The video shows a web interface with a floating eight ball and the prompt, "Ask the mystical magic eight ball." The input field asks, "What would you like to know?"

This is a simple web application I created to play with OpenAI's GPT-3 API. I am presenting it in video form because OpenAI currently has very strict guidelines about exposing the API publicly and I don't have the motivation to implement the necessary features it would take to go live.

The app uses the davinci completion endpoint, and this is the prompt data object if you are able to try it in the playground yourself:

{ prompt: "I am the mystical magic eight ball. Ask me any question and I will tell you the answer.\n<q>What will the weather be like tomorrow?<a>Overcast skies <enda>\n<q>What's my favorite color?<a>Blue.<enda>\n<q>Am I going to win the lottery?<a>If you play the right numbers<enda>\n<q>" + question, temperature: 1, max_tokens: 50, top_p: 1, frequency_penalty: 0, presence_penalty: 0, stop: ["\n"] }

When I gained access to the GPT-3 private beta, one of the most surprising things I found in the beta-testing community was its faith in the model's pre-training, which is admittedly massive. With the vast stores of knowledge that GPT-3 has been trained on, could I trick it into telling the future?

I asked GPT-3 to play the role of a Magic 8 Ball in the prompt, but did not supply it with any of the 20 canonical Magic 8 Ball answers so that it would answer to the best of its ability.

I then asked the series of questions in bold multiple times and received the answers in caps, documented in the video above via screen recording:

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