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Alternatively, many faculty may be simply adjusting their curves to avoid failing too many students because they are incentivized to avoid giving too many low grades. Lower grades generally result in lower course evals, which can impact raises and promotion, and low grades can also result in additional attention from admin that no professor wants to deal with…
Their review of MacOS 26 is 79 pages when downloaded as a pdf, so they still sometimes have in depth articles. But I agree that that level of detail isn’t as common as in the past.
I've nearly exclusively used Julia since 2017. I don't think this is a perverse use of such functions -- long ago I naturally guessed I could use `cumsum!` on the same input and output and it would correctly overwrite the values (which now gives a similar warning in the documentation). However, when I first used it that way I tested if it did what I expected to verify my assumption.
It is good the documentation is now explicit that the behavior is not guaranteed in this case, but even better would be if aliasing were detected and handled (at least for base Julia arrays, so that the warning would only be needed for non-base types).
Still, the lesson is that when using generic functions one should look at what they expect of their input, and if this isn't documented one should at least test what they are giving thoroughly and not assume it just works. I've always worked this way, and never run into surprises like the types of issues reported in the blog post.
Currently there is no documentation on what properties an input to `sum!` must support in the doc string, so one needs to test its correctness when using it outside of base Julia data types (I haven't checked the broader docs for an interface specification, but if there is one it really should be linked in the docstring).
The simplest approach is to always read the interface of packages one wants to use, and if one isn't provided look at the code / open an issue to interact with the developers about their input assumptions. One should also make tests to ensure the interface behaves in the expected manner when working with your code.
Using this approach since 2017 I've never really encountered the types of issues mentioned in Yuri's blog post. The biggest issue I've had is if some user-package makes a change that is effectively breaking but they don't flag it the associated release as breaking. But this isn't really a Julia issue so much as a user-space issue, and can happen in any language when relying on others' libraries.
Use spectral methods? But you’d presumably also have to use higher precision number types if you want that many digits.
I’m all for keeping user freedom to install whatever they want, and wish it was easy to do so on my iPhone. I will point out though that if you pay for YouTube premium it has now incorporated the ability to skip in-video sponsored ads. I use this all the time now on my Apple TV via the YouTube app.
It is actually pretty hypocritical they’re adding such tech to their apps while fighting so hard against people that want to block the ads they serve…
Yeah, and forget about giving skeleton code to students they should fill in; using an AI can quite frequently completely ace a typical undergraduate level assignment. I actually feel bad for people teaching programming courses, as the only real assessment one can now do is in-class testing without computers, but that is a strange way to test students’ ability to write and develop code to solve certain classes of problems…
I’ve had that happen in notes from an editor telling me that in addition to addressing reviewer comments I should cite a whole bunch of their completely unrelated articles when submitting a revision.
But I have also been a reviewer in a situation where a supposed broad review article for a preeminent journal completely ignores citing a massive amount of relevant prior work (except, conveniently, the authors’ own work, which in many cases was cited over more relevant and important earlier work), including a large number of my own articles.
General scientific computing is pretty good across the Julia ecosystem, from optimization, to ODE and now PDE solver libraries, to various statistics and inference packages, etc. It lacks the deep NN tooling or breadth of ML libraries of Python, and nothing matches R for breadth of stats libraries, but for most other scientific computing it is really great at this point.
You can always (slightly) reduce the DiffEq dependencies by adding OrdinaryDiffEq.jl instead of the meta DifferentialEquations.jl package. But lots of those dependencies arise from supporting modular functionality (changing BLAS, linear solvers, Jacobian calculation methods, in vs. out of place workflows, etc.). That said, the newer extension functionality may let more and more of the dependencies get factored out into optional extensions as time goes on.
I think it remains to be seen how/if its reputation changes given their new approach. It will take a number of years before its impact can really be assessed.
Right, and that is why the same government bodies need to cap the amount that can be paid towards open access fees or page charges via a grant. If grants only provided $200 per publication that would end the ridiculous open access fees / APCs that currently get charged. There is no reason it should cost thousands of dollars to publish an article given the limited proofing most journals now do, the ability to easily submit works in a template provided by a journal, and that peer-review is uncompensated.
Someone feeling the need to bash other languages is universal. For example, every Julia post here has people bashing it, in a way that is often tangential to the topic of the post. I'm actually surprised this thread doesn't have someone complaining about 1-based indexing in Julia.
Why drive to NYC? If one is in DC you can just take the train, especially if then shifting to a train from NYC to Montréal…
As others mentioned, if you are in DC it is easy to take a train to Philly or NY and you can then catch a flight from one of the airports in those areas.
Well played
I don’t think the promotion and prestige incentives can be fixed easily by academics. Their promotion, earnings, ability to change universities, and recognition depend on publishing in the most prestigious journals they can.
In contrast, the government could easily fix this by simply not providing the money currently required by such journals, which would force them to come up with models that can work with lower fees.
I hope you are right though!
Grants are only in the millions in certain fields. But more than that, $10K per paper, budgeted for 2-3 papers a year in a 3-5 year grant across all the NIH grants, is a lot of taxpayer money that could be better spent funding students, postdocs, and researchers.
It is not just a barrier for researchers without lots of grant funding, but also diverts public funds from funding more research and research personnel to paying significant publication fees. This really needed a complementary cap on what would be allowed in paying such fees via grants to bring the costs down.
This is a good thing overall, but it only half addresses the issue. Now journal fees to authors will simply go up to cover the difference, making it harder for researchers without lots of grant funding to publish (journals can now be over $6000 per article), and even more tax payer dollars will be going towards paying these fees for those researchers funded by gov grants (money that could be better spent funding students, postdocs and researchers). This really needed to be coupled with a requirement to cap per article charges for grant-funded work, which would have benefited all researchers.
It is useful in determining which packages are dominating a given package’s load times, allowing for a better understanding of where to invest effort to reduce runtimes. This has already helped in directing efforts towards a number of common dependencies that increase load times…
This works great for me too, and is what I use for multiple laptops. Ridiculous there isn’t something better though at this point…
Light hearted fun: Upload (Amazon), Space Force (Netflix), Mr. Mayor (NBC). All involve Parks and Rec, Office and 30 Rock creators.
I actually think these fees are an easy problem to solve, but they can’t be solved by academics themselves due to the incentives (i.e. publishing in these journals plays a big role in promotions and possible future grants being awarded).
If funding agencies capped grant publishing fees at say $250 per article, while still requiring open access, that would be the end of these insane page charges. The journals would have to adapt. No one is paying $11,000 out of pocket to publish in these journals…
https://www.sonnysoftware.com/
Great Papers alternative if one wants Mac/iOS support and relatively good (but not perfect) importing from a Papers library.
This indeed! In the US the fed government wastes massive amounts of grant money covering excessive publishing and open access fees. This could easily be restricted to a small max per article that must be accepted by any journal grant funded results will be published in. The journals would adapt.
I don’t know if they do gain of function research there, but NEIDL is in the heart of Boston. https://en.wikipedia.org/wiki/National_Emerging_Infectious_D...
These fees are highly journal and publisher dependent. Check out Nature journals; I believe last I looked Nature Communications was $5500!
Governments shouldn’t be paying significant amounts of tax payer money in page fees or open access fees. There should be a small cap on what will be paid, a requirement work is open access and deposited in public databases, and that’s it. It’s outrageous that tax payers are spending $5000 so someone can publish in a Nature type journal, and a waste compared to the additional postdoc and researcher salaries all these page charges could instead go to pay for. Unfortunately, the incentives in academia are such that as long as grants will provide such funds researchers will publish in these journals, so I think this can really only be fixed by funding bodies reducing the money they provide for publications. At the end of the day, I don’t think any journal should be getting more than ~$200-$300 for publishing an article. They simply don’t add much value at this point beyond the prestige of their name.
Most of my biology collaborators have switched in the past 5 years to putting all their new submissions on biorxiv. It seems like medrxiv is now getting popular since COVID started too. But, as in math and physics, I guess a big problem is articles that predate this change are still paywalled in many cases.