It should also be noted that time during which a geomagnetic reversal takes place is by any estimates 2k--12k years. So even if we're headlong into it, Comparatively, magnetic North's speedy yearly drifting would overshadow any observation of an overall movement of the poles to flip (if the pole's wobbles were a consistent-direction drift then it would be in the Antarctic within 400 years.) And because airport runways are numbered according to their magnetic compass direction (instead of true), the wobbly North pole means regular runway repainting, costing the aviation industry upwards of tens of dollars per year!

They rightly pan Horizon Worlds as it's presented now as disturbingly reminiscent of the empty-but-not-insignificant hype around Second Life. And of course the utopian attitude of tech bros is a meme ("Making a difference; making the world a better place... through minimal message oriented transport layers.").

But Facebook really did make the world better... at first. And if they wanted to they could go significantly farther and make the world better, by just doing what they do now, but cut back the design in which anything productive that someone wants to do on there is through a clutter of garbage that's worse than the worst targeted ads from faceless corporations -- that which reinforces addictive behavior. Instead, look at Facebook's special-purpose competitors -- take Meetup and Google Groups for irl socializing and networking, something that could be done for free on Facebook, but that many are avoiding because of that ickiness. Company feeds on Twittertagram are duplicated on Facebook, so there's no reason why I should be able to view people's Twitter posts without logging in while Instagram and Facebook are locked. If the original idealism was that more access + more communication + more socialization (irl and virtual) generally grows your userbase while also improving society, then just in terms of how they've shifted the design of their core product, they've been working against that.

The essay page accompanying the graphic makes a nowadays too-typical optimistic pitch: Yes, the US and OECD energy sector is decreasing emissions and emissions-per-unit-GDP is dropping, but total emissions are still increasing in the OECD -- that is, our growth (in consumption and production) significantly outpaces our efficiency gains. [This was wrong when I typed it, which is why I usually link to stuff in-line and don't just go by what I remember from podcasts in November -- I'll have to make the corrections later tonight.] Among other things, this makes us look doubly hypocritical when we say to middle-income countries and India especially that they need to moderate their own pace of growth (against more expensive and slow-to-build upfront infrastructure costs that would all have to be subsidized) for the sake of CC mitigation.

It looks like just a "low resolution" vector file used for the map. I'm sure the author can swap in a base map with more path points -- probably from the same source as their original map -- and recreate the graphic within a few minutes.

The obvious comparison is to the Big Mac Index. It would be interesting to see the strength of correlation, and if the breaks in correlation would correspond to specific regions or characteristics of countries. (Big Mac Index data available via Statista if anybody wants to run something like that.)

Methods of getting O2 and water from the moon's surface has been researched around the world for decades. Somehow I don't think the final piece to this puzzle is that NASA or ESA just need to hire some scrappy Canadian Arctic oil drillers a la Armageddon (199suck).

Meanwhile, the only material that the article says specifically is of commercial value to mine on the moon is He3. The reason it's valuable, according to the article, is due to its potential in fusion, which they say is something to anticipate because of a breakthrough in fusion, which they link to within their own magazine. And of course, like all other breakthroughs in, and current research around, practical or scalable fusion, it's D-T and has zero to do with He3, which would require from the ground up entirely new engineering to be developed and scaled.

I suppose if I were to invest in a Canadian company that wants to do space mining, I'd ask first if they had or were bidding on a known contract with a space agency that's actually going to the Moon; and if they're talking about He3 and all that, I'd ask if they know what is the absolute capacity of that market, at the current trend of the field. If that passes, then price elasticity is next. This process is part of what I call an Elf Aquitaine hoax sniffer.

This is a quite appropriate thought experiment to all the AI doomsday panic that's being posted. I feel like it could use some refinement though, and the reason is because it feels very much like it's invoking the literary trope of the doppelganger, but I don't think it's explicit enough at it to be fully effective.

Eliciting the doppelganger trope would I think for most people, even those who aren't that familiar with much literature or film directly, make people think about how old this concept truly is. My own visual for the sci-fi doppelganger is the mechanical duplicate in Metropolis, which nicely fits this thread as it was part of a layered allegory that begins with the day-to-day workers moving through a soulless system to provide luxury for others. The machine could replace the worker, production would improve, and the worker would no longer be a ritual sacrifice to capitalism (but implicitly, where would he go?); instead the machine replaces the one person proposing a solution to the working class-vs-elite problem with an agent of the whole system's destruction. (Hopefully that's an abstract enough meta-summary that nobody will try to remember any of that when they eventually go see it -- which they will, because it's amazing.)

The point is that we have centuries of people freaking out over -- and making amazing literature about -- essentially the same root fear. AI is the new golem, the invading Body Snatcher, your Link's Shadow! But the hero does not fear! The hero stands in the corner and mashes, mashes B!

How does a graph like this get made for an aerospace company like this -- or I suppose any giant company -- where there are long-term contracts with some significant risk, or current sales that may include a contract for years of included maintenance, as well as sales of hardware alone? I know accounting isn't trivial and there are proper methods of balancing all of this each year, so I suppose I'm asking if someone has a hint as to how this stuff all gets tucked away in a chart like this? (Tbc this is a question reflecting my basic ignorance of accounting -- I'm not saying anything is missing or not properly represented; I am asking if someone might explain how all these types of contracts with complex breakdowns are represented in this visualization)

(Also OP needs to include the source in the image, including date created and date of dataset,)

I second this. Raise and educate, and worry about getting your teen past this first finish line while staying clear of the worst possibilities such as drunk drivers or major health worries. I'll piss enough time away on Reddit for both of us.

The ecosystem model in which loss of biodiversity reaches a tipping point upon which the food web collapses is basically as old as practical numerical computation being available for general research -- the 1970s. The question of how precisely you can characterize the tipping point is a key one in network theory/ecology/biology. So as we have good data on certain ecosystems, such as around agriculture and in certain well-studied areas of rainforest, it is of interest to know whether the next species to go locally extinct will collapse the local ecosystem, as does happen (this or similar network phenomena may be a major cause of the colony collapse epidemic in American honeybees currently, which is chicken-or-egg devastating to biodiversity in areas in which it occurs, and is of course of huge financial concern to agriculture).

So the relation of these kinds of papers to Climate Change and the Anthropocene extinction (i.e. humans destroying habitats and causing things to go extinct super quick) has been warned about for decades. That's the pop sci magazine reporting.

This is awesome new research because they applied this technique -- a rather tricky one in general -- to a very tricky fossil record (for which they also expanded the existing model), and got it seems rather conclusive results. So it probably speaks to the strength of the theory in general, but I would always be cautious about that, since being a powerful tool -- thus being conducive to wide applicability, thus being widely applied, thus being a big part of many explanations -- is not the same thing as conclusively making up proportionally that percentage of the actual explanation... if that sentence construction makes sense. Especially in networks, and especially in systems with limited data.

I am in the sciences but I've read into philosophy quite a bit. One important thing I've learned, after quite a long time, is that whenever I'm reading something, and I'm ready to object that "Physics proves that's incorrect!", then I'm in the process of missing the point.

For those passing by, everyone's referring to Nagel's famous essay on the predictive limitations of the connectivist model in the NMR era vis a vis Chiroptera.

What wouldn't fit my worldview? What contradicts what I've said? The numbers are important, sure -- it tells you that there is a significant mutual economic interest, ramped up to 11 since the war began. The reason for looking up an analysis is because they can interpret those numbers over the past several years, and in context of the region and of Russia's, India's, and China's trade and foreign policy in general, and tell you, again, who's the boss in the relationship.

For a start, consider trade. Russia's available export markets were dramatically cut since the war began, and as its economy has been primarily driven by oil and gas exports, it slashed prices to find new buyers fast. China came first, then India, who together import an equal share of about 40% of Russia's crude (-ish -- the numbers are fluctuating per the article; it was about the same share in December; Russia also majorly exports gas and refined fuel of course). Note how dramatically India's imports rose, supposedly once it got the right price and political incentive. If Russia said tomorrow "we're mad -- no more oil", then India goes back to their old supplier -- but who else does Russia have to sell that 20% of crude to, that they already sell well below market price?

That's a very basic analysis on how what looks to be a mutual trade agreement might actually be extremely one-sided, but there's so much in the three-way relationship that you have to look at a full analysis. And one about the last 5--10 years, not an analysis of the Cold War.

I will not debate the thesis. I will admit that every blog post using the premise of "The latest advancement in neural nets brings us one step closer to the Singularity" begins with an eyeroll of dread from me, but I will at least pick apart the first section for problems, which hopefully will be informative for those evaluating for themselves how seriously to take this person.

>Intelligence, as defined in this article, is the ability to compress data describing past events, in order to predict future outcomes and take actions that achieve a desired objective.

The first two elements of that is the definition for any model, which is exactly what both AI and deterministic regression algorithms all do. I think "take actions" would imply that AI model either makes a explicit recommendations, except that no premises are given in the definition for which there is context to give recommendations (to whom? for what?). Regardless, it seems to me less of a definition for "intelligence", in any useful sense, as it is of "model".

>Since its introduction, the theory of compression progress has been applied to a wide range of fields, including psychology, neuroscience, computer science, art, and music.

The problem is that Schmidhuber 2008 only exists as a preprint and later as a conference paper -- it was never peer-reviewed. The paper seems to justify that it is a widely applicable concept, but it wasn't apparent to me on a search that the theory was actually applied by someone to one of these fields in some manner that was substantial. I'm not saying it's a bad paper or theory, but that this essay doesn't really justify why it brings it up so much (particularly given the very limited definition of intelligence above, and just the way ANN are known by everybody to work), and giving a real example of it being useful would have helped.

>The equation E = mc^2

For the newbies out there, this is what's called a red flag.

The next paragraph actually helpfully links to Towards Data Science's page on Transformer, which is actually really good in that they illustrates, complete with animations, the mechanics of ANNs. So definitely check it out. The next sentence linked in the essay, however, is literally linking the paper that defined Transformer with the defining phrase used in the paper -- as if that would enlighten the reader of the essay somehow? The final sentence of the paragraph is once again a completely generic description of all ANNs ever.

>The weights that define it’s behavior only take up 6GB, meaning it stores only about 1 byte of information per image.

This is completely the wrong way to think about it if you're trying to understand these things, so I hope he actually knows this.

The next few paragraphs seem to be ok descriptors. Then we get to here:

>With just a small amount of data and scale, the model will learn basic word and sentence structure. Add in more data and scale, and it learns grammar and punctuation.

First, this is the connectivist problem/fallacy in early AI and cog sci -- the notion that because small neuronal systems could be emulated somewhat with neural nets, and because neural nets could do useful biological-looking things, that then the limiting factor to intelligence/ability is simple scale: more nodes, more connections, more power. Obviously this wasn't correct in either ANNs or BNNs. Further, in this paragraph he seems to have lost track of whether he was talking about the objective function in ChatGPT. Either way that's definitely not how any NLP works at all. Unfortunately this paragraph only gets worse. It's disappointing, since the preceding paragraphs had otherwise indicated to me that the writer probably knew a little about neural nets in practice.

>Just last week, a paper was published arguing that theory of mind may have spontaneously emerged

PREPRINT. Not published. No peer review yet. I won't comment on the paper myself as I am not a peer in the field. It's a dramatic claim and it will have proper evaluation.

This is all I'll do of this, as it's a long essay and I think there's enough that you all can judge for yourself from what I've evaluated of the first few paragraphs.

Please look up any reputable analysis on who has the upper hand in the relationship: India vs Russia; or also for fun, China vs Russia.

If it has no consequences, then it doesn't take balls to do.

The GA vote probably has more importance as a short-term PR boost (or burden) with headlines like these, so the countries that voted against the resolution probably were able to do something more in terms of moderating the Russia-China axis than the rest of the countries. Why? Because the only reason countries have to vote for anything not relevant to their politics is for something in return -- so every vote against is something Russia (or perhaps China) had to trade in. Of course most things aren't wholly zero-sum like that, but it's still the important thing to keep in mind with almost any assembly vote -- but especially GA -- that much or most of the real work is in the whipping behind the scenes.

Exactly. With Lightfoot's datapoints being essentially entirely measured during the Pandemic (and the known, but still poorly understood, insanity of fluctuation in certain oddly specific crime rates nationwide during the Pandemic), and that roughness of granularity, I recommend rejecting this chart as useless.

(This goes beyond the notion of evaluating one term of a mayor on 3 datapoints of a single crime metric compared to many more terms and many more datapoints of a previous mayor -- one basic problem of granularity is that each datapoint has a certain sampling bias depending on the cutoff -- you can see this yourself by recalculating the murder rate from daily statistics, but use a different year-to-year cutoff date -- that's one type of this bias. It's not a problem with more datapoints depending on the metric, but here you have only 3 for Lightfoot.)

I didn't think there could be something less meaningful than a GA resolution vote until I saw a chart of a GA resolution vote.

(Though in fairness I read that a GA resolution does have the tiniest, barest iota of consideration in international law when it comes to evaluating norms -- worthwhile enough to get a footnote in international court rulings from time to time. Norms are evaluated far more heavily based on the domestic law of parties and their peers as well as, well, norms -- what everyone's just been doing in similar situations for decades.)

As I found out not too long ago, that debate was already mostly settled when I learned it and is long-settled now -- gas giants have a icy-rocky planetary core formed in the accretion disk along with the other rocky planets, and the much larger mass that they build up allows them to hold an enormous atmosphere during accretion while the rocky planets will bleed or evaporate most or all of theirs away. (See perhaps NASA's brief on planet formation -- I feel like Wikipedia's article is skirting the gas giant issue so probably has some conflict between editors.)

A failed star is a brown dwarf, which can form as part of a binary just like any stellar binary. The reason this particular system isn't that is that they say it's specifically a Jupiter-like gas giant. Further, they obviously got the mass since afaik methods of finding exoplanets will always get the orbit (by wobble at least), and the article says recorded the light during transit, so they would have calculated the radius; thus they'd be able to calculate the planet's density. Now, the density of Jupiter is 1.33 g/cm^3. Compare a brown dwarf, which as a failed star has no (or very little) core fusion to provide pressure that counteracts the enormous compression that's from the gravity of its enormous mass (about .07 solar masses, which is still huge) -- it is thus degenerate matter (in the core at least), as in a white dwarf, and at least in one case the average density was calculated at 108 g/cm^3. There would be plenty of other evidence to line up too -- I'm sure they weighed the possibility that it could be a brown dwarf, or at the very least a very unusual type of planet that must be tested for everything.

(And just for fun, the densities of main-sequence and off-sequence stars are all "known" (more or less -- it's not pure hydrogen or pure clean fusion), because math. I can't find a simple list, but you can find masses and radii -- anyway, as a type-M star, it is about 5 g/cm^3; compare the Sun at about 1.4 g/cm^3 -- more mass means more pressure inward, but also more fusion so more pressure outward,(See Thompson, Astr 1144 Lect.10, OSU)

I didn't find it funny, but I am now in a deep poetic reflection on the state of ubiquitous hyperliteracy that the Information Age and over a decade in this social media and ad-monetized content saturation of the internet has brought upon the entire world, from the richest to the most destitute.

Indeed, what isn't read all over?

The premises, the part that you put in bold, are complete fantasy -- I just want to make sure everyone is aware of this in case they might think it's based on any kind of real literature. It's like when a sci-fi book opens with something like "The accepted phases of matter have been unchanged since Aristotle: solid, liquid, gas, and plasma, aka quintessence. But what would if we discovered a fifth phase? What new future would it usher in for humanity?" or perhaps "The Maya warned us. Nostradamus warned us. Now, it's December 31, 2011 -- did anyone listen?" I'm serious -- it's pretty much at that level of sci-fi.

The most important thing to note is that from what you wrote there's complete misconception of all understanding of what mental illness is, even from as little as Freud understood. So bearing all that in mind, you basically have license to construct whatever model of psychology you want. Just remember that it'll be roughly the equivalent of the humours theory.

Tesla only decided to build such an entry entry-level vehicle to compete with BYD, whose EV sales exceed Tesla, and who has a much more diversified and integrated worldwide battery manufacturing system. BYD's bestselling Han goes for about $40k in the OECD, but they could conceivably sell the Dolphin in the US at around $20k after additional duties, targeted taxes, and price adjustment to the US market (it's ~$15k in China).

BYD is not the only foreign EV manufacturer who can, does, and will undercut Tesla if they get into the same market. It's only a matter of what Tesla's strategy will be. Arguably from some in the business, Tesla should not compete at the budget level, and instead remain a brand name like BMW or Apple. The arrival of low-cost players will expand the share of consumers who choose EVs in the first place, and thus the number of consumers who will later upgrade to a luxury brand -- thus Tesla would encourage its low-cost rivals to enter the US.

I'm assuming this map is based on a classification model that was fit to the demographics listed for each state, and that you are presenting the solution it gave you without further modification. It would be nice if you would describe the specific classification model and parameters you used, because I worry that some people might assume you just made up a bunch of regions on your own inspection and gave them alt-hist-style names -- they'll be hoping this is still a data sub and not a sci-fi/fantasy/Kevin-Costner-film-trivia sub.

For those worried about medical logistics and claims: somehow I don't predict the public health data will show a dramatic decline in those seeking prescriptions for lower back pain, corresponding with a dramatic rise in new complaints of chronic assbleeds.

QC can't be developed past a fizzled-out tinker-toy if there's nobody willing to pay for it (there's a finite amount of VC out there, and they all want to believe there'll be returns before they die). There's nobody to pay for it if there's no viable commercial market. There's no viable commercial market if they can't even conceive of a business model.

(The government would fund QC for cryptography, sure, but meeting those requirements is many orders easier and cheaper than getting a generalized QC of the kind everyone's excited about.)

And this is not an isolated problem. I saw a talk by IBM recently that also said they had something in QC that was commercially viable, but after a few questions it was clear they had nothing even close to a realistic (if any) idea for what their business model would look like -- it was like it hadn't even occurred to them to consider that kind of thing before claiming something was commercially viable.