D-Machine

Interesting. Pink Lady is a favorite for me, and Sweetango is great too, but I'd consider Cosmic Crisp very, very close to Pink Lady in overall balance (I do agree Pink Lady is better though). I'm in Canada and Cosmic Crisp is special / protected and seems to always have to come from the States, whereas I can get the others fresher and grown locally, so perhaps that is a factor.

Saying fruit isn't "healthy" doesn't mean it is unhealthy, there are plenty of neutral things here. But if you are treating fruits and veggies as the same (e.g. X servings of fruits and veggies), generally, anyone making X be 100% fruit is likely going to be less healthy than anyone making X be 100% veggies. And since all fruits do contain a lot of sugar (EDIT: and thus calories, which generally we already get too much of today), you should indeed moderate your consumption of fruits.

It is very hard, by contrast, to say a person can eat "too much veggies", unless they are doing something crazy like eating extreme amounts of the same greens high in oxalates or something.

Basically, enjoy a fruit or two a day, if you like them. Or don't. But you aren't "eating healthy" just because you eat a lot of fruit, nor are you eating unhealthily if you eat zero fruit.

It is reasonable to presume that balance has been undermined. In general "eat your fruit and veggies" should probably be modified to "eat your veggies", which generally have fiber and better nutrient density, without the unnecessary sugar. Modern fruit really is basically plant candy. And sure, that's better than actual candy or junk food, but I no longer think it is really scientifically tenable to call most fruit "healthy".

Wait what? Cosmic Crisp is like the clearest example of a balance between sweet and tart. What would you consider a balanced variety?

Set and setting can help make a positive experience likely, yes, I think what proponents often miss is that for the vast majority of people, the experience will mostly just be "interesting" and "memorable", and not particularly transformative. I.e. transformative / curative effects seem to be rare, IMO for the reasons I already stated.

Oh, I don't doubt that sometimes something fundamental can be altered. The best sort of broad explanation I've seen that jives with the experience is maybe the one I've found here: https://www.frontiersin.org/journals/human-neuroscience/arti..., which I think would agree with your notion of a "reset" to fundamental neural structures. And yes, for certain conditions, like cluster headaches, as far as I know, psychedelics are the only things showing much real promise.

It can also just be easy for some proponents to forget that tonnes of people do and have done these things, with no clear significant lasting effects. And it is also common even for enthusiasts to say they they need to do take trips somewhat regularly (e.g. every few weeks or months) to regain the benefits. One-off miracles obviously happen, but I think are statistically likely the exception. And you can reverse or reject your insights, so for sure the trip is only one piece of the puzzle.

I'd love to see more serious research on psychedelics in general, to better engineer for useful and changing experiences. As it stands, just "take the psychedelic, manage your set and setting, and you'll have a significant positive effect" is generally not very plausible nor I think actually supported empirically or even by most anecdotes.

Right, when you take it, it becomes clear it just injects salience / profundity / meaning into whatever you happen to be focused on or have on your mind (EDIT: mostly this is the main effect, but there can be novel perspectives / insights, and other audio-visual changes, but IMO it is the felt meaning that primarily drives the more credulous claims). Without adequate preparation, this is likely to be worthless in most cases, harmful in other cases, and helpful in some again. However, not all causes of depression or addiction are about accepting death, or a salience / meaning problem, and even when that kind of issue is involved, a momentary experience of profound meaning is NOT actually necessarily transformative either (i.e. you can and in fact must still choose how to interpret that experience, once out of it).

So it would actually be very surprising if it was just a clear net positive overall

While I am quite skeptical of the claims linked above, that link does indeed cover the FNR at the FPR of 0.005, and finds it broadly to be on the same order of magnitude, i.e. also below 0.005.

We just perceive it as such, and this should be fairly hard to argue against with all the scientific advances we have made up to this point, at least as long as you assume consciousness involves biology and physics at least somewhat.

Otherwise, you can't explain e.g. smooth perceptions of low FPS stimuli, delayed reaction times, and must ignore obvious limits on various biological and neurological rhythms, or other possible limits on continuity (e.g. quantum stuff) and rates generally.

If you are interested in some serious discussion, see https://lossfunk.com/papers/ai-consciousness.pdf, especially the early section "Consciousness as Family Resemblance". I suppose another is Ned Block on consciousness being a "mongrel concept", and the distinction between access vs. phenomenal

The first paper picks out e.g. arousal/wakefulness, phenomenal quality / qualia, unity (how we feel sensory inputs and qualia as a unified scene), access consciousness (instrumental self-observation and modification broadly), meta-cognition and self-modeling, emotional valence (e.g. pain/pleasure).

One might also include intelligence (abstract reasoning / argument, information integration and abstraction, attention) broadly, and also agency / desires / drives / will. Insofar as these are aspects of consciousness, yes, AI (and simpler algorithms and mechanistic structures) demonstrate aspects of consciousness. But insofar as embodiment, self-reflexivity and qualia (phenomenal consciousness) are the more mysterious and more obviously unique aspects of consciousness, current LLMs very clearly are lacking these things in most ways (whereas animals are much less clearly lacking, especially when you get to mammals and primates).

Seriously, just ask an AI this stuff, you'll get very detailed responses, nothing I am saying here is new or obscure.

The major error made by most people in this thread is thinking it is possible to give a single definition of consciousness that is coherent and matches common usage. The folk concept of "consciousness" couldn't be a more clear definition of a family resemblance category, so discussions using the folk concept are an utter waste of time.

Move to the different aspects / parts / things involved when we talk about consciousness (experience / phenomenal consciousness, self-modeling, intelligence, agency, embodiment, wakefulness/alertness, attention, etc) and you can have very clear, meaningful, and unambiguous discussions on almost every point, but there is no coherent unified "consciousness" as normal people use it, and the folk concept can't be salvaged.

This article is bad because it just keeps trying to make the folk concept do work that the concept is simply too messy to handle usefully. But in fact if you avoid trying to find some mysterious essence or all-capturing definition, there is huge progress and lots of interesting stuff to say (https://plato.stanford.edu/entries/consciousness/).

I've seen papers claim that there are anywhere from 12 to 40 competing definitions (https://philpapers.org/rec/VIMMAT), or, more accurately, there are something like 12 to 40 different aspects which all relate to "consciousness", which is very clearly a family resemblance category.

"Is X conscious or not" is an entirely unserious question today, unless this is just a headline followed by actual (and explicit) examination of the various aspects of consciousness being discussed. But, even still, LLMs are probably only conscious in like 2-3 or so ways, most of those meaning broadly "intelligence", i.e. reasoning, problem-solving, etc. When it comes to anything experiential or embodied, AI might eventually get more of these, but LLMs based on recursively applied linear algebra are clearly missing too many core aspects of consciousness to be considered conscious in any broad sense.

Embarrassingly incompetent article. Given that one can observe up to 40 definitions of consciousness (https://philpapers.org/rec/VIMMAT - also many definitions are unrelated at all), "consciousness" is almost certainly just a family resemblance category at best, and talk about whether or not something is "conscious" without providing definitions is simply completely unserious.

To make progress, you have to talk about kinds / aspects of consciousness. AI does and will share some of these aspects with humans, but it will not and does not share others. It is really that simple. For the most part, modern AI implemented via LLMs has almost none of the stronger or most core aspects of consciousness.

For huge parts of the article "intelligence" and "consciousness" are conflated, which is mostly extremely unhelpful, as this is not generally a core feature of most aspects of "consciousness".

The moral arguments are also incompetent, i.e. claiming "Moral reasoning is [...] is necessarily subjective" is just clearly empirically wrong, as in fact LLMs can produce moral reasoning (i.e. verbalized moral arguments that are coherent), as can p-zombies (i.e. there is nothing 'necessary', in the philosophical sense of the term, about subjectivity here). The only way the argument holds is if you tautologically define moral reasoning as requiring that reasoning be produced by a consciousness, but this is question-begging.

All these policies actually sound good, SSRIs should not be first-line, as there is extremely limited evidence of meaningful effectiveness for anti-depressants generally.

Mmeta-analytic assessments of effect sizes show the observed effects are usually below what is required to count as a minimal clinically important difference, and antidepressants only target generally the "positive" symptoms of depression (sadness, anxiety) while doing little for the "negative" ones (anhedonia, lack of meaning, lack of motivation). They also have some serious side-effects, like emotional blunting and severe sexual dysfunction, the latter of which can persist for months even after stopping to take the drugs.

Even the usual excuses people make for these drugs ("Sure, the average effect is small, but they really help some people" and "Eventually the doctor finds the right one for you") are generally not supported by actual studies addressing these claims either.

There absolutely should be more monitoring and less careless prescribing of SSRIs and anti-depressants generally.

Ironic because it is the people who push for just passing everyone that are actually doing it to just "make the problem go away", in reality.

There's no hypothetical here IMO, this is a real-world problem, and also you aren't limited to pass/fail decisions as a teacher, except in exceptional cases of borderline grades. Otherwise, there is a passing grade / requirements, and grades can be determined by objective tests (all students get the same difficulty tests). Also you have something like an average of many courses over many years to make the pass/fail decisions, ultimately, if we are talking about getting a diploma and/or graduating high-school here.

Also, it depends what you see the discussion as. If laws are supposed to do the right thing, then "pass everyone always" is really starting to look like the wrong thing, even where the intentions are seemingly "good" because they avoid "disparate impact" (in the short term on very narrowly-chosen metrics). Then if your argument is "yeah well we can't do the right thing because lawsuits", well, yes, I agree, practically, but then these lawsuits are basically also evil and/or misguided.

I'd prefer more proof / context than GP gave, but I personally find it very useful to see people making judgements about AI-assistance of articles. Almost no such articles are worth my time, and the more HN people saying it, the more I know not to click past the HN headline.

> Could you prove the disparate impact is random and your pass criteria isn’t racist?

Can those in favor of grade inflation and meaningless credentials prove their decisions also don't have disparate impact and aren't racist? Based on some recent US Supreme Court decisions re: affirmative action, it would seem unlikely this case would be any different. The hard questions about long-term harms to students and society are simply not being asked seriously enough.

Requiring years of schooling that is essentially worthless / provides credentials with no information also has disparate impacts, possibly worse than just properly failing people and letting them sort themselves / be sorted into positions that are actually suitable for them and allow real growth. Schooling is a huge percentage of a modern person's life now.

Yes you are citing my link... which is pure speculation. Do you have anything to actually add?

I asked ChatGPT a simple baking question today (https://chatgpt.com/share/6a1a1445-cc10-83ea-bf1f-957c07ce7e...), and got this rather strange preamble before my response:

    "Could hidden user memory materially change what I should recommend? **No.**"

A typical answer then followed. Users on Reddit report the behaviour as well (https://old.reddit.com/r/ChatGPT/comments/1traouv/why_is_it_...), and the linked article suggests this is new.

The thing is, I have memory disabled. So is this an internal prompt just being exposed ("Does the user have any memories that are relevant? No, [because they don't have any].") or does it mean they are in fact keeping hidden memories / context and using these to inform responses, but didn't find anything relevant for this particular question?

While I suspect the former, the possibility of the latter concerns me somewhat.

Yes, sorry about the edits.

IMO the correct framing most supported by the evidence is that a few vulnerable populations (most likely within a certain age bracket, and already dealing with other significant life issues) are definitely at risk of nontrivial harm from social media. Otherwise, for the majority, it is likely a wash. And since the bias in studies is to look for negatives (much like drug studies don't properly measure negative side effects until much later), we also can't say if there aren't subgroups benefiting hugely as well (e.g. autistic people that can connect online, or other people with unusual interests that before would have remained isolated and disconnected, feel crazy, etc).

So, yes, small effects can be important. The observed effects for social media are quite small and consistent with being driven solely by a small, vulnerable population, however, and this make broad social injunctions and moral panic less defensible.

Also, these are effects on self-report or other psychological instruments, where in general you need to find something like a minimal clinically important difference before you can determine if you care practically about these things. E.g. if a standardized regression coefficient of 0.1 translates to a 1-point shift on a 20-point life-satisfaction scale, is this even something I (or anyone) can even notice? Does it even rise above measurement error?

Since no one is doing that kind of research here, we just get these (relatively meaningless) standardized effect sizes, and it is really basically impossible to know if we should care at all about the observed effects. This is mainly what I mean by the evidence being flimsy / weak, it is really too inconclusive to drive decisions at this point.

> That sounds like we'll devolve into wars over resources

Two astronauts meme: "Wait, it's all been over resources?" "Always has been"

You're gish-galloping a bunch of random studies, most of which appear to be cross-sectional. I've linked a broad review.

Even the longitudinal studies are poor here. See, for example, as this Nature article notes:

    "The study has multiple limitations that need to be considered. First, to interpret the parameters from our analyses as estimates of causal effects one would need to adopt the following assumptions: (a) there are no time-varying unobserved confounders that impact the relation between social media use and life satisfaction; (b) the model adequately accounts for unobserved time-invariant confounding through the inclusion of a random intercept; (c) there is no measurement error in the variables; (d) the time interval between studies (one year) is the right length to capture the effects of interest; and (e) the bidirectional links estimated by our longitudinal model are linear in nature. Only if these assumptions are met can this observational study be said to capture the causal effects between social media and life satisfaction. Second, the data are self-report and therefore only allow inferences about the impact of self-estimated time on social media, rather than objectively measured social media use." https://www.nature.com/articles/s41467-022-29296-3#Sec2

I'd also suggest looking at the coefficients (effect sizes) in the above (standardized regression coefficients barely approaching 0.2 - and this is one of the stronger findings), and other articles. The effects here, even if we were to pretend they were clearly established, are incredibly tiny. Examples:

- social media explaining only 0.4% of variance (https://pubmed.ncbi.nlm.nih.gov/30944443/)

- social-media/mental-health effect around β = .061 (https://christopherjferguson.com/Social%20Media%20Meta.pdf)

These are basically nothing, and yet you have such absolute confidence from people that social media is this big harmful thing. The evidence just isn't there.

No, the evidence is quite flimsy and correlational, and this is clearly a moral panic.

EDIT: See e.g. https://www.nationalacademies.org/read/27396/chapter/6#93, and if you think this is what constitutes "clear evidence", well, you have some very questionable epistemological standards.

EDIT2: Also, limit yourself to proper longitudinal studies and then look at the actual effect sizes reported. You will find, yes, there is broad evidence that social media is likely slightly more harmful to adolescents than beneficial / not harmful, but the actual effect size is so tiny broad interventions are unlikely to have practical consequences. I.e. the most plausible explanation is that the vast majority people are not meaningfully affected, and small subgroups benefit and/or are negatively affected.

It is the usual pseudoscientific / social science attempts to launder "statistical significance" (which you get trivially with enough samples) into practical significance, in order to justify sweeping societal changes.

But with "consciousness" we don't have even a stipulative definition, more like 40 different competing definitions (https://philpapers.org/rec/VIMMAT) which are in many cases only loosely related, and generally are talking about very different things. When the situation is this bad, I am skeptical you can make scientific progress.

Except you can't be sure it isn't producing nonsense when you do this, and generally the model(s) will be overconfident. This has been studied, see e.g. https://openreview.net/pdf?id=E6LOh5vz5x

    > An alternative way to obtain uncertainty estimates from LLMs is to prompt them directly. One benefit of this approach is that it requires no access to the internals of the model. However, this approach has produced mixed results: LLMs can sometimes verbalize calibrated confidence levels (Lin et al., 2022a; Tian et al., 2023), but can also be highly overconfident (Xiong et al., 2024). Interestingly, Xiong et al. (2024) found that LLMs typically state confidence values in the range of 80-100%, usually in multiples of 5, potentially in imitation of how humans discuss confidence levels. Nevertheless, prompting strategies remain an important tool for uncertainty quantification, along with measures based on the internal state (such as MSP).

IMO it is you who are moving the goalposts, most likely in an attempt to hide the fact you were unaware of calibration before this discussion.

> It would still be incredibly useful to have a machine that can merely matches the equivalent statement of confidence or uncertainty that a human would assign to their mental model, even if badly calibrated.

If human feelings are badly calibrated, they are useless here too, so no, I don't agree. Things like "confidence" only matter if they are actually tied to real outcomes in a consistent way, and that means calibration.

> But If we artificially constraint outputs to "Yes" and "No", and calculate the softmax for Yes to be 0.7 and No to be 0.3, that does lead to a straightforward probability calculation. [Not the naïve calculation you would expect, because of how softmax is computed. But you can derive an equation to convert it into normalized probabilities.]

There is nothing straightforward about this, and no, there is no such formula.

> I'm not talking about calibrated probabilities at all. Just the notion of "how confident do I feel about this?"

If all you care about is vibes / feels, sure. If you actually need numerical guarantees and quantitative estimates to make your "feelings" about confidence mean something to rigorously justify decisions, you need calibration. If you aren't talking about calibration in these discussions, you are missing probably the most core technical concept that addresses these issues seriously.

> The question is about relative uncertainty, and the softmax values are just fine for that.

They really aren't, especially if you consider the chain of thought / recursive application case, and also that you can't even assume e.g. a difference of 0.1 in softmax values means the same relative difference from input to input, or that e.g. an 0.9 is always "extremely confident", and etc. You really have no idea unless you are testing the calibration explicitly on calibration data.

> But there are alignment tools to extract out these latent-space probabilities for researchers in the frontier labs

You can get embeddings: if you can get calibrated probabilities, you'll need to provide a citation, because this would be a huge deal for all sorts of applications.