> Some researchers have challenged parts of this picture, however; a 2024 study, for example, suggested waste clearance is actually faster during waking than during sleep.
That’s a pretty big ambiguity in the story!
That’s a pretty big ambiguity in the story!
Uncertainty isn't good for engagement, even if it's correct.
It is not that hard. It is a fruit roughly the same size and appearance as an orange, but more bitter. See! I explained it. :) Joking asside, what are you trying to explain about grapefruit to your elderly parents? Is it the weird way it interacts with certain medicines?
https://pmc.ncbi.nlm.nih.gov/articles/PMC3589309/
>Our research group discovered the interaction between grapefruit and certain medications more than 20 years ago [1990s].1–3 Currently, more than 85 drugs, most of which are available in Canada, are known or predicted to interact with grapefruit. This interaction enhances systemic drug concentration through impaired drug metabolism. Many of the drugs that interact with grapefruit are highly prescribed and are essential for the treatment of important or common medical conditions. Recently, however, a disturbing trend has been seen. Between 2008 and 2012, the number of medications with the potential to interact with grapefruit and cause serious adverse effects (i.e., torsade de pointes, rhabdomyolysis, myelotoxicity, respiratory depression, gastrointestinal bleeding, nephrotoxicity) has increased from 17 to 43, representing an average rate of increase exceeding 6 drugs per year. This increase is a result of the introduction of new chemical entities and formulations.
Obviously that form is ovesimplified. But since I’m not a pharmacist, nor a doctor I can allow this simplification for myself because it “fails-safe”. That is it might make me refrain from eating grapefruit in a situation where I could safely do so, but it will save me from eating grapefruit in situations where it is not safe. It would be harder if I would need to remember that I must eat grapefruit in some situations and can’t eat in other situations.
The reason why I’m saying this is because this is how I would approach explaining this to someone. By oversimplifying to the point where the safe story is easy to remember. People already understand that they can’t mix alcohol and certain medications. So it is just one more thing you can’t mix with medication.
But your overall point makes sense because so many of these claims are based on studies that boil down to “playing the carefully controlled odds.”
That is my other “tasty fruit with a weirdly dangerous rare side-effect” fact.
Could Ice Cream Possibly Be Good For You? https://archive.is/quPv4
Disclaimer: I'm not a big wine drinker, but ice-cream here I come...
> I have to tell my parents to stop reading
I'm livid about this because this erodes public trust in science. Worse, people don't see that connection...
I don't understand how major news publications can't be bothered to actually reach out to authors. Or how universities themselves will do that and embellish work. I get that it's "only a little" embellishment, but it's not a slippery slope considering how often we see that compound (and how it is an excuse rather than acting in good faith). The truth is that the public does not understand the difference in the confidence levels of scientists for things like "anthropomorphic climate change" vs "drinking wine and eating chocolate is healthy for you." To them, it's just "scientists" who are some conglomerate. It is so pervasive that I can talk to my parents about something things I have domain expertise and written papers on and they believe scientists are making tons of money over this while I was struggling with student debt. I have to explain when I worked at a national lab isn't full of rich people[0]. There's a lot of easier ways to make money... And my parents, each, made more than any of the scientists I knew...
[0] People I know that have jumped ship and moved from lab to industry 2x-3x their salary (these are people with PhDs btw).
https://www.levels.fyi/companies/oak-ridge-national-laborato...
https://www.levels.fyi/companies/lawrence-livermore-national...
[Side note]: I wish we were able to be more honest in papers too. But I have lots of issues with the review system and the biggest is probably that no one wants to actually make any meaningful changes despite constant failure in the process and widespread frustration.
Of course, we haven't even touched on the replication crisis, of which thankfully my dad is blissfully unaware.
A lesson I continually fail to learn is that it isn't about the actual things. Information is a weapon to many people. Not a thing to chase, to uncover, to discover, but a thing that is concrete and certain. I still fear the man that "knows", since all I can be certain of is that he knows nothing.
I've also stopped watching TV entirelly when they shutdown analog TV as that was a nice natural ending of the traditional TV. Continuing required a repeated action (buying MPEG2 tuners when it was obvious that newer codecs will be used in a few years) and it was very easy to just do nothing instead.
This, but also the implication is that if they'll waste $10k on break dancing, then they must be wasting similar amounts on thousands of other programs and the leave it for the reader to imagine what those might be and get angry about whatever they made up in their mind.
> then they must be wasting similar amounts on thousands of other programs
I cannot express how large of sum of money this is. Only that if you think you understand you're wrong (I do not understand). If you are indeed correct and a large portion of the money is composed of things costing under $1m then we're seriously SERIOUSLY fucked. Because a trillion is a million million.
As with most things, I have extremely high confidence that follows a power distribution (go look up Pareto). So there's going to be thousands of things more than $100m in cost.
So I'm extremely confident that if you're picking 10 examples to show on screen and of any single one of those values is under $10m then you're either grossly incompetent or showing rage bait. Because even $10m is chump change when we're talking about these numbers. You certainly aren't providing any meaningful communication to your viewers. At best you're accidentally grossly misrepresenting the problem. While I'm a fan of Hanlon's Razor, extreme incompetence in your domain of expertise is no different from malice.
[0] a bill is 156mm x 66.3mm. California is 1,220km long. 1220000/0.063=19,365,079. Oregon is 580km long. $2T is so much fucking money you could place $100 bills side by side along the length of California and if you did this a thousand times you'd be $63.5bn shy of $2T. If you did it 1033 times you still be $1.5bn short.
I agree there's massive amounts of wasteful programs at that scale. But massive amounts of them gets you nowhere close to the actual number. That's the point.
Money is also very weird since it compounds. Both large wealth and government money are completely different classes, as well as different from each other. People try to think of both those versions of money in relation to how they use money themselves. Which just leads to misunderstandings.
The problem is that without science and stem foundations it is very hard for people to even understand what is and isn’t known.
My mum used to send me all kind of articles about chakras. “there are kids born now who have their sixth chakra open” and “this chakra is orange, and that chakra is indigo”. One day my mom, my then girlfriend, and me were chatting about what specialisation my girlfriend is thinking about pursuing at medical school. She told her that she is thinking about specialising in endocrinology. My mom become really angry and cided us for using such “big words” to “lord our education over her”. So to placate her we explained that it is a doctor who studies hormones, measures hormone levels and treats diseases of the hormone system. She got visibly surprised and the only things she asked “you can measure hormones?”
The conversation continued of course but that question, and the genuine surprise on her face remained with me. The thing is, she trully did not know that we can measure hormones. And if you don’t know that hormones are as real as the legs of the table, and chakras are as real as santa claus, then they both sound equally plausible theories about health. And when you race the stories against each other “i’m not feeling well because my heart chakra is blocked, and I need healing crystals and massages to get well again” vs “i’m not feeling well because my thyroid gland is not producing enough thyroxine, and i need to take suplements in a pill form” then the first one wins because it is simpler and neater sounding. But one is kinda bulshit and the other is a real thing. But you won’t know that unless you understand that we can measure hormones, and nobody even has any idea what it would mean to measure a chakra.
> this thing about the "confidence levels of scientists" for climate change; there is a well-known issue with this myth of a "97% consensus" on that topic.
I do agree we shouldn't embellish things. That this actually undermines a point rather than strengthens it. If that's your point, I'm with you.
I also agree that a lot of stem people are too arrogant. This is especially common in CS and there's a strong negative stereotype that I think people should be aware of.
Honestly, it sounds like you strongly agree with my original statement. How science communication is doing serious harm to public perception of science. I'm not saying abandon education btw, just that we're doing a bad job when optimizing for views rather than strongly constraining for maintaining integrity and honesty
I don’t known what the vast majority thinks. I haven’t talked with them.
> My mom become really angry and cided us for using such “big words” to “lord our education over her”.
Joking aside, I think one of the most important things anyone can learn in life is being comfortable not knowing and being comfortable asking. As a researcher I don't understand other researchers who have such high confidence and are happy to claim they understand when a low threshold is obtained [0]. Personal I feel as I learn a subject I only get to "oh I think I might get this" to only then find a new rabbit hole. Though, personally, I enjoy this. It's why I research ¯\_(ツ)_/¯
I'm not sure how to teach that but I'm at least happy to say I don't know. Like how I totally forgot what an endocrinologist did until you said it lol. There's no shame in not knowing things. But I'm guessing your mom (like my parents) is very uncomfortable with not knowing things. In that case, any answer is better than no answer. Because knowing is valued over understanding. I do think there's social aspects that reinforce this, but I'm not sure what to do besides demonstrate my own stupidity lol
[0] I find people's judgement of understanding a subject is extremely subjective. Even when we remove the set of cases where it's being said to placate another or move a conversation along. I mean honest proclamations.
Compare to the invention of the perceptron, which took a joint effort between a polymathic neurophysiologist and a logician.
sounds similar to the problem with tech coding interviews. ive refactored the backend orchestration software of a SaaS company's primary app and saved 24tb of RAM, while getting 300% faster spinup times for the key part of the customer app, but i bomb interviews because i panic and mix up O(n) for algorithms and forget to add obvious recursion base cases. i know i can practice that stuff and pass, its just frustrating to see folks that have zero concept of distributed systems getting hired because they succeed at this hazing ritual.
but with that said, i suppose no industry or job will ever be free from "no true scottsman" gate-keeping from tenured professionals. hiring someone that potentially knows more than you puts your own job security at risk.
In other fields, it is expected that if you can "talk the talk" you can "walk the walk." Mostly because it is really hard to talk in the right way if you don't have actual experience. Tbh, I think this is true about expertise in any domain. I don't think it is too hard to talk to a programmer about how they'd solve a problem and see the differences between a novice and a veteran.
A traditional engineering interview will have a phone screen and an in person interview. Both of which they'll ask you about a problem similar to one they are working on or recently solved. They'll also typically ask you to explain a recent project of yours. The point is to see how you think and how you overcome challenges, not what you memorize. Memorization comes with repetition, so it's less important. I remember in one phone interview I was asked about something and gave a high level answer and asked if it was okay for me to grab one of the books I had sitting next to me because I earmarked that equation suspecting it would be asked. I was commended for doing so, grabbed my book, and once I reminded myself of the equation (all <<1m?) gave a much more detailed response.
In a PhD level interview, you're probably going to do this and give a talk on your work. Where people ask questions about your work.
IMO the tech interviews are wasteful. They aren't great at achieving their goals and are quite time consuming. General proficiency can be determined in other ways, especially with how prolific GitHub is these days. It's been explained to me that the reason for all this is due to the cost of bad hires. But all this is expensive too, since you are paying for the time of your high cost engineers all throughout this process. If the concern is that firing is so difficult, then I don't think it'd be hard to set policy where new employees are hired in under a "probationary" or "trial" status. It shouldn't take months to hire someone...
What part is too time consuming? What you describe in the engineering interview sounds like a software engineer interview process as well.
The stereotypical software engineering interview is heavily leetcode dependent. It's why leetcode exists and they can charget $150/yr for people to just study it (time that could be spent on learning other things). I mean somewhere like Google you can have 3-6 rounds in the interviewing process.
[0] Maybe you'll use a board or paper to draw illustrations and help in your explanations, but you're not going to work out problems. No one is going to give you a physics textbook problem and say "Go".
I suppose that you will reply "talk to them" or "look at their experience". But, we have learned through squillions of posts here on HN, it just isn't enough. There are many charlatans that will slip through that type of interview process -- "great talker / good looking". This is the reason for the three-decade-long "arms race" in the technical interview process where programming problems become harder and harder over time. (Side comment: Does anyone think that people who can solve harder leetcode problems have a higher IQ? Controversially, on balance, I believe it to be true, and, thus, I think programming tests are a great way to filter for higher IQ candidates.)
LeetCode specifically is famously dissimilar to day to day programming, and therefore (probably) a bad measure for Quality
It's like saying that having a degree is better because it proves that you can follow trough
It's not necessarily wrong, but it's a tertiary situation that doesn't neccesarily correlate (Even if it might, mostly)
> But, we have learned through squillions of posts here on HN, it just isn't enough.
> There are many charlatans that will slip through that type of interview process
The real question is the "optimization" question. Considering the time and cost of the interview process, along with the difficulty to remove bad employees, how effective is the interview process. You are optimizing for the best candidate but it's a constrained optimization problem. Otherwise you need infinite resources. So don't ignore the constraints. There's more that I haven't mentioned.
> Does anyone think that people who can solve harder leetcode problems have a higher IQ?
I've been asked about my former projects, my roles, what I liked or didn't like about them, how do I approach a new project, what did I find most interesting, etc.
I gather there are a lot of fakers in the software dev world. So maybe that's why more places try to make you prove you can actually write code.
Reaching for a book to answer, makes sense to me. That's what you'd do on the job, and nobody would think less of you for it.
I've seen that at BigCo, but that's the exception. Every other place strongly prefers a start date of ASAP, with O(weeks) from initial contact as a next-best option. If you state that you aren't available for months you probably won't be hired.
> concern is that firing is so difficult
There are lots of concerns.
Keep in mind, 95% of resumes are some sort of bot/scam, and 0.5% of the rest are actually at the skill level I'm looking for. There are lots of potential explanations, and I don't think it's that only 0.5% of developers are who I'm looking for (there are sampling biases, survivorship bias, and all sorts of things at play in that data), but from my position doing the screening and interviewing those are the stats I see.
1. Suppose you actually did hire everyone who passed a 1hr screen. You'd still have 20+ failed candidates before you found the right person. Even with a 2-week trial period, that's 3/4 of the year not having your projects properly staffed, a demoralizing experience for all their coworkers, and 3/4 of a SWE-year in wages and benefits lost.
2. Is it really fair to hire somebody if I know there's a 95% chance I intend to fire them? What if they have to move? What if they hadn't quit their old job till I accepted them? I suppose if somebody said they were confident in themselves and were willing to risk a trial period I might allow it, but the current set of social expectations is that once you're hired your employer will spend months at a bare minimum trying to make you successful, I'd want to be cautious with that sort of arrangement out of respect for the candidates.
3. Onboarding is even more expensive than it might seem since it sucks away your more senior talent for the training. If the cost of a bad engineer were just the normal day-to-day post-onboarding it wouldn't be _that_ terrible (you still have attrition and other knock-on effects to worry about), but having multiple onboarding sessions for a single hire (because of multiple trial periods) is the most expensive part of the process.
etc
> General proficiency can be determined in other ways, especially with how prolific GitHub is these days
I agree. Walking through a project with a candidate is one of my favorite interview sessions. They tend to be more comfortable, I tend to learn more, and I get to learn something about their technical communication on top of any coding knowledge.
Not everyone has a GH with anything interesting, so I make other interviews available for everyone, but my life is a little easier if public "proof" (till you talk to the candidate you really have no idea how much they know or who wrote what, but I thankfully haven't seen that problem yet in an interview) exists.
> Suppose you actually did hire everyone who passed a 1hr screen.
What I talked about is something people already do in other domains. We're not talking about something theoretical here. There's even other commenters saying that what I said was similar to how they were hired. So again, we're not talking about something theoretical.
And this all ignores that the authors are PhD scientists. So I'm confused how this is categorized as "medical field" in the first place. I found that the ability to memorize is essentially useless in PhD level biological science (I studied immunology, so I can't necessarily speak to other fields), and it is all systems level conceptualizing.
I think this is a team with many talented people who came together to do their best. But I'm sure I'm naive. There seems to have been a lot of new interest and debate about what is happening in the glymphatics sphere.
Others can be guilty of similar sins, of course, and since the early 20th century, when philosophy and the classical liberal arts in general evaporated from school curricula, scientists have generally been quite poor at this, despite unwittingly treading into subject matters they are ill-prepared to discuss. Compare how a Schroedinger or a Heisenberg[2] talk about philosophical stuff, and then look at someone like Krauss [3]. The former may not have been great philosophical thinkers, but there is a huge difference in basic philosophical education and awareness, and these are not just isolated cases.
[0] https://edwardfeser.blogspot.com/2011/01/against-neurobabble...
To really answer your question, I think I need to talk about the books modern day neuroscientists are writing and I have to say I simply agree. I think these self-help kind of books are not good! Too bad they are so easily propagated in the media.
The classic meme is that MDs love organic chemistry, but they hate biochemistry [1], because one is about memorization and the other is...less so, anyway.
But then again, neuroscientists do tend to love their big books of disjointed facts, so maybe it's more like medicine than I realize. I remember the one class I took on neuroscience was incredibly frustrating because of the wild extrapolations they were making from limited, low-quality data [2], that made it almost impossible to form a coherent theory of anything.
[1] ...except for the Krebs cycle! Gotta memorize that thing or we'll never be able to fix broken legs!
[2] "ooh, the fMRI on two people turned slightly pink! significant result!"
It's not impossible for people who are good in memorization to also be good in understanding systems.
Those people, in turn, are the ones doing this research.
Although common, it's not quite so that only people with a pure medical background do neuroscience.
All in all, having met quite some people in the field, the things you're hinting at never occurred to mee as an actual problem. My guess is because the people who actually have issues get weeded out very soon. Like: before even finishing their PhD. It's not an easy field.
and it might not be "good at memorization" that's being selected, it might be "conscientiousness", one of the Big Five, and a relatively important parameter.
That being said, I think the rise of "evidence-based" medicine is also causing issues. It gets used as a cop-out to avoid thinking about the mechanics of what is actually happening in an injury. While this is certainly a good things for treatments where A or B superiority is uncertain, there's a lot of cases where I think an RCT just doesn't really make sense.
A pet example:
I broke my ankle recently, and this dug into the literature and common practice. A significant number of people will get end-stage arthritis a few years after "simple" ankle fractures and often the doctors have no idea why. At the same time, an important part of ankle anatomy is often left unfixed (the deltoid ligament) because a few studies back in the 80s found it wasn't necessary to fix it. The bone that serves an equivalent purpose IS fixed (if broken) though. Mechanically, they restrict the ankle joint and prevent it moving in certain directions.
When presented with biomechanical reasons for fixing it, and concurrent common poor outcomes for some patients, I've seen the response from surgeons thusly - "it's not supported by evidence" presumably because there isn't an RCT demonstrating definitive superiority.
So much of medicine and treatment is literally just hearsay and whatever your surgeon happened to read last week. As a whole the standard is rising, but so much research is so disjoint, disorganised and inconsistent that doctors often have no definitive guidance. It's probably more of a problem in some fields (like ortho) than others, but its still surprising when you see it yourself.
> So much of medicine and treatment is literally just hearsay and whatever your surgeon happened to read last week.
> Also note that the medical field selects hard for people who can memorize information, to the exclusion of people who can understand systems.
I understand testing knowledge and intelligence is an intractable problem, but I my main wish is that this would simply be acknowledged. That things like tests are _guidelines_ rather than _answers_. I believe that if we don't acknowledge the fuzziness of our measurements we become overconfident in them and simply perpetuate Goodhart's Law. There's an irony in that to be more accurate, you need to embrace the noise of the system. Noise being due to either limitations in measurements (i.e. not perfectly aligned. All measurements are proxies. This is "measurement uncertainty") or due to the stochastic nature of what you're testing. Rejecting the noise only makes you less accurate, not more.
I refer to them as "fuzzy databases" (this is a bit more general than transformers too), because they are good at curve fitting. There's a big problem with benchmarks in that most of the models are not falsifiable in their testing. Since it is not open of what they have trained on, you cannot verify that tasks are "zero-shot"[0]. When you can, they usually don't actually look like it. Another example is looking at the HumanEval dataset[1]. Look at those problems and before searching, ask yourself if you really think they will not be on GitHub prior to May 2020. Then go search. You'll find identical solutions (with comments!) as well as similar ones (solution is accepted as long as it works).
IME there's a strong correlation between performance and number of samples. You'll also see strong overfitting to things very common.
That said, I wouldn't say LLMs aren't able to perform novel synthesis. Just that it is highly limited. Needing to be quite similar to the data it was trained on, but they __can__ extrapolate and generate things not in the dataset. After all, it is modeling a continuous function. But they are trained to reflect the dataset and then trained to output according to human preference (which obfuscates evaluation).
Additionally, I wouldn't call LLMs useless nor impressive. Even if they're 'just' "a fuzzy database with a built in human language interface", that is still some Sci-Fi shit right there. I find that wildly impressive despite not believing it is a path to AGI. But it is easy to undervalue something when it is highly overvalued or misrepresented by others. But let's not forget how incredible of a feat of engineering this accomplishment is even if we don't consider it intelligent.
(I am an ML researcher and have developed novel transformer variants)
[0] A zero-shot task is one that it was not trained on AND is "out of distribution." The original introduction used an example of classification where the algorithm was trained to do classification of animals and then they looked to see if it could _cluster_ images of animals that were of distinct classes to those in the training set (e.g. train on cats and dogs. Will it recognize that bears and rabbits are different?). Certainly it can't classify them, as there was no label (but classification is discrimination). Current zero-shot tasks include things like training on LAION and then testing on ImageNet. The problem here is that LAION is text + images and that the class of images are a superset (or has significant overlap) with the classes of images in ImageNet (label + image). So the task might be a bit different, but it should not be surprising that a model trained on "Trying for Tench" paired with an image of a man holding a Tench (fish) works when you try to get it to classify a tench (first label in ImageNet). Same goes for "Goldfish Yellow Comet Goldfish For The Pond Pinterest Goldfish Fish And Comet Goldfish" and "Goldfish" (second label in ImageNet).
(view subset of LAION dataset. Default search for tench) https://huggingface.co/datasets/drhead/laion_hd_21M_deduped/...
(View ImageNet-1k images) https://huggingface.co/datasets/evanarlian/imagenet_1k_resiz...
(ImageNet-1k labels) https://gist.github.com/marodev/7b3ac5f63b0fc5ace84fa723e72e...
> if something happens comprehensively across fields, it's likely to be a good idea.
This is related to "trust, but verify". If a big player is doing something it is worth looking at to see if it's a good idea for you. Same with when something is popular. But you have to be careful too. It's easy to miss context or small details that make a big difference. As an example, Google has a surplus of high quality candidates. Any arbitrary filter is helpful to them as they just need to down select. So a highly noisy process (i.e. random with a small bias) will yield good results for them. You'll even MEASURE positive results! This isn't necessarily (might be, might not be) true for anyone who isn't big tech or highly bureaucratic. (Same is true for college admissions)
It's important to remember that big players don't maintain their status simply because no other can out innovate. Rather momentum is a bitch. It can make up for a lack of innovation and still out compete.
But in my experience neuroscientists have to have a solid level of systems thinking to succeed in the field. There are too many factors, related disciplines (from physics to sociology), and levels of analysis to be closed off.
Honestly 'our knowledge of [X] is largely mechanistic and without a sense of the larger picture' is weirdly applicable to most scientific fields once they escaped the 'natural philosophy' designation.
This sounds like one of those complete bullshit memes that certain groups of people like to repeat. Very similar to tech people being "creatives" while other groups like sales are somehow not. Utter bullshit.
> Compare to the invention of the perceptron, which took a joint effort between a polymathic neurophysiologist and a logician.
While cross-field collaboration often yields the best insights, I hope you're not implying that computer scientists are somehow better at "understanding systems" compared to biologists. Not only are computer scientists hugely guilty of pretending that various neural networks are anything at all like the brain (they are not), its also the case that biological systems are fantastically more complicated than any computing system.
Easy to agree with
> to the exclusion of people who can understand systems
On what basis do you draw this conclusion? I'm not saying the field is full of systems thinkers, but I have no evidence that they are at higher or lower concentration than many other skilled disciplines. Many of the specialties within medicine require systems thinking to be effective physicians.
Neuroscience is in the same quadrant of the knowledge / hype plot as nutrition science.
I think there's a sense in which that's true (I've especially heard it with respect to the foundations of maths), but I worry about that way of thinking. There absolutely are places where we have consensus, even on subjects of extreme complexity. And the fact that we really do have consensus can be one of the things that's most important to understand. I don't want people doubting our knowledge that, say, too much sugar is bad, that sunscreen is good, that vaccines are real and so on.
A lot of what passes for nuanced decoding of the social and institutional contexts where science really happens, looks to outsiders like "yeah, so everything's fake!"
And when the job of communicating these nuances falls into the hands of people who don't think it's important to draw that distinction, I think that contributes to an erroneous loss of faith in institutional knowledge.
There's a difference between "cigarettes cause cancer" and "phones cause cancer". The former is very definitely true, confirmed by many studies, and the health impact is very significant. The latter is probably untrue (there are studies that go both ways, but the vast majority say "no cancer"). Even if there's any impact, it's extremely minimal when compared to cigarettes.
People can't distinguish between those two levels of "causes cancer" in a headline.
Neuroscience postdoc here. Yes. This is broadly true of all science communication in mass media. https://phdcomics.com/comics.php?f=1174
Science requires, at its core, falsifiability. Just a little education on the philosophy of science is enough to rid most scientists of bravado; to make them wince at words like "fact" and "prove" in scientific contexts.
I imagine this has an impact on personality as well, in the long run.
The fact that you had to add the parenthetical here to hedge your bet demonstrates that you don't even entirely believe your own claims.
[0]: https://www.wiley.com/en-us/Philosophical+Foundations+of+Neu...
[1]: https://cup.columbia.edu/book/neuroscience-and-philosophy/97...
> Many STEM people hate this because they want to axiomatically believe materialist science can reach everything, despite the evidence to the contrary.
Do we have actual evidence that it can't reach everything? That would be "evidence to the contrary". What you have given is evidence of its inability to reach everything so far, in its current form. That's still not nothing - the pure materialists are committed to that position because of their philosophical starting point, not because of empirical evidence, and you show that that's the case. But so far as I know, there is no current evidence that they could never reach that goal.
[Edit to reply, since I'm rate limited: No, sauce for the goose is sauce for the gander. The materialists don't get the freebee, and neither do you. In fact, I was agreeing with you about you pointing out that the materialists were claiming an undeserved freebee. But you don't get the freebee, for the same reason that they don't.]
The philosophical definitions also sometimes preclude any human from being able to meet the standard, e.g. by requiring the ability to solve the halting problem.
Without knowing which thing you mean, we can't confidently say which arrangements of matter are or are not conscious; but we can still be at least moderately confident (for most definitions) that it's something material because various material things can change our consciousness. LSD, for example.
I feel really encouraged here, because I think this example has surfaced recently (to my awareness at least) of a good example of material impacts on conscious states that seems to get through to everybody.
I think the one about drugs is helpful because it speaks to the special things the mind does, the kind of romanticized essentialism that's sometimes attributed to consciousness, in virtue of which it supposedly is beyond the reach of any physicalist accounting or explanation.
Is software electrical? It certainly runs on electrical hardware. And yet, it seems absurdly reductionist to say that software is electrical. It's missing all the ways in which software is not like hardware.
Is consciousness similar? It runs on physical (chemical) hardware. But is it itself physical or chemical? Or is that too reductionist a view?
(Note that there is no claim that software is "woo" or "spirit" or anything like that. It's not just hardware, though.)
Humans being unable to figure out how inanimate matter gives rise to consciousness is not evidence that "strict materialism on consciousness is misguided". Or is there some other evidence I'm unaware of?
> Please don't fulminate. Please don't sneer, including at the rest of the community.
Sure, and maybe Cthulu is about to awaken the sunken city of R'lyeh. You can't prove me wrong either.
https://www.thetransmitter.org/glymphatic-system/new-method-...
> The new paper used many of the techniques incorrectly, says Nedergaard, who says she plans to elaborate on her critiques in her submission to Nature Neuroscience. Injecting straight into the brain, for example, requires more control animals than Franks and his colleagues used, to check for glial scarring and to verify that the amount of dye being injected actually reaches the tissue, she says. The cannula should have been clamped for 30 minutes after fluid injection to ensure there was no backflow, she adds, and the animals in the sleep groups are a model of sleep recovery following five hours of sleep deprivation, not natural sleep—a difference she calls “misleading.”
> “They are unaware of so many basic flaws in the experimental setup that they have,” she says.
> More broadly, measurements taken within the brain cannot demonstrate brain clearance, Nedergaard says. “The idea is, if you have a garbage can and you move it from your kitchen to your garage, you don’t get clean.”
> There are no glymphatic pathways, Nedergaard says, that carry fluid from the injection site deep in the brain to the frontal cortex where the optical measurements occurred. White-matter tracts likely separate the two regions, she adds. “Why would waste go that way?”
>That’s a pretty big ambiguity in the story!
no, it's not: "waste clearance faster during waking than sleep" does not mean it's adequate to the job, and waste clearance at night could still be critically important. We also do not know what the waste consists of comprehensively and having a specific sleep system implies its doing something.