When the victim's relatives send them money because they need to eat and pay rent after handing everything over to the scammer, the persistent backdoor lets that money be drained as well... You're underestimating the persistence and ruthlessness of the scammers.
I have to assume that some of that 4% has second order negative effects on US importers and consumers.
Profit margins can not always go down by 4% and in those cases goods and services would then not be available to US importers and consumers is only one example.
My assumption is that the 96% statistic does not fully encapsulate the negative costs to consumers. I have to to wonder how much higher the burden is over 96% when all second order effects are taken into account.
Importer != Consumer. I think that's very obvious to anyone paying attention to this whole thing. In fact, it's a small minority of imports that are direct to consumer.
It absolutely is a mix of the importer (e.d. manufacturer, producer, wholesaler, retailer, etc.) absorbing some in their margin and the consumer picking up the bill via price increases for the rest.
It's quite obviously not 96% being paid by the consumer across the board just from looking at the CPI numbers.
All this study states is the obvious: foreign producers didn't lower their cost by much in response to tariff burden. They largely charged the same rate to a buyer in the US vs. a buyer in Germany.
This isn't to defend the tariff situation - just that this study gets trotted out a whole lot in an extremely disingenuous manner. Other data that exists is better that measures direct consumer impact.
The study makes it clear that the people footing the bill for the tariffs are in the US - it is not the rest of the world paying Trump's taxes, it's Americans, whether directly as consumers or importers.
You're measuring binary outcomes, so you can use a beta distribution to understand the distribution of possible success rates given your observations, and thereby provide a confidence interval on the observed success rates. This week help us see whether that 4% success rate is statistically significant, or if it is likely to be noise.
I’ve only ever gotten, like, slight wording suggestions from reviewers. I wish they would write things like this instead—it is possibly meaningful and eminently do-able (doesn’t even require new data!).
Taking a slightly closer look at the paper, you've got K repositories and create a set of test cases within each repository, totaling 130-ish tests. There may be some 'repository-level' effects - ie, tasks may be easier in some repo's than others.
Modeling the overall success rate then requires some hierarchical modeling. You can consider each repository as a weighted coin, and each test within a repository as flip of that particular coin. You want to estimate the overall probability of getting heads, when choosing a coin at random and then flipping it.
Yeah - it's interesting where the edge is. In theory, an llm trained in everything should be more ready to make cross-field connections. But doing that well requires certain kind of translation and problem selection work which is hard even for humans. (I would even say, beyond PhD level - knowing which problem is with throwing PhD students at is the domain of professors... And many of them are bad at it, as well.)
On the human side, mathematical silos reduce our ability to notice opportunities for cross-silo applications. There should be lots of opportunity available.
This is a very reasonable drawing of a bicycle. It has a solid rear triangle, and forward swept front fork, which is an important detail for actually being able to steer the bike. The drivetrain is single speed, but that's fine, and the wheels are radially laced, which is also fine: both of those simplified details are things which occur in real bicycles.
> and forward swept front fork, which is an important detail for actually being able to steer the bike.
...but no crown or any sort of indication that the fork is separate from the frame, making it impossible to steer. Yay.
> the drivetrain is single speed, but that's fine, and the wheels are radially laced, which is also fine: both of those simplified details are things which occur in real bicycles.
A $1 fee is fine for Indian software developers and it kills the spam. If it's a greater burden for people in India than the US, well, not all solutions are perfect, but some are useful.
Because it discriminates a marginalized group which is by tradition very important to the FOSS community: students
Also, no it wouldn't kill spam. The spam would be moved to pwned machines where the owner would suddenly have an incentive (financial) to fix the system, if they know.
What remains is people who would be so rich that $1 means nothing to them. Ie. white collar criminals who are already rich enough to not care.
>contributing to an open source project that you're likely already benefiting from.
Yes, but many people benefit for free. You see the backwards incentives of making the most interested (i.e. the ones who may provide the most work to your project) pay?
And none of that even guarantee support. Meanwhile you donate more and you get to tell people what the build. It's all out of what.
And 2.5s is best case. Signal strength issues, antenna alignment issues, and all sorts of unknown unknowns conspire to make high-integrity/high-throughput digital signal transmissions from a moon-based compute system have a latency much worse than that on average.
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