I assume you are one of those people that wants the web to go back to the 2000 era. Where JS is not as wide spread and multimedia is expensive to load. That's why I assume if you want the web to be simpler you advocate for removing many of the current web standards/API. I meet too many people like that hence my immediate assumption

The alternative to a less complex web is we will have more native applications. And honestly, I do not prefer that

I think the program specifically targets the people that are an active user of framework AND actively attend those events anyway. So being paid by framework doesn't change whether that person goes to an event or not. That makes a certain sense IMHO since if you are only attending if being paid to do so, then you are not a volunteer.

I think sandboxing the filesystem by default is a good security measure. For Android it makes sense since you can sideload an app and that always carries risks. I think it can be improved on the UX side without compromising much on security but that is not my expertise. And note that I have not used iOS devices in ages too so I don't know how they handle the filesystem now.

A word strings together form a sentence which carries meaning yes, that is language. And the order of those words will affect the meaning too, as in any language. LLM then will reflect those statistically significant words together as a feature in higher dimensional space. Now, LLM themselves don't understand it nor can it reason from those feature. But it can find a distance in those spaces. And if for example a lot of similar kanji and the translation appear enough times, LLM will make the said kanji and translation closer together in the feature space.

The more token size, the more context and more precise the feature will be. You should understand that LLM will not look at a single kanji in isolation, rather it can read from the whole page or book. So a single kanji may be statistically paired with the word "king" or whatever, but with context from the previous token it can become another word. And again, if we know the literary art in advance, we could use the different model for the type of language that is usually used for that. You can have a shonen manga translator for example, or a web novel about isekai models. Both will give the best result for their respective types of art.

I am not saying it will give 100% correct results, but neither does human translation as it will always be a lossy process. But you do need to understand that statistical models aren't inherently bad at embedding different meanings for the same word. "Ruler" in isolation will be statistically likely to be an object used to measure or a person in charge of a country depending on the model used. But "male ruler" will have a significantly different location in the feature space for the same LLM for the former, or closer for the latter case.

The word parameters here must be defined. Is it the weight they are talking about or the input being used to answer the question? For the former, yeah, it's like a person was reading a book and not an open book at all. But if it were used in the input, then it is practically an open book. They have the context on the same input.

Being wrong about being a pedant or on opinion? Also, the reply doesn't specify any correction, just stating that I don't know what being pedantic and unskilled is. And I do admit I am being pedantic from my understanding of pedantic, hence the current discussion. I do love to argue for the sake of arguing. I can learn a lot from arguing. So if people would like to debate me, feel free to do so. Please state what about my statement that is wrong?

I don't think it's anyone. The difference is that one job training requires extensive facility and infrastructure in place to do the training, while the other is trivial. You can train a lot of people to flip burgers with a lot less resources than training a surgeon to do surgery.