This is why it is critical for true open sources LLMs to continue to be available.

There's also a huge reason for research and any attempts to claim AGI. The training data is massive and far larger than any single person or even small group can look through. AND we know that the filters aren't always accurate. All benchmark results necessitate a grain of salt. I mean at times Gemini has been "better" than GPT on benchmarks but at the same time was saying that cockroaches will crawl into your penis. But there's plenty of papers showing that accuracy of answers (of any model) highly correlates to the frequency of that information and I think you can prove this to yourself pretty quickly if you ask it some coding questions and try to ask about some more obscure topics. Not that you can't get the answers, but that when you can get them, they are harder to get.