Previous discussion (where I originally posted this gist): https://news.ycombinator.com/item?id=14150854
2,428 karma · joined March 14, 2012
tl;dr MIT is selling off half of 18.0.0.0/8 (8 million IPs)
The MCE seats also serve this purpose.
> I'm willing to bet that people with similar flying habits to me provide the majority of profit for an airline as well.
Well, because it encourages people like you to keep their "status," and people without "status" now have to pay extra for a regular seat, it probably benefits the airline. But it is another fare class that the airline invented to make more money, much like the basic economy fares discussed in the article.
My academic institution refuses to pay for any kind of seat upgrades, so from my perspective, the rational response is to fly on another airline. I will probably have to avoid airlines that start "offering" "Basic Economy" fares for the same reason.
1. I was bothered by things that usually don't bother me.
2. I had trouble keeping my mind on what I was doing.
3. I felt depressed.
4. I felt that everything I did was an effort.
5. I felt hopeful about the future. (REVERSED)
6. I felt fearful.
7. My sleep was restless.
8. I was happy. (REVERSED)
9. I felt lonely.
10. I could not "get going."
So yes, it seems like responses to 2, 4, 5, and 10 could have something to do with the nature of the work in addition to students' mental state. But it is also possible that feeling that way about one's work takes a toll on one's mental health. I don't think it's appropriate to conclude anything based on this survey, but it certainly seems to call for further investigation.
The reason academics argue about citation counts isn't necessarily that they care, but that, at many institutions, citation counts are directly tied to hiring decisions.
But I think it's bullshit to say that not bruising egos is an important skill, especially in science. The kinds of scientists whose egos are easily bruised are the kinds of scientists who Max Planck was talking about when he said "science progresses one funeral at a time." People who refuse to acknowledge constructive criticism unless it's sugar-coated will continue to pursue the same ideas even after others have proved them wrong.
This is a systematic issue. Science is full of people with big egos. When scientist A criticizes scientist B's idea, ideally scientist A would think really hard about scientist B's criticism and either say "yes, you're right" or "no, here's what you're missing" (ideally with experiments). Scientists with big egos don't do this. They reject other scientists' criticism out of hand, and they criticize people based on feelings rather than ideas. The problem is contagious: Scientists with big egos attract more scientists with big egos, since those are the people who continue to believe they are great despite the barrage of nonsensical criticism. And egos tend to grow larger, not smaller, as people rise in rank.
Appropriately weighing others' evaluations of your ideas is really hard. It requires the technical skill necessary to come up with those ideas in the first place; the social skill to distinguish between sycophantic praise and true positive evaluation; and the emotional control to ignore anger or disappointment that might result from negative evaluation and focus on the content instead. In my experience, people who can do these things make much better scientists, and are much better to work with. They are less guarded when brainstorming ideas and more willing to change their minds in the face of superior evidence. But in modern science, there are relatively few incentives that favor accurate self-evaluation, and many that favor persistence above all else. In a world where ~5% of incoming graduate students go on to become tenured professors, people who aren't great and know it (or are great but don't know it) drop out early, and the people looking for positions end up being a combination of great people and mediocre people who think they're great.
My goal is to provide an opinion that balances yours, because there are likely many people in your situation, and I don't think they should give up on existing treatments quite so quickly. I know how it feels to see someone you know and love afflicted by mental illness, and I also know how, if treatment as usual doesn't work, it feels like there must be something out there that can help them if you can only find it. But I'm also a neuroscientist (albeit in a subfield without any connection to the study of mental illness) and I know that scientists really do the best they can, and are generally willing to pursue any route if they think it might lead to a better understanding of their subject of study, or, in the case of mental illness, a treatment that can work better than what's out there today.
> Antipsychotics have been shown again and again to be ineffective over the long term:
I am not qualified to assess this evidence, since I don't have an extensive knowledge of this field nor the time to acquire that knowledge, but here is a Cochrane review incorporating 65 RCTs that shows antipsychotics are effective for maintenance:
http://www.cochrane.org/CD008016/SCHIZ_maintenance-treatment...
It is true that the reduction in the risk of relapse appears to decrease with the duration of the study, which is definitely a disquieting finding and deserves further study, but there was still a reduction in risk in the longest study included (3 years).
However, it is not clear whether the changes in CAR are causal or symptomatic. For example, psychosis might lead to a disrupted wake-sleep cycle, which could then lead to blunted CAR. To determine whether there is a causal effect, you'd need to perform a longitudinal study, measuring CAR in patients who are at first normal but some of whom later go on to develop a psychosis, and show that the CAR differences predate the development of psychotic symptoms, instead of developing later. The paper notes that such longitudinal studies are "clearly needed."
Mental illness is complicated. While it can clearly be explained scientifically, if the answer were easy, we would have found it by now. With that said, existing treatments have been shown to improve outcomes in double-blind placebo-controlled studies, even if we can't fully explain why, and that is why they are used. There are certainly problems with these treatments: They don't work for many patients and they often have undesirable side effects. But overall, we know that they help people, which is why we use them.
There are undoubtedly better treatments out there, but either they haven't been discovered yet or they haven't been proven to help. There is no nefarious motive behind sticking to the status quo. Researchers know that, if they were to publish a paper showing spectacular results from a treatment with few side effects, it would be great for the people they're trying to help, and also for them and their career. Instead, people stick to the status quo because, historically, alternative treatments have not been as effective.
Anatomy also helps with the brain, but not nearly as much. People are still trying to figure out how the nematode C. elegans does its relatively simple thing even though the full connectome of its 302 neurons was published 30 years ago. But in larger brains, the fact that neurons are clustered according to what they do and projections are clustered according to organization in the places that they project from provides at least some level of knowledge. We are not merely applying Granger causality willy-nilly to random neural activity. We know what's connected to what (at a gross level) and in 6-layer cortex we even have an idea of the hierarchy based on the layers in which projections terminate (which is how Felleman and Van Essen got Fig. 13b in the paper).
OTOH, I think our failure to understand many neural networks at a conceptual level is quite disturbing, and perhaps a sign that the kind of conceptual understanding we seek will be forever beyond our reach. The authors mention this toward the end of the paper, although I think they overstate our understanding of image classification networks; I've never seen a satisfying high-level conceptual description of how ImageNet classification networks actually see. One possibility is that we simply don't have the right concepts or tools to form this kind of high-level description. Another possibility is that there simply is no satisfying high-level way to describe how these networks; there are only the unit activation functions, connectivity, weights, training data, and learning rule. We can find some insights, e.g., we can map units' receptive fields and determine the degree to which different layers of the network are invariant to various transformations, but something with the explanatory power of the CPU processor architecture diagram in Fig. 2a may very well not exist.
I hope that the brain's anatomical constraints provide some escape from this fate. Unlike most convolutional neural networks, the brain has no true fully connected layers, and this may serve to enforce more structure. We know that there is meaningful organization at many different scales well beyond early visual areas. At the highest levels of the visual system, we know that patches of cortex can be individuated by their preferences for different types of objects, and similar organization seems to be present even into the "cognitive" areas in the frontal lobe. It remains to be seen whether it's possible to put together a coherent description of the function of these different modules and how they work together to produce behavior, or whether these modules don't turn out to be modules at all.
> Either way, if you’ve used iTunes Match as a convenient way to free up space on your Mac by deleting your own copy of any of your music, don’t cancel your subscription in favor of Apple Music if you want to keep that music DRM free.
Given the reference to freeing up space, it seems like he is talking about the original music files within iTunes and not a backup.
> If you haven’t deleted your own copies of your music, then there’s nothing to worry about. If you download onto other devices from Apple Music, those devices will get the DRM versions, but you’ll still have your DRM-free originals.