A man named John Schulman talked about a new AI model called GPT-4. He said that it might not be as smart as we want because it doesn't have enough information to learn from. But he also said that people can find ways to teach it better and make it smarter in the future. Read from source...

1. The title is misleading and sensationalized. It implies that GPT-4 performance has challenges due to a lack of data, when in fact the main challenge is how to use the existing data more effectively and efficiently to improve model quality and avoid overfitting or memorization.
2. The article cites Sam Altman's criticism of GPT-4 as "dumbest model", but does not provide any evidence or reasoning behind his claim. It seems like an emotional reaction rather than a constructive critique.
3. The article mentions John Schulman's podcast interview, but does not include any direct quotes or links to the source. This makes it hard for readers to verify the information and assess the credibility of the author.
4. The article uses vague terms like "limited amount of data" and "data wall" without defining them or explaining how they affect AI models. It assumes that the reader is familiar with these concepts, which may not be the case for many people who are interested in learning more about AI and GPT-4.
5. The article does not provide any balanced perspectives or alternative viewpoints on the topic. It only focuses on the negative aspects of GPT-4 and its potential limitations, without acknowledging the progress and achievements that have been made by OpenAI and other researchers in the field.

Bullish on AI models