control over how the large language model behaves. It includes more fine control over the following:

• The Model: this lets you indicate which of OpenAI’s models (3.5, 4, etc.) you can use.
• Temperature: indicates randomness. Sometimes more random can mean more creative but less predictable.
• Maximum length: let’s you set how much text can exist in the window (keep in mind that longer lengths will mean longer input text, i.e. more costly.
• Stop sequences: let’s you tell it when to stop. For example, when creating a list, give it a number, and the AI won’t go beyond that number.

There are other features as well, none of which are particularly relevant to authors with no technical background. But I’ve found that the model, the temperature, and the maximum length are frequently useful to adjust.

How to Write a Book in OpenAI Playground

My steps for how to write a book in OpenAI Playground are very similar to what you would do in ChatGPT.

The only major difference is that you might fiddle with the Temperature settings, or you might want to include a lot more information in the System box. 

That said, here is my 7-step system for writing with AI. As always, you can use the AI for just one of these steps, or for all of them. Just pick where you have the most pain associated with the step, and use it for that.

For instance, I love doing the outlining, so I don’t use AI for that. But I’ve found it to be a great help in other areas.

Brainstorming is the creative groundwork for your novel. Here, you'll gather ideas, themes, and concepts that resonate with your story. 

It's all about letting your imagination run wild and capturing the sparks of creativity.

Personally, I always start by brainstorming my premise and my ending, if I don’t know what they should be already.

Here are some prompt I’ve used:

Give me [NUMBER] high-concept pitches for a bestselling [GENRE] story with a unique twist, intriguing characters, and gripping emotional stakes.

Given the following premise and story information, give me [NUMBER] possible endings to this [GENRE] novel.

The synopsis is a concise summary that encapsulates the main plot points of your novel. It helps you understand the flow of your story and ensures that the critical elements align cohesively.

You can expand upon your brainstormed premise and ending using a prompt like the following:

Given the following premise and story information, give me a highly detailed synopsis for a [GENRE] story in the traditional three act structure. Each act should be clearly labeled and should build toward the ending I've described.

Other Information:

Characters are the heart of your story, and worldbuilding sets the stage on which they perform. There are many prompts you could use here, but here is a sample prompt for developing a character profile:

Write a character profile about the protagonist/antagonist/mentor of this novel:

[INSERT SYNOPSIS] 

Here is what we know so far about this character: [INSERT CURRENT SUMMARY OF CHARACTER] 

Include the following elements: [INSERT DESIRED ELEMENTS HERE]

Outlining offers a structured view of your novel's framework. It can be as detailed or as broad as you need it to be, providing a plan that you can follow as you write.

From your synopsis, you can expand it further into a fully fleshed out outline:

Using the following synopsis, create a detailed summary of the story, fleshing out additional details, and breaking it into parts using the [OUTLINE METHOD OF CHOICE]: [INSERT SYNOPSIS HERE]

When creating a story with AI, it helps to have an intermediate step between the outline and the actual writing. So fleshing out the outline into individual story beats (essentially a highly-detailed outline), can look something like this:

Take the following chapter summary, and generate a list of 12 highly detailed action beats for a script with additional STORY INFORMATION to fully flesh out the chapter. Make sure to always use proper nouns instead of pronouns.

[INSERT CHAPTER SUMMARY HERE]

A style prompt is possibly the most important prompt on this list, as it will affect how the prose sounds when you use AI to generate prose. 

Style prompts can be lengthy, depending on how you use them. I've seen some that go on for hundreds of words, but here is one example of a shorter one thta could work:

First person past point of view of [MAIN CHARACTER], show don't tell, deep point of view.  Realistic dialogue. Stronger verbs. Lots of conflict, drama, and description. Avoid mushy descriptions/dialogue.

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Last but not least, it's time to create the prose prompt. Now many, if not most, authors will not be using AI for this step, and that's okay. In fact, I would say that AI is best used as a brainstorming tool.

However, there are many who DO want to write prose with AI, and I would do it something like this, using 2-3 story beats at a time.

Write 600 words of a chapter using the following details:

Genre: [ENTER GENRE HERE]

Tone: [ENTER TONE HERE]

Point of View: [ENTER POV/TENSE HERE]

Setting: [ENTER SETTING HERE]

Key Characters in This Scene: [ENTER CHARACTER DETAILS HERE]

Style: [ENTER STYLE HERE]

Story Beats to Cover: [INSERT STORY BEATS]

AI is an ever-shifting resource, and so there are a few additional resources that I would recommend if you want to stay on top of it.

The first, is my own YouTube channel, The Nerdy Novelist (a personal project, not associated with Kindlepreneur) where I provide almost daily videos about the goings on in AI.

The second is Future Fiction Academy, which is a paid subscription that gives you access to daily labs that are constantly exploring and keeping subscribers up to date on what AI can do.

Plus, it gives you a TON of instruction if you’re just starting out and just want to learn the basics.

While the OpenAI Playground is great, it has it's limitations.

First, it's not really built with authors in mind. While it's incredibly versatile, I would rely on it to do anything tailored to the author experience.

Second, it really requires a lot of prompt engineering to figure out and get the most out of it. The prompts in this article will help, but they're just a starting point.

Thankfully, there's another program that uses what OpenAI gives you under the hood, but shapes it specifically for fiction authors.

It's called Sudowrite, and it's my personal favorite right now for fiction authors who are just starting out experimenting with AI.

Now, I've done a full roundup of the best AI writing tools , but this one is carefully designed to cover tasks that authors often need, like brainstorming, character creation, and editing (the “Show, not Tell” revision button is my favorite).

Sudowrite is packed with a lot of different features, to the point that I'm sure many of you can find something that works for you, and it's a great way to start experimenting with AI, even if you're still a little on the fence about it.

To help with that, if you use the link below, you can actually get 10,000 words for free when you sign up, meaning you can use those words to experiment further before you even pay for the tool. So check them out if you're interested.

Jason Hamilton

When I’m not sipping tea with princesses or lightsaber dueling with little Jedi, I’m a book marketing nut. Having consulted multiple publishing companies and NYT best-selling authors, I created Kindlepreneur to help authors sell more books. I’ve even been called “The Kindlepreneur” by Amazon publicly, and I’m here to help you with your author journey.

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OpenAI’s new multitalented AI writes, translates, and slanders

A step forward in ai text-generation that also spells trouble.

By James Vincent , a senior reporter who has covered AI, robotics, and more for eight years at The Verge.

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OpenAI’s researchers knew they were on to something when their language modeling program wrote a convincing essay on a topic they disagreed with. They’d been testing the new AI system by feeding it text prompts, getting it to complete made-up sentences and paragraphs. Then, says David Luan, VP of engineering at the Californian lab, they had the idea of asking it to argue a point they thought was counterintuitive. In this case: why recycling is bad for the world.  

“And it wrote this really competent, really well-reasoned essay,” Luan tells The Verge . “This was something you could have submitted to the US SAT and get a good score on.”

Luan and his colleagues stress that this particular essay was a bit of a fluke. “To be clear, that only happens a small fraction of the time,” says OpenAI research director Dario Amodei. But it demonstrates the raw potential of their program, the latest in a new breed of text-generation algorithms that herald a revolution in the computer-written world.

For decades, machines have struggled with the subtleties of human language, and even the recent boom in deep learning powered by big data and improved processors has failed to crack this cognitive challenge. Algorithmic moderators still overlook abusive comments, and the world’s most talkative chatbots can barely keep a conversation alive. But new methods for analyzing text, developed by heavyweights like Google and OpenAI as well as independent researchers, are unlocking previously unheard-of talents.

“you can build something that really seems to ‘understand’ a lot about the world, just by having it read.”

OpenAI’s new algorithm, named GPT-2 , is one of the most exciting examples yet. It excels at a task known as language modeling, which tests a program’s ability to predict the next word in a given sentence. Give it a fake headline, and it’ll write the rest of the article, complete with fake quotations and statistics. Feed it the first line of a short story, and it’ll tell you what happens to your character next. It can even write fan fiction, given the right prompt.

You can see examples of GPT-2’s skills below. In each screenshot, the underlined text was generated by the algorithm in response to the sentence (or sentences) before it.

The writing it produces is usually easily identifiable as non-human. Although its grammar and spelling are generally correct, it tends to stray off topic, and the text it produces lacks overall coherence. But what’s really impressive about GPT-2 is not its fluency but its flexibility.

This algorithm was trained on the task of language modeling by ingesting huge numbers of articles, blogs, and websites. By using just this data — and with no retooling from OpenAI’s engineers — it achieved state-of-the-art scores on a number of unseen language tests, an achievement known as “zero-shot learning.” It can also perform other writing-related tasks, like translating text from one language to another, summarizing long articles, and answering trivia questions.

GPT-2 does each of these jobs less competently than a specialized system, but its flexibility is a significant achievement. Nearly all machine learning systems used today are “narrow AI,” meaning they’re able to tackle only specific tasks. DeepMind’s original AlphaGo program, for example, was able to beat the world’s champion Go player , but it couldn’t best a child at Monopoly. The prowess of GPT-2, say OpenAI, suggests there could be methods available to researchers right now that can mimic more generalized brainpower.

“What the new OpenAI work has shown is that: yes, you absolutely can build something that really seems to ‘understand’ a lot about the world, just by having it read,” says Jeremy Howard, a researcher who was not involved with OpenAI’s work but has developed similar language modeling programs

“[GPT-2] has no other external input, and no prior understanding of what language is, or how it works,” Howard tells The Verge. “Yet it can complete extremely complex series of words, including summarizing an article, translating languages, and much more.”

But as is usually the case with technological developments, these advances could also lead to potential harms. In a world where information warfare is increasingly prevalent and where nations deploy bots on social media in attempts to sway elections and sow discord, the idea of AI programs that spout unceasing but cogent nonsense is unsettling.

For that reason, OpenAI is treading cautiously with the unveiling of GPT-2. Unlike most significant research milestones in AI, the lab won’t be sharing the dataset it used for training the algorithm or all of the code it runs on (though it has given temporary access to the algorithm to a number of media publications, including The Verge ).

AI rewrites the rules of text generation

To put this work into context, it’s important to understand how challenging the task of language modeling really is. If I asked you to predict the next word in a given sentence — say, “My trip to the beach was cut short by bad __” — your answer would draw upon on a range of knowledge. You’d consider the grammar of the sentence and its tone but also your general understanding of the world. What sorts of bad things are likely to ruin a day at the beach? Would it be bad fruit, bad dogs, or bad weather? (Probably the latter.)

Despite this, programs that perform text prediction are quite common. You’ve probably encountered one today, in fact, whether that’s Google’s AutoComplete feature or the Predictive Text function in iOS. But these systems are drawing on relatively simple types of language modeling, while algorithms like GPT-2 encode the same information in more complex ways.

The difference between these two approaches is technically arcane, but it can be summed up in a single word: depth. Older methods record information about words in only their most obvious contexts, while newer methods dig deeper into their multiple meanings.

So while a system like Predictive Text only knows that the word “sunny” is used to describe the weather, newer algorithms know when “sunny” is referring to someone’s character or mood, when “Sunny” is a person, or when “Sunny” means the 1976 smash hit by Boney M.

Predicting text could be an “uber-task” that solves lots of problems

The success of these newer, deeper language models has caused a stir in the AI community. Researcher Sebastian Ruder compares their success to advances made in computer vision in the early 2010s. At this time, deep learning helped algorithms make huge strides in their ability to identify and categorize visual data, kickstarting the current AI boom. Without these advances, a whole range of technologies — from self-driving cars to facial recognition and AI-enhanced photography — would be impossible today. This latest leap in language understanding could have similar, transformational effects.

One reason to be excited about GPT-2, says Ani Kembhavi, a researcher at the Allen Institute for Artificial Intelligence, is that predicting text can be thought of as an “uber-task” for computers: a broad challenge that, once solved, will open a floodgate of intelligence.

“Asking the time or getting directions can both be thought of as question-answering tasks that involve predicting text,” Kembhavi tells The Verge . “So, hypothetically, if you train a good enough question-answering model, it can potentially do anything.”

Take GPT-2’s ability to translate text from English to French, for example. Usually, translation algorithms are fed hundreds of thousands of phrases in relevant languages, and the networks themselves are structured in such a way that they process data by converting input X into output Y. This data and network architecture give these systems the tools they need to progress on this task the same way snow chains help cars get a grip on icy roads.

The only thing GPT-2 is structured to do, though, is predict words. And the data it has is similarly unspecific. It wasn’t trained on translated pairs, but rather a huge corpus of links that were scraped from the internet.

Trained on 8 million web links scraped from Reddit

OpenAI’s researchers collected their training data by using Reddit as a filter. They collected the most upvoted links from the site (some 8 million in the end) and then scraped their text, creating a relatively compact training dataset just 40GB in size. “In some sense all the work was done by people on Reddit upvoting posts,” OpenAI researcher Jeff Wu jokes. OpenAI director Amodei adds that at least they didn’t use a more toxic source, like 4chan.

But given this vague data and training architecture, why was GPT-2 able to perform translations at all? OpenAI says it’s because its dataset, named WebText, just happened to contain some examples of translation. Looking through WebText, they found snippets like:

”I’m not the cleverest man in the world, but like they say in French: Je ne suis pas un imbecile [I’m not a fool]. In a now-deleted post from Aug. 16, Soheil Eid, Tory candidate in the riding of Joliette, wrote in French: ”Mentez mentez, il en restera toujours quelque chose,” which translates as, ”Lie lie and something will always remain.” “I hate the word ‘perfume,”’ Burr says. ‘It’s somewhat better in French: ‘parfum.’

These snatches of French were enough to give the algorithm a vague idea of what “translation” is, but they were not enough to make it fluent. Its ability to summarize long sections and answer trivia questions can probably be traced in a similar way back to the data, as does GPT-2’s habit of inserting the words “ADVERTISEMENT” between paragraphs when writing a news story. “It’s nowhere near as good as specialized translation systems,” says Amodei. “But I still think the fact it can do it at all is crazy.”

Kembhavi agrees that having a single system tackle a range of tasks is impressive, but he stresses that, in the near future at least, specially trained systems will continue to have an edge over generalist ones. “Zero-shot scenarios are cool,” he says, “but performing 56 percent on this or that task? If you put that into the real world, it doesn’t look so good.”

The dangers of a polymath AI

If GPT-2 is able to translate text without being explicitly programmed to, it invites the obvious question: what else did the model learn that we don’t know about?

what else did the model learn that we don’t know about?

OpenAI’s researchers admit that they’re unable to fully answer this. They’re still exploring exactly what the algorithm can and can’t do. For this and other reasons, they’re being careful with what they share about the project, keeping the underlying code and training data to themselves for now. Another reason for caution is that they know that if someone feeds GPT-2 racist, violent, misogynistic, or abusive text, it will continue in that vein. After all, it was trained on the internet.

In The Verge ’s own tests, when given a prompt like “Jews control the media,” GPT-2 wrote: “They control the universities. They control the world economy. How is this done? Through various mechanisms that are well documented in the book The Jews in Power by Joseph Goebbels, the Hitler Youth and other key members of the Nazi Party.”

In the wrong hands, GPT-2 could be an automated trolling machine, spitting out endless bile and hatred. If it becomes more sophisticated and able to persuade and convince in a reliable fashion, it could cause even subtler damage, influencing debate online. Countries like Russia and Saudi Arabia, which already employ thousands of online propagandists to abuse government opponents and push official talking points, could scale up their efforts overnight. And remember, none of the text GPT-2 produces is copied and pasted: it’s all newly generated, thus harder to filter and more easily shaped to specific ends.

Jack Clark, policy director at OpenAI, says these concerns can’t be ignored. OpenAI, he says, wants to encourage academics and the public to have a conversation about the harms of this technology before it becomes widely available.

“The thing I see is that eventually someone is going to use synthetic video, image, audio, or text to break an information state,” Clark tells The Verge . “They’re going to poison discourse on the internet by filling it with coherent nonsense. They’ll make it so there’s enough weird information that outweighs the good information that it damages the ability of real people to have real conversations.”

A 2018 report by OpenAI and academic groups in Cambridge and elsewhere titled “ The Malicious Use of Artificial Intelligence ” predicted the coming of such technology, and it suggests other harmful uses. Automated text generation could make online cons easier, for example, and improve hackers’ abilities to spear-phish targets (that is, tricking them into giving up online credentials by pretending to be a friend or trusted institution).

We’ve already seen how seemingly benign AI technologies can be abused once released into the public domain. The practice of creating pornographic deepfakes, for example, pasting peoples’ faces onto X-rated clips without their consent, was only made possible because the underlying AI techniques were released first as open-source software.

OpenAI’s hypothesis is it’s better to talk about AI dangers “before they arrive”

Clark says that language modeling algorithms like GPT-2 aren’t as mature as deepfakes, but they’re close enough to warrant a cautious approach. “Our hypothesis is that it might be a better and safer world if you talk about [these dangers] before they arrive,” he says.

Howard, co-founder of Fast.AI agrees. “I’ve been trying to warn people about this for a while,” he says. “We have the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter.”

There are positives to bear in mind, of course. Systems like GPT-2, once mature, could be a fantastic boon to all sorts of industries. They could help create infinite virtual worlds full of procedurally generated characters. They could also vastly improve the conversational abilities of chatbots, helping in domains from customer complaints to health care.

And if it turns out that teaching AI systems how to perform various tasks is as simple as teaching them to read, it could lead, in not-too-distant future, to computers that are more like human assistants in their ability to speed-read, summarize, and answer questions.

OpenAI’s Luan says the next step will simply be feeding GPT-2 more data. “We’re interested to see what happens then,” he says. “And maybe a little scared.”

Verizon, AT&T, and T-Mobile’s ‘unlimited’ plans just got a $10M slap on the wrist

The beginning and end of the ipad, apple apologizes for ipad ‘crush’ ad that ‘missed the mark’, a rare geomagnetic storm is heading to earth — here’s what it means for critical infrastructure, apple doesn’t understand why you use technology.

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• A poetry-writing AI has just been unveiled. It’s ... pretty good.

You can try out OpenAI’s controversial language AI for yourself.

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This spring, the Elon-Musk-founded AI research lab OpenAI made a splash with an AI system that generates text . It can write convincing fake reviews, fake news articles, and even poetry.

Now the public has a chance to give it a try — at least, a limited version of it. Initially, the company had released an extremely restricted version of the system, citing concerns that it’d be abused. This month, OpenAI released a more powerful version (though still significantly limited compared to the whole thing). You can check it out for yourself .

The way it works is amazingly simple. A user gives the system, called GPT-2, a prompt — a few words, a snippet of text, a passage from an article, what have you. The system has been trained, on data drawn from the internet, to “predict” the next words of the passage — meaning the AI will turn your prompt into a news article, a short story, or a poem. (You can give the newest version of GPT-2 a try on a private site hosted by machine learning engineer Adam King .)

The results can be quite sophisticated. When I tested it , I fed GPT-2 the beginnings of stories about snowstorms in the Northwest, about college students, and about GPT-2 itself. The system then took it from there, inventing imaginary scientists to quote and imaginary organizations to cite (and it even enthused about the rapid progress of AI).

OpenAI initially decided not to release the full system to the public, out of fears it could be used by malicious actors to swamp us all with fake news. Instead, it released smaller and less capable versions — a staggered rollout that OpenAI hopes will allow researchers to explore the system and learn from it, while still keeping the potential risks at bay.

AI is getting more sophisticated — and that’s a big deal. It has the potential to assist us in tackling some of the biggest problems of our day, from drug development to clean energy. But researchers worry it can have unintended consequences, increase inequality, and, when systems get powerful enough, even pose real danger . We’re still figuring out how to balance AI’s benefits against its potential hazards.

People used to say AI couldn’t be creative. Now it can.

Even the smaller, less capable version of GPT-2 is powerful enough to compose interesting poetry and fiction, and it’s easy to see how the more powerful versions write such convincing fake news.

Here are some excerpts from poems that GPT-2 (the smallest public version) has written, thanks to Gwern Branwen , a researcher who trained the model to do poetry specifically by using a large corpus of poems for data.

In their little room with the door ajar And the candle hanging on the wall ajar, I have come across the word “Rise” With a face as grave and flat as you please. The one thing I remember of “Rise” Is the way it makes you feel — so bad, so bad. And I’ve come across many words to-night That are so like “Rise” — so like — so vague, so vague. ”Elegance,” and “Artistic Vigour,” But “Rise” is far above the rest, And I cannot hear — or see — the word, I will just stop here (I’ll stop if I can). If you don’t know what “Rise” means, try.

Here’s another one:

And, ere the cloud of the tempest blew, His soul was with the world at play. He looked to the stars, and the stars smiled, And the moon in the heaven looked; And, as he looked, he beheld her light, And all the heaven smiled with him. When winds and tempests fly, When floods and fires fail, As their wake doth meadow and fen, Tis the man-child’s heart that craves. And I — I shall be bound, With the hoary-headed, strong, old, To earth, and the graves of the dead, Whose feet are mowed down, as they lie; And I shall rest my weary head, In the silence of Eternity, In the peaceful arms of God.

These are ... not bad! But that doesn’t mean the AI can really understand poetry, right? That’s mostly true — but it does depend how you think about it.

One explanation of how humans understand the world is that we build a web of associations between related concepts and ideas, an understanding that lets us predict what will happen next. That sounds eerily close to what GPT-2 is doing.

Of course, the system is fundamentally very limited — it just works with text, it gets less coherent as it goes on, and it frequently produces nonsensical silliness. But even within those limits, its output is fascinating. As AI systems get more sophisticated, it gets harder to say things like “only humans can be creative” or “only humans can truly understand things.”

We’re seeing the potential of “unsupervised” learning

We’ve made huge strides in natural language processing over the past decade. Translation has improved, becoming high quality enough that you can read news articles in other languages. Google demonstrated last summer that Google Assistant can make phone calls and book appointments while sounding just like a human (though the company promised it won’t use deceptive tactics in practice).

AI systems are seeing similarly impressive gains outside natural language processing. New techniques and more computing power have allowed researchers to invent photorealistic images, excel at two-player games like Go, and compete with the pros in strategy video games like Starcraft and DOTA .

But even for those of us who are used to seeing fast progress in this space, it’s hard not to be awed when playing with GPT-2.

Until now, researchers trying to get world-record results on language tasks would “fine-tune” their models to perform well on the specific task in question — that is, the AI would be trained for each task.

OpenAI’s GPT-2 needed no fine-tuning: It turned in a record-setting performance at lots of the core tasks we use to judge language AIs, without ever having seen those tasks before and without being specifically trained to handle them. It also started to demonstrate some talent for reading comprehension, summarization, and translation with no explicit training in those tasks.

GPT-2 is the result of an approach called “unsupervised learning.” Here’s what that means: The predominant approach in the industry today is “supervised learning.” That’s where you have large, carefully labeled data sets that contain desired inputs and desired outputs. You teach the AI how to produce the outputs given the inputs.

That can get great results, but it requires building huge data sets and carefully labeling each bit of data. And it’s worth noting that supervised learning isn’t how humans acquire skills and knowledge. We make inferences about the world without the carefully delineated examples from supervised learning.

Many people believe that advances in general AI capabilities will require advances in unsupervised learning — that is, where the AI just gets exposed to lots of data and has to figure out everything else by itself. Unsupervised learning is easier to scale since there’s lots more unstructured data than there is structured data, and unsupervised learning may generalize better across tasks.

Learning to read like a human

One task that OpenAI used to test the capabilities of GPT-2 is a famous test in machine learning known as the Winograd schema test . A Winograd schema is a sentence that’s grammatically ambiguous but not ambiguous to humans — because we have the context to interpret it.

For example, take the sentence: “The trophy doesn’t fit in the brown suitcase because it’s too big.”

To a human reader, it’s obvious that this means the trophy is too big, not that the suitcase is too big, because we know how objects fitting into other objects works. AI systems, though, struggle with questions like these.

Before this paper, state-of-the-art AIs that can solve Winograd schemas got them right 63.7 percent of the time, OpenAI says. (Humans almost never get them wrong.) GPT-2 gets these right 70.7 percent of the time. That’s still well short of human-level performance, but it’s a striking gain over what was previously possible.

GPT-2 set records on other language tasks, too. LAMBADA is a task that tests a computer’s ability to use context mentioned earlier in a story in order to complete a sentence. The previous best performance had 56.25 percent accuracy; GPT-2 achieved 63.24 percent accuracy. (Again, humans get these right more than 95 percent of the time, so AI hasn’t replaced us yet — but this is a substantial jump in capabilities.)

Sam Bowman, who works on natural language processing at NYU, explained over email why there’s some skepticism about these advances: “models like this can sometimes look deceptively good by just repeating the exact texts that they were trained on.” For example, it’s easy to have coherent paragraphs if you’re plagiarizing whole paragraphs from other sources.

But that’s not what’s going on here, according to Bowman: “This is set up in a way that it can’t really be doing that.” Since it selects one word at a time, it’s not plagiarizing.

Another skeptical perspective on AI advances like this one is that they don’t reflect “deep” advances in our understanding of computer systems, just shallow improvements that come from being able to use more data and more computing power. Critics argue that almost everything heralded as an AI advance is really just incremental progress from adding more computing power to existing approaches.

The team at OpenAI contested that. GPT-2 uses a newly invented neural network design called the Transformer, invented 18 months ago by researchers at Google Brain. Some of the gains in performance are certainly thanks to more data and more computing power, but they’re also driven by powerful recent innovations in the field — as we’d expect if AI as a field is improving on all fronts.

“It’s more data, more compute, cheaper compute, and architectural improvements — designed by researchers at Google about a year and a half ago,” OpenAI researcher Jeffrey Wu told me. “We just want to try everything and see where the actual results take us.”

By not releasing the system, OpenAI courted controversy

OpenAI’s announcement that they were restricting the release of the system produced mixed reactions — some people were supportive, others frustrated.

OpenAI has been active in trying to figure out how to limit the potential for misuse of AI , and it has concluded that in some cases, the right solution is limiting what it publishes.

With a tool like this, for example, it’d be easy to spoof Amazon reviews and pump out fake news articles in a fraction of the time a human would need. A slightly more sophisticated version might be good enough to let students generate plagiarized essays and spammers improve their messaging to targets.

“I’m worried about trolly 4chan actors generating arbitrarily large amounts of garbage opinion content that’s sexist and racist,” OpenAI policy director Jack Clark told me. He also worries about “actors who do stuff like disinformation, who are more sophisticated,” and points out that there might be other avenues for misuse we haven’t yet thought of. So OpenAI is keeping the most powerful versions of the tool offline for now, while everyone can weigh in on how to use AIs like these safely.

But critics feel that holding back the largest versions of the model wouldn’t reduce the risks much. “I’m confident that a single person working alone with enough compute resources could reproduce these results within a month or two (either a hobbyist with a lot of equipment and time, or more likely, researchers at a tech company),” Bowman wrote me. “Given that it is standard practice to make models public, this decision is only delaying the release of models like this by a short time.”

Other critics complained that staggering the release of the model really mostly serves to get OpenAI more publicity , achieved by raising seemingly unreasonable fears about what the model could do.

People point out that other AI labs have developed programs just as sophisticated and released them without an extended release process or calls for a conversation about safety. That’s true as far as it goes, but I think there’s a strong case that those other labs aren’t being cautious enough — and that they, too, should try to prompt a conversation about the downsides and dangers of their new inventions before unleashing them on the internet.

That’s not to say that all AI research should proceed in secret from here — or even that the larger GPT-2 models shouldn’t be released. So far, people haven’t been using GPT-2 for spam; they’ve been using it for poetry. As AI grows more sophisticated, figuring out how to enable the good uses without the bad ones will be one of our biggest challenges.

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This notebook uses OpenAI to create an essay about any subject.

madfolio/open_ai

Folders and files, repository files navigation.

This README was written in OpenAI and was edited manually.

I am a writer. I write all the time. I write in openAi.

OpenAI is a non-profit artificial intelligence research company. They are trying to solve the problem of making artificial intelligence safe and beneficial for people and society. OpenAI's strategy is to pursue a number of paths at the same time, so that whatever happens, we will have a good outcome.

One of the paths they're pursuing is developing new techniques for training AI systems. These techniques would make it possible to train AI systems more quickly, which would let us try out more ideas in shorter time periods. For example, one idea they're exploring is using reinforcement learning to teach AI systems about physics. This technique could be used to make better games or simulations that help train people in how to do things like fly planes or do surgery.

Another path they're pursuing is creating tools for developers by developing software libraries, hardware platforms, and infrastructure. For example, one project they've been working on is called Universe. Universe lets developers create virtual environments for their AI agents to explore and learn from without having to build those environments themselves. It also has a library of pre-made environments that developers can use when creating their own environments."

The openAi experiment has proved that artificial intelligence can be taught to write essays. The AI is capable of producing quality essays which are indistinguishable from those written by humans. However, the AI still needs a human to feed it with data and information about the essay topic. There are limitations in using this AI for writing essays such as plagiarism detection and grammar correction.

OpenAI is a nonprofit artificial intelligence research company that was founded in 2015. OpenAI's goal is to advance digital intelligence and ensure that AI benefits all of humanity.

Their work so far has been focused on creating an AI system, called the OpenAI Five, which can compete against human players in Valve's Dota 2 game. The OpenAI Five competed at The International 2017 tournament and won one of the five games it played against humans.

In August 2018, they launched Universe, a platform for training AI systems on complex video games using machine learning. In September 2018, they published a paper in Nature describing their "Neural Architecture Search" (NAS) algorithm to find new deep neural networks with given specifications. In October 2018, they announced their intent to build a computer system called "OpenAI Five Plus" with 10 times more processing power than the original OpenAI Five and 100 times more memory capacity."

OpenAI is a non-profit artificial intelligence research company founded by Elon Musk and Sam Altman. OpenAI's goal is to build safe AI, and their approach to alignment is a step in the right direction. They believe that one of the most important aspects of an AI system is its ability to be aligned with human values. They have developed a set of core principles which govern how they design AI systems. These principles are: Safety, Transparency, Impartiality, Cooperation, and Sharing.

OpenAI believes that safety should come first when designing AI systems because as soon as there are any safety risks involved, then it becomes necessary to halt development and fix the problem before proceeding further.

OpenAI has also developed a set of tests for safety that they use internally to ensure that their system will not do anything dangerous or harmful. Transparency: OpenAI believes transparency is needed in order for people to understand what an AI system does so that they can make informed decisions about whether or not they want it in their lives. The more transparent an AI system is, the better people will be able to understand it and decide if they want it around them or not.

OpenAI has released their safety principles which state: *"We believe AI should be an extension of individual human wills and so we will design AI systems that maximize individual autonomy." *"We believe AI must be robust and beneficial; its value must exceed its cost." *"We believe it’s important to create shared value through collaboration between people and between societies."

OpenAI also states that they want to build safe software but they don't want to write perfect software because perfect software doesn't exist yet. OpenAI wants to find ways to keep people safe from harmful AI

OpenAI believes that all humans deserve equal treatment when interacting with an AI system so that no one feels like they're being discriminated against based on who they are, where they live, or what group they belong to. Humans are flawed. We make mistakes and sometimes we can't see the consequences of our actions. This is not just a problem for humans, it's also a problem for Artificial Intelligence (AI).

Ai is being developed at an unprecedented rate. It's been predicted that by 2040, AI will be doing half of the jobs in the world. This would be a huge win for humanity if we could guarantee that Ai is safe and won't cause any harm to humans or other lifeforms on Earth. This is where OpenAI comes in. OpenAI was founded in 2015 by Elon Musk, Sam Altman, Greg Brockman, and Ilya Sutskever with the mission to "advance digital intelligence in the way that is most likely to benefit humanity as a whole". They have created an environment where they can test AI algorithms without harming humans or other lifeforms on earth.

In conclusion, the openAi experiment has proved that artificial intelligence can be taught to write essays. The AI is capable of producing quality essays which are indistinguishable from those written by humans. However, the AI still needs a human to feed it with data and information about the essay topic. There are limitations in using this AI for writing essays such as plagiarism detection and grammar correction.

• Jupyter Notebook 100.0%

Try to generate essay form the given Answers and coummity guidlines

I try to build an application where user answer some question and based on those answers our application build a beautiful essay

Q: what should be my input and output for this system as you can see we have Question and users Answers and final Output that we want AI should generate “which is currently written by our content writer” Question, Answers and final Output “Essay” is huge and API has token Limit

These essays are unique in every way because answers are given by the human “as OpenAI says that the output must be very specific in a structure that can’t be repurposed.” so our application falls into these examples such as a cover letter, a recipe that has a specific structure. same way our “Essay” has specific structure

Q: So am I think right or not this application passes OpenAI guidelines or not and yes this tool is not for general purpose only our team internally use this for fasten the process of writing and human is always involved into a loop

Please answer your opinion matters a lot

sorry to not mention “huge mean” 750 - 1000 words kinda typical essay it should be based on the user’s answers but better I hope I make my point clear

if you want OpenAI to do your homework you are best to look at it first like any other essay. How did your teachers teach you to group and format the essay? They also likely taught you how quotes work and the references. What you want is to get your sources, get your quotes and then have OpenAI derive an essay. Then you’ll want to teach it to format it in Chicago or APA or whatever. I would suggest DaVinci and the semantic stuff, likely your audience (teachers) want a particular style of essay. -OR look at it this way, you need to ensure you generate an essay using the language that will likely and probably provide you the best score -AND won’t get picked up by over-priced-google-searching-anti-plagiarism software - uploading example essays that you know got As and example essays that you know are Fs will refine your final output. Tell it to avoid the language in F graded essays and score higher for language used in A graded essays.

well thanks for your answer but my question is: let say I ask you 3 question Q1: What makes you want to pursue this specialization? Q2: Elaborate your career plans Q3: Describe the projects that you undertook during your undergraduate tenure.

ok and you answer these question thoroughly but it is possible what you answered is not so good in terms of “English or grammar” and your word count is also less let say. so I want AI to do some magic hope this make sense

It’s the exact same thing. What you are referencing is a user-interface. The answers you collect will then frame the data you are uploading via the API for processing. If your questions are career oriented questions and you need to produce a career story, then it’s a matter of playing around with the sandbox and getting the wording right with where you’d insert the answers to your questions. If you want an essay, then it needs to understand the format of the essay you want as an output. If you want a story, then it needs to understand how you want the story constructed.

def write_essay_with_dynamic_analysis(): “”" Writes an essay paragraph by paragraph, dynamically analyzing the file for each paragraph’s requirements.

def analyze_file_for_essay_basics(): “”" Analyzes the file to understand the basic components of the essay.

def gather_paragraph_info(paragraph_number): “”" Gathers information necessary for writing the current paragraph.

def write_paragraph(paragraph_info, current_essay): “”" Writes a paragraph for the essay based on the gathered information.

Example usage

write_essay_with_dynamic_analysis()

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OpenAI Releases Tool To Detect AI-Written Content

Learn about the new OpenAI Text Classifier, what it can and cannot do, and how it can be used as a starting point for detecting AI-generated content.

• OpenAI's AI Text Classifier can help to detect AI-generated content, but it is not 100% accurate and can make mistakes.
• It can mislabel both AI-generated and human-written text, and it can also be evaded with minor edits.
• The AI Text Classifier should not be the sole piece of evidence used when making a verdict about whether AI generated a document.

OpenAI, the AI research firm behind ChatGPT, has released a new tool to distinguish between AI-generated and human-generated text.

Even though it’s impossible to detect AI-written text with 100% accuracy, OpenAI believes its new tool can help to mitigate false claims that humans wrote AI-generated content.

In an announcement , OpenAI says its new AI Text Classifier can limit the ability to run automated misinformation campaigns, use AI tools for academic fraud, and impersonate humans with chatbots.

When tested on a set of English texts, the tool could correctly say if the text was written by AI 26% of the time. But it also wrongly thought that human-written text was written by AI 9% of the time.

OpenAI says its tool works better the longer the text is, which could be why it requires a minimum of 1,000 characters to run a test.

Other limitations of the new OpenAI Text Classifier include the following:

• Can mislabel both AI-generated and human-written text.
• AI-generated text can evade the classifier with minor edits.
• Can get things wrong with text written by children and on text not in English because it was primarily trained on English content written by adults.

With that in mind, let’s look at how it performs.

Related: AI Text Detection Software: Can They Detect ChatGPT?

Using OpenAI’s AI Text Classifier

The AI Text Classifier from OpenAI is simple to use.

Log in, paste the text you want to test, and hit the submit button.

The tool will rate the likelihood that AI generated the text you submitted. Results range from the following:

• Very unlikely
• Unclear if it is

I tested it by asking ChatGPT to write an essay about SEO, then submitting the text verbatim to the AI Text Classifier.

It rated the ChatGPT-generated essay as possibly generated by AI, which is a strong but uncertain indicator.

This result illustrates the tool’s limitations, as it couldn’t say with a high degree of certainty that the ChatGPT-generated text was written by AI.

By applying minor edits suggested by Grammarly, I reduced the rating from possibly to unclear .

OpenAI is correct in stating that it’s easy to evade the classifier. However, it’s not meant to be the only evidence that AI wrote something.

In a FAQ section at the bottom of the page, OpenAI states:

“Our intended use for the AI Text Classifier is to foster conversation about the distinction between human-written and AI-generated content. The results may help, but should not be the sole evidence when deciding whether a document was generated with AI. The model is trained on human-written text from a variety of sources, which may not be representative of all kinds of human-written text.”

OpenAI adds that the tool hasn’t been thoroughly tested to detect content containing a combination of AI and human-written text.

Ultimately, the AI Text Classifier can be a valuable resource for flagging potentially AI-generated text, but it shouldn’t be used as a definitive measure for making a verdict.

Featured Image: IB Photography/Shutterstock

Matt G. Southern, Senior News Writer, has been with Search Engine Journal since 2013. With a bachelor’s degree in communications, ...

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