Applications of GPT-3

Picture by: Yannic Kilcher


Prior to the release of GPT-3, the largest language model was Microsoft’s Turing NLG, introduced in February 2020, with a capacity of 17 billion parameters.

The quality of the text generated by GPT-3 is so high that it is difficult to distinguish from that written by a human, which has both benefits and risks. So now let’s talk about thee advantages and disadvantages of GPT-3.


  1. Affordance Prediction : GPT-3 can be used in the field of robotics for afforandance prediction. For example you have a robot and you give it an object then using the afforande prediction model it can make out what it can do with the that object. A demo is prepared by Siddharth Karamcheti which can be found here.
by: Siddharth Karamcheti

2. Question and Answer generation : GPT-3 can be used for generating questions from some given data and even answer those questions. A demo is prepared by Mckay Wrigley which can be found here.

3. Generation of Deep learning models : It can be used generate deep learning models just by getting the information of the dataset. A demo was made by Matt Shumer which can be found here.

by: Matt Shumer

4. Text Generation : GPT-3 can generate text that can easily pass the Turing Test. It generated this essay using a prompt. It is indistinguishable from human-written essays.

by: Theguardian



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