sure
the ones inside the article: "{} simple illustration, naive style, pale colors"
the ones in the related / main page: "{} digital art illustration, tetradic moody subdued colors"
I'll contemplate this issue later. I deem this risk to be lower than not discovering a reliable acquisition channel or not being able to attain high margins.
Instinctively it appears as though I'm creating original content. However, all this legal stuff is often counterintuitive.
It's not that straightforward. I would say that the most important part of pre-processing is how to break the transcript into parts.
But there are many more things to improve. It's a pipeline: you can add more models, you can train them, you can change prompts, you can post-process the results. But it takes time. More time each step.
No, sorry. If I do that, I have to make the plans even more expensive. And users will randomly get free summaries, which will confuse them. "Why should I pay if sometimes I get them for free for no reason?"
I have tried many (all the popular) huggingface summarization models, they don't compare to GPT. Basically, they highlight the parts they think are important. But they can't "understand" and generalize.
Frankly, I haven't read the papers about summarization. But I will have to when I'll work on reducing costs.