#Analyzing Fundamental Data

[stockexperttrading]

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[unicodehealthcareservices45]

[feminist-space]

"Balaji’s death comes three months after he publicly accused OpenAI of violating U.S. copyright law while developing ChatGPT, a generative artificial intelligence program that has become a moneymaking sensation used by hundreds of millions of people across the world.

Its public release in late 2022 spurred a torrent of lawsuits against OpenAI from authors, computer programmers and journalists, who say the company illegally stole their copyrighted material to train its program and elevate its value past $150 billion.

The Mercury News and seven sister news outlets are among several newspapers, including the New York Times, to sue OpenAI in the past year.

In an interview with the New York Times published Oct. 23, Balaji argued OpenAI was harming businesses and entrepreneurs whose data were used to train ChatGPT.

“If you believe what I believe, you have to just leave the company,” he told the outlet, adding that “this is not a sustainable model for the internet ecosystem as a whole.”

Balaji grew up in Cupertino before attending UC Berkeley to study computer science. It was then he became a believer in the potential benefits that artificial intelligence could offer society, including its ability to cure diseases and stop aging, the Times reported. “I thought we could invent some kind of scientist that could help solve them,” he told the newspaper.

But his outlook began to sour in 2022, two years after joining OpenAI as a researcher. He grew particularly concerned about his assignment of gathering data from the internet for the company’s GPT-4 program, which analyzed text from nearly the entire internet to train its artificial intelligence program, the news outlet reported.

The practice, he told the Times, ran afoul of the country’s “fair use” laws governing how people can use previously published work. In late October, he posted an analysis on his personal website arguing that point.

No known factors “seem to weigh in favor of ChatGPT being a fair use of its training data,” Balaji wrote. “That being said, none of the arguments here are fundamentally specific to ChatGPT either, and similar arguments could be made for many generative AI products in a wide variety of domains.”

Reached by this news agency, Balaji’s mother requested privacy while grieving the death of her son.

In a Nov. 18 letter filed in federal court, attorneys for The New York Times named Balaji as someone who had “unique and relevant documents” that would support their case against OpenAI. He was among at least 12 people — many of them past or present OpenAI employees — the newspaper had named in court filings as having material helpful to their case, ahead of depositions."

[nothorses]

I came across this paper:

https://www.academia.edu/71372307/Trans_masculinities_embodiments_performances_and_the_materiality_of_gender_in_times_of_change

I'm not well-versed in academic language so I can't really understand all of it, but it seems kind of gross and condescending, especially when it's using testimonials of transmasc's desire to be seen as men to, idk, prove that masculinity isn't really queer or something? I'm curious how other (smarter) people would interpret it.

I mean, your understanding of it is just as important as mine! I'm happy to add my thoughts, though.

My understanding is that their thesis is essentially "masculinity is related to maleness and the male body specifically, and we know that because transmascs want to have male bodies". They allow for some nuance here in references to other literature, and I agree with that angle of their argument overall, but their premise is fundamentally flawed in the exclusion of trans theory and trans narratives.

Like, yes, masculinity is in some way related to appearance and the "male body", and there are a lot of reasons for that! But is the dysphoria of trans people really ironclad "proof" of what maleness and masculinity are? And why don't they spend any time talking about what dysphoria actually is, what trans people think it is, why trans people think they feel the way they do, or what trans academics have to say about any of this?

I have a lot of other issues with this paper as well, and I could probably write a paper just as long as theirs going into all of the reasons for that. But I think that answers your biggest question; what they're trying to prove, how they're trying to prove it, and why that comes across so weird.

To your other question ("is it condescending?"): I think this is kind of subjective overlay, but the way they go about analyzing their data is pretty condescending, in my opinion. They tend to frame their participants' responses as kind of misguided or ill-informed, particularly Diniz- who they definitely discuss as "trying to justify his choices" to identify as nonbinary while also seeking medical transition, like this is inherently contradictory and must therefore rely on some kind of delusion or desperation. It's weird!

I do also want to point out, briefly, that they also really cherrypick which claims they bother sourcing, and how they try to back them up.

They argue that trans men have male privilege based on the opinions of, like, three of their 30 total participants- and then carry this as "fact" through the entire paper, uncontested. That's extremely fucking weird and super suspect in a paper like this! I just wrote my own qualitative research paper based on interviews (which is what this is), and it's pretty standard to acknowledge the limitations of your research, and to position your results as non-definitive. Like, that's been a major part of every discussion with everyone I've talked to about my research. I would not have been greenlit to receive my degree if I hadn't been careful to avoid framing my research the way these people frame theirs.

The other weird thing they do is cherrypick statistics- or rather, one single statistic- to "prove" that transmascs do not suffer as much as other trans people, or possess some kind of privilege. They only cite murder statistics from one source; apparently that's the only relevant metric for quantifying all oppression? They also fail to acknowledge any possible shortcomings of this statistic, like the issues of under-reporting and misgendering of transmasc victims.

I could go on; I have a lot of gripes. But I think your criticism is totally valid, this was a weird and frustrating read.

Also curious if @genderkoolaid has thoughts- you tend to talk about gender studies from an academic position more, and you probably have a lot more field-specific expertise than I do. I'll boost other additions too, I love a good academic discussion!

[globalnewscollective]

AI and Donald Trump Are Watching You—And It Could Cost You Everything

Imagine this: You post your thoughts online. Or you express support for human rights. Or you attend a peaceful protest. Months later, you find yourself denied a visa, placed on a watchlist, or even under investigation—all because an algorithm flagged you as a ‘threat.’ This isn’t a dystopian novel. It’s happening right now in the U.S.

How AI Is Being Weaponized Against Protesters and Online Speech The Trump administration has rolled out AI-driven surveillance to monitor and target individuals based on their political beliefs and activities. According to reports, these systems analyze massive amounts of online data, including social media posts, protest attendance, and affiliations.

The goal? To identify and suppress dissent before it even happens.

Here’s what this means:

Attending a Protest Could Put You on a Government Watchlist – AI systems are being trained to scan for ‘suspicious behavior’ based on location data and social media activity.

Your Social Media History Can Be Used Against You – The government is using algorithms to flag people who express opinions that don’t align with Trump’s agenda.

Expressing Your Opinion Online Can Have Consequences – It’s not just about attending protests anymore. Simply posting criticism of the government, sharing articles, or even liking the ‘wrong’ post could get you flagged.

Dissenters Could Face Harsh Consequences – In some cases, simply supporting the wrong cause online could lead to visa denials, surveillance, or worse.

AI and Student Visa Bans: A Dangerous Precedent Recently, AI was used to screen visa applicants for supposed ‘Hamas support,’ leading to students being denied entry to the U.S. without due process. This is alarming for several reasons:

False Positives Will Ruin Lives – AI systems are not perfect. Innocent people will be flagged, denied entry, or even deported based on misinterpretations of their online activity.

This Can Be Expanded to Anyone – Today, it’s foreign students. Tomorrow, it could be U.S. citizens denied jobs, housing, or government services for expressing their political views.

It Sets a Dangerous Global Example – If the U.S. normalizes AI-driven political suppression, other governments will follow.

Marco Rubio’s ‘Catch and Revoke’ Plan: A New Threat Senator Marco Rubio has proposed the ‘Catch and Revoke’ plan, which would allow the U.S. government to scan immigrants’ social media with AI and strip them of their visas if deemed a ‘threat.’ This raises serious concerns about surveillance overreach and algorithm-driven repression, where immigrants could be punished for harmless or misinterpreted online activity. This policy could lead to:

Mass Deportations Based on AI Errors – Algorithms are prone to bias and mistakes, and immigrants may have no recourse to challenge these decisions.

Fear-Driven Self-Censorship – Many may feel forced to silence themselves online to avoid government scrutiny.

A Precedent for Broader Use – What starts with immigrants could easily be expanded to citizens, targeting dissenters and activists.

What’s at Stake?

The ability to speak freely, protest, and express opinions without fear of government retaliation is a fundamental right. If AI surveillance continues unchecked, America will become a place where thought crimes are punished, and digital footprints determine who is free and who is not.

The Bigger Picture

Technology that was meant to make life easier is now being turned against us. Today, it’s AI scanning protest footage. Tomorrow, it could be predictive policing, social credit systems, or AI-driven arrest warrants.

What Can You Do?

Be Mindful of Digital Footprints – Understand that what you post and where you go could be tracked.

Support Digital Rights Organizations – Groups like the ACLU and EFF are fighting against mass surveillance.

Demand Transparency – Governments must be held accountable for how they use AI and surveillance.

Freedom dies when people stop fighting for it. We must push back before AI turns democracy into an illusion.

Source:

https://www.fastcompany.com/91295390/how-the-trump-administration-plans-to-use-algorithms-to-target-protesters

[mariacallous]

In just a few months, Donald Trump’s second presidential term has drastically reshaped the United States federal government and moved to consolidate the power of the executive branch. At the behest of the president, numerous federal agencies have undertaken aggressive, invasive initiatives to crack down on immigration, police speech, investigate political opponents, curtail US public health efforts and emergency preparedness, and more.

With so much happening at once, numerous organizations and individuals have launched databases, interactive maps, and other trackers to catalog these government actions and their impacts on people’s civil rights across the US. Using open source intelligence, public data, news coverage, and other research, these tools are vital resources for documenting, contextualizing, and analyzing the flood of federal activity that is fundamentally reshaping the US. Here are a few prominent examples.

The Impact Map

by The Impact Project, Americans for Public Service

This interactive map tracks changes to US federal government funding, workforce, and policy across the country, documenting things like mass worker firings, hiring freezes, funding cuts, and lease terminations. The tool also shows places where funding has subsequently been unfrozen, federal workers have been rehired or may be, or the federal government has added a new service or benefit.

The map includes notations to specifically document impacts in rural US counties, areas in which the population is majority non-white, places where 20 percent or more of the population live below the poverty line, and indigenous lands. It also catalogs responses to these initiatives, including legal actions as well as local and state responses to funding cuts.

United States Disappeared Tracker

by Danielle Harlow, data analyst

This dashboard tallies the number of people impacted by the Trump administration’s mass deportations carried out by US Immigration and Customs Enforcement (ICE). The number is already over 4,000. The tool also monitors the status of each individual to the degree that information is available, noting their names, original country of origin, and where they are being detained, when available.

The tracker crucially follows each individual’s status, noting whether they are in ICE custody, have been released temporarily or permanently, have been deported, have “self-deported,” or have died in ICE custody. The tool also lists how many days their ordeal has continued.

ICE Flight Tracking

by Tom Cartwright, immigration rights advocate

Tom Cartwright is a retired JP Morgan executive who uses flight monitoring data from around the country to track ICE Air deportation flights, return flights, and flights within the US. He posts regular, specific updates on his Bluesky social media page and produces monthly reports for the immigration rights group Witness at the Border about ICE Air flights and tallies. In the past 12 months, Cartwright has collected data on roughly 8,000 ICE Air flights, including 824 in April. More than 1,500 of that 12-month total were “removal flights,” while about 1,400 were “removal return” flights. The other roughly 5,000 trips were “ICE Air domestic flights” within the US.

Regulatory Changes Tracker

by The Brookings Institution

The think tank Brookings has built a database cataloging significant regulatory changes implemented since the start of the second Trump administration. It includes new executive orders and regulatory freezes as well as Trump administration changes to executive orders that were issued by past administrations. For example, the White House rescinded a 2022 Biden executive order aimed at lowering the cost of prescription drugs and another from that year calling for research into cryptocurrency regulation.

Trump Administration Litigation Trackers

by Just Security and Lawfare

The law and policy publications Just Security and Lawfare each offer databases that track lawsuits challenging Trump administration initiatives. The tools include case names, docket numbers, and jurisdictions, as well as the executive action being challenged and the status of the litigation. In most cases, the Trump administration has pursued its agenda without congressional oversight or corresponding legislation, and a number of Trump administration efforts that have been challenged in court thus far have either been paused or permanently blocked from continuing.

Far Right Groups Targeting Pride Month

by Teddy Wilson, Radical Reports

Anti-LGBTQ+ groups, including fundamentalist Christian nationalists and white supremacist extremist groups, have targeted Pride Month events previously and are expected to again this June, particularly given the Trump administration’s violent rhetoric and executive actions related to trans rights. This map is tracking Pride Month events around the country and indications that radical opposition groups plan to target the gatherings.

[linkons-most-wanted]

Who in the world ranked sylus an extrovert when all his lore says he doesn't like crowds or people and feels drained by them? 😭

Ah, great question! 😈 You’ve unleashed the personality framework hyperfocus, haha. This got long.

“Introvert” and “extrovert” aren’t really scientific distinctions—they’re patterns of referring to people that crop up throughout a lot of humanity’s history of trying to describe people. That’s why they’re included in OCEAN (the “big five”), the most data-driven of the personality models. OCEAN is based on lexical analysis—what traits do people naturally talk about the most?

Anyway, so you get different schools of thought around the traits, some with better statistical backing than others.

What you’re thinking of is the classic “does being around people/crowds energize or drain you” but I don’t find that rule of thumb to be particularly helpful. Ask any ENFP—we love being around other people, rallying them for a cause, inspiring and persuading—but wow do we need a nap afterward.

OCEAN describes Extroversion as the spectrum from bold/energetic to shy/bashful. When Sylus wants to be left alone, he is certainly not shy about it. 🤣

I find it more useful to think about introversion vs extroversion as an “orientation”—do you tend to want to act/operate on the external world? Or your internal world?

Taking control, exerting influence, claiming dominion, competing with others—these are all externally-directed things.

Sylus is fundamentally a character that exerts his influence on the world around him, leaving his mark wherever he goes. Just because he doesn’t like crowds doesn’t mean he doesn’t want to create and control the world those crowds move through. He doesn’t need to want to meet every person in the N109 Zone to want them to flinch when they hear his name.

So, in that sense, Sylus is extremely externally-oriented, outward-directed, extro-verted.

Notably, ENTJ is often called the “commander” type, and for good reason.

Sylus has his moments of introspection, of course, as all extroverts do. But when it comes to the general balance between ruminating on something internally and acting in the world, he’s going to tend to act.

I like the articles from 16 Personalities a lot because they take the big five traits from OCEAN and map them onto the letters people are familiar with from the MBTI, plus the idea of “turbulence” to capture the “neuroticism” dimension of OCEAN. On introversion vs extroversion they call out how extroverts tend to enjoy thrilling activities, push boundaries/limits, take the lead, and get bored easily. That’s Sylus to a T.

If you’ll permit me one last tangent, I see a lot of people look at the stereotypical traits of introverts and sort of map that to neurodivergence. I had a boss who was really into “introversion” and would say things like “well, I’m an introvert, that’s why I don’t like eye contact. That’s why I have to analyze how I behave and practice presenting in a certain way. That’s why I struggle to talk to others.” It was fascinating how clearly he’d mapped and attributed his autistic traits (which were plentiful and apparent) onto the idea of “introversion”.

Being drained by crowds, sensitive to bright lights and loud noises, calculating and restrained when interacting with others—these aren’t traits of introversion necessarily, they’re traits of neurodivergence, especially the autism spectrum. So I don’t want to take away from anyone the relatability of Sylus hating crowds—it’s just not because he’s introverted, rather, because he has sensory sensitivities. And whether you want to interpret that as simply being due to his dragon senses (he can smell all those foul souls all the time, after all) or due to him being a subtly AuDHD-coded character (my take) is up to you.

And just in case this hits any folks outside my usual pro-self-diagnosis, pro-disability-accommodation, anti-pathologizing corner of the internet, I just want to add that neurodivergence is a lot more plentiful than people realize. We can call it “sub-clinical” ie not impairing enough to need formal diagnosis, but autistic and ADHD traits (and other forms of neurodivergence) crop up a lot in fiction not because people are setting out scientifically to represent those traits, but because we intuitively understand some people are just different that way. Some people are dynamic, engaging leaders who hate bright lights and crowds. Some people are the “quirky” friend who always has a new project, etc.

Anyway, I could clearly talk about this for ages, so I’m happy to field any follow-up questions on personality frameworks or how we can apply them in fiction!

[grison-in-space]

look computational psychiatry is a concept with a certain amount of cursed energy trailing behind it, but I'm really getting my ass chapped about a fundamental flaw in large scale data analysis that I've been complaining about for years. Here's what's bugging me:

When you're trying to understand a system as complex as behavioral tendencies, you cannot substitute large amounts of "low quality" data (data correlating more weakly with a trait of interest, say, or data that only measures one of several potential interacting factors that combine to create outcomes) for "high quality" data that inquiries more deeply about the system.

The reason for that is this: when we're trying to analyze data as scientists, we leave things we're not directly interrogating as randomized as possible on the assumption that either there is no main effect of those things on our data, or that balancing and randomizing those things will drown out whatever those effects are.

But the problem is this: sometimes there are not only strong effects in the data you haven't considered, but also they correlate: either with one of the main effects you do know about, or simply with one another.

This means that there is structure in your data. And you can't see it, which means that you can't account for it. Which means whatever your findings are, they won't generalize the moment you switch to a new population structured differently. Worse, you are incredibly vulnerable to sampling bias because the moment your sample fails to reflect the structure of the population you're up shit creek without a paddle. Twin studies are notoriously prone to this because white and middle to upper class twins are vastly more likely to be identified and recruited for them, because those are the people who respond to study queries and are easy to get hold of. GWAS data, also extremely prone to this issue. Anything you train machine learning datasets like ChatGPT on, where you're compiling unbelievably big datasets to try to "train out" the noise.

These approaches presuppose that sampling depth is enough to "drown out" any other conflicting main effects or interactions. What it actually typically does is obscure the impact of meaningful causative agents (hidden behind conflicting correlation factors you can't control for) and overstate the value of whatever significant main effects do manage to survive and fall out, even if they explain a pitiably small proportion of the variation in the population.

It's a natural response to the wondrous power afforded by modern advances in computing, but it's not a great way to understand a complex natural world.

[drowned-cypress]

I'm fixating on this idea currently; Architects, from what we know, seem to be a peaceful species. But they would be so scary if you got them pissed off.

What do you think about angry Architects? :3

We know that architects do experience anger. Al-An specifically worries that his people might be angry at him. I'm reminded of this post, which notes that one of the symptoms of Kharaa is increased aggression, and speculates that Al-An may have already had his people's anger aimed at him.

The thing about anger, and emotions in general, is that it's a physical reaction. Emotions were evolved as a part of a series of biological responses designed to serve specific functions to help an organism survive in their environment.

So what would anger physically look like in an architect? They have fundamentally different biology. In humans, anger involves primed adrenal responses to better prepare the body to fight. It basically triggers the fight part of the fight or flight response. This includes doing things like dilating the pupils, desensitizing the body to pain, sweating, slowing digestion to let the sympathetic nervous system use energy more efficiently, and heightening the senses. Architects don't have eyes, or a digestive system, but the principle is the same. The physical reaction would need to divert energy away from unnecessary biological processes to allow the body to spend more energy enhancing the senses and improve reaction time. I'm reminded of this post which sorts Al-An's bioluminescent colors by energy, with higher energy emotions emitting lower energy colors. I thought this was interesting because it could mean that architects turn red when they're angry as an energy saving feature.

What about body language? We can really only speculate based on the kinds of animals they incorporated into themselves, and their general body shape. There's a data entry that says they most closely resemble several species of mountain goat. Goats express annoyance by pawing, and stomping. Goats also display aggression by staring as a threat, tucking their chins and presenting their horns as a threat, rearing, chasing, pushing, and headbutting. These can all potentially apply to architects (yes you can stare without eyes, it's a stance thing,) assuming you believe that their horns are defensive and not actually sensory organs. I think it's more likely that they use their hooves and claws as weapons than their horns, but they could still display aggression by kicking or snapping their claws in threat.

That's analyzing potential architect behavior at the most basic animal level. Architects aren't animals though. They've extensively modified their bodies through genetics and cybernetics. They don't even identify with their own bodies anymore. Their bodies are just tools to them. Architects conceive of themselves as primarily a collection of data. I do wonder if they even experience emotions the same when they're in purely data format (like when they're in storage) as they do in their bodies. Storage is supposed to involve whole brain emulation, so presumably they should be able to emulate anger, but it's also possible that they don't feel emotions in storage the same way they do when they have bodies because they allow the body to regulate that kind of thing. There's also a good chance they modified their bodies to regulate their emotions at will, meaning, if they start experiencing physiological effects of an emotion, and they would like to stop, they can. Body producing adrenaline for a situation in which that is not actually helpful? Just turn it off. It seems like something they would do.

[what-about-zaladane]

The "Big Four": Why Mercury Deserves a Spot Next to Your Sun, Moon and Rising

The three pillars of modern astrology, after you get past Sun sign astrology, are your Sun, Moon and Rising sign (which I have complicated thoughts about -- but more on that later).

Sun: Your core self, ego and identity

Moon: Your emotional landscape, habits, and inner needs

Rising (Ascendant): How you interact with the rest of the world. How others first see you.

But to me, these "Big 3" leave out a very important part of the human experience: cognition and mental processing. Without it, I believe we can't capture the full complexity of who a person is at their most fundamental, and why they make the decisions that they make.

Why Mercury?

Mercury rules how we think, process, and communicate. It is the superego to the Moon's id and the Sun's ego. (I don't have a clean Freudian metaphor for the Rising, sorry.) It translates our internal motions and worlds (Sun and Moon) to the external (Ascendant). Without considering Mercury we risk ignoring that very crucial bridge between our motivations and our actions. No other planet has this level of foundational role in our psyche -- other than the Big 3.

Mercury helps you process and articulate your emotional needs (Moon)

Mercury helps you understand your own core motivations and desires (Sun)

Mercury impacts how the Rising sign is actually translated to the world -- after all, thinking (or lack thereof) is fundamental to making decisions on how and where to act.

How Mercury Fits In the Big 4

Imagine a two-dimensional axis:

If we consider Mercury (thinking) and the Moon (feeling) as opposites on one axis, and the Sun (internal drives) and the Ascendant (external actions) as opposites on the other, we start to see a workable framework for balancing the respective powers of the "Big 4" in a chart. As I like to call them:

Sun: How you want (motivation)

Moon: How you feel (emotion)

Rising: How you move (embodied expression)

Mercury: How you think (cognition)

For example, we might consider how dignified or debilitated a given planet is, and then we can see where along each axis a native might fall.

That's all mostly incidental though -- what I really care about is incorporating Mercury into the core reading of the chart as a balancing agent between the other three.

With Mercury, we have a richer, more nuanced framework. We can see how the energies and motions of the other chart objects are integrated and expressed via the processing of Mercury -- the integration of inner and outer worlds.

A note on sect doctrine and traditional importance:

A fair point to raise is that traditionally (hellenistically?) the Sun and Moon are considered important due to their centrality in sect doctrine, while the ascendant is critical due to setting the planetary rulers for each house. I'd argue that Mercury also has a soft signal of importance -- it is the only sect-neutral planet that can be a native of either. I'd argue that this points to its utility and function as a "bridging" energy between two diametrically opposed halves (the day and night sect; the inner and outer psychological words)

A Quick Example: Marilyn Monroe

Marilyn has:

Gemini Sun: Restless, observant and clever. Motivated to gather data and make sense of the world. Performs intelligence as allure.

Aquarius Moon: Emotional glass walls -- she watches, analyzes and retreats. Needs emotional freedom but fears it. A coolness to this placement.

Leo Rising: A sparkling icon, a force of expansive personality, a walking light source. Projects warmth, sensuality and confidence to everyone around her.

But the addition of her Gemini Mercury shows how she takes her Big 3 personality (charismatic, emotionally complex, and deeply creative) and filters it through her deep intellectual curiosity, wit, and remarkable communication and negotiation skills. Without Mercury, we don't have a clear window into how emotion and personality are translated into words and actions.

Mercury is how her Sun learned to articulate itself.

It's how her Moon kept intellectual distance from the pain.

It's how her Rising crafted a language of seduction and softness.

Mercury-Moon-Sun-Rising: An Active Feedback Loop

I'm borrowing here from my limited knowledge of psychological systems theory, so forgive me if I mis-step.

With Mercury in place, we can model identity as an adaptive feedback system rather than a static map.

Moon triggers feelings -> interpreted by Mercury

Mercury builds narrative -> energizes or inhibits Sun motivation

Sun expresses intention -> channeled through Rising action

Rising behavior leads to experience -> which re-informs and triggers Moon

Loop complete. When you're well-integrated, the cycle hums along. When you're fractured or "unhealed" one part hijacks the loops or shuts down the others. That is the client story every chart is showing.

Try It Out Yourself!

Try reading your chart with Mercury as part of your core system. You can ask yourself some questions:

How do you process what you feel? (Moon)

How do you think about and negotiate your desires? (Sun)

What story do you consciously tell when you step out into the world? (Rising)

That's Mercury. That's cognition as a bridge.

A Quick Note on Rising Sign

I disagree with the idea that your rising sign is solely "your mask" or affects only your 1st house. In fact, your rising sign is the key to the rest of the chart -- how sign rulership over every house clicks into place (especially in the Whole Sign System). I'm currently writing up a post about my problems with the Rising Sign and my suggestion that we expand our view into a Rising Archetype, divorced from a single sign and instead incorporating all 12. More later! :D

[marimayscarlett]

I seem to be haunted a bit by bad luck on here - prepared an answer for an ask yesterday, but instead of posting it, Tumblr swallowed the ask and it's nowhere to be found. Since I always type my answers in a Word document, I still have it and answer it in a proper post. The ask was signed with "RZK obsessor", so if that's you, here's your answer to your ask 🔎 which was something along the lines of:

Anon: Can you confirm the existence of RZK?

Hi 👋

Now ☝ Getting to the bottom of this kind of fundamental question does require a bit of a planned approach and care. So, at the start of the research process, one should ask which approach and research path to take when tackling this question: the philosophical route, the one of scientific research, or perhaps one's own wealth of experience? I’d say, let’s just go with all three.

Philosophical thoughts on the existence of our beloved Richard

From a philosophical standpoint, one must first ask - are we dealing with Richard as a tangible, real entity, or is this a collection of idealized versions of fundamental concepts? Wishful and idealistic projections designed to show just how diverse a single individual can be? Included in this are the epitome of confident presence on stage:

the audaciously good looks in every kind of stage outfit, be it leather, dramatic coats, feathers or questionable sleeves (wet or not):

and the efortless serving of rock star attitude, no matter how tight the clothing:

as well as exuding the most cozy vibes in rather eyebrow-raise-inducing attire:

Richard embodies so many concepts in one person that it’s hard to believe such traits can coexist in a single individual - perhaps Richard is Schrödinger's guitarist? Simultaneously existing and not existing, until you see him live and promptly lose all sense of composure...

2. Scientific research and evaluation of existing data on the topic of the existence of Richard

Like any good scientist, one must disclose the sources used and where one has gained knowledge and insights in order to report on their research in a credible manner.

To get to the bottom of the question of Richard’s existence, I have spent nearly the last 10 years meticulously studying every music video and their corresponding making ofs to the point where I can recite every line by heart (even the ones that make me want to sink into the ground out of secondhand embarrassment - "so ein Gesäuge", I’m looking at you). I went to the cinema three times to analyze Richard's presence on the big screen, absorbed recordings of live performances to examine and cross-reference his alluring movements on stage, and created a seven-page long table in Word to organize his interviews by date and topic, tracking his statements and quotes - I mean, quotes like the following have to be proof that this man exist, who else could express things like that so calmly, right?:

Every fur frog tastes different. Pure question of taste. There is no judgment in the text. We’re not saying it stinks.

I believe the music itself must be the king, but I want to be the queen.

The result of this research so far: Things are looking pretty good that Richard actually exists! But I understand what you mean - sometimes it’s hard to believe that this person truly walks, no, struts among us on this earth.

That’s why I had no choice this year but to take my research to the active side of things. Which brings us to:

3. The fan experience as a way to proof his existence once and for all - with my own two eyes

Even though we have countless recordings at concerts of him, from the 90's:

to the 2000s:

all the way into the 2010's:

to today:

it’s still hard to truly grasp that he exists in flesh and blood. Even I sometimes catch myself looking at pictures of him and thinking, “Wow… he actually exists! He’s real!”, fascinated anew every single time.

This year, as part of my research, I was fortunate enough to practice my research in the Feuerzone three times, and I must say: the moment Richard stepped onto the stage, I was often left speechless. He has an incredibly majestic presence, very focused and fully immersed in his role as the serious rock star - with moments of warmth (towards his band mates) and small glimpses into his thoughts (the annoyed look he gave in Dresden when he forgot his pyro arm for DRSG was so expressive; he rolled his eyes so hard, he surely could see into his brain). I was utterly captivated and thoroughly enjoyed watching him play and use iconic gestures (like during Du hast 👆☝✋👉), and to witness his presence and mannerism live on stage really was a highlight for me. Here's some of my research footage (grainy and shaky, and please be aware of me screaming, but all in the name of science):

After this intense period of dedicated research, I can confidently say: You don't confirm Richard's existence - you witness and experience it 😌

[materialsscienceandengineering]

How much/quickly do you think AI is going to expand and improve materials science? It feels like a scientific field which is already benefiting tremendously.

My initial instinct was yes, MSE is already benefiting tremendously as you said. At least in terms of the fundamental science and research, AI is huge in materials science. So how quickly? I'd say it's already doing so, and it's only going to move quicker from here. But I'm coming at this from the perspective of a metallurgist who works in/around academia at the moment, with the bias that probably more than half of my research group does computational work. So let's take a step back.

So, first, AI. It's... not a great term. So here's what I, specifically, am referring to when I talk about AI in materials science:

Most of the people I know in AI would refer to what they do as machine learning or deep learning, so machine learning tends to be what I use as a preferred term. And as you can see from the above image, it can do a lot. The thing is, on a fundamental level, materials science is all about how our 118 elements (~90, if you want to ignore everything past uranium and a few others that aren't practical to use) interact. That's a lot of combinations. (Yes, yes, we're not getting into the distinction between materials science, chemistry, and physics right now.) If you're trying to make a new alloy that has X properties and Y price, computers are so much better at running through all the options than a human would be. Or if you have 100 images you want to analyze to get grain size—we're getting to the point where computers can do it faster. (The question is, can they do it better? And this question can get complicated fast. What is better? What is the size of the grain? We're not going to get into 'ground truth' debates here though.) Plenty of other examples exist.

Even beyond the science of it all, machine learning can help collect knowledge in one place. That's what the text/literature bubble above means: there are so many old articles that don't have data attached to them, and I know people personally who are working on the problem of training systems to pull data from pdfs (mainly tables and graphs) so that that information can be collated.

I won't ramble too long about the usage of machine learning in MSE because that could get long quickly, and the two sources I'm linking here cover that far better than I could. But I'll give you this plot from research in 2019 (so already 6 years out of date!) about the growth of machine learning in materials science:

I will leave everyone with the caveat though, that when I say machine learning is huge in MSE, I am, as I said in the beginning, referring to fundamental research in the field. From my perspective, in terms of commercial applications we've still got a ways to go before we trust computers to churn out parts for us. Machine learning can tell researchers the five best element combinations to make a new high entropy alloy—but no company is going to commit to making that product until the predictions of the computer (properties, best processing routes, etc.) have been physically demonstrated with actual parts and tested in traditional ways.

Certain computational materials science techniques, like finite element analysis (which is not AI, though might incorporate it in the future) are trusted by industry, but machine learning techniques are not there yet, and still have a ways to go, as far as I'm aware.

So as for how much? Fundamental research for now only. New materials and high-throughput materials testing/characterization. But I do think, at some point, maybe ten years, maybe twenty years down the line, we'll start to see parts made whose processing was entirely informed by machine learning, possibly with feedback and feedforward control so that the finished parts don't need to be tested to know how they'll perform (see: Digital twins (Wikipedia) (Phys.org) (2022 article)). At that point, it's not a matter of whether the technology will be ready for it, it'll be a matter of how much we want to trust the technology. I don't think we'll do away with physical testing anytime soon.

But hey, that's just one perspective. If anyone's got any thoughts about AI in materials science, please, share them!

Source of image 1, 2022 article.

Source of image 2, 2019 article.

[anythingforstories]

I might flip if I see one more little baby writer talk about how they find AI to be super helpful to assist them in raising the quality of their writing.

Because peel back the layers, and really what's going on is that they have no self-confidence. They don't think their writing is very good. And instead of pushing through the ugly phase, they've been told again and again by giant corporations with huge ad budget that their shiny AI is what's going to help writers make their work good.

They're told that AI is the solution to make their descriptions better, or to analyze their writing for flaws.

So these little baby writers (we're talking 13, 14 years old) are turning to AI, because they recognize the flaws in their writing and want a solution.

But they don't have the expertise to understand why their writing has flaws. Because it does! When you start doing something, you start as a novice and need to learn. But the AI gives quick "fixes" that make it look better at a glance but lack consistency, finesse, or intentionality. It makes their writing a generic imitation of an amalgamation of training data.

And the baby writers think it's good! Because they don't have the fundamental skills to understand why it's not, so they look at the fancier words or the more concise sentence and think it's better.

(Not to mention the bias so many people have to think computers are more reliable than people... no wonder the baby writers shut off their brains and just accept what AI tells them!)

I'm not mad at the baby writers; I'm sad for them. AI is being pushed on them by corporations who want to shove AI into every imaginable use case, whether or not it's actually desirable or useful. They're being marketed to by soulless entities that care about the bottom line and jumping on the AI hype, not about human creativity.

They're being sold lies.

And they don't even have the foundation to see that. They're just scared that people will see their messy writing and have the mindset that they should be cranking out professional-level stories early on. Kids are scared to look like they're not experts in everything they try.

So to all the little baby writers (whether you're 13, 23, or 113)...

It's okay to write something cringey.

It's okay to have flaws.

It's okay that you're not an expert.

It's okay if it takes years to become good at a skill.

Everything you write yourself—intentionally and carefully—will still be better than whatever AI tells you you should be writing.

Focus on your fundamentals; that will take you much further than AI's quick "fixes."

Remember why you love writing. Even when it's hard. Even when it takes you a long time.

And then consider why on earth you would want to outsource that joy to a machine.

[fossilprep]

There's a lot this article touches on, but the parts about fossil preparation are kind of in poor taste. I'll go over some of it under the cut.

There's a reason we usually don't publish on things we prepare. They say it right here - we can literally, whether purposeful or accidental, modify fossils as we see fit. We could imitate pathologies or create marks with air scribes or picks that are misinterpreted as pathologies, remove or obscure parts of a fossil that may be diagnostic, etc. (Of course we don't endear to do these things, they're just possible).

Whether through inexperience or poor dexterity some budding preparators can cause damage that only someone with a trained eye could notice. Preparators aren't always required to be trained in the sciences or have thorough anatomical knowledge, and thus can reconstruct things wrong, without scientific guidance. Like filling holes where there's supposed to be… holes! Like a fenestrum or foramen, for example. This is why we have references, but more importantly, we do the minimum unless instructed to do otherwise by a supervisor or exhibits team - one of a few scenarios where a curator can rightfully step in.

This is why we're trained to preserve almost any bone we see. Often there are small isolated bone chunks hovering in matrix that are thrown in a box with the specimen. A lot of pieces can't be reattached because they're too weathered or of indeterminate origins (“IBF’s” for short).

"Creating" something "artistic" is another way of implying we're making it up as we go.

If someone hands me a fossil and tells me to look at this "multimedia sculpture", I'd be confused. It's a fossil, not an art project.

Academic fossil preparation is fundamentally a scientific endeavor that also requires artistic abilities, but not creativity. We use various methods that are tried and true (and sometimes experiment with new ones) to expose an element from matrix.

The act of preparing a fossil is not providing new data. The fossil itself is the data. We just make it available. That being said, if we provide measurements, take and analyze samples of the matrix for various analyses, then that's providing valuable data. Would that warrant an authorship? Maybe.

This raises another question though. If anyone who worked on a fossil gets an authorship, then can authorship compound?

The person who found the fossil but didn't do anything with it afterwards - just dug it up and sent it to the lab, for example. Do they get to be an author? On our field crews we have up to 30 people over the whole season. 30 coauthors and 99% of them are not scientists.

The collections manager who just painted a number on it, catalogued it, and put it away?

How about the curator who allowed a researcher access to the collection who didn't collect any data but just answered some emails and opened the drawer for it to be studied?

The land owner who gave you permission to dig?

Finally, the preparator who just exposed it from the rock. They do more science inherently than the others, but if no parts of the scientific method were conducted and no data was produced (save for the fossil simply being brought back into the world), do they get an authorship?

tl;dr We don't need authorships for the act of preparing fossils unless we provide data and go through the scientific process (like what's usually required for any authorship). Many parts of the process is not science. Just acknowledge our work in your paper and we'll be more than happy.

[rjzimmerman]

Excerpt from this story from Medium:

The illegal killing of a federally protected gray wolf near Sisters, Oregon, last month is just one in a long line of recent wolf poaching across the West, from the Canadian border to Mexico.

It’s not looking good at the state level either as reports from Washington indicate 10% population declines in wolves over the past year — most of which were human-caused deaths. Most insidiously, some Republicans are trying to roll back the protection wolves do have, which would turn western states into bloodbaths like those in the northern Rockies, where wolves aren’t federally protected.

But the current threats to legal protections for wolves are more than just an attack on a beloved wild animal. They have broader, more devastating implications for western lands.

Wolves are an essential part of healthy, functioning wild landscapes. Like other keystone species, such as bears, beavers, bison and birds, wolves contribute to ecosystem restorations and help build a wilder landscape.

The famous reintroduction of wolves to Yellowstone in 1995 and 1996 was part of an effort to restore ecological balance lost by the eradication of wolves earlier in the century and the resulting damage elk caused to riparian areas without their key natural predator. Now, for the first time, the long-term and profound effects of wolves and other large carnivores on Yellowstone’s ecosystem have been quantified by a new study.

The restoration of wolves and other large predators has transformed parts of Yellowstone, benefiting trees like willow, aspen, alder, and berry-producing shrubs.

For decades experts debated the effects of restoring wolves to Yellowstone. In the early days of wolf recovery there, plants began to grow after decades of suppression by elk in some areas of northern Yellowstone. Only now has the full picture of this recovery become clear and it turns out it’s not just how tall trees grow that matter.

Drawing on existing data from more than two dozen stream sites in Yellowstone collected between 2001 to 2020, researchers found a 1,500% increase in the volume of willow crown along stream banks. Examining the abundance and crown volume of a specific plant, like willows, that play a fundamental role in the ecosystem points us to a better understanding of how reintroducing wolves affects other species in the food chain.

And it’s not just limited to parts of northern Yellowstone. Similar effects showing the benefits of wolves to their ecosystems were found in Olympic, Banff, and Jasper national parks.

A previous study, Rewilding the American West, analyzed the ecosystems and habitats of 92 threatened and endangered species in 11 states in the Western United States. Their findings suggest that recovering gray wolves is one key to revitalizing native ecosystems, along with reintroducing beavers and retiring livestock grazing allotments on federal land.

Rewilding is about revitalizing healthy, native ecosystems. Adding wild animals and plants to the landscape isn’t enough on its own, though — we also need to subtract threats so they can thrive.

[askviktor]

greetings, viktor (is it okay if i adress you by your name?)

i hope you are doing well. it was my lifelong dream to study physics. i managed to get in a college to fulfill that dream but apparently getting into one was way easier than finishing it. i really love physics and i think understanding how universe works is fundamental for our development as humanity but as i start studying in college i found myself losing my passion and feeling under-qualified for this major. it saddens me deeply and i lost all my confidence. i feel lazy and less than my peers.

sorry for the rant, you must be busy but as a fellow scientist (a successful and hard-working one i should add) i think you might have some advice for me. i really want to keep going but i can't seem to study because it never feels enough. have you ever felt like this? how do you keep yourself motivated and be a more disciplined person? thanks in advance and sorry again for bothering you.

anon.

(I apologize for not replying as our beloved Viktor, but as a former physics major, I very much empathize with your message. I worked very hard and eventually felt that the pace at which I needed to learn was one I could not maintain with my physical and neurological disabilities. I did well in an accelerated private high school, but a post-graduation brain infection and other difficulties made the return to college in my thirties a rough adjustment. I have switched to my other passion, writing, for my degree. I too felt a great deal of depression as I struggled with an incredibly difficult subject, especially as I did all in my power to succeed. My husband fully believes I could have continued, but I now know I made the best choice for me. In my spare time, I teach myself math and read my physics books, without the stress of grades.

All this said, I truly believe all of us can learn whatever we wish with enough time, patience, and hard work. I highly recommend learning about how to learn; I found the information in "A Mind for Numbers" by Barbara Oakley especially encouraging and helpful. Invest in a tutor and take great care in crafting a distraction-free, but balanced study schedule. Ask the "dumb" questions that 75% of your peers are afraid to ask. Interleave different types of problems, and take breaks so your brain can alternate between diffused and focused thinking. Keep a picture of whatever goal you may have at your desk. Go to office hours.

And do not forget that learning and memorization take time. As a person accustomed to a 4.0, I had to accept that lower grades were the norm in my major. We see lone geniuses in the media and expect simplicity; real scientists struggle together. But, back to Viktor...)

Yes, Viktor is fine. Thank you for asking.

Failure is data, is it not? Perhaps you may find this surprising, but I struggled academically when I began at Piltover. While I had raw intelligence, I found many holes in my previous, primarily self-administered education as I proceeded through the Academy. Tutors and extra practice helped me to catch up. Analyze your data with fellow students, and help one another succeed.

Be kind to yourself; the universe is ineffably complex, and you are but one person. But, never, ever sell yourself short. The mind has great plasticity.

Good luck, my friend.