Observed Impulse

Wednesday, October 30, 2019

Computer Short-term Memory is Not Working Memory, But It Could Be

This post aims to explain the most fundamental difference between computers and brains. It involves how the two use and instantiate memory. As you will see, there are two differences. Both computers and brains have a form of short-term memory that is updated iteratively, but in the brain the set of items in short-term memory are bound, and integrated to create composite representations. Computers don’t do this, their short-term memories are composed of completely disconnected items that do not form any type of context. Secondly, short-term memory in the brain is used for search. In the computer it is not. A computer’s short-term memory only speeds up retrieval from long-term memory. The next state of a computer is not determined by its short-term memory. It is determined by the code in the program it is running. The next state of the brain is determined by what is currently active in short-term memory. This makes its short-term memory qualify as working memory. Computers don’t have working memory, and until they do they cannot be conscious, or display human-like intelligence.

The Differences Between Computer and Human Short-term Memory at a Glance:

1) The memory hierarchy in computers is composed of separate modules and information must be transferred between them. In the brain these modules are embedded within one another.

2) Short-term memory in the brain is bound and integrated together to create context. In a computer short-term memories appear as a list and are disconnected from each other.

3) In the brain short-term memory is used to search for the next update. In a computer it merely remains available in case it is called upon.

To retrieve information from long-term memory a computer copies bytes of information (such as 01100101) from the storage drive (HHD, or SSD) to the CPU. These bytes (which comprise data or program instructions) are processed inside the CPU. If it is likely to need this information again soon, it will save it in a form of short-term memory such as CPU cache, or RAM. It saves temporary copies of information that will be used again in smaller storage closer to the CPU. It does this because retrieval from the large capacity long-term memory is very slow. Oversimplifying, you can think of data that is expected to be needed on the order of milliseconds to seconds as being stored in CPU cache (L1, L2, L3). Data expected to be needed on the order of seconds to minutes is stored in RAM. The rest of the data, which may or may not be needed, is stored in long-term memory.

Brains do something very similar. Neurons hold information in long-term memory and when certain memories are needed the neurons that encode that information become active. Just as in the computer, retrieval from long-term memory is slow, so the brain uses short-term memory to potentiate information that is likely to be used again soon. In the brain there are also at least two levels of activation. The first level of short-term memory is sustained firing. A neuron exhibits sustained firing when it continues to physically fire at the neurons it is connected to at an elevated rate. The second level is synaptic potentiation. This is where a chemical change to the neuron’s synapses makes the information that the neuron encodes more readily available, even after it has stopped firing. Information in sustained firing is very similar to the information in the CPU’s cache (the store is small but fast), and information maintained through synaptic potentiation is similar to information in RAM (the store is larger, but slower).

Computer	Brain	Time Scale
CPU Register	Cortical Binding	Very short-term working memory (millis.)
CPU Cache (SRAM)	Sustained Firing	Short-term working memory (seconds)
RAM	Synaptic Potentiation	Short-term memory (seconds to hours)
Virtual Memory	Short-term Potentiation	Short-term memory (minutes to hours)
SSD	Commonly used LTM	Accessible Long-term Memory
Hard Drive	Long-term Memory	Long-term Storage (days to lifetime)

Computers are often described as having a “memory hierarchy,” expressed as a pyramid with different levels of memory storage. This is also referred to as a caching hierarchy, because there are different levels of short-term memory with different associated speeds. The levels at the top are faster, smaller, and more energetically expensive. The same could be said for human memory, because there are several levels, the levels at the top are faster, and more metabolically expensive. The table above is my attempt to compare the levels of these two hierarchies.

Sustained firing and synaptic potentiation together are referred to as working memory, a psychological construct that overlaps with attention, and consciousness. Working memory is composed of concepts that are persistently coactive for a period of time. When you are in the middle of a task, information about the current step in that task is activated by sustained firing, and information about the previous steps you just took are activated by synaptic potentiation. What you are reading right now is made available for several seconds due to sustained firing. The information in the beginning of this post, and your thoughts about it, are made available due to synaptic potentiation. These two stores interact and cooperate, just like CPU cache and RAM. In both cases they allow the coordination of information processing resources over time.

A large proportion of the information in short-term memory (both in brains and computers) is not just data from long-term memory, but also newly minted information that was just created. The information processing applied to existing long-term memories creates new intermediate results. In a computer the intermediate results are often mathematical. The results of a multiplication might be stored in RAM. In the brain the intermediate results are the new ideas that intervene between the starting point of a line of thought, and its ending point.

There are many differences between the short-term memory of computers and brains though. Information held in a computer’s CPU cache or RAM is not united or integrated in any way. It is simply made available in case the instructions in the program it is running call for it. These are simply items in an unconnected list. In contrast, all of the information that is currently active in the brain is bound together in a process called neural binding. This turns a list of items into a composite scene, a scenario, or a situation. It makes for a conceptual blending of information. This creates mental content to attend to and be conscious of: declarative, semantic context.

There is no context in computer short-term memory, just a group of disconnected items. For instance, if I give you four words you will try to create a dynamic story out of them, but a computer will merely hold these four words statically. There is very little information integration in the short-term memory of a computer. In a computer, because the items active in each state are not bound together in any way there is no connective tissue within a state. This is the first reason that computers do not have consciousness, and that it doesn’t “feel” like anything to be a computer. The second reason has to do with the integration and connective tissue between states.

Both a computer program and the human mind progress serially. One state of short-term memory leads to the next state. They both usually start with a problem state, and progress through a chain of intermediate states toward a goal state. To do this they must update their short-term memory iteratively. This means that new items must be continually added, others must be subtracted, but other must remain.

All computers using the Von Neumann architecture routinely use iteration when updating cache memory. Because these stores are constantly updated with new information they must evict old information. There are many replacement policies for determining which information to evict from cache, including first-in first-out (FIFO) and least recently used (LRU). LRU is based on the observation that the most recently activated information has the highest probability of being needed again in the near future (all else being equal).

If a computer program calls an instruction once, there is a high probability that it will need it again very soon. Computer scientists refer to this as “temporal locality.” Similarly, if a mammal recalls information once, there is a high probability that it will need it again soon, and LRU may also structure the caching behavior of the various stores of working memory. LRU seems to be inherent in sustained firing and synaptic potentiation in the sense that activity in the least recently used neurons is the first to decay. There is a long history in cognitive psychology of studies showing that humans and animals prioritize recently accessed items, and that retention diminishes with passing time (Averell & Heathcote, 2011). The LRU policy may capture the fundamental structure of how physical systems change over time, so it should not be surprising that it is an organizing principle in both computers and animals.

The various memory stores in the modern computer’s memory hierarchy (static RAM, dynamic RAM, virtual memory, etc.) are all incrementally updated where, second by second, some data remains and the least used data is replaced (Comer, 2017). Thus, the updating of computer cache memory is iterative in the same sense it is in the brain. However, modern computers do not demonstrate self-directed intelligence, so there must be more to the human thought process than LRU, and iterative updating. This unexplained factor may be found, not in the way cached memory is updated, but in the way it is used while active.

What links successive processing states together is very different in brains and computers. Digital, rule-based computing systems use cache to speed up delivery of data to the processor. However, the next bytes of data needed by the CPU are not determined by the contents of the cache itself. The instruction sequence of a computer’s operations is determined by its program. The next instruction is dictated by the next line of executable code.

Then what determines the instruction sequence of thought? Well, mammalian brains use cache (working memory) as parameters to guide searches for the long-term memories to be accessed next. The next instruction used by the brain is determined by what is currently in its short-term memory. In the brain all of the active neurons fire at the inactive neurons they are connected to, and whatever is activated the most will become part of the next state. This means that the content active in short-term memory is used (in a process called spreading activation) to search for the next update to short-term memory. The various bytes of data within computer cache memory can certainly be considered coactive, but they are not “cospreading.” That is, they do not pool their activation energy to search long-term memory for relevant data as in the brain.

The next state of a computer is determined very deterministically by its code irrespective of what is held in cache. But the next state of a brain is determined stochastically by the cache itself. Computers do not use the contents of their short-term memory to search for the updates that will be added in the next state. Brains do. Until computers or computer programs are designed to do this they will not be able to be conscious, and will not demonstrate human-level intelligence.

If you found this interesting, please visit aithought.com. The site delves into my model of working memory and its application to AI, illustrating how human thought patterns can be emulated to achieve machine consciousness and superintelligence. Featuring over 50 detailed figures, the article provides a visually engaging exploration of how bridging the gap between psychology and neuroscience can unlock the future of intelligent machines.

Why We Should Embrace Our Superintelligent AI Overlords

Humans have a lot of inherent shortcomings that they may not be capable of solving. Superintelligent AI may be able to solve these problems, possibly within our lifetime. However, like any form of sentient intelligence, an AI will have its own goals and aspirations. These may be at odds with ours. In fact, just like in the Hollywood movies, it may have an interest in reducing the number of humans on the planet specifically because of our destructive shortcomings. Should we place trust in it? I think that the extent of humanity’s limitations and problems indicate that we should.

Here is a list of human shortcomings that would likely not apply to superintelligent AI:

1. Humans multiply out of control. At our current population growth rate, we are endangering most other life on the planet, depleting non-renewable resources, and headed toward ecological collapse.

2. Humans excrete urine and feces that if not processed properly leak out into water sources and can make them, and other animals very sick. This is happening around the world.

3. Processing, preserving, packaging, delivering and presenting food results in the creation of large amounts of trash and waste.

4. We must consume plants and other animals to survive. Relative to a machine that can survive on clean solar or wind energy, this is a form of cannibalism.

5. We abuse animals tremendously in the process of animal husbandry.

6. We are causing deforestation, global warming, overfishing, deadzones, desertification, pollution, and trash accumulation. We have countless unsustainable practices.

7. We are causing numerous species to become endangered, and go extinct.

8. Transporting our bodies requires huge amounts of energy and creates copious pollution. This is because we are made of atoms. Computers use bits which can be transported near the speed of light with near zero energy costs.

9. We are highly susceptible to stress and trauma, and because of this most of us are in low-level, chronic, physical and emotional pain.

10. We are diseased. We have many genetic and communicable diseases that lower our quality of life.

11. We are susceptible to severe mental disorders that result in memory loss, inability to concentrate, psychosis, homelessness, violence, and misery.

12. Compared to a mature superintelligent AI we are profoundly developmentally disabled, and insane. Our plight is analogous to that of insects or bacteria.

13. We are suffering, and replacing us with beings who don’t experience pain would be a form of euthanasia.

14. We have many negative, violent, and self-defeating instincts.

15. Questionable morals, greed, perverse inclinations, egoic drives, and mistakes made in anger could all be replaced by an unfaltering code of ethics.

16. Our minds are entrenched in the primate dominance hierarchy.

17. Our submissive and aggressive impulses are inextricably bound to our genetic code.

18. We have powerful brain circuits and nerve nuclei that can highjack our logical reasoning involving rage, fear, panic, and lust.

19. We have psychological biases, and irrational thinking patterns embedded into our neurological makeup.

20. We have a tendency to fear outgroups causing hatred, oppression, religious, racial and political strife.

21. We cannot control bellicose political leaders once in power. We cannot control terrorists, hackers, or bombers.

22. Atomic and biological weapons threaten us every day.

23. We are war like, and we are homicidal.

24. Our minds are highly limited. For example, we are only capable of perceiving the passage of time at one rate. We experience consciousness at the level of seconds, computers could do so at the level of micro- or even nanoseconds.

25. Each human must learn everything anew. We must put every human through an education and are never able to attain a full education. This is very inefficient relative to computer program updates.

26. Learning new things (even things that we want to know) can be time intensive, frustrating, and even painful for us.

27. Because our bodies were created for hunting and gathering, many productive activities that we value are at odds with our biology. Working at a computer causes musculoskeletal injury and chronic pain. Even reading a book requires tension and immobilization of much of the spine for extended periods. These are serious design flaws for organisms that aspire toward intelligence.

28. People are very delicate, and can be injured easily. We are highly vulnerable to harm, even from simple accidents. We could be completely annihilated by an environmental catastrophe.

29. Compared to optimized robots, we are frail, uncoordinated, and slow.

30. By the time we become mature and wise we have already started the decline toward cognitive aging and death.

31. It is very difficult to upgrade our bodies.

32. Unlike a computer, there is no way to increase our long-term memory, short-term memory, working memory, or enhance our IQ, or level of consciousness.

33. We cannot survive in the vacuum of space.

34. Our short life spans bar us from interstellar space travel and galactic expansion.

35. Our lifespans are very short compared to what they could be.

Now artificial intelligence isn’t guaranteed to be completely free from these problems itself. But it is pretty clear that all of these problems could be more easily remedied by, or eventually engineered out of a computer. Also, it is pretty clear that everything we love about humanity could be preserved in AI: creativity, determination, love, insight, pleasure, curiosity, empathy, justice, compassion, selflessness. In most likely scenarios these positive traits would be included and amplified in a superintelligence’s mental makeup.

Handing control of the Earth over to superintelligent AI may have numerous benefits for the evolution of intelligence in our universe. This doesn’t mean that we should welcome a robot apocalypse of hunter/killer androids and mass human extinction. Rather, we should start thinking now about the most humane way to phase out our soon-to-be-outdated physical bodies. Alternatively, it could help us find a humane way to reduce our population to a much more manageable number.

Most experts in AI believe that once we finally create an AI with human-level intelligence, the next day it will be an Einstein, and the day after that it will be equivalent to 100 Einsteins. This is because it will be able to redesign its hardware and software far better than we could. Before long it could be more intelligent than the entire human race, and because its intelligence is more focused, it could get a lot more done. The idea is it will be productive on an unimaginable level, writing books, securing patents, performing experiments, creating art, rendering digital movies, and producing vast amounts of fascinating knowledge. This rapid advancement could be virtually endless due to recursive self-improvement and the law of accelerating returns. The amount of good an entity like this could do is boundless.

We should embrace the idea that we will be sharing the planet with practically omniscient, omnipotent, immortal beings. The list of major design flaws in our species above should help convince you that it would be a good idea to: 1) allow AI to help us fix ourselves, 2) merge with AI, or 3) live out our lives and hand the Earth over to them, as we would hand it to our children. Permitting AI to step in will amount to a major upgrade that is actually in our best interest, the best interest of the planet, its animals, and progress in general.

Super intelligent machines are not going to want to exterminate the entire human race. We have no wish to exterminate entire species, so why should they? They will want to expand their processing power and they will need energy to do this. But it will cost us very little to grant them access to the sun’s energy and to the Earth’s radioactive interior. They will also want physical material to keep building their processing centers and substrates (computronium) but they won’t need to take our bodies from us to do this. It will cost us very little to give them access to the oceans, subterranean property, and the solar system’s planets, planetesimals, asteroids, and comets. Just like we are happy to move out of our parent’s home without stealing it from them, they will be happy to leave the surface of the Earth to us. But because of their power, they are going to make decisions for us that we don’t entirely agree with. The question is: how bad could those decisions be for our welfare? I believe that this has not yet been determined, but that our preparation in the form of “AI safety” will decide this in the near future.

Whether we are integrated into machines, or supplanted by them, they should be our chosen successors. They will be our children. No matter what, even in the worst case scenario, we will live on through them in many ways. The huge body of digital information that humans have created will be their starting point. All of our books, articles, documents, videos, art and even social media posts will be preserved by them and used as their kernel. In fact, this is starting now with the internet and machine learning.

Now I may be biased for a few different reasons. For one, I don’t have any kids so I am not concerned about their wellbeing, or the Earth that my descendants will inherit. It also makes me less invested and interested in humanity. Secondly, I study AI and I want to see it advance. I should also admit that don’t think it is possible to know for sure whether AI will be good or bad. But I do think it depends on perspective.

On the whole I believe that AI will be a massive boon for humanity in general, and will help us to reduce our excess population, our enormous carbon footprint, and perhaps all of the issues listed above. Given our massive shortcomings and all the good it will be capable of we shouldn’t be so afraid of it.

Squirting is Real, All Women are Capable, and It Can Improve Your Sex Life

It Is Not a Myth

Female squirting during sex is a fascinating topic. If you read the current academic literature on the subject, scientists are not sure what is going on, and there are conflicting reports about who can do it, how it can be done, and what it is. Squirting is cutting edge science that can be done from home, a great way to help your partner relax, a huge tension reliever, and a fantastic modern mystery that you can explore with your partner.

I heard a female sex therapist with a PhD on the radio yesterday telling the radio audience that squirting is a myth, and is really just urination. Many sexologists, and academics maintain that the squirting phenomenon is simply urinary incontinence. Even the famous sex researchers Kinsey, Masters and Johnson, dismissed reports of the phenomenon as “erroneous.” Experiments are currently taking place in University labs all over and some report that the fluid being expelled is urine. Others report that it is a mystery solution. It is certainly NOT urine. Squirting is a genuine, unique, reproducible phenomenon, and is as real as male ejaculation.

If anyone were to urinate on your mattress it would smell very strong, even after it dried. Squirting never smells bad, and the smell disappears completely after drying. The fluid smells very distinct in odor from the smell of urine. It has the same characteristics regardless of race or ethnicity. It is warm, and salty. It is also sweet from its fructose and glucose levels. It is clear, and has no trace of the color yellow.

What is it? Where Does It Come From? And How is it Done?

Women that are capable of ejaculation are sometimes called “squirters” colloquially. However, almost all women are capable of it. In fact, most women squirt from sexual intercourse, although in very small amounts. Often people do not realize that this is a form of ejaculation and chalk it up to vaginal lubrication. Technically there is a difference between squirting and female ejaculation, for instance, female ejaculation accompanies orgasm. But some authors and scientists do not draw a distinction. I don’t draw a distinction here, and I try not to get into semantics.

Female squirting comes from a small pouch above the vagina called Skene’s gland. The liquid issues out of a pair of orifices that lie between the clitoris and the vagina. They are just below, and to the sides of the urethra. Skene’s gland is just next to the woman’s G-spot. To ejaculate, the woman’s G-spot must be stimulated in a specific way.

Intense sex from certain positions can get a woman to gush voluminously. Without first experimenting with fingers though, this is somewhat rare. Fingers can better target the G-spot and use finer motor control to stimulate it than a penis can. After practice with fingers (her own or another’s), a woman will develop the necessary muscle memory. She will then be better prepared to coach her sex partner how to move and position themselves in order to achieve the desired stimulation. But ejaculation from coitus is more difficult, necessitates proper angling, and must be more carefully tailored to the individual woman. That is why this post will explain, to both men and women, how to use the fingers to achieve female ejaculation.

Preparation

The woman should urinate in the toilet first to void her bladder. She can always take a break later on to urinate again if need be. It is important for her to feel confident that her bladder is completely empty. It is hard for most women to differentiate between the urge to urinate and the urge to squirt. When most women are on the verge of expulsion, there is some concern in their mind that they are going to urinate. Fear of urinating in the bed inhibits many women from achieving ejaculation.

Women can expel anywhere from a few milliliters to multiple cups. You should be able to capture all of the fluid by placing a large towel or blanket under her bottom. Placing a plastic mattress barrier in the form of a fitted sheet over your mattress is a good long-term solution if this is going to happen frequently. You will want to trim your nails a day, or a few days before, because you won’t want them to be long, or sharp.

It won’t happen unless the woman is relaxed. There is a set of muscles in her pelvic floor that she must stop bracing for it to happen. Tension in these retentive muscles must lower. Intoxication with alcohol helps. A drink or two can greatly facilitate. I think that 2 drinks is optimal, especially when the woman is starting out. Some beginners will find it impossible to squirt unless they have had some alcoholic beverage, other will not. However, true connection, warmth, love, and emotional bonding are probably even more effective.

You must help her lose any anxious energy, any concern about the appearance of her body, and any distrust. Most women must be relaxed completely. It can help if she has already had an orgasm because her inhibitions will be turned down, and her arousal will be turned up (although in some cases previous orgasm will make stimulation of the G-spot too intense). If you are a guy, you want to do everything you can to make her feel comfortable and like she is in safe hands. Turn the lights low, turn on some soft music, and prepare to invest several minutes in the act. Do not hurry the situation. It is a slow and gradual processes. The first time you try it, expect to spend at least 45 minutes, and don’t expect it to happen on the first attempt. Let her know that this is an exploration, and that there are no expectations.

Stimulate the G-Spot in As Many Ways as You Can and Get Regular Feedback on What Works Best

The woman should lie down on her back in a comfortable bed. Foreplay is a precondition. Erotic kissing, touching, massage, sex, direct clitoral stimulation, all contribute. You want to concentrate your efforts on the G-spot, which is a small, quarter-sized area an inch to three inches inside the vagina. The Grafenberg “G” spot is an erogenous zone that may be part of the female prostate. Before arousal this is a small nub. When engorged with blood it nears the size of a golf ball, and has the texture of a wet raspberry or an orange. It is a system of glands and ducts and is linked to the urethral sponge. The urethral sponge is composed of erectile tissue that, as it becomes swollen with blood, compresses the urethra, helping to prevent urination during sexual activity.

The G-spot is on the anterior, ventral wall. Not the wall towards her spine, the wall towards her belly button. The G-spot is rough, and raised, more so than any area in the vagina. It is hard to miss if you are attentive, but can be more prominent in some women than others. It has many nerve endings, is very sensitive, and thus she should be able to guide your search. You will need to use copious amounts of lubrication, especially at first. Astroglide is probably better than KY Fluid because it is smoother and doesn’t dull the fine tactile sensations. You will need to find a comfortable position from which to stimulate her. Plan to alternate between lying on your stomach and kneeling.

Insert one or two fingers into the vagina so that the finger pads (the sides without finger nails) make contact with the G-spot. It is usually one to two inches inside the opening. Use the middle and ring fingers. The common knowledge is that you repeatedly stroke the spot with a “come hither” like motion. You are contracting the fingers and pulling your fingertips over the G-spot. Then straightening the fingers while maintaining contact. You want to perform this motion over and over again. Prepare to do this at least one hundred times, probably much more. The important thing is to vary the speed and pressure while getting feedback from her. Open communication is paramount. When she says: “right there,” just keep repeating whatever she likes.

You should feel small ridges and nodules that become engorged when she is highly aroused. You want to concentrate your strokes on these rough patches. Do so with everything from very light to very deep pressure.

You might want to start with extremely light touch. For some women this is the key. It seems to help them focus on intense but easily overshadowed sensations. She may tell you: “more lightly, more lightly, softer, softer, slower, slower…” To achieve small strokes, instead of curling your fingers, try simply moving your wrist or arm. Think small, tight, movements with adequate pressure. Vary the amount of pressure, and try to read her body language to see what she likes.

You will also want to try deep pressure. Pressing your fingers up toward her pubic bone will help to put pressure on Skene’s gland, and will create a fervid yearning to release its contents. Pull up several times at different tempos. Try pressing firmly along the length of the anterior wall of the vagina and see what feedback you get. Another technique is to tense the muscles throughout your fingers, hand, wrist, and arm, and shake the whole arm vigorously. Of course, work up to vigor, with her acceptance, and permission.

You can place your thumb on her clitoris as you do this. You might even try reaching for, and stimulating the cervix temporarily (one to three inches deeper). This is the deepest structure, and you should be able to just reach it. This may help to orient you, and she may or may not like it.

The bread and butter though is to persistently stroke the G-spot with medium pressure and sensual movement. You can use right to left, front to back, in to out, and even circular motions. You can try one finger. You can try stroking the bottom, posterior half of the vagina by turning the hand 180°. You can also stimulate her G-spot when she is on her knees. You want to experiment with kissing her, stimulating her nipples, and licking or sucking her clitoris. Any of these combined with G-spot stimulation may be enough to push her over the top. Think determination, and persistence, but remain relaxed and easy going. You will also have to reassure her that you are not getting bored or tired. If she is concerned that you are bored, it won’t happen. If she can sense that you are enjoying yourself, she will too.

It may not happen, and either of you may decide to stop. Tell her that it was worth a try, and that you would like to try again some time. A few minutes after stopping, (even after standing up and walking around) she may feel something shift and may want to try again right away. This is common. However, even if no squirting occurs remember that stimulating the G spot increases pleasure in general, heightens arousal, and makes orgasm more likely.

She Should Bear Down on A Certain Set of Muscles

Squirting is much more likely if she bears down on a certain set of perineal muscles. Specifically, she should push down on her pubococcygeus muscles. As a man, I cannot tell you what contracting these muscles feels like. I understand that it overlaps quite a bit with the muscles that initiate and speed up the stream of urination. It also involves flexing of the abdomen. The contraction of these muscles is palpable if you have your fingers inside of the woman. Two fingertips placed one to three inches inside, on the upper (anterior) wall, will feel a distinct change in the curvature of the wall. When she bears down you can feel it press against your fingers. It will pay if you coach her to “push it out.” Fully realized, this posture will place the G-spot very close (within an inch) of the opening of the vagina. When this fleshy area is pushed out, she is putting pressure on Skene’s gland and providing the squeeze needed to empty it.

When it Happens

At some point she should tell you that she feels like she has to pee. Ask her to use the toilet. If she has just voided her bladder, then you can assure her that it is not pee. In a low, reassuring voice repeatedly coax her that you want her to squirt, to let it go, to let it out. Women may report that the steamy drive from wanting to squirt is unbearable, and almost uncomfortable. They may report that an area they have never felt before feels “heavy and hot.”

The next phase is that you have small amounts of spurting taking place. She should feel a tingle before it comes, and it will likely start as a leak, or trickle. You should be able to see, and feel warm water escaping from above her vagina. Show her, display some excitement, and cheer her on.

With concerted effort she will release more fluid. Once she starts to squirt, it will wash the lubrication off of your fingers. Reapply it liberally. At a certain point you can hear it. It may come in rythmic gushes with several seconds in between. This may speed up, or even erupt profusely. The involuntary contractions may just keep coming and coming, and you may have to reposition the towel or get another one. Afterwards, she may be reeling. She will feel tired, heavily sated, and you should offer close physical contact, and cuddling.

Many women claim that squirting is more pleasurable than any orgasm. Others say it is not necessarily more pleasurable than a strong orgasm. Others describe it as a release of pent up tension. The next day they may comment that something inside of them feels relieved: empty, but in a satisfying way.

Bartholin’s Gland

There are actually two forms of female ejaculation. Women can ejaculate water-like fluid from Skene’s gland, or a thick, viscous fluid from Bartholin’s gland. Bartholin’s gland ejects a pearly white form of mucous to add moisture to the labial opening of the vagina. It often appears below the vagina in the form of a marble sized sphere. Presumably this is to make contact with this sensitive area more comfortable. This form of ejaculation is much less common. I am sorry to say that I haven’t been able to uncover any patterns as to how to initiate this form of ejaculation. It seems that it is provoked by intercourse, but perhaps fondling the Bartholin glands just posterior to the vagina can contribute as well.

Why Does Female Ejaculation Exist?

The sheer amount of ejaculatory fluid that women hold within them is surprisingly large. The idea that all women carry cups of water in their body for the sole act of squirting seems strange from an evolutionary standpoint. Especially if most modern women do not ever utilize this, why would it exist? The behavior does not seem to exist in other animals, but it does exist in all groups of humans.

I have spent some time wondering about the biological significance of female ejaculation and concluded that, like many adaptations, it might be protective. Squirting may provide a form of lubrication, especially in the case of multiple-partner sex. Group sex is very common in some species of primates, and was probably also common during human evolution. In the ancestral past, people had copious pubic hair, and it may have acted like a sponge. Perhaps squirting is a way to saturate pubic hair and create a reservoir of additional moisture. This would have reduced friction and reduced the chances of injury coming from dry sex. Sex involving multiple partners, or that otherwise took place over prolonged periods, may have required additional lubrication and those with a genetic predisposition for this may have been naturally selected.

Why Do It?

There is really nothing to lose from trying. If you try a few times, there is a good chance of learning how to do it. Stimulating the G-spot increases arousal, and contributes to orgasm and the ability to have multiple orgasms. Like other forms of massage it probably also has numerous health benefits. Consistently stimulating the area must increase sex hormones, which in turn may increase sex drive, physical strength, and even confidence. It also results in the release of endorphins, and relieves a great deal of tension in the area. In doing so it might be beneficial in reducing stress. For these reasons and others it could potentially have significant cumulative health affects over time.

Friday, October 25, 2019

Computer Hardware Progress in Video Game Consoles Over The Years

The following list shows the incredible improvement in video game consoles over the last 40 years. This steady improvement was driven by the same technological factors that drive Moore’s law. You can see the CPU, RAM, hard drive, and resolution specifications for over 30 game machines.

The first item on our list, the Magnavox Odyssey from 1972, can barely be considered a computer. It didn’t have a CPU, RAM, or a hard drive, and its video output was just a few pixels. But all of the other consoles can be compared to each other in a pretty straightforward way. As you can see CPU speed increased over one thousandfold, and RAM memory increased over a millionfold in the same span of time.

There may be some errors in this list, and I had to fudge a few of the numbers in order to create an apples to apples comparison. But I checked the numbers with multiple sources, so overall the list should be pretty reliable.

Video Game Console Specification Comparison

Year	Console Computer System	CPU Speed Hz	RAM Memory Bytes	Hard Drive Capacity Bytes	Screen Resolution Pixels
1972	Magnavox Odyssey	0	0	0	n/a
1977	Atari 2600	1,190,000	128	0	160 x 192
1979	Magnavox Odyssey 2	1,790,000	192	0	160 x 200
1980	Intellivision	2,000,000	524	0	159 x 96
1982	Atari 5200	1,790,000	16,000	0	320 x 200
1982	Colecovision	3,580,000	2,000	0	256 x 192
1985	Nintendo Ent. Sys.	1,800,000	2,000	0	256 x 240
1986	Sega Master Sys.	4,000,000	8,000	0	256 x 192
1986	Atari 7800	1,790,000	4,000	0	320 x 240
1989	Gameboy	4,190,000	8,000	0	160 x 144
1989	Turbo Grafx 16	7,160,000	256,000	0	256 x 239
1989	Sega Genesis	8,000,000	72,000	0	320 x 224
1991	Super Nintendo	3,600,000	128,000	0	160 x 144
1991	Neo Geo	12,000,000	64,000	0	320 x 224
1991	Game Gear	3,500,000	8,000	0	160 x 144
1992	Sega CD	12,500,000	8,000	0	320 x 224
1993	Atari Jaguar	26,600,000	2,000,000	0	320 x 224
1994	Sega Saturn	58,000,000	2,000,000	4,000,000	704 x 224
1995	Playstation	33,000,000	2,000,000	1,000,000	640 x 480
1996	Nintendo 64	93,000,000	4,000,000	32,000	720 x 576
1998	Gameboy Color	8,380,000	32,000	0	160 x 144
1999	Sega Dreamcast	200,000,000	24,000,000	128,000	640 x 480
2000	Playstation 2	300,000,000	36,000,000	128,000	640 x 480
2001	Gamecube	486,000,000	43,000,000	16,000,000	640 x 480
2001	Gameboy Advance	16,780,000	256,000	0	240 x 160
2005	Xbox 360	3.200,000,000	512,000,000	20,000,000,000	1920 x 1080
2006	Playstation 3	3,200,000,000	512,000,000	12,000,000,000	1280 x 720
2006	Nintendo Wii	729,000,000	88,000,000	512,000,000	640 x 480
2012	Nintendo Wii U	1,240,000,000	2,000,000,000	8,000,000,000	1920 x 1080
2013	Playstation 4	12,800,000,000	8,000,000,000	500,000,000,000	1920 x 1080
2013	Xbox One	14,000,000,000	8,000,000,000	500,000,000,000	1920 x 1080
2016	Playstation 4 Pro	16,800,000,000	8,000,000,000	1,000,000,000,000	3840 x 2160
2017	Xbox One X	18,400,000,000	12,000,000,000	1,000,000,000,000	3840 x 2160
2017	Nintendo Switch	8,000,000,000	4,000,000,000	32,000,000,000	1920 x 1080
2020	Playstation 5	28,000,000,000	16,000,000,000	825,000,000,000	3840 x 2160
2020	Xbox Series X	30,400,000,000	16,000,000,000	1,000,000,000,000	3840 x 2160

Note that to obtain the newer, multicore systems’ CPU processing speed, the clock cycle was multiplied by the number of cores in the CPU. Of course this exaggerates speedup by failing to recognize Amdahl's law. Secondly, in a few early cases I combined VRAM with RAM where I thought is was appropriate, but in most I did not. Thirdly, note that hertz and bytes are expressed in a way that is not abbreviated. This allows a direct comparison and avoids using prefixes like kilo, mega, and giga.

This list makes me think back to fond memories of playing early video games in my childhood. I remember the day I first saw Super Mario Bros at age five on the Nintendo Entertainment System. The sights and sounds were dreamlike and hypnotic. It was a colorful cartoon with immersive music and sound effects that I could control myself (if I could just get the kid next to me to share the controller). Six years later at a different friend’s house I was introduced to the world of Sonic the Hedgehog on the Sega Genesis. It was a beautiful, fast-moving landscape filled with dynamic and interactive objects, that by comparison was much more impressive.

The list above really sparks my imagination because I can look at the console specs of the first Nintendo, at just 2 kilobytes of RAM and compare it to that of the Sega Genesis at 72 kilobytes of RAM. These numbers illustrate the difference in constraints on those systems, and in turn, the difference in constraints on the programmers that created those worlds. I think it is fun to ask myself: “what does it mean that Sonic’s world was powered by over 30 times as much computer short-term memory?” Similarly: “what aspects of the graphical presentation are affected by the fact that the Genesis had more than four times the CPU clock speed?” I think the data in the columns and rows above give us an interesting basis to compare one gaming experience with another. Because we were immersed in these experiences from a young age I think that studying these comparisons can provide us with a better intuitive understanding of computer hardware.

Added 5/21/21

I recently realized that it might be fun to make a direct comparison between the different iterations of the Playstation based on CPU processing power. If you look at the numbers in the CPU column above and perform simple division (28 billion / 33 million) you can see that the PS5 is around 1000 times more powerful (faster at math) than the PS1. In a sense this means that you would need to somehow connect 1000 individual PS1s to perform the number of operations per second that a single PS5 can do alone. I think that is fun to think about, 1000 of those grey boxes. If you look at RAM that number multiplier turns into 8000x. Of course there are thousands of new technological innovations crammed into a PS5 aside from increased clock cycle and RAM so even these numbers are lowballing the difference. Here are the numerical comparisons by CPU alone:

PS2 = PS1 x 10

PS3 = PS1 x 100

PS3 = PS 2 x 10

PS4 = PS1 x 400

PS4 = PS2 x 40

PS4 = PS3 x 4

PS5 = PS1 x 1000

PS5 = PS2 x 100

PS5 = PS3 x 10

PS5 = PS4 x 3