It's not a tautology because it's not guaranteed. There are plenty of plausible sounding claims that fail to be true. That's why science is needed: to provide _empirical_ evidence for/against a claim.
Not to be an "uhm actually" guy but this goes into a lot of interesting philosophy in the first half of the 20th century. You would probably agree that "a fish is a fish" is a tautology, but for more complicated things it gets murkier and murkier. Separating out what are the tautologies from not was a big effort. Then Quine came along, and a big portion of people migrated away from the distinction
I dabble in "um actually"s myself (especially given that my original comment was one), so no worries :)
I don't disagree with your comment exactly. But I primarily wanted to push back on a common response to scientific works. Something to the effect of "Well obviously, everyone knew that!".
Except they didn't because they (presumably) didn't actually investigate. And even after the science, they still don't _know it_ know it. But post-scientific inquiry, they have a much stronger claim to the knowledge than they did before. So the type of dismissal in the root comment is seriously missing the point.
I'd be interested in knowing what the CO2 emissions were from these. You still need to feed the yeast, so you'll have the CO2 emissions involved in growing a crop associated with this. And if you look at the chart in the OP, you'll see that grain production is about half the CO2 emissions of milk. That's likely part of the milk CO2 production accounting.
In addition, you'll need more cleaning/sterilization/mixing. I'd guess that it's lower, but I wonder how much lower.
And then there's the other products that generally get thrown into the mix to make up for things like missing fats. For example, a vegan cheese based on bacteria will often include coconut oil, probably to get the same fat profile.
Whey is an interesting product in general because it's a waste product of cheese making.
Feed efficiency is critical when doing these calculations as cows inherently need energy to survive not just produce milk. As such even if you use the same crop two different sources of protein can have wildly different levels of CO2 emissions embedded in their creation. https://en.wikipedia.org/wiki/Feed_conversion_ratio
I think it is likely more efficient. That said, cows do have the advantage that the food they consume needs little to no processing in order to produce milk. The yeast needs pretty precise processing of the incoming mash both to make sure a wild yeast strain doesn't make it's way in, and to make sure the yeast ultimately produces the right proteins.
You can't just throw in grass clippings into a vat and get whey. You can throw grass clippings into a cow to get milk (though, TBF, I dislike grassy milk).
I agree it’s likely to be more labor intensive per lb of feedstock, but only 21% of calories in milk are protein and overall milk has ~10% of the initial energy. So you’re looking at ~2% of the energy from these crops ending up as milk protein.
That’s a lot of room for improvement which then means far less labor on growing crops.
Cows are pretty terrible because of methane from their burps (not farts; burps). People are working on that but it's still real. A 50% drop would be very significant
Ohhh thank you! I thought the same as the parent comment: I expected that button to turn off the animation immediately. I guess the author wanted the yellow background to "melt" the snowflakes?
I used this recently for my resume and I recommend it.
I have the technical background to write Latex and Typst documents but I honestly didn't want the headache. Plus I'm the type to futz with styling all day long instead of putting down actual content. RenderCV was simple to use and did exactly what I wanted.
You don't have that power, you'll either be beaten by your adversaries unless you only target weak people. And then you'll be arrested. You don't have the power you claim to have. You can't punch people.
> as a code reviewer [you] are only expected to review the code visually and are not provided the resources required to compile the code on your local machine to see the compiler fail.
As a PR reviewer I frequently pull down the code and run it. Especially if I'm suggesting changes because I want to make sure my suggestion is correct.
I don't commonly do this and I don't know many people who do this frequently either. But it depends strongly on the code, the risks, the gains of doing so, the contributor, the project, the state of testing and how else an error would get caught (I guess this is another way of saying "it depends on the risks"), etc.
E.g. you can imagine that if I'm reviewing changes in authentication logic, I'm obviously going to put a lot more effort into validation than if I'm reviewing a container and wondering if it would be faster as a hashtable instead of a tree.
> because I want to make sure my suggestion is correct.
In this case I would just ask "have you already also tried X" which is much faster than pulling their code, implementing your suggestion, and waiting for a build and test to run.
I do too, but this is a conference, I doubt code was provided.
And even then, what you're describing isn't review per se, it's replication. In principle there are entire journals that one can submit replication reports to, which count as actual peer reviewable publications in themselves. So one needs to be pragmatic with what is expected from a peer review (especially given the imbalance between resources invested to create one versus the lack of resources offered and lack of any meaningful reward)
> I do too, but this is a conference, I doubt code was provided.
Machine learning conferences generally encourage (anonymized) submission of code. However, that still doesn't mean that replication is easy. Even if the data is also available, replication of results might require impractical levels of compute power; it's not realistic to ask a peer reviewer to pony up for a cloud account to reproduce even medium-scale results.
No, because this is usually a waste of time, because CI enforces that the code and the tests can run at submission time. If your CI isn't doing it, you should put some work in to configure it.
If you regularly have to do this, your codebase should probably have more tests. If you don't trust the author, you should ask them to include test cases for whatever it is that you are concerned about.
If there’s anything I would want to run to verify, I ask the author to add a unit test. Generally, the existing CI test + new tests in the PR having run successfully is enough. I might pull and run it if I am not sure whether a particular edge case is handled.
Reviewers wanting to pull and run many PRs makes me think your automated tests need improvement.
The 2nd link seems reasonable to me? Why does a study about 25k workers in Denmark (11 occupations, 7k workplaces) not count as evidence? If there was a strong effect to be found globally, it seems likely to be found in Denmark too.
Also, what about the other links? The discussions about the strange accounting and lack of profitability seem like evidence as well.
If anything, this article struck me as well-evidenced.
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