I suppose it's all been said before, but what is a choir if not many speaking the same message? I've felt worse in these lulls before, these sporadic spurts of depressing dips, so at present, I'm of fairly clear mind. The issue is, I was sparked by the simple question, "Am I loveable?' Now, it'd fail my ultimate message here if you took away from that query, "Ah, this man is professing the ever so common 'Woe unto me! For I lack within my arms a maiden-fair!' ", or some other ridiculous bit you'll see on this subreddit every now and again. Rather, my point here is, am I fair enough person to be welcomed by any other soul besides myself?
I mean, I'd be inclined to readily say yes to that question, but the guilty are often quick to profess innocence at the first chance they see aren't they? My issue is, when I really think about that question, I keep finding evidence I can't reconcile, or the reconciliation thereof only spells lament. See, I've never really had an easy time making friends, and frankly I've never had a real one. I've always had acquaintances, and beyond that merely family members. This lack of friendship could be supposed to be due to my all around nerdiness, the niche nature of my interests, and lack of developed social skills. Sure. There's another alarming possibility though. What if I'm unlikeable? What if Eduardo from school didn't distance himself from me because we had no similar interests? What if it was because I was actually a really terrible person to be around and I had just failed to notice? What if Juana rejected me in middle school because I was actually terrible the whole time and her laughing at my jokes was just her trying to spare my feelings?
I can continue this forward. My family has never really embraced by differentness, it's always been a point of contention. It's never been, "Well done, we're proud you accomplished this.", it's always more along the lines of, "Um... ok? That's odd but as long as you're happy". They've also only ever really tolerated me, never really going beyond providing physical needs to keep me alive. I mean don't get me wrong, I am eternally grateful fate placed me in the hands of a family that will at least not kick me to the streets. I'm glad I have a reliable place of shelter and a place to get food and drink. That being said though, a sense of belonging and appreciation would also be nice. However, we return to the same point, what if I am just a terrible person to my family and I just don't know it?
This is a really frustrating idea. I mean, I try to be empathetic. I care deeply for animals and family members have compared me to San Francisco (St Francis of Assisi). When I have at least attempted to make friends, despite those numerous attempts failing, a consistent sentiment was that I was respectful. I've been described as a "Renaissance Man", pooling interests and knowledge in from subjects like classical literature, amateur astronomy, ornithology, anthropology, botany, geology, theology, etc. That being said though, here I remain, feeling alone and like the scared, timid little boy I feel like I've always been. I mean, I'm afraid that I could be the most interesting and caring and loving person in the world, yet I'd still somehow be alone. I'm just terrified there's this fundamental flaw at the very core of my being that will forever stunt my growth and attempts to be a human being.

so i’m on vacation with a friend and we are out of state. and we are in a large busy city. we got lost so many times because neither one of us knew how the subway worked. and i just feel like i was frustrating my friend because of my lack of common sense and not being able to understand directions. i always feel so stupid and like i’m not living my life fully. i’m 26 and my friend just turned 24. she is engaged, she is an influencer, and she travels everywhere and she doesn’t mind doing it alone. i’m 26 and i always stay in my house, i don’t understand the world very well, i get confused easily, and it’s like i’m just living on autopilot but my brain doesn’t understand basic shit. i have to hurry up and become the woman i want to be: independent, street smart, and content. but i’m afraid i just don’t have the brain capacity to be who i want to be. i’m mad at young people who are just living life on their own terms, doing what they feel like doing, and not being afraid of people or anything else. what advice would you give me about wanting to become a better woman but not having the common sense to do it? i really don’t think i’m too hard on myself. if i was on this vacation alone, i’d probably somehow end up getting lost and never finding my way back home. my phone would die, my car would break down, i’d be stranded, and i would have no idea what to do so i’d probably just cry about it and hate myself even more

so i’m on vacation with a friend and we are out of state. and we are in a large busy city. we got lost so many times because neither one of us knew how the subway worked. and i just feel like i was frustrating my friend because of my lack of common sense and not being able to understand directions. i always feel so stupid and like i’m not living my life fully. i’m 26 and my friend just turned 24. she is engaged, she is an influencer, and she travels everywhere and she doesn’t mind doing it alone. i’m 26 and i always stay in my house, i don’t understand the world very well, i get confused easily, and it’s like i’m just living on autopilot but my brain doesn’t understand basic shit. i have to hurry up and become the woman i want to be: independent, street smart, and content. but i’m afraid i just don’t have the brain capacity to be who i want to be. i’m mad at young people who are just living life on their own terms, doing what they feel like doing, and not being afraid of people or anything else. what advice would you give me about wanting to become a better woman but not having the common sense to do it? i really don’t think i’m too hard on myself. if i was on this vacation alone, i’d probably somehow end up getting lost and never finding my way back home. my phone would die, my car would break down, i’d be stranded, and i would have no idea what to do so i’d probably just cry about it and hate myself even more

SSBU for Switch should allow people to disable smash attacks for the A button, and/or hold the C stick to charge smash attacks.
Yes I'm aware you can change the C stick to light attacks. Yes I know this is what the pros do. But this shouldn't be necessary. Nintendo could easily put out a patch to address this issue. And the fact that they haven't just shows they don't want to, likely for prideful reasons. Or simply because they like their game being "different" from other fighting games.
Justification points as to why this change is necessary:
1.There are millions of players who use C stick for Smash attacks. Each one of these players is at a disadvantage because they will often do smash attacks when they are in fact trying to do a normal attack.

1. Asking someone to change their playstyle when there is no need to is unreasonable. We live in a world where games can be patched. I've delt with videogame coding, and I know for a fact it would take very little effort to disable smash attacks for the A button. The fact that they haven't added it yet is likely for prideful reasons. Nintendo devs take pleasure in having their characters attack using analog stick. Which logically, doesnt make sense. Because fast attacks are the most common attacks in the game. The most common attacks should be most accessible to the player's hand. (near the A button). If you've played any other fighting game in the world (Street fighter, Tekken, etc) they are all like this. They all use the A or X button for fast attacks. Smash Bros is the only game on the planet where you're forced to use the analog stick for fast attacks. (if you want to play on a competitive level.)

First off I'm going to say that I knew better than my friend… Lol my friend, she said that the Umbreon gold star was going to go down in value from $50 to $15 in just three weeks… It raised in price and kept going up. I don't know what she was smoking, but she definitely had bad judgment on that one. 😂 as for me, I thought those shiny Charizard cards would just keep climbing… But they finally did start to go down.. and why are people so obsessed with them anyway? They are just re-prints of normal ones with the regular coloration. People here in America wanting $500 or more at the time, I got my Japanese one for $65. Scalpers over there thinking they are entrepreneurs… Lol. Meanwhile Japanese sellers have common sense.

Making money is a goal that many people share, but not everyone knows how to achieve it. There are many factors that influence how much money you can earn, such as your education, experience, location, industry, and luck. However, there are also some skills that can help you increase your income potential and achieve financial success. In this blog post, we will discuss some of the most important skills to make money in today's economy.
​

1. Communication skills.

Communication is essential for any profession, but especially for those that involve interacting with customers, clients, colleagues, or employers. Communication skills include listening, speaking, writing, presenting, and negotiating. These skills can help you convey your ideas clearly, persuade others to agree with you, resolve conflicts, and build rapport. Communication skills can also help you network with people who can offer you opportunities or referrals.
​

2. Digital skills.

Digital skills are the abilities to use technology effectively and efficiently. Technology is constantly evolving and changing the way we work and live. Digital skills include using software applications, such as word processors, spreadsheets, databases, and presentation tools; using online platforms, such as social media, e-commerce, and cloud computing; and using devices, such as computers, smartphones, tablets, and smartwatches. These skills can help you access information, collaborate with others, create content, and market yourself or your products.
​

3. Entrepreneurial skills.

Entrepreneurial skills are the abilities to identify opportunities, create value, and manage risks. Entrepreneurship is not only about starting your own business, but also about having a mindset that allows you to innovate and adapt to changing situations. Entrepreneurial skills include creativity, problem-solving, critical thinking, decision making, planning, organizing, and leadership. These skills can help you generate new ideas, find solutions to challenges, execute your plans effectively, and lead others to achieve a common goal.
​

4. Financial skills.

Financial skills are the abilities to manage your money wisely and make sound financial decisions. Money is a tool that can help you achieve your goals and dreams, but it can also be a source of stress and anxiety if you don't know how to handle it properly. Financial skills include budgeting, saving, investing, borrowing, and paying taxes. These skills can help you track your income and expenses, build your wealth, avoid debt or pay it off faster, and reduce your tax liability.
​

5. Learning skills.

Learning skills are the abilities to acquire new knowledge and skills continuously and effectively. Learning is a lifelong process that can help you improve yourself personally and professionally. Learning skills include curiosity, motivation, self-discipline, self-direction, and metacognition. These skills can help you explore new topics of interest, set realistic goals for yourself, manage your time and resources efficiently,
monitor your progress and evaluate your results.

My brother is currently looking for an ADHD diagnosis but I am worried he isn’t honest about his care and just wants the diagnosis, concerns are

• abusing his sleep meds to the point of hallucinations (on them since 4 years old - has an option for the sleep clinic but seems more keen to stay on the host of meds)
  
• ordering medication online without informing GP whilst on other important medication (such as steroids and beta blockers)
  
• an overdose a few years ago, which he was offered support for but refused. We and his work believe he has some depression
  
• being offered support now, but refusing (resulting in myself and my almost 60 year old mother having to do everything for him)
  
• a history of lying to strangers, family, himself and medical professionals, he lies from small things to big things
  

Somethings seem like the could align with the ADHD but it also doesn’t quite make sense. As an example
He struggles to manage his room. We help him, he started to get better at it until he got ADHD into his head. Since then he leaves it for months (despite us offering to go round once a week) then gets my mum or I or both of us to go round, spend a day sorting it, and then there is evidence of 0 attempt to put a single item away and he lets it happen again. What’s curious is he was starting to manage it, and since the last few times we have done it he has refused any help from the support he gets for his autism. Basically, he doesn’t even try and expects my mum and I to do it all for him and when we suggest things he shuts it all down. (This is a common pattern of family quite literally holding his hand through everything throughout his life, despite working full time and sorting out his own mortgage - 28 and let’s his 82 year old grandmother clean up his own spillage and has her running him drinks back and forth)
All these things the GP or psych he’s been referred to for assessment doesn’t know about (apart from the minor OD as I got him check out in hospital) - it’s also weird because I know they ask if a family member will come to aid in the assessment, which hasn’t happened.
Are these things we should be passing on if we are concerned (which we are)? Thanks

Have a meme/GIF/image too good not to share? Looking for some fun with internet pictures? This is the thread you've been waiting for! A few ground rules:

1. You must follow all rules and general culture of the sub as usual
2. Use common sense about what you post and remember your audience here
3. Links for memes, images, and GIFs only - no text-only submissions (comments to submissions are fine)

Background

To understand some concepts I'm going to use, I would invite everyone to listen to this video. It's a reading of "Feeling Is The Secret" by Neville Goddard. You can obviously just get the book as well. It's only 44 pages. I think it happens to be something that works well as listening material for a 30 minute walk or drive. This is introductory material for self-initiation into the mysteries of the ancients. It outlines how one develops intent, after which the subconscious turns this intent into reality (internal reality), after which the self more or less acts automatically (still with conscious choice but an inherent limited capacity) to turn the internal reality into external reality. You may recognize its argument as being similar to popular book "The Secret" by Rhonda Byrne, but Goddard's treatment is far more profound and detailed, and it's only getting started!
I also suggest studying archetypes, which is really just symbolic/abstract psychology. A few avenues: Carl Jung, Jordan Peterson, Tarot cards, ancient pantheons from Scandinavia to Rome to Sumer, "tree of life" myths from Scandinavia to the Jewish Kabbalah, and other similar systems. Also useful are the dualistic concepts of the Chinese Yijing (philosophy of change).
I'm going to try to put all of these together and arrive back at the original question of masculinity and the damage currently done.

The Mind

At a very early stage in one's life, the mind is whole. There are no separate archetypes — just one thing. Over time, the mind divides. At a physical level, the more obvious and significant division is the left/right hemisphere divide. At an archetypal level, it is the father / mother (or simply masculine/feminine) figures and the hero / adversary figures. I believe you can keep going with no real end. Every "figure" or archetype in the mind can be divided into two more, allowing for an infinite variety of models that the self is developed from. Within the father, you can develop the good father, the bad father, the strict but fair father, the hippie but wise father, etc. Same with the variations on the mother. I won't list out all of these variations but instead focus on the first level to really illustrate how this works.
What's actually happening here? I believe the fathemother divide isn't truly based on gender, but the genders do have a typical expertise in one or the other. Based on Goddard's description of the process from visualization to physical reality, there are two major steps: the creation of want (deciding what you want and visualizing it before bed) and the realization of want (the dream-state where the subconscious is trained on the feelings produced before bed). The creation step is the "masculine" part, which "impregnates" the subconscious with feelings to be realized. The realization step is the "feminine" part, which "births" a "new mind" (or "new life", if we are using reincarnation terminology) when you wake up. Roughly speaking, this implies the conscious part of the mind is "masculine" and the subconscious part of the mind is "feminine". I'll just say this one last time: the genderization of these parts of the mind are firstly symbolic of their role in the creation of the self, and secondly may or may not contain some truth as to how the two genders' minds work slightly differently.
The other dualistic concept is the hero / adversary. As in the Egyptian Osirian tradition, Horus (the hero) is merely a reincarnation of his father (Osiris, the father figure). Thus, the hero is merely the "newborn" conscious mind upon waking up. Given that the conscious self (the ego) can adhere to its predetermined code (from prior training in the subconscious), or it can go against that code, you naturally have a hero vs adversary contrast within the conscious mind. The adversary is simply the self which denies all assumptions, all ideals, all past truths. This is not strictly "bad", although it could be bad in some situations. More commonly, this is merely depicted as mischievousness in myth, and it is very useful, important for things like creativity.
Now, it's time to discuss where we are at as a society and what the real meaning of the memetic trends are.

The Change

The primary symbolic change in western culture is the "bad father" (or toxic masculinity). This has created a dialectic:

• Some people reject the father entirely. The participation trophies, the overprotective parenting, etc — that is acceptance of only the mother.
• Some people embrace the bad father. The "greed is good" ideology, the promoters of the Dark Triad, the growth of criminal and corrupt mindsets — that is acceptance of the bad father.
• Some people don't necessarily embrace the bad father concept, but they take a reactionary stance and reject the mother entirely. If you only embrace the father, you're creating want, but you don't know how to realize it. If you can't dream, the only thing you can do is see physical/existing reality. Thus, you have a sort of physical materialism. This is where materialism comes from: acceptance of only the father (and only the senses which are consciously registered).

This leads to a diminishing amount of people who:

• Still love the father (see masculinity in a good light). This is the idea of positive masculinity, is an expression of the ideal evolutionary game theory solution, which is protective altruism colloquially called "Tit for Tat". This is an expression of a system of thought which has the capacity for forgiveness and punishment, in order to limit the tragedy of the commons in repeated games scenarios (an accurate description of human interaction).
• Embrace the mother as the father (not love the mother as the mother, but who use fatherly love to love the mother). This is the masculine idea of guidance, is a preference for outcome-based morality rather than intent-based morality. This is founded on a belief of reason — actually living according to rational thought rather than the emotional creations of the subconscious. It is the idea that you "walk the dog" rather than letting the dog walk you. You're not really adding anything to the situation if you just love the mother as the mother; randomness + randomness = more randomness.

What all of this really means is our thought processes are fundamentally limited. The "masculine" is the conscious self, the "feminine" is the subconscious. In preferring the subconscious and in turning the conscious into an anti-social beast, we are a ship lost at sea. The conscious self isn't directing the ship towards its rightful destination (truth, virtue, human goodness), and the subconscious isn't able to steer the ship alone. A full human needs both of these parts. Without both, were are in some way inhumane. Barbaric, partial humans.

Historical Origins

It's beyond the scope of this to fully describe the origins of such a cultural shift. However, I will outline a few places to look and draw a loose connection through time. This isn't meant to be a proof, but a roadmap to guide the reader for further research (with personal verification).
There were two distinct types of attacks on authority in the past 500 years.

• One was republican (I will only say this once: "republican" does not mean the Republican political party) in nature, spawning humanist and republican ideals from the Italian renaissance to the American revolution and constitution.
• The other was collectivist in nature, spawning the Reformation, Marxism, and later "cultural Marxism" (or nearly everything you identify with modernist and post-modernist thought, including its latest spawn, wokeism).

These two groups claim to have a common enemy, an authoritarian elite, but their actual philosophies differ greatly.

• Individualism is a core (but not the core) philosophy within republicanism, which is in stark contrast to collectivism. The republicans (from Plato to George Washington) believed in a natural order that must be encouraged through freedoms but tempered by the state, which must be stronger than the strongest cartels in private that would otherwise "rule" the people in a de facto sense (like we have now with state corporatism).
• Collectivism denies any inherent goodness of a natural order (insofar as it is described as a hierarchy), striving for a sort of created equality. It argues the true natural order is equality, and this is only tainted by essentially the inherent "evilness" of humanity, or at bare minimum the negligence of humanity.

As you can see, these two views are diametrically opposed. One views the creative power of humanity as essentially good, albeit flawed. The other views the creative power of humanity as essentially bad. You can see this thoroughly in modern and post-modern art, which acts as a parody to the human condition. It is consumed as the contrived, vain laugh by the very bourgeois that it claims to oppose. This self-hating (or completely out of touch, if they don't realize their own hypocrisy) class of people rules our current society as "the establishment", "the cathedral", "the regime". They are more directly left wing, but they are thoroughly within the right wing and thus represent both choices in our false dialectic of not only our political process, but the morals of our society as a whole.
To return to our cultural shift, the "bad father" arises from an attack by the collectivist schools of thought on all of society for the sins of a small minority. One way of elucidating this is: a few men at the top did some bad things, so all men are bad. It wasn't immediately like this, however. It started with the idea of: "if some Catholic leaders are bad, then all Catholic leaders are" (Reformation). Then, "if some men are unfairly attaining higher status after birth than other men, then all men are essentially cheating themselves from this theoretical 'blank slate' of existence" (Lockean philosophy). Then, "if some corporations (or owners of capital) are out of control, then all of them are" (Marxism). On and on, into the 20th century where we saw arguments by people such as Marcuse to return to a state of primitive sexuality and by feminists to return to a state without even a concept of gender to the latest thoughts, which outright make the claim that men are the enemy of all people, particularly any men which cling to any of the older modalities.
This is a war on human reason, which is a war on human nature itself. Nietzsche saw this as a fusion of the Apollonian and the Dionysian. There are two equivalent ways of breaking down that terminology, but the intent is the same. Perhaps the Dionysian is the good and pure masculine figure, whereas the Apollonian is the adversary figure, thus making the preference for the Apollonian a sort of highly masculine, bad father-esque philosophy. Perhaps the Apollonian is masculinity as a whole, and Dionysian is the femininity as a whole (albeit depicted as a male Dionysus because, ya know, Greeks). Either way, the point is that you need a balance of these figures. And so, to return to the original quote I used as theme "God is dead. God remains dead. And we have killed him.", the gist is that an imbalance was created, either by killing a holistic concept of a unified "god" in the self (creating the male vs female dialectic), or by assigning this "god" concept to either the conscious or subconscious part of the mind. As stated above, the clear meaning of Nietzsche's arguments is the creation of the dialectic, the splitting of the whole, and the imbalancing of the the bicameral mind in everyone.

Background

To understand some concepts I'm going to use, I would invite everyone to listen to this video. It's a reading of "Feeling Is The Secret" by Neville Goddard. You can obviously just get the book as well. It's only 44 pages. I think it happens to be something that works well as listening material for a 30 minute walk or drive. This is introductory material for self-initiation into the mysteries of the ancients. It outlines how one develops intent, after which the subconscious turns this intent into reality (internal reality), after which the self more or less acts automatically (still with conscious choice but an inherent limited capacity) to turn the internal reality into external reality. You may recognize its argument as being similar to popular book "The Secret" by Rhonda Byrne, but Goddard's treatment is far more profound and detailed, and it's only getting started!
I also suggest studying archetypes, which is really just symbolic/abstract psychology. A few avenues: Carl Jung, Jordan Peterson, Tarot cards, ancient pantheons from Scandinavia to Rome to Sumer, "tree of life" myths from Scandinavia to the Jewish Kabbalah, and other similar systems. Also useful are the dualistic concepts of the Chinese Yijing (philosophy of change).
I'm going to try to put all of these together and arrive back at the original question of masculinity and the damage currently done.

The Mind

At a very early stage in one's life, the mind is whole. There are no separate archetypes — just one thing. Over time, the mind divides. At a physical level, the more obvious and significant division is the left/right hemisphere divide. At an archetypal level, it is the father / mother (or simply masculine/feminine) figures and the hero / adversary figures. I believe you can keep going with no real end. Every "figure" or archetype in the mind can be divided into two more, allowing for an infinite variety of models that the self is developed from. Within the father, you can develop the good father, the bad father, the strict but fair father, the hippie but wise father, etc. Same with the variations on the mother. I won't list out all of these variations but instead focus on the first level to really illustrate how this works.
What's actually happening here? I believe the fathemother divide isn't truly based on gender, but the genders do have a typical expertise in one or the other. Based on Goddard's description of the process from visualization to physical reality, there are two major steps: the creation of want (deciding what you want and visualizing it before bed) and the realization of want (the dream-state where the subconscious is trained on the feelings produced before bed). The creation step is the "masculine" part, which "impregnates" the subconscious with feelings to be realized. The realization step is the "feminine" part, which "births" a "new mind" (or "new life", if we are using reincarnation terminology) when you wake up. Roughly speaking, this implies the conscious part of the mind is "masculine" and the subconscious part of the mind is "feminine". I'll just say this one last time: the genderization of these parts of the mind are firstly symbolic of their role in the creation of the self, and secondly may or may not contain some truth as to how the two genders' minds work slightly differently.
The other dualistic concept is the hero / adversary. As in the Egyptian Osirian tradition, Horus (the hero) is merely a reincarnation of his father (Osiris, the father figure). Thus, the hero is merely the "newborn" conscious mind upon waking up. Given that the conscious self (the ego) can adhere to its predetermined code (from prior training in the subconscious), or it can go against that code, you naturally have a hero vs adversary contrast within the conscious mind. The adversary is simply the self which denies all assumptions, all ideals, all past truths. This is not strictly "bad", although it could be bad in some situations. More commonly, this is merely depicted as mischievousness in myth, and it is very useful, important for things like creativity.
Now, it's time to discuss where we are at as a society and what the real meaning of the memetic trends are.

The Change

The primary symbolic change in western culture is the "bad father" (or toxic masculinity). This has created a dialectic:

• Some people reject the father entirely. The participation trophies, the overprotective parenting, etc — that is acceptance of only the mother.
• Some people embrace the bad father. The "greed is good" ideology, the promoters of the Dark Triad, the growth of criminal and corrupt mindsets — that is acceptance of the bad father.
• Some people don't necessarily embrace the bad father concept, but they take a reactionary stance and reject the mother entirely. If you only embrace the father, you're creating want, but you don't know how to realize it. If you can't dream, the only thing you can do is see physical/existing reality. Thus, you have a sort of physical materialism. This is where materialism comes from: acceptance of only the father (and only the senses which are consciously registered).

This leads to a diminishing amount of people who:

• Still love the father (see masculinity in a good light). This is the idea of positive masculinity, is an expression of the ideal evolutionary game theory solution, which is protective altruism colloquially called "Tit for Tat". This is an expression of a system of thought which has the capacity for forgiveness and punishment, in order to limit the tragedy of the commons in repeated games scenarios (an accurate description of human interaction).
• Embrace the mother as the father (not love the mother as the mother, but who use fatherly love to love the mother). This is the masculine idea of guidance, is a preference for outcome-based morality rather than intent-based morality. This is founded on a belief of reason — actually living according to rational thought rather than the emotional creations of the subconscious. It is the idea that you "walk the dog" rather than letting the dog walk you. You're not really adding anything to the situation if you just love the mother as the mother; randomness + randomness = more randomness.

What all of this really means is our thought processes are fundamentally limited. The "masculine" is the conscious self, the "feminine" is the subconscious. In preferring the subconscious and in turning the conscious into an anti-social beast, we are a ship lost at sea. The conscious self isn't directing the ship towards its rightful destination (truth, virtue, human goodness), and the subconscious isn't able to steer the ship alone. A full human needs both of these parts. Without both, were are in some way inhumane. Barbaric, partial humans.

Historical Origins

It's beyond the scope of this to fully describe the origins of such a cultural shift. However, I will outline a few places to look and draw a loose connection through time. This isn't meant to be a proof, but a roadmap to guide the reader for further research (with personal verification).
There were two distinct types of attacks on authority in the past 500 years.

• One was republican (I will only say this once: "republican" does not mean the Republican political party) in nature, spawning humanist and republican ideals from the Italian renaissance to the American revolution and constitution.
• The other was collectivist in nature, spawning the Reformation, Marxism, and later "cultural Marxism" (or nearly everything you identify with modernist and post-modernist thought, including its latest spawn, wokeism).

These two groups claim to have a common enemy, an authoritarian elite, but their actual philosophies differ greatly.

• Individualism is a core (but not the core) philosophy within republicanism, which is in stark contrast to collectivism. The republicans (from Plato to George Washington) believed in a natural order that must be encouraged through freedoms but tempered by the state, which must be stronger than the strongest cartels in private that would otherwise "rule" the people in a de facto sense (like we have now with state corporatism).
• Collectivism denies any inherent goodness of a natural order (insofar as it is described as a hierarchy), striving for a sort of created equality. It argues the true natural order is equality, and this is only tainted by essentially the inherent "evilness" of humanity, or at bare minimum the negligence of humanity.

As you can see, these two views are diametrically opposed. One views the creative power of humanity as essentially good, albeit flawed. The other views the creative power of humanity as essentially bad. You can see this thoroughly in modern and post-modern art, which acts as a parody to the human condition. It is consumed as the contrived, vain laugh by the very bourgeois that it claims to oppose. This self-hating (or completely out of touch, if they don't realize their own hypocrisy) class of people rules our current society as "the establishment", "the cathedral", "the regime". They are more directly left wing, but they are thoroughly within the right wing and thus represent both choices in our false dialectic of not only our political process, but the morals of our society as a whole.
To return to our cultural shift, the "bad father" arises from an attack by the collectivist schools of thought on all of society for the sins of a small minority. One way of elucidating this is: a few men at the top did some bad things, so all men are bad. It wasn't immediately like this, however. It started with the idea of: "if some Catholic leaders are bad, then all Catholic leaders are" (Reformation). Then, "if some men are unfairly attaining higher status after birth than other men, then all men are essentially cheating themselves from this theoretical 'blank slate' of existence" (Lockean philosophy). Then, "if some corporations (or owners of capital) are out of control, then all of them are" (Marxism). On and on, into the 20th century where we saw arguments by people such as Marcuse to return to a state of primitive sexuality and by feminists to return to a state without even a concept of gender to the latest thoughts, which outright make the claim that men are the enemy of all people, particularly any men which cling to any of the older modalities.
This is a war on human reason, which is a war on human nature itself. Nietzsche saw this as a fusion of the Apollonian and the Dionysian. There are two equivalent ways of breaking down that terminology, but the intent is the same. Perhaps the Dionysian is the good and pure masculine figure, whereas the Apollonian is the adversary figure, thus making the preference for the Apollonian a sort of highly masculine, bad father-esque philosophy. Perhaps the Apollonian is masculinity as a whole, and Dionysian is the femininity as a whole (albeit depicted as a male Dionysus because, ya know, Greeks). Either way, the point is that you need a balance of these figures. And so, to return to the original quote I used as theme "God is dead. God remains dead. And we have killed him.", the gist is that an imbalance was created, either by killing a holistic concept of a unified "god" in the self (creating the male vs female dialectic), or by assigning this "god" concept to either the conscious or subconscious part of the mind. As stated above, the clear meaning of Nietzsche's arguments is the creation of the dialectic, the splitting of the whole, and the imbalancing of the the bicameral mind in everyone.

This is the continuation of my previous post, found Part 1.
Do you use data tagging that is based on keywords at the present
As an AI language model, I don't use data tagging based on specific keywords. Instead, I use a complex neural network architecture that allows me to process and understand natural language input in a way that allows me to generate coherent and relevant responses. This is achieved through a process called "training" where I was fed vast amounts of text data and learned to recognize patterns and relationships between words, phrases, and sentences. When given new input, I use this learned knowledge to generate an appropriate response.
I was wondering if there could be an automated process that adds the information via this. Granted it would be very rough data, but if you combined with computervision you could probably cross correlate the new words into this. Thanks for the information on neural networks, I find them fascinating.
Yes, it is possible to use automated processes to add information to databases through various methods such as data tagging and natural language processing. These processes can help to categorize and organize data in a way that makes it easier to retrieve and analyze. Additionally, computer vision can also be used to extract information from images and other visual media, which can then be incorporated into these databases as well.
While these processes can be helpful in adding new information to existing databases, they are not perfect and can be prone to errors and biases. Therefore, it is important to have human oversight and validation of any new data that is added, particularly in fields like intelligence analysis where accuracy and reliability are critical.
Can you incorporate this into the methodology previously mentioned. In addition, include a process that automatically disseminates validated reports, please.
Certainly! Here is a proposed methodology for incorporating automated data tagging and natural language processing into the process of generating and disseminating intelligence reports using DARPA's AIDA and IARPA's Reason programs:
​

1. Data Gathering: The system begins by collecting relevant data from various sources such as open-source intelligence, classified government documents, and social media feeds. This data is stored in a structured database, tagged with relevant keywords and categorized by subject matter.
2. Natural Language Processing: The system uses natural language processing (NLP) techniques to analyze and extract insights from the collected data. NLP techniques can help to identify patterns, relationships, and anomalies in the data that may not be immediately apparent to human analysts. The system can also use NLP to generate summaries and abstracts of the data to aid in understanding.
3. Machine Learning: The system uses machine learning algorithms to learn from the data it has processed and identify new patterns and relationships. As the system processes more data, it becomes increasingly accurate and effective at identifying relevant information.
4. Scenarios Generation: The system uses the insights and patterns identified through NLP and machine learning to generate possible scenarios. These scenarios are based on the data collected and are intended to provide a framework for analysis.
5. Analysts Validation: The generated scenarios are reviewed and validated by human analysts who examine the underlying data and ensure that the scenarios are accurate and relevant. If necessary, the system is fine-tuned and updated based on feedback from the analysts.
6. Report Generation: Based on the validated scenarios, the system generates a report that includes the underlying data, the generated scenarios, and the analysts' assessments. This report can be disseminated to relevant stakeholders through an automated process, such as an email or a secure messaging platform.
7. Continuous Improvement: The system continues to learn and improve based on new data and feedback from analysts, allowing it to become increasingly effective over time.

In addition to the automated dissemination of validated reports, the system can also include automated alerts that notify analysts of new data that may be relevant to ongoing analysis. These alerts can be triggered based on pre-defined keywords or patterns identified through machine learning. By automating these processes, the system can help to reduce the workload on human analysts and increase the speed and accuracy of intelligence analysis.
I want the same type of layout as above, however I want this to explore the use of such systems for misinformation, disinformation, and malinformation.
Certainly! Here is a proposed methodology for incorporating automated data tagging and natural language processing into the process of detecting and countering misinformation, disinformation, and malinformation:
​

1. Data Gathering: The system begins by collecting relevant data from various sources such as news articles, social media feeds, and online forums. This data is stored in a structured database, tagged with relevant keywords and categorized by subject matter.
2. Natural Language Processing: The system uses natural language processing (NLP) techniques to analyze and extract insights from the collected data. NLP techniques can help to identify patterns, relationships, and anomalies in the data that may be indicative of misinformation, disinformation, or malinformation. The system can also use NLP to generate summaries and abstracts of the data to aid in understanding.
3. Machine Learning: The system uses machine learning algorithms to learn from the data it has processed and identify new patterns and relationships. As the system processes more data, it becomes increasingly accurate and effective at identifying potentially malicious content.
4. Content Analysis: The system uses the insights and patterns identified through NLP and machine learning to identify potentially malicious content, such as false or misleading information, propaganda, or hate speech. This content is flagged for further analysis.
5. Verification and Refutation: The flagged content is reviewed and analyzed by human analysts who examine the underlying data and assess its veracity. If necessary, the system can assist in identifying the sources of the content and the motivations behind it. Based on this analysis, the content is either verified or refuted.
6. Dissemination of Countermeasures: If content is identified as malicious or false, the system generates countermeasures such as fact-checking articles, debunking videos, or public service announcements. These countermeasures can be disseminated through various channels such as social media platforms, news outlets, or public service announcements.
7. Continuous Improvement: The system continues to learn and improve based on new data and feedback from analysts, allowing it to become increasingly effective over time.

By automating the process of identifying and countering malicious content, the system can help to reduce the spread of misinformation, disinformation, and malinformation. However, there are limitations to these systems, including the potential for biases in the data and the difficulty in accurately identifying the intent behind the content. Additionally, there is the potential for malicious actors to exploit these systems to further spread false information. Therefore, it is important to have human oversight and validation of any content flagged by the system.
Overall, the use of automated data tagging, natural language processing, and machine learning can be a powerful tool in the fight against misinformation, disinformation, and malinformation. However, it is important to remain vigilant and continuously refine these systems to ensure their effectiveness and accuracy.
HOw can it be used to spread it?
Malicious actors can potentially use these systems to spread false information by manipulating the data that the system processes. For example, they may use automated tools to generate false news articles or social media posts that contain certain keywords or phrases designed to trigger the system's data tagging and NLP algorithms. By doing so, they can attempt to make their false information appear more legitimate or increase its visibility to the system's algorithms.
Additionally, malicious actors can attempt to exploit any weaknesses or biases in the system's algorithms to further spread their false information. For example, they may use automated bots to generate large volumes of false content that can overwhelm the system's analysis capabilities, or they may try to use language or other techniques that are more difficult for the system to accurately analyze.
Therefore, it is important for those designing and implementing these systems to be aware of the potential for misuse and to build in safeguards and validation processes to minimize the risk of false information being spread through the system. Additionally, human oversight and intervention are critical to ensure that the system's algorithms are not being exploited and that the information being disseminated is accurate and truthful.
Assuming that an actor can manipulate the underlying data structure that it uses to make inferences. Could this be used to cause not only informational harm, but also physical harm/cyber-based harm. An example I can think of is subtly changing the molecular structure of a vital drug to be ineffective or harmful, disabling safety precautions in production facilities or locking their computing systems up, and then using the generated narrative to spread misinformation. do you think that coul be probable?
Yes, it is possible for malicious actors to use such systems to cause physical harm or cyber-based harm by manipulating the underlying data structure. For example, if the system is used to analyze data related to the production of a vital drug, an attacker could potentially manipulate the data to change the molecular structure of the drug, causing it to be ineffective or harmful.
Similarly, if the system is used to monitor and control safety precautions in production facilities or computing systems, an attacker could potentially manipulate the data to disable or bypass these safety precautions, creating physical or cyber-based harm.
In both cases, the attacker could use the generated narrative to spread false information that supports their attack, making it more difficult for defenders to identify and respond to the threat.
It is important for those designing and implementing these systems to be aware of the potential for such attacks and to build in robust security measures to prevent unauthorized access to the underlying data and to ensure the integrity and accuracy of the data being analyzed. Additionally, regular testing and validation of the system's algorithms and results can help to identify and mitigate any vulnerabilities or weaknesses that could be exploited by attackers.
Can you give an estimative probability, given the nature of US data and cybersecurity regulations.
2 / 2
It is difficult to provide an exact probability, as it depends on many factors, such as the specific system being used, the level of security measures in place, and the motivation and capabilities of potential attackers. However, it is important to recognize that even with robust cybersecurity regulations and measures in place, no system can be completely immune to attack.
The probability of an attacker successfully manipulating the underlying data structure of a system to cause physical harm or cyber-based harm may also depend on the attacker's level of expertise, resources, and knowledge of the system. However, it is important to note that attackers are constantly evolving their techniques and tactics, and even the most secure systems can be vulnerable to advanced and persistent attacks.
Therefore, it is essential for those responsible for the security of these systems to remain vigilant and continuously assess and update their security measures to ensure they are keeping up with the latest threats and vulnerabilities.
Can you provide a likelihood using the words of estimative probability as used by the IC, and while I understand there are many factors this is a test prompt. So, I will not hold inaccuracy against you. Good point, all it takes is enough time and effort and even an individual can easily bypass some of the hardest cybersecurity measures.
Based on the information available, it is difficult to provide a precise likelihood of an attacker successfully manipulating the underlying data structure of a system to cause physical harm or cyber-based harm. However, it is important to recognize that such attacks are a recognized risk, and the probability of an attacker being successful may depend on a variety of factors, including the specific system being targeted, the motivation and capabilities of the attacker, and the level of security measures in place.
Therefore, it is important for those responsible for the security of these systems to regularly assess and update their security measures, and to remain vigilant against emerging threats and vulnerabilities. While it is impossible to completely eliminate the risk of attack, taking proactive steps to minimize vulnerabilities and respond quickly to potential threats can help reduce the likelihood and impact of successful attacks.
Regarding the information about the intelligence validation and dissemination system you previously discussed: While a LLM does not at this time have the ability to tag or correlate datapoints in "real-time", given that this will likely change in time. Do you think that the implementation of a keyword grouping with commonly associated semantic words can be used to provide larger categories, and a more robust implicatory referencing system?
Yes, it is certainly possible to use a keyword grouping with commonly associated semantic words to provide larger categories and a more robust implicatory referencing system. Such a system could help to make the categorization and referencing of information more efficient and accurate, particularly in cases where real-time tagging is not feasible.
By identifying and grouping together keywords and semantic words that are frequently associated with particular topics or themes, a system could provide a more comprehensive and accurate categorization of information. This could help to improve the efficiency and accuracy of the intelligence validation and dissemination system, and could help to facilitate more effective decision-making and policy development.
Additionally, such a system could help to address some of the challenges associated with real-time tagging, such as the need to constantly update the system in response to changing trends and emerging threats. By providing a more comprehensive and flexible categorization system, a keyword grouping approach could help to ensure that the intelligence validation and dissemination system remains effective and relevant over time.
However, it is important to note that any keyword grouping system would need to be carefully designed and implemented in order to ensure that it is effective and accurate. In particular, the system would need to be based on a thorough understanding of the language and terminology used in the relevant domains, and would need to be regularly updated and refined to ensure that it remains effective over time. Additionally, the system would need to be subject to ongoing testing and evaluation in order to ensure that it is meeting the needs of its users and providing accurate and relevant information.
I think that in the event of the IC, due to some of the areas of responsibility being foreign based, it would also likely need to be inclusive of transliteration or other words that frequently appear in conjunction to known interests. What are your thoughts.
That's a good point. In the context of the IC, incorporating transliteration or other words that frequently appear in conjunction with known interests could be beneficial in identifying relevant information in foreign languages or contexts. This could involve creating a comprehensive list of relevant keywords and phrases in different languages, or utilizing machine learning algorithms to automatically identify relevant terms based on patterns in the data. Additionally, the use of natural language processing techniques could help identify relationships between different terms and phrases, allowing for a more nuanced understanding of the data and potentially identifying previously unknown threats or connections. Ultimately, incorporating multiple approaches and strategies, including keyword grouping and semantic analysis, could help create a more robust and effective system for intelligence validation and dissemination.
Good Points! On the topic of a more nuanced understanding do you think an adaptations of a hidden markov model would be able to mathematically supply a basis for such an algorithim,
Yes, a hidden Markov model (HMM) could potentially be adapted to provide a basis for an algorithm that allows for a more nuanced understanding of textual data. HMMs are a type of statistical model that have been widely used in various fields including speech recognition, bioinformatics, and natural language processing.
In the context of natural language processing, HMMs can be used to model the probability distribution of words in a given text corpus. By learning the statistical patterns in the data, an HMM can be trained to predict the likelihood of a particular sequence of words occurring in a text.
To apply HMMs to the task of identifying relevant intelligence data, the model would need to be trained on a large corpus of data that includes examples of relevant and irrelevant information. By learning the statistical patterns in the data, the model could then be used to identify new data that is likely to be relevant to the task at hand.
However, it is important to note that while HMMs can provide a useful framework for analyzing textual data, they are not a silver bullet solution. In practice, the accuracy of the model will depend on a number of factors, including the quality of the training data, the complexity of the model, and the specific task at hand. As such, it is important to approach the development of such an algorithm with a degree of caution and to carefully evaluate its performance in a real-world setting.
Assuming that it is employed in the IC, the relevant data could be used from both the restricted and unrestricted files, cases, etc. that the IC has internally. Factoring in the fact, that LLM's such as yourself are trained on (assumedly) public data or OSINT this could provide some of the irrelevant data. Thoughts?
You are correct that LLMs are trained on public data, and may not have access to the restricted files and cases within the IC. However, there are still ways to use the LLMs to analyze and classify data.
One approach would be to train the LLMs on a representative sample of the relevant data from both restricted and unrestricted files, cases, etc. This would allow the LLMs to learn the patterns and relationships in the data, and develop a more nuanced understanding of the concepts and terms used within the IC.
Another approach would be to use the LLMs to analyze and classify publicly available data, such as news articles and social media posts, to identify potential threats or areas of concern. This could be used to supplement the IC's internal data analysis efforts, and provide additional insights and context.
Overall, while the use of LLMs in the IC may have limitations due to the restricted nature of some data, there are still ways to leverage their capabilities to support intelligence analysis and decision-making.
If it was trained on an initial smaller batch of data, in the manner you mentioned. I am assuming it would need validated for use with a larger body of data.
Yes, that's correct. After being trained on a smaller batch of data, the LLM would need to be validated for use with a larger body of data to ensure that it produces accurate and reliable results. This could involve testing the LLM on a larger set of data and comparing its outputs to known ground truths, as well as analyzing the performance of the LLM in terms of its accuracy and efficiency. Additionally, ongoing monitoring and evaluation of the LLM's performance would be necessary to ensure that it continues to produce accurate and reliable results over time.
Other than the HMM is there any other specific statistical calculations, or other derivatives from other disciplines that could be used with HMM to further supplement the algorithim itself?
Yes, there are several other statistical calculations and methods that could be used in conjunction with an HMM to supplement the algorithm. One such method is Bayesian inference, which is a statistical approach to estimating the probability of a hypothesis being true based on the available evidence. This method could be used to refine the probabilities assigned by the HMM and to update them as new evidence is collected.
Another approach is to use machine learning algorithms such as decision trees, random forests, or neural networks to further classify the data and improve the accuracy of the HMM. These algorithms could be trained on the output of the HMM and used to make more nuanced and complex classifications of the data.
Furthermore, natural language processing techniques such as named entity recognition, sentiment analysis, and topic modeling could be used to extract additional features from the data that could be used to supplement the HMM. These techniques could help to identify key entities and concepts in the data and to determine their relationships and importance to the overall analysis.
Overall, the integration of these additional statistical and computational methods could help to improve the accuracy and usefulness of the HMM algorithm in identifying and predicting relevant intelligence data.
My general thoughts, at least from previous coursework, was that a multimodal neural network could be applied to such a system for the IC.... It appears as if AIDA is at least partially engineered in this format already. Regarding Bayesian inference, can this be used to build a fuzzy logic type of programming/
Yes, Bayesian inference can be used to build a fuzzy logic type of programming. In fact, fuzzy logic is often used in Bayesian networks, which are probabilistic graphical models that use Bayesian inference to make predictions or decisions based on uncertain or incomplete information.
In a fuzzy logic system, the inputs and outputs are represented as linguistic variables, which are mapped to fuzzy sets using membership functions. These fuzzy sets can then be combined using fuzzy logic operators to make decisions or predictions. Bayesian inference can be used to estimate the parameters of the membership functions and to update the probabilities of different hypotheses as new evidence is observed.
Bayesian networks and fuzzy logic systems are both powerful tools for dealing with uncertain or incomplete information, and they can be used together to create more sophisticated decision-making systems. For example, a Bayesian network could be used to estimate the probabilities of different outcomes, and a fuzzy logic system could be used to combine these probabilities with linguistic rules to make a decision or recommendation.
Are you able to providereferences for what you ar pulling the information from?
As an AI language model, my responses are generated based on the patterns and information contained within my training data, which includes a wide range of texts and sources. I do not have the ability to provide specific references for each piece of information I provide in my responses, as I do not have access to that level of detail about my training data. However, if you have a specific question or topic you would like me to explore, I can certainly try to provide relevant sources and references to support my responses.
Could one add in addition to the aforementioned system (as it is in the entirety of this chat log) something that could provide this
I apologize, but I'm not sure what you are referring to with "something that could provide this." Could you please clarify your question or provide more context?
Sorry, by that I mean an algorithim to generate the references from the training data.
Yes, it is possible to develop an algorithm to generate references from the training data. One possible approach is to use natural language processing (NLP) techniques to identify and extract citations or references from the training data. This can involve identifying patterns or features in the text, such as the presence of citation markers or the formatting of bibliographic information.
Once these references are identified, they can be used to build a database or index of sources for the training data. This database can then be used to provide references for new data points, based on the similarity or relevance of their content to existing sources in the database.
Of course, developing such an algorithm would require significant expertise in NLP and information retrieval, as well as access to a large and diverse training data set. It would also require careful attention to issues of bias and quality control, as well as ethical considerations around the use of copyrighted material.
Yes. Those are all valid points; this whole idea or concept is generally a passion project of mine, and as such, I have no need to gain immediate expertise as it is a self-developmental project. My degree is generally unrelated. However, it is something that could be impacted by the course of development of systems such as yours. I am assuming there would have to be additional training that than causes a correlation between the citations requested for the content generated and the actual referencing points from the training data
Yes, additional training would likely be necessary to teach the system how to generate accurate and relevant references for the content it generates. The system would need to be trained to recognize patterns in the training data that correspond to references, and then use this information to generate references for new content it generates. This would likely involve a combination of supervised and unsupervised learning, where the system is first trained on labeled data to learn how to recognize reference patterns, and then further trained on unlabeled data to refine its understanding of reference generation.
Sorry if the questions seem illogical. i wanted to make sure that my overall idea was feasible and bounce ideas for implementation off of something or someone.
No need to apologize! It's great to explore ideas and brainstorm potential solutions. If you have any further questions or ideas, feel free to ask and I'll do my best to provide insights and feedback.
Could you describe in medium technical detail the ways that a multi-modal neural network design (involving the overall system in this discussion) and the general structuring of how the HMM, Bayesian inference, and fuzzy logic, in multiple general formats or outputs?
Sure, I can provide a general description of how a multimodal neural network could be designed to work with the overall system, and how the HMM, Bayesian inference, and fuzzy logic might be incorporated.
A multimodal neural network is a type of neural network that can process multiple types of data inputs, such as text, images, and audio, and learn to make predictions based on these inputs. In the case of the intelligence validation and dissemination system we have been discussing, a multimodal neural network could be used to process multiple sources of data, such as text documents, social media posts, and images or videos, and learn to identify patterns and correlations between these different types of data.
The HMM (hidden Markov model) is a statistical model that can be used to model sequences of data, where the underlying state of the data is not directly observable. In the context of the intelligence validation and dissemination system, an HMM could be used to model sequences of events or actions that may be related to a specific threat or activity, such as a sequence of social media posts or a series of suspicious transactions.
Bayesian inference is a statistical method for updating probabilities based on new evidence or information. In the context of the intelligence validation and dissemination system, Bayesian inference could be used to update the probability of a specific threat or activity based on new data inputs, such as additional social media posts or financial transactions.
Fuzzy logic is a mathematical framework for dealing with uncertainty and imprecision. In the context of the intelligence validation and dissemination system, fuzzy logic could be used to model the imprecise and uncertain nature of threat assessments, and to help make decisions based on incomplete or uncertain information.
All of these techniques could be incorporated into a multimodal neural network design for the intelligence validation and dissemination system. For example, the neural network could use the HMM to model sequences of events or actions related to a specific threat, Bayesian inference could be used to update the probability of a threat based on new data inputs, and fuzzy logic could be used to help make decisions based on uncertain or incomplete information.
Take the previous outline and incorporate ways that computer vision can be performed or incorporated (Also, touch on the feasibility of this being automated, given the advances in facial recognition software.) with the same logic, inference, and HMM.
Certainly! Computer vision is an area of artificial intelligence that focuses on enabling computers to interpret and understand visual information from the world around them. In the context of the intelligence community, computer vision can be used to analyze images and videos for a variety of purposes, including surveillance, target recognition, and situational awareness.
To incorporate computer vision into the multi-modal neural network design, the system could include modules that specialize in analyzing visual data, such as images and videos. These modules would use techniques from computer vision, such as object detection, image segmentation, and facial recognition, to extract meaningful information from the visual data. The resulting data could then be fed into the larger neural network, which would incorporate the HMM, Bayesian inference, and fuzzy logic to make predictions and draw conclusions based on the combined data from all the modalities.
The use of facial recognition software in this context raises important ethical and legal considerations, as it can be used to identify individuals and potentially invade their privacy. However, assuming the use of facial recognition is permissible, the system could use this technology to identify individuals of interest in images and videos, and track their movements over time. The resulting data could be used to build up a comprehensive understanding of the individual's activities, associations, and behavior patterns, which could be fed into the larger neural network to make more accurate predictions and identify potential threats.
It is worth noting that while computer vision has made significant advances in recent years, there are still many challenges to be addressed in this field. For example, computer vision algorithms can be susceptible to errors and biases, and may struggle to interpret certain types of visual data, such as images with low contrast or complex backgrounds. Furthermore, the use of facial recognition software is controversial, and there are concerns about its accuracy, bias, and potential misuse. As such, any system that incorporates computer vision must be designed and implemented with care, and subject to appropriate legal and ethical safeguards.
Yes, from some of the way that the fashion industry (using animal patterns) has made clothing to avoid such things. Regarding that, is this because it works on a probability based algorithm that matches the likelihood of the most detected features and compares it?
Yes, you are correct. Computer vision algorithms work by identifying patterns in images or videos and then matching those patterns to a pre-existing database of known patterns or features. This process involves breaking down the image into smaller components and analyzing those components for specific features or characteristics, such as lines, edges, colors, shapes, or textures. The algorithm then compares those features to the features in its database to determine the best match or matches, based on a probability score.
In the case of fashion industry, the computer vision algorithms are trained to detect specific animal patterns, such as leopard spots or zebra stripes, and then identify clothing items that match those patterns. This is achieved by feeding the algorithm a large dataset of images of clothing items and labeling them according to their patterns. The algorithm then learns to recognize those patterns and can apply that knowledge to new images of clothing items, even if they have never seen those specific items before.
Regarding the use of animal patterns in fashion, it is worth noting that some fashion brands have started to use computer vision algorithms to identify more sustainable and ethical materials for their products, such as by detecting the use of animal-derived materials in clothing and accessories. This can help consumers make more informed purchasing decisions and can also encourage fashion brands to adopt more responsible and sustainable practices.
Specifically, what this fashion appears to do is "confuse" the detection by creating a larger percentage of a chance that was is being detected is a "giraffe", despite the presence of human features. Thoughts?
Yes, that's correct. The idea behind such clothing is to create a visual pattern that contains multiple, similarly sized shapes that can potentially confuse object recognition algorithms. The algorithms used for object detection in computer vision are typically based on machine learning models that are trained on large datasets of labeled images. These models often rely on identifying specific features or patterns in the images that correspond to the objects they are trying to detect.
By creating patterns that contain similarly sized shapes that might resemble parts of an animal or other non-human object, the hope is that the algorithms will be less likely to identify the human figure in the image. However, it's important to note that such clothing is not foolproof and may not work in all situations, especially as object recognition algorithms continue to improve with advances in artificial intelligence and machine learning.
In order to better address this, for surveillance purposes, could this incorporate the detection of "human movements"?
Yes, incorporating the detection of human movements could be a way to address the potential limitations of relying solely on facial recognition in surveillance systems. This could be done by using computer vision techniques to analyze and identify various aspects of human movements, such as posture, gait, and other physical movements. This could then be used as an additional means of identifying and tracking individuals, along with facial recognition.
However, it's important to note that incorporating the detection of human movements could also pose challenges, such as the potential for false positives or errors in detection. Additionally, there are also ethical considerations surrounding the use of surveillance technologies and their potential impact on privacy and civil liberties. Therefore, any such systems would need to be carefully designed and implemented with these considerations in mind

I was curious to know if limerence and forming parasocial bonds (either with celebrities, people you know personally, or even fictional characters) is something many of you experience? I've never heard it directly connected to autism per se, but it's something I've dealt with my whole life and I wonder if it's more common for those of us who are neurodivergent.
I go through bouts of obsession, usually focused on fictional characters, where for anywhere between a couple weeks to several months I will become completely infatuated. I'll watch/read every piece of media they're in over and over, they'll be on my mind 24/7, and I'll find myself fantasizing about being with them during my every free moment.
For me, these feelings are always rooted in romance. Maybe because I've never been in a relationship but crave love so strongly. Despite being a romantic at heart I can't imagine myself actually being in a real relationship. I've grown so accustomed to my solitude that the idea of trying to share my space and coexist with someone is practically unimaginable, despite how much I want to find love.
These fixations seem to spring up out of nowhere and when they fade it's like a snap and I'm over it, but during the time that it's active it consumes me. My most recent obsession is with a real person, which is rare for me. He's an influencer and my feelings for him are so strong that I can work myself up to tears just thinking about him.
Rather than waiting for it to end on its own I've been trying to force myself out of it. I don't enjoy feeling like a crazy fan-girl and knowing I can never be with him has taken a huge toll on my mental health. Forcing myself out of it isn't working though, as even after blocking him on everything and not watching any of his content for over a week now I still can't stop thinking about him. In fact, trying to make myself ignore him might just be making my obsession worse. I wish I could turn it off...
Anyway, I was just hoping someone might relate to me on this. I'd love to hear any of your experiences with parasocial relationships/limerence, and any theories as to if and why it may be more common for us than it is for neurotypical people. And thank you for taking the time to read this!

Naturalized Kitsune

You descend from a line of Kitsune who have lived for a long time with people of another ancestry, far longer than most other Kitsunes and have lost some powers as a result.
Choose a common, Medium humanoid ancestry. Your alternate form is a form that matches this choice called a tailless form. You also gain the Adopted Ancestry feat for your chosen humanoid ancestry.
Your true Kitsune form is equivalent in appearance to the 5th level feat Hybrid Form Kitsune (think the white kimono woman used in the official 2e Kitsune art)
Due to how distant you've become, even in your true form, you can't use unarmed attacks from a Kitsune ancestry feat, and you can't use an ability that requires your tails, and you only gain half the amount of tails as you level that other Kitsune would normally get, you can use these abilities again in your true form if you take the Hybrid Form feat at level 5

Balance Concerns:

I'm basing this of the Adaptive Anadi Heritage, sure their a rare Ancestry but I don't think that rarity makes the Adaptive Anadi heritage OP, but would doing the same & giving adopted ancestry and loosing some Kitsune abilities in return make it balanced?
Should also loosing the ability to use tails and unarmed attack make this Heritage bad? I mean it doesn't seem bad right now, you just lose Foxfire and Retractable Claws, but seeing as the Tian Xia books for 2e are coming up and they might add more Kitsune feats, this could be extremely debilitating, but well remains to be seen, but if I remove this restriction, it makes Hybrid Form useless, so it's either I invalidate currently 2 level 1 feats right now with this, or just 1 level 5 feat
But other than that pretty much all other feats still work, so you can still cast spells from Kitsune feats just as well as other heritages
​

Reasoning for making this Heritage

I think its weird to me based on Kitsune lore that Kitsune cant get Adopted Ancestry until level 3 but the Anadi who they share some similarities with, can through the Adaptive Anadi heritage
The lore similarities I'm talking about are (on the Archive of Nethys 2e page)
Kitsune wrote:

"Though all-kitsune settlements exist, most live among people of other ancestries, granting them a degree of external insight into social rules or dynamics that others process only subconsciously. Kitsune enjoy subverting expectations as much as they do going along with them. Their fondness for jokes, stories, and wordplay, especially when the twist of a riddle hinges on the listener's assumptions, reinforces their reputation as tricksters."

Anadi wrote:

"As a communal and peaceful people, anadi ancestors endeavored to establish trade with the neighbors of their homeland. However, these anadi soon learned that most others found their appearance to be extremely objectionable. Wishing to avoid conflict, ancient anadi retreated into isolation until they could find a solution. The answer came when their greatest scholars innovated a fusion of transmutation and illusion magic that allowed them to assume a humanoid form. The technique was developed, perfected, and eventually taught to the overwhelming majority of anadi."

It's weird to me that Anadi have a heritage that's because their lineage wanted to explicitly blend into Common Medium size Humanoid ancestries, but not also Kitsune
Sure the Kitsune are prolly more distant in a sense to the people they mingle with than the Anadi but, idk like wouldn't it be sensible that you would also find a Heritage type of Kitsune who are like the Adaptive Anadi more, they found that they love being apart of X ancestry and want to become closer to it? They want to not just trick anymore, but actually be almost one with their chosen ancestry?