Btw, I asked it:
> How can you improve GPT3 or ChatGPT?
Answer:
> There are several ways that GPT-3 (Generative Pre-trained Transformer 3) and ChatGPT could be improved:
> 1. Increase the size of the model: GPT-3 is already one of the largest language models available, but increasing the size of the model could allow it to perform even better on tasks such as language translation and summarization.
> 2. Train the model on more diverse data: GPT-3 is trained on a large dataset, but it could be improved by training it on a wider range of data sources, including more diverse languages and dialects.
> 3. Improve the model's ability to handle long-range dependencies: Language models like GPT-3 and ChatGPT are sometimes limited in their ability to understand and generate text that contains long-range dependencies, such as references to events or characters that were introduced earlier in the conversation.
> 4. Enhance the model's ability to handle out-of-vocabulary words and rare words: GPT-3 and ChatGPT can sometimes struggle to generate coherent text when they encounter words that are not in their vocabulary. Improving the model's ability to handle these cases could improve its overall performance.
> 5. Train the model on more tasks and domains: GPT-3 and ChatGPT are trained on a wide range of tasks, but there is always room for improvement. Training the model on more tasks and domains could make it more versatile and able to handle a wider range of inputs.
It is probably right with every point. So it can improve itself.
Yes, none of this is really novel. All this is basically well know. But so what? This is still a good answer to the question. TacticalCoder suggested this test. I'm not arguing that this was a good test. Actually I already implied in my earlier answer that I don't think this is really a good test for AGI or human-level intelligence.