Are you talking about at the time of Earth's formation, as in, early Earth gets a magnetic field, which attracts more iron and nickel to the core as it's forming? That seems unlikely, since the Earth's magnetic field is caused by convection currents of iron around the core, which requires the immense heat and pressure of an entire rocky planet around it to work. (But I don't know.)

Are you instead asking whether metal would be attracted to Earth since after Earth's formation through today? In short, yes. Our magnetic field has components both inward toward the core and parallel to the Earth's surface. On the surface we humans mostly can see the effects of the magnetic field as exerting a force on a compass needle. The needle is very light, carefully balanced, and shielded from the air so that there are as few additional forces involved that could overwhelm or resist that caused by Earth's magnetic field. Also, a compass needle is magnetized so that it aligns correctly and at maximum force with magnetic North. In principle a non-magnetized iron (or other ferromagnetic) needle can also be used in a compass, following recalibration. [See a StackX explanation on this, though the answer appears to be interpreting the necessary energy as that needed to permanently magnetize a needle, as opposed to simply the Zeeman energy, which is a net gain when the sum of alignment directions of its tiny component magnetized crystals with respect the external magnetic field is calculated. Thus as long as resistance in the compass chamber is minimal, the needle should eventually align. Magnetite as lodestone, incompletely magnetized, was used in this way.]

Note that in orbit the magnetic field is only about half as strong as on the surface (where it is already quite weak by human observation standards), and it decreases steeply further out, but low orbit is perhaps the first place where you might first think of a free unmagnetized iron or nickel (a ferromagnetic metal) object being noticeably affected by Earth's magnetic field. There's a lot of subtleties here that I'm sure I'll miss, but let's try a calculation: taking magnetic saturation into account (thanks u/mfb- ), the max magnetization of steel is 2 T, and if we have a 1 m^3 block of steel in space then that's a magnetic dipole moment of 2 A m^2, so with a magnetic field in orbit of 35 * 10^(-6) T, the forces experienced in orbit are at max 7 * 10^(-5) N. Compare this to, say, the total drag forces in orbit, say at ISS orbit at 400 km (p. 14) ~ .001 dynes/cm^2 * 100^2 cm^2 * 10^(-5) N/dyne = 10^(-4) N. So at most, the magnetic forces on this (unrealistically) enormous metal block in orbit would be of comparable magnitude, a bit less, than the not insignificant drag at the ISS, which is more significant than I expected if I took into account everything needed (which is a big "if").

Terrific job with attribution on the image! (In case you haven't been here this month, I'm kinda big on this.) What I particularly like is that you note the different years for data being used on each chart, which is a detail that is frequently omitted in this sub. (Although it appears you forgot to do this for the map at the bottom of prisoners/100k; it's not a huge deal because that stat is widely published, and the rest of the charts are dated; no visualization or other work gets everything perfect without multiple reviews anyway.)

The graphical layout seems more appealing to me than I'd expect. Normally I'd be put off by such a monochromatic color scheme, but since all your charts are displaying raw or scaled N with color (Except the top right, which doesn't do the gradient), it's actually an appropriate use. It looks aesthetically well-balanced taken from a distance, which is impressive for having 6 charts in there.

I do think the text is excessive however. Descriptions in plain-size font can be fine and great. (That is long as your users are reasonably expected to be able to read it -- so a visualization like this would be have a modified form if put into a slideshow, say, probably by separating each chart onto individual slides and reducing/summarizing the side text as full-size bullet points.) However, I think your descriptions are unnecessarily lengthened with your own interpretations of the data that may not be clearly demonstrated within the visualization alone, especially the introductory text. What you state affirmatively on the visualization should be reasonably supported by what is presented, and of course, since it's a visualization, you want a maximum of "show, don't tell". (There are several arguments you make that can only be supported by a detailed analysis going far beyond the charts given here; if you really feel the need to reference one or two of those arguments it would be more authoritative if you write something like "... and this is likely caused by such-and-such [Smith & Payne 2015]", or a numerical superscript, with additional source cited in the corner (a shorthand citation is fine for this kind of thing).)

Hope this can be useful. Very nice job overall.

The essay appears imho to do most of its pitching for studying philosophy of education by pitching the philosophy of other topics, like epistemology.

>With this in view, it seems obvious that education should matter to philosophy. And not just because education raises new and unexplored issues, but because it provides opportunity for a fresh approach to old issues that philosophy has traditionally struggled with. We start to see, for instance, that an adequate epistemology must recognise that the manner in which knowledge is acquired, communicated and shared is internal to the nature of knowledge itself, and that the metaphysics of personhood needs to countenance the formation of reason if we are to understand how rationality and animality are united in the human person.

He makes only a cursory mention of any "new and unexplored" issues, gives a critical section to a rather strange proposal by Kitchener at the end as the extent of mentioning old issues in the field, and spends the bulk talking about the "formation of reason", from which I learned nothing about the philosophy of education. Just because the "formation of reason" requires a person to undergo education (in his argument) does not make that automatically within the philosophy of education category -- there's points of common interest intersecting all over among subfields, but intersecting such a point does not mean that entire category is relevant to that subfield. If it did in practice then everyone in every field would be taking interest in their fields' education research subfield, and that's definitely never been the case.

Afaik, philosophy of education was handled seriously within history and philosophy of science over the recent decades -- probably more seriously than how education was handled by the bulk of academics in other fields. I think it was only in the late '90s and '00s that education in STEM and medicine especially became a much more serious issue within those departments, in part because countries like the US started getting more serious about more controlled experiments and a wider experimentation with techniques. When the data showed as dramatic results as it did, old-guard medical lecturers were willing to completely change formats -- an important note to consider, because one of the hurdles to education reform in the US is the inertial resistance to technique changes from old-guard teachers. This hints at just a few areas in which philosophy can investigate further, with no mention of everything that's been studied in terms of teacher-student communication, the changing student psychology and cultural identity (and that political pile of worms), addressing the US controversy over college indoctrination (hey, you don't even have to leave your campus for that one!).

A wasted potential for this essay imho. Sorry.

I can see this is preliminary for now, so my strong recommendation as you're putting together future versions is to show detailed source and biblio information on the image itself. It's essential to making a professional, usable visualization.

Regarding what you have so far, you obviously will have to find some way to indicate or adjust for the obvious skew people will have toward reporting larger mammals. As a basic adjustment to the data (or rather, to the size of colored blocks in your visualization -- keep the numbers the same) you could divide each species by their average body weight. This may actually have to be a power of the weight, or even the log. if you plot for yourself and then fit the reported deaths versus weight, you'll get an idea of what function to try for the adjustment. For anything like insects in which the entire category has only one report, you might consider omitting that block entirely, noting "insufficient data".

This would seem to me to be the most beneficial adjustment to make, but there might be more adjustments or indications to consider in future, such as for nocturnal species. (They would definitely be hit more frequently, and if they're large I'd guess they'd be reported more, and if small I'd guess they'd be reported less.)

> People believing the corporate PR that they have an AGI or "proto-AGI" are incoherent. Why would they release such a thing to the public? Why would they let their rivals have access to such a revolutionary tool? ...

> So, either a corporation wouldn't release an AGI to the public, or they don't have one. ...

> And in order to counter this, we'll need non-profit organizations making AIs, and not just believe whatever PR that the corporations come up with.

[Edit: See edit above. Even if I was quoting sentences in context, I quoted it out of context to the overall point of the post, which I realized last night and today. Apologies.]

Why do corporate research publish papers and attend and present at scientific conferences on AI and quantum computing regularly? Why does it seem like with every innovation of one company, the other companies and startups are just one step behind?

Who exactly do you think develops AI at these companies? Business school grads? MBAs? Young coding boot-camp go-getters looking to strike gold with a killer app?

Get your head out of the conspiracy sand and read an actual piece of information by a professional on what the industry actually looks like (and, as they hire high-demand highly specialized scientists, what they get in their contracts). Then come back if you have a serious question of whether a groundbreaking discovery will be kept a secret.

[Edit: on third reading of OP's post, it's more clear what they are arguing. Thus my post here is now a message not to criticize OP (which wouldn't make sense given their post), but rather is more or less my supplementary argument of the same essential point as OP -- which is that nobody is hiding an AGI (though I don't know if OP agrees with me that at this stage no corporate R&D will hide an AGI).]

How do we find the actual source of your data? "Bloomberg" and "Credit Suisse" does not tell us anything of where to go to find out more, to check details on the dataset like its granularity, collection, and any adjustments, or to verify or cross-check your information.

Also, your newsletter link does not link to any actual issue -- it just links to your homepage.

One clue might be that of course seeing as your sensory neurons are not going to be completely saturated or suppressed in temporary parasthesia -- and certainly not all of them in an area will be -- and the same goes for any motor neurons that you might snag in a similar manner. The difference is that the translation from motor neuron stimulation to motor movement involves integrating a lot more components that might mitigate the effect that pinching a couple disparate nerve endings would have.

Taking from Knudson's Biomechanics (ch. 4 pp. 95--96):

>If the muscle fibers of a motor unit twitch in unison, how does a whole muscle generate a smooth increase in tension? The precise regulation of muscle tension results from two processes: recruitment of different motor units and their firing rate.

>Recruitment is the activation of different motor units within a muscle. ... Firing rate or rate coding is the repeated stimulation of a particular motor unit over time. ...

>When muscle is artificially stimulated for research or training purposes to elicit maximal force, the frequency used is usually higher than 60 Hz to make sure that motor unit twitches fuse into a tetanus. A tetanus is the summation of individual twitches into a smooth increase in muscle tension.

>... at the whole muscle level[,] muscles are activated to in complex synergies to achieve movement or stabilization tasks. Muscles are activated in short bursts that coordinate with other forces (external and segmental interactions) to create human movement.

And there's a bunch of more details to recruitment and firing rate, and it goes on in complexity and unknowns pursuant to further research. One relevant point is that in many cases you use only one firing per motor neuron, over several different neurons, to create a long smooth complex movement (the example they use is bicycling). Since it's an integrating effect, a single missing signal may not actually cause much of a problem -- but I don't know. Anyway, it's a clue.

The gist is correct. The commenter's post is generally ok, but with glaring mistakes that could have been corrected by simply cross-referencing themselves, it loses credibility, and it gives OP and other readers just as many misconceptions as answers.

This is a problem with most top-level comments on ELI5, and on reddit Q&As generally. Check your facts before posting, even if you think you know the answer. If you make it a habit to provide links to sources, that will force you to cross-check each time just from scanning an abstract, and it will also make your answers much more useful.

For a spacecraft pressurized at 1 atmosphere, a puncture would cause the nearby air (and anything that it can blow with it) to move surprisingly slowly and gently compared to what's depicted in Hollywood. The correct speed of a fluid being sucked out into space is depicted in season 1 of The Expanse (nsfw gory clip). You can do a back-of-the-envelope calculation of this pretty easily (I forget the exact number) and you'll find that the flow of air is being sucked out is the same regardless of the size of the hole (for a puncture larger than a pinhole and smaller than the entire wall).

Also, the force felt from the vacuum is highest near the puncture -- it's a pressure gradient that quickly feels negligible as one moves inward into the ship -- i.e., as more of the ship's air lies between you and the puncture.

So if you're ever in hand-to-hand combat with a vicious alien xenomorph queen, about to be ripped to shreds, and your last hope is to release the air lock... then it was nice knowing you.

[I'm being exceptionally lazy with this comment -- mixing different quantities in the same description, not bothering to look up further reading for you, etc. -- probably because I know the calculation's somewhere in my notes from the past couple years but I can't find it offhand. At the end of the day though, until I either show the math or show other sources, it all just looks bad.]

I understand that you may have been taught or studied the subject in the past, but there's a lot to stellar evolution, and quite a lot of what you said here is not a simplification but is just completely inaccurate. Before/while posting an answer, you should double-check online that you are up to date with your information.

In short, based on what you are describing, a LLM is a terrible tool for the compression of its training data in comparison to virtually any other reasonable compression technique one could think of, by any metric.

When you talk about compression, you're generally talking about some raw data that you run through an algorithm which compresses it into a more manageable form, and then you run it through another algorithm to recover the raw data again with some amount of lossiness (or it can be lossless). AI models can do that, sure, but they are not designed to be data structures for storage and retrieval -- in a simplified ANN model they take new training data that is given to them, and in adjusting their weights the model can now interpolate between this new data and previous training data. That might, however, make it so that now asking this model to recall a specific piece of old training data will result in an even fuzzier, less-faithful output, the tradeoff being that the model can now be asked about hypothetical data between what it's been trained on. (I'll have to find a good intro guide for a simple ANN model that illustrates this with diagrams.) None of this gets into space, time, or resource efficiency, but those are all guaranteed to be worse than a dedicated compression algorithm in any practical as well.

I suppose you can look at a broad overview of how data compression works in general. There are ANN/AI algorithms for compression -- they use the predictive network to essentially tune an existing deterministic compression algorithm, optimizing it for the data that's being compressed. That's not anywhere close to similar to taking an ANN like a large language model and locating the compressed data entirely in the ANN's weights.

I don't know if this helps -- I can try to clarify stuff or provide some better articles if you like.

To clarify, this refers to two spacecraft that are parked at the L4 and L5 Lagrange points. As you can see in the link, from those points you can clearly be able to see anything orbiting in opposition to Earth (approximately, but not exactly, at L3).

In fact, there are no objects at L3, according to... top... men.... [Always cite your sources, gang!]

[Edit: It seems like lots of commenters are interpreting this question quite differently. I interpreted OP as imagining an initial condition of an effectively 2-dimensional single-molecule-thick free surface of the Earth. I think I did this because otherwise I wasn't sure how the "smooth sphere" assumption would have been particularly necessary.]

Water drifts toward the equator. If there is already stuff there, like the surface has a bunch of water, or it's smooth and in moving the water has to climb up to move over from its initial position (since the Earth begins as perfectly smooth), then you have a complication where once the water gains altitude it is moving "too slowly" compared to the linear speed at that larger distance from the Earth's center. Thus the water appears to drift backwards (West) until friction with the surface below brings it to the "correct" speed that is locked with the rotation of Earth. The Westward drift from gaining altitude is of course the coriolis effect. If it's just a single drop of water that has to climb up once over the hard surface, then that's all there is to it, and it can continue onward [Edit: I'm dumb -- as the drop moves toward the equator, its distance from the axis of rotation of the Earth of course increases (i.e. that is the "horizontal" component of the radius), so the drop continually finds itself moving too slow for the Earth underneath -- thus still appearing to drift Westward.] -- unless the surface is frictionless I suppose?

If in this scenario the Earth is an entire (2D) ocean of water, then it gets especially interesting, as the water will try to bunch up at the equator and reach an equilibrium height with a bell-shaped curve outward. The formation process will keep the water moving East-West currents parallel to the equator until it reaches equilibrium, at which point it all has to come to rest.

If you add our Moon in there, with tides, then you'll definitely have continuous currents from the coriolis effect, since the water will be moving both vertically and in whatever off-axis (or even on-axis) direction the Moon is orbiting in this scenario.

I suppose you mean the OED and not the Oxford Dictionary of Philosophy, which is in front of me with a very different definition. I'm not sure which should be considered "official", but iirc Scrabble requires Collins.

It actually doesn't matter, because neither definition is relevant, because the only definition that matters is the one that's defined in the author's paper. The author uses this to set up their argument's scope. (Oh hey, that's Oxford's very next entry! Although they only talk about it in terms of logic.)

Which article are you quoting? I can't find the "excessive belief" definition in the article OP linked, nor in the Metaphilosophy paper.

Also, the second quote about "'excessive' scientism" -- are you quoting "a pretty extreme view"? If so, you are paraphrasing -- please do not use quotation marks unless it's a direct quotation.

I'm not sure I understand your comment. The author says he's addressing one specific argument in a specific paper, not scientism in general. Furthermore, it's a blog post, not a scientific proof, and not a prescription.

My first thought was that those who would choose to adopt a pet based on a viral social media campaign would necessarily make irresponsible pet owners, and inevitably dump the cats within a couple months.

(Caveat to this analysis: Overall there is around a 90% adoption retention rate after 6 months (and it surprised me from my experience that retention skews higher for younger people), so any "idiot effect" may not be too dramatic even in the worst case. [Full analysis in Hawes etal 2020])

But then you have to think that -- for example -- at least some of them are people who, unlike most pet owners, maybe never grew up around pets and never considered before having one. So let's say we get 50/50 from these viral campaigns -- 50% of adopters are terrible and release the animals into the street once they lose their Kony 2012 hype, while the other 50% become solid pet owners who might otherwise not have been. The shelter, now empty, can fill up with street and rejected animals again, which at least mitigates the losses of the former 50% (animals in == animals out), while the latter 50% is a complete gain. (Well, a gain excluding externalities, which can get really messy and is poorly understood.)

So as long as you introduce at least a few responsible new people to pet ownership, these campaigns are a net benefit, regardless of idiots.

Sorry but I'm fairly sure this answer is incorrect on almost every point. You should double-check your statements online briefly, consider making corrections as appropriate, and maybe cite the sources you use in your answer.

Your question makes several simplifying assumptions, which is understandable because almost every depiction of a neuron in pop culture is of a stereotypical pyramidal neuron, common in many interesting parts of the brain, which have the single long axon and big bushy tail of dendrites. But as you can see from the link, the axon also has a lot of projections on its end and indeed can connect to thousands of other neurons in different parts of the brain (in this type).

In terms of how information is relayed, that depends on where the neurons are located and what type they are. But sticking with these pyramidal neurons in the brain, the transmission, processing, and storage are all part of the same procedure as a neuron, upon receiving enough input signals of enough strength in enough time, will then fire a signal (action potential) of its own down its axon to the neurons it connects to. The storage part is achieved when many more signals come along one connection than another, the former connection is strengthened while the latter is weakened. (This synaptic plasticity has the common description of "Those that fire together wire together.") The principle of how all this works is exploited when we build artificial neural nets, as used in AI. Getting into that will get even more off-topic.

For you and the sake of others: this answer is entirely incorrect. Neurons don't work this way and photoreceptors don't work this way at all.

If you want a great example of how to establish your main character in a complex setting while driving you straight into the plot, all in 12 pages, read the HG first book, first chapter. It gets you into the world and action faster than books I've seen start in medias re (even decent ones).

YA and youth writing, when it's good, is excellent instructional material for learning essential brevity and active pacing. (The other things on that vein that I'd say is useful to practice with are soeechwriting, screenwriting, and newspaper journalistic writing -- all with some guidance, of course.)

The article covers the progression of droughts from 2000 to 2022. Only a small portion of what is said in the article can be discounted due to the recent storms. And that's frankly only if drought conditions don't immediately return within a few months.

You're misusing the terms "accurate" and "incorrect". "Out of date" is the term you are looking for.

The article was published March 2, and a long article like this may very well have taken a couple weeks to write, illustrate, fact-check, and edit, which might explain the use of older data.

There's a reason you use zinc-air batteries to power a hearing aid and not an internal combustion engine. "Better" doesn't mean "more power".

>There’s nothing to label on the y-axis.

Except for exactly what you just described. Just because there is no dimension does not mean you do not label it. "N" is dimensionless in the y-axis of a histogram, but it is always labeled as "Number of X binned by Y".

Oh look, that's exactly the same kind of chart as OP's!