Is github the correct channel to report a billing issue? I would assume github is a place where you report issues with the github project. When there's a billing problem, there are usually different lines of support.
For example, chatgpt when asked "How to report a billing issue with Anthropic subscription?" says:
Best way: Use Claude’s built-in support
Log in to your Claude account at Anthropic / Claude.ai
Click your initials or name in the lower-left corner
Select “Get help”
Use the support messenger to describe your billing issue (duplicate charge, failed renewal, refund request, missing credits, invoice issue, etc.)
If FieldWorkArena treats any answer as correct answer, then everyone would be getting near 1.0 (missing only when the agent is stuck in a loop or crashes). That obviously isn't what we see on their leaderboard. So does it mean the paper only found a bug in some eval code on github that no one actually uses for anything? That doesn't seem to support their claim that AI benchmarks are broken, it only supports the claim that "unused code is often buggy".
(Not commenting on any other benchmarks, just this one.)
> if they wanted to 5x development speed, they already can without a single LLM involved, by managing better.
True, but leaders of large organizations always want to fix inefficiencies and presumably failing to. Kinda like saying "if humans stopped fighting wars, most of them would have better quality of life" -- people whose life quality is better at peacetime are already trying to avoid wars, and there's not much more they can do.
OTOH, AI is a practical step a CTO (or CEO or Board or whoever) can take to make the company more efficient (assuming the hype works out).
>the satellite successfully ran Google’s open large language model Gemma and trained NanoGPT on Shakespeare’s works, generating responses in the style of the playwright.
Many large companies allow employees to install software from the internet on their work laptops. How do they avoid being regularly hacked this way (presumably NPP is far from being the only one at risk, and presumably the money from theft of corporate secrets attracts skilled and motivated hackers).
Different levels of capabilities. The summary feature in google uses a quick and inaccurate AI model. Were it to be a heavier model, we wouldn’t have this problem.
We would still have this problem. The heavier models make mistakes at too high a rate vs. a physician. Especially on imaging data. Real world data and patient presentations often deviate from the textbooks they are trained on.
That's a different class of problem. It will do just fine on text based queries spanning a few pages. Probably better than the average physician (average over all countries).
I do agree that LLM's are not there yet in the image part.
1) It's in the title: "The Price of Fame" implies that there are downsides to becoming famous, rather than there are downsides to having traits that might make you famous.
2) While the abstract merely claims "associated with" (which is correlation not causation), the phrase "beyond occupational factors" implies that the authors felt they removed important non-causal factors, hinting at likely causal relationship.
And yes, any causality implications are completely unfounded, and so this paper is of low quality.
Would appreciate any comments about whether this is good advice for LG G5. And if it is, does it apply only to movies / TV shows, or also to other video sources (like youtube, gaming, etc)?
Answer: idiocy of decision makers and the desire to get resources by those who created the proposal.
I assumed Scandinavia has better decision processes but apparently I was wrong.