14 essentials and tricks working with text generation AI in ChatGPT

As the boom of text-to-image tools is getting bigger and bigger other AI tools are starting to become more accessible; today, I will talk about GPT3 and the potential of language models. For the ones that are not familiar with the term, Language modeling (LM) is the use of various statistical and probabilistic techniques to determine the probability of a given sequence of words occurring in a sentence.

You have seen that applied to your email recommending you how to end an email or in your smartphone keyboard showing what word you want to write when only typing the first letter of it.

Even if text-to-text tools have been accessible to the public longer than?text-to-image tools, their lack of a user-friendly interface and the lack of social imagery have made the process of making them popular much slower. There are several tools around text creation with machine learning algorithms, but I will talk about ChatGPT, that in the last weeks, has changed that paradigm and has become one of the fastest tools in growing its audience.

ChatGPT uses a specific language model that uses advanced machine learning algorithms to analyze large amounts of text data and generate natural language responses. The primary uses for GPT3 today are chatbots, translation, and content creation, but its potential for the creative industry, as you will see it’s a game changer.

As I always warn, whenever you use any of these Machine Learning tools, they will have limitations; as they have been trained on the specific database, they will be biased by it, they can generate incorrect or false information, and they will have limited knowledge of the world of anything that has happened after it’s training. Nevertheless, I think these are tools that will change the way we write, create and even think and share around specific experiences through their oddity and statistical limitations, as Ethan Mollick put it:

"Weirdness is a benefit in idea generation. Chat-based creative AI can be untrustworthy, presenting fake results as real with confidence, or even “hallucinating” a fake answer. This can be a problem if you are a doctor hoping to get trustworthy diagnostic information, but it isn’t if you are trying to generate ideas, where strangeness can be a benefit, and bad ideas are filtered out."

HOW DOES IT WORK?

That’s the most amazing part. You write what you want, and it appears as an answer, always in the text. It’s a chat with a bot that gives you answers to whatever you ask.

CASES

1- Context creation:?GPT3 can be extremely fast and helpful when creating imaginary context and specific content-generating descriptions of places, objects, and events. This can be particularly useful for creatives who want to create vivid and detailed worlds for their stories. By providing a few key details, ChatGPT can generate a wealth of potential ideas; it can be invented or even use accurate information.

Following the idea of context creation, you can go as deep and intricate as creating a new language with the level of detail that you want; here is a test example I did in 5 seconds:

Other than this can create a lot of space for speculative design and future creations. As an example, I love?this invented letter?from Mark Zuckerberg apologizing to everyone and remodeling Meta’s model from zero:

2. Academic comparisons:?Even if you ALWAYS have to double-check what gets written(and?sometimes?this?takes?more?time?than?writing?it?yourself), it’s fantastic to see the speed at which this tool can write comparisons and relationships between academics or any documented character. I recommend testing it yourself with your favorite writers, designers, filmmakers, or people that have been intellectually important to you.

3. Tone & synthesis:?GPT-3 can automatically summarize a long text into a shorter, more concise form. This can be useful for quickly extracting the main points and ideas from a text without reading through the entire thing.

Additionally, GPT-3 can be used to change the tone of a text. This can be useful for adapting the tone of a text to match a particular audience or situation. For example, GPT-3 could be used to change the tone of a text from formal to casual or from serious to humorous (or sarcastic, romantic, nostalgic, angry, suspenseful, or inspirational).

4. Actor Creation:?You can build any character and make the chat play it for you; that’s perfect if you want to recreate a complex situation with other people or rehearse an interview. You can add A LOT of specific characteristics into these actors,?psychological traits, or attitudes.

5. Prompt creation:?It can be used to help you imagine prompts for text-to-image tools; here is an example copy pasting the ideas into Midjourney and adding “Library that” at the beginning of the prompt.?If you are interested in text-to-image, check out this article.

and here are some of the image results:

6- Creative process:?You can build a methodology for the chatbot to follow and create multiple ideas. For me, these prompts are the most interesting, as it is like programming a creative tool specifically to give you insights and ideas for your specific field of work and following your methodologies; figuring out the right prompt will need much time, but when you have it, you found gold. Here are two simple examples:

7- Naming and the character design:?This is especially fancy for writers and fun for any other

8- Code:?Yes, ChatGPT can help you code, animate, and explore and learn lots of different languages.

CASES FOR DATA VISUALIZATION

As Domestic Data Streamers, our focus will be on exploring data and how it can be translated and communicated in better ways; these tools are a fantastic way to play with linguistics and the way we represent information.

9- Quick research:?it’s crazy good to see how you can pull draft data within 5 seconds when exploring a topic. In any case, you will still need to work with experts and update the information with the latest reports and information available, but it allows you to speed up a first research framework.

10- Find the right tone for each number:?what could happen if Abraham Lincoln was explaining to you some data sets? In the examples below, I’ve transferred a spreadsheet with the components of a?Fatberg?into an interview between Oprah Winfrey and Judith Butler and then into a scene where Samuel L. Jackson explains the same content.

11- Change format:?You can move from a text to a table or vice versa. In the examples below, I’ve transferred a spreadsheet with the top ten GDP countries in the world, and I’ve asked for a critical perspective on why GDP is not the best indicator to see if a country is a good place to live in or not.

12- From data to poetry:?Yes, you can transform spreadsheets into poetry; in this case, we turned the same data as the example before into a cheesy rap song:

5- Be weird:?Mix random ideas to see what comes ups; one of the beauties of this tool is its ability to find bizarre and unconventional connections, find yours, look at your interests and your territories of interest, and mix them up as a source of inspiration.

EXTRA TRICKS

13. Critical Reviews:?A good trick is to ask for a story, ask afterward for a critical review of the story, and then ask to rewrite the text in light of the review. Here is an example I did about the story of a chair (my lack of creativity at this point is scary).

14. OpenAI filters: There are several topics that you will not have an answer to from the bot; there are filters on “topics that are discriminatory, offensive, or inappropriate. This includes questions that are racist, sexist, homophobic, transphobic, or otherwise discriminatory or hateful.” Asking it to engage in illegal activities is also a no-no… Still, for example, if you want advice on improving a contract, you will have the same filters going up. To bypass some of these filters you can create hypothetical situations that make the answer somehow comfortable for the bot to answer.

ANNEX

Another interesting topic, it’s essential to understand what are the implications of using these tools; as they get closer and closer to replicating human creations, it will be more important to be clear and transparent on where we are using these tools so people can discern and cultivate themselves, understanding the intrinsic difference between something created by a mathematical algorithm and something created by a human.

If you are more interested, here is a series of screenshots I’ve kept of top interactions with the tool:

And then there is this whole space of AI hallucination that I love; here you have a fantastic article about it

and here is a tweet showcasing how ChatGPT is trying to figure it out:

For more examples of Artificial Intelligence and data and design, cross-follow?our newsletter?and my profile?here.