GPT-4 vs GPT-3

By Tiringindi Learnmore


 The Bot Rush

As articulated on the previous blog by this author, the most recent accomplishment in OpenAI's endeavour to scale up deep learning is GPT-4. Unlike GPT-3, which is unimodal and can only accept text inputs, it is a sizable multimodal model that receives picture and text inputs and emits text outputs. Compared to GPT-3, GPT-4 is more dependable, inventive, and capable of handling significantly more complex instructions. When working with users on creative and technical writing activities like songwriting, screenwriting, or figuring out a user's writing style, it can generate, edit, and iterate with them. Additionally, GPT-4 is more aligned and secure than GPT-3. Compared to GPT-3, it is 40% more likely to produce factual responses and 82% less likely to reply to requests for requests for content that is not permitted.

GPT-3 is a model for unsupervised learning, and GPT-4 is a model for supervised learning. As a result, GPT-4 is SUPERIOR to GPT-3 in terms of accuracy and its ability to produce natural language that is more sophisticated. Additionally, GPT-4 can produce lengthier and more sophisticated text than GPT-3, which makes it more suitable for jobs like summarising and answering questions. The new model performs admirably in side-by-side tests, although not as admirably as its test results might suggest. In certain cases, GPT-3 actually provided the more helpful response.

Finally, this could be the best approach to compare GPT-4 to GPT-3: Less awful are its poor responses. GPT-4 is weak when given a direct factual inquiry, but significantly better than GPT-3 at not just outright lying to you.

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