jncfhnb

23 ms·

331.
by jncfhnb 2y ago
I think he would have more sway over trump if he had billions more dollars not lost on X tbh
332.
by jncfhnb 2y ago
It’s randomish. There are facts about the possible layouts you can memorize. I don’t know most of these rules but there’s never 5 in a row; or even 4 in a row if you’re the team with one fewer (second team to play). Edit: because the game
333.
by jncfhnb 2y ago
It’s not particularly clear that X played a significant role
334.
by jncfhnb 2y ago
If an LLM states an answer and then provides a justification for that answer, the justification is entirely irrelevant to the reasoning the bot used. It might be that the semantics of the justification happen to align with the implied logic
335.
by jncfhnb 2y ago
If you really want to get good, your goal is not so much to get as many tiles as possible, but rather to get the tiles that are semantically distinct from your opponent’s. A single mistake that triggers your opponent’s tile is generally eno
336.
by jncfhnb 2y ago
Ehhh I don’t think that’s accurate. The problem is not linking 4 words. It’s linking 4 words without accidentally triggering other, semantically adjacent words. This task could probably be solved nearly just as well with old school word 2 v
337.
by jncfhnb 2y ago
An individual person can do whatever they want. It sounds surprising to me that trans people broadly prefer trans people is all.
338.
by jncfhnb 2y ago
> most of these trans women are interested only in people similar to themselves. IE, queer, non binary, trans That sounds kind of odd to me. I don’t have any experience or insight to people’s experiences here but I would assume that mos
339.
by jncfhnb 2y ago
Perverted is just some other person being judgmental.
340.
by jncfhnb 2y ago
If you’re going to use classic ML why not just train a model based on the vector representations of the product descriptions?
341.
by jncfhnb 2y ago
The problem is that it doesn’t satisfy food cravings that have been fostered by shitty food.
342.
by jncfhnb 2y ago
I call bullshit. I don’t really believe they’re saying don’t fund startups. I also don’t believe for a second that they think they can stunt progress. We didn’t have the internet in the 60s.
343.
by jncfhnb 2y ago
The effectiveness of policies is influenced by your starting position. South America is relatively poor. The United States is the best positioned country in the world by a long shot.
344.
by jncfhnb 2y ago
And the thread is about how LLM training interacts with copyright. Not whether OpenAI or Meta coincidentally blatantly copied other works.
345.
by jncfhnb 2y ago
I disagree. This thread seems to be about LLMs on a fundamental level.
346.
by jncfhnb 2y ago
“They” might be doing that. But this is not intrinsic to LLM usage
347.
by jncfhnb 2y ago
You can absolutely use the story frameworks that Disney has done. You cannot make a story featuring Simba.
348.
by jncfhnb 2y ago
Yes. As long as you don’t reproduce other people’s stuff specifically.
349.
by jncfhnb 2y ago
4 should be enough for anybody.
350.
by jncfhnb 2y ago
The problem statement was text that random humans can read and OCR cannot. If you want to provide a good faith answer at least make it English. I assume this is French but it’s obviously much harder to evaluate on both ends when you’re mixi
351.
by jncfhnb 2y ago
That’s comprehension of English not reading characters
352.
by jncfhnb 2y ago
What methods have you tried?
353.
by jncfhnb 2y ago
Also, you seem to have taken issue with the phrase “random humans” because you’re confused at what’s being done here. It is random humans. Non experts. Experts are asking for the help of non experts. > Anyone with an internet connection
354.
by jncfhnb 2y ago
The alternative is me saying that appealing to their “expertise” is an appeal to authority fallacy that flies in the face of general evidence that modern OCR is far better than humans at character recognition. Especially random non speciali
355.
by jncfhnb 2y ago
Then please provide a single example that we can’t instantly solve. Happy to prove them wrong.
356.
by jncfhnb 2y ago
Text that is _intentionally constructed_ to fool computers but not humans is obviously out of scope. But they’re generally easily solved with OCR these days anyway.
357.
by jncfhnb 2y ago
I would challenge you to find a picture of text that you think a human can read and OCR cannot. I’m happy to demonstrate. The text shown in this article is trivial.
358.
by jncfhnb 2y ago
There are conceivable reasons why they may be telling a half truth here. Just engaging the public is a worthy goal here.
359.
by jncfhnb 2y ago
Ozempic tends to change not just the total number of calories but also the timing and the cravings for shitty food. Calories in / calories used is NOT a complete model because different foods can have different caloric retention. The m
360.
by jncfhnb 2y ago
I don’t think I believe that OCR can’t do it but random humans can OCR is VERY good

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