I don't feel the numbers without the harness are useful.
People will use the model with the harness. I know that harness may not be optimized to this model, but it's still more useful to see the numbers from an imperfect harness than from a no harness setup.
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).
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).
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)?
1) A lot of informal (i.e., not in a scheduled meeting) chats are more valuable than meetings. They are much more rare when people WFH.
2) Many folks tend to be more distracted when WFH. TLs don't have a perfect vision into whether someone spent 4 hours on a bug (or a design doc) or 2 hours on the bug / design doc and 2 hours on online shopping / playing with kids.
It's quite confusing to me that none of the comments I saw in this thread don't discuss those factors (I'd be fine if people mentioned them and explained why they are not too important).
Obviously there are also factors in favor of WFH: commute costs, personal satisfaction (which may indirectly improve productivity and/or retention of the best people), noise in the workplace, lack of meeting rooms, etc. But it's far from obvious to me if, on balance, WFH or RTO works better for building a successful company.
Also, I'm wondering if any other manufacturer would make the crank and the drum from the same material. Wouldn't it be like $100 extra to make a stainless steel spider?
I'm now completely confused. Wallets were drained years ago? So $15B worth of bitcoin was already transferred? From whom to whom? And then why is this entire post considered news, if the wallet is empty?
Fairness doesn't come into play here, this is just about predicting which of the overwhelmingly many sources of information are worth paying attention to.
Feel free to come up with your own predictive model of whether someone is worth listening to. It's hard to compare such models fairly, but if you feel yours is better, it might be worth sharing.
Even if this bug never existed, models can still see lookahead commits during pretraining. Do we expect this bug to have a greater impact than the pretraining leakage?
Obviously having something available during test time is more valuable than buried somewhere in the pretraining mixture. But in pretraining it happens presumably with high probability (why wouldn't coding models pretrain on the entire github), while in test time it apparently happened only very occasionally?
> Perhaps I missed something, but most of my friends have been on the lookout and I have had a number of games referred to me; none of them came close to Balance of Power in algorithmic sophistication.
So it's not like he missed the simulation genre evolution, he just disagrees with the direction that evolution took. And he suggests it's because the time has not yet come for his ideas.
An obvious retort is: maybe people don't (and won't) want to play games with sophisticated algorithmic simulation because they are boring. He doesn't seem to offer any good argument about why his ideas are "good but too early" as opposed to merely "bad". As such, I find his post not very persuasive.
People will use the model with the harness. I know that harness may not be optimized to this model, but it's still more useful to see the numbers from an imperfect harness than from a no harness setup.