Update

blender.md

@@ -2,4 +2,4 @@
 
 Blender is an "[open-source](open_source.md)" 3D modeling and [rendering](rendering.md) [software](software.md) -- one of the most powerful and "feature-rich" (read [bloated](bloat.md)) ones, even compared to [proprietary](proprietary.md) competition -- used not only by the [FOSS](foss.md) community, but also the industry (commercial [games](game.md), movies etc.), which is an impressive achievement in itself, however Blender is also a [capitalist](capitalist.md) software suffering from many not-so-nice features such as [bloat](bloat.md).
 
-After version 2.76 Blender started REQUIRING [OpenGL](opengl.md) 2.1 due to its "[modern](modern.md)" [EEVEE](eevee.md) renderer, deprecating old machines and giving a huge fuck you to all users with incompatible hardware (for example the users of [RYF](ryf.md) software). This new version also stopped working with the [free](free_software.md) [Nouveau](nouvea.md) driver, forcing the users to use NVidia's proprietary drivers. Blender of course doesn't at all care about this. { I've been forced to use the extremely low FPS [software](sw_rendering.md) GL version of Blender after 2.8. ~drummyfish }
+After version 2.76 Blender started REQUIRING [OpenGL](opengl.md) 2.1 due to its "[modern](modern.md)" [EEVEE](eevee.md) renderer, deprecating old machines and giving a huge fuck you to all users with incompatible hardware (for example the users of [RYF](ryf.md) software). This new version also stopped working with the [free](free_software.md) [Nouveau](nouvea.md) driver, forcing the users to use NVidia's proprietary drivers. Blender of course doesn't at all care about this. { I've been forced to use the extremely low FPS [software](sw_rendering.md) GL version of Blender after 2.8. ~drummyfish } 

computer.md

@@ -1,6 +1,6 @@
 # Computer
 
-The word *computer* can be defined in many ways and can also take many different meanings; a somewhat common definition may be this: computer is a machine that automatically performs mathematical computations. We can also see it as a machine for processing information or, very generally, as any tool that helps computation, in which case one's fingers or even a [mathematical](math.md) formula itself can be considered a computer. Here we are of course mostly concerned with electronic [digital](digital.md) computers.
+The word *computer* can be defined in many ways and can also take many different meanings; a somewhat common definition may be this: computer is a machine that automatically performs mathematical computations. We can also see it as a machine for processing [information](information.md) or, very generally, as any tool that helps computation, in which case one's fingers or even a [mathematical](math.md) formula itself can be considered a computer. Here we are of course mostly concerned with electronic [digital](digital.md) computers.
 
 We can divide computers based on many attributes, e.g.:
 
@@ -16,7 +16,7 @@ Computers are studied by [computer science](compsci.md). The kind of computer we
 - **[hardware](hw.md)**: physical parts
 - **[software](sw.md)**: [programs](program.md), made by [programmers](programmer.md)
 
-The power of computers is limited, [Alan Turing](turing.md) mathematically proved that there exist problems that can never be completely solved by any [algorithm](algorithm.md), i.e. there are problems a computer (including our [brain](brain.md)) will never be able to solve (even if solution exists). He also invented the theoretical model of a computer called the [Turing machine](turing_machine.md). Besides the mentioned theoretical limitation, many solvable problems may take too long to compute, at least with computers we currently know (see [computational complexity](computational_complexity.md) and [P vs NP](p_vs_np.md)).
+**The power of computers is limited**, [Alan Turing](turing.md) mathematically proved that there exist problems that can never be completely solved by any [algorithm](algorithm.md), i.e. there are problems a computer (including our [brain](brain.md)) will never be able to solve (even if solution exists). This is related to the fact that the power of mathematics itself is limited in a similar way (see [Godel's theorems](incompleteness_theorems.md)). Turing also invented the theoretical model of a computer called the [Turing machine](turing_machine.md). Besides the mentioned theoretical limitation, many solvable problems may take too long to compute, at least with computers we currently know (see [computational complexity](computational_complexity.md) and [P vs NP](p_vs_np.md)).
 
 ## Typical Computer
 

digital.md

@@ -4,8 +4,10 @@ Digital [technology](tech.md) is that which works with whole numbers, i.e. discr
 
 Normies confuse digital with [electronic](electronic.md) or think that digital computers can only be electronic, that digital computers can only work in [binary](binary.md) or have other weird assumptions whatsoever. **This is indeed false!** An [abacus](abacus.md) is digital device. Fucking normies.
 
-The advantage of digital technology is its resilience to noise which prevents degradation of data and accumulation of error -- if a digital picture is copied a billion times, it will very likely remain unchanged, whereas performing the same operation with analog picture would probably erase most of the information it bears due to loss of quality in each copy. Digital technology also makes it easy and practically possible to create fully programmable general purpose [computers](computer.md) if great complexity.
+The advantage of digital technology is its resilience to noise which prevents degradation of data and accumulation of error -- if a digital picture is copied a billion times, it will very likely remain unchanged, whereas performing the same operation with analog picture would probably erase most of the information it bears due to loss of quality in each copy. Digital technology also makes it easy and practically possible to create fully programmable general purpose [computers](computer.md) of great complexity.
 
 **Digital vs analog, simple example:** imagine you draw two pictures with a pencil: one in a normal fashion on a normal paper, the other one on a grid paper, by filling specific squares black. The first picture is analog, i.e. it records continuous curves and position of each point of these curves can be measured down to extremely small fractions of millimeters -- the advantage is that you are not limited by any grid and can draw any shape at any position on the paper, make any wild curves with very fine details, theoretically even microscopic ones. The other picture (on a square grid) is digital, it is composed of separate points whose position is described only by whole numbers (*x* and *y* coordinates of the filled grid squares), the disadvantage is that you are limited by only being able to fill squares on predefined positions so your picture will look blocky and limited in amount of detail it can capture (anything smaller than a single grid square can't be captured properly), the [resolution](resolution.md) of the grid is limited, but as we'll see, imposing this limitations has advantages. Consider e.g. the advantage of the grid paper image with regards to copying: if someone wants to copy your grid paper image, it will be relatively easy and he can copy it exactly, simply by filling the exact same squares you have filled -- small errors and noise such as imperfectly filled squares can be detected and corrected thanks to the fact that we have limited ourselves with the grid, we know that even if some square is not filled perfectly, it was probably meant to be filled and we can eliminate this kind of noise in the copy. This way we can copy the grid paper image a million times and it won't change. On the other hand the normal, non-grid image will become distorted with every copy and in fact even the original image will become distorted by aging; even if that who is copying the image tries to trace it extremely precisely, small errors will appear and these errors will accumulate in further copies, and any noise that appears in the image or in the copies is a problem because we don't know if it really is a noise or something that was meant to be in the image.
 
-Of course, digital data may become distorted too, it is just less likely and it's easier to deal with this. It for example happens that space particles (and similar physics phenomena, e.g. some quantum effects) flip bits in computer memory, i.e. there is always a probability of some [bit](bit.md) flipping from 0 to 1 or vice versa. We call this **data [corruption](corruption.md)**. This may also happen due to physical damage to digital media (e.g. scratches on the surface of CDs), imperfections in computer network transmissions (e.g. packet loss over [wifi](wifi.md)) etc. However we can introduce further measures to prevent, detect and correct data corruption, e.g. by keeping [redundant](redundancy.md) copies (2 copies of data allow detecting corruption, 3 copies allow even its correction), keeping [checksums](checksum.md) or [hashes](hash.md) (which allow only detection of corruption but don't take much extra space), employing error correcting codes etc.
+Of course, digital data may become distorted too, it is just less likely and it's easier to deal with this. It for example happens that space particles (and similar physics phenomena, e.g. some quantum effects) flip bits in computer memory, i.e. there is always a probability of some [bit](bit.md) flipping from 0 to 1 or vice versa. We call this **data [corruption](corruption.md)**. This may also happen due to physical damage to digital media (e.g. scratches on the surface of CDs), imperfections in computer network transmissions (e.g. packet loss over [wifi](wifi.md)) etc. However we can introduce further measures to prevent, detect and correct data corruption, e.g. by keeping [redundant](redundancy.md) copies (2 copies of data allow detecting corruption, 3 copies allow even its correction), keeping [checksums](checksum.md) or [hashes](hash.md) (which allow only detection of corruption but don't take much extra space), employing error correcting codes etc. 
+
+Another way in which digital data can degrade similarly to analog data is **reencoding between lossy-[compressed](compression.md) formats** (in the spirit of the famous "needs more jpeg meme"). A typical example is digital movies: as new standard for video encoding are emerging, old movies are being reconverted from old formats to the new ones, however as video is quite heavily lossy-compressed, losses and distortion of information happens between the reencodings. This is best seen in videos and images circulating on the internet that are constantly being ripped and converted between different formats. This way it may happen that digital movies recorded nowadays may only survive into the future in very low quality, just like old analog movies survived until today in degraded quality. This can be prevented by storing the original data only with lossless compression and with each new emerging format create the release of the data from the original.

history.md

@@ -78,6 +78,6 @@ On 25 August 1991 **[Linus Torvalds](linus_torvalds.md) announced [Linux](linux.
 
 After this very recent history follows, it's hard to judge which recent events will be of historical significance much later. 1990s have seen a huge growth of computer power, video [games](game.md) such as [Doom](doom.md) led to development of [GPU](gpu.md)s and high quality computer graphics along with a wide adoption of computers by common people, which in turn helped the further growth of Internet. During the 90s we've also seen the rise of the [open source movement](open_source.md). Shortly after 2000 [Lawrence Lessig](lessig.md) founded [Creative Commons](creative_commons.md), an organization that came hand in hand with the [free culture](free_culture.md) movement inspired by the [free software movement](free_software.md). At this point over 50% of US households had a computer. Cell phones became a commonly owned item and after about 2005 so called "[smart](smart.md) phones" and other "smart" devices replaced them as a universal communication device capable of connecting to the Internet. Before 2020 we've seen a huge advancement in [neural network](neural_network.md) [Artificial Intelligence](ai.md) which will likely be the topic of the future. [Quantum computers](quantum.md) are being highly researched with already existing primitive prototypes; this will also likely be very important in the following years. Besides AI there has appeared a great interest and development of [virtual reality](vr.md), [drones](drone.md), electromobiles, robotic Mars exploration and others. However the society and technology has generally seen a decadence after 2010, [capitalism](capitalism.md) has pushed technology to become hostile and highly [abusive to users](capitalist_software.md), extreme [bloat](bloat.md) of technology causes highly inefficient, extremely expensive and unreliable technology. In addition society is dealing with a lot of serious issues such as the [global warming](global_warming.md) and many people are foreseeing a [collapse of society](collapse.md).
 
-## Recent History
+## Recent History Of Technology
 
 TODO: more detailed history since the start of Unix time

optimization.md

@@ -6,12 +6,12 @@ Optimization means making a program more efficient in terms of consumption of so
 
 These are mainly for [C](c.md), but may be usable in other languages as well.
 
-- **Tell your compiler to actually optimize** (`-O3`, `-Os` etc.).
+- **Tell your compiler to actually optimize** (`-O3`, `-Os` flags etc.).
 - **[gprof](gprof.md) is a utility you can use to profile your code**.
 - **`<stdint.h>` has fast type nicknames**, types such as `uint_fast32_t` which picks the fastest type of at least given width on given platform.
 - **Keywords such as `inline`, `static` and `const` can help compiler optimize well**.
 - **Optimize the [bottlenecks](bottleneck.md)!** Optimizing in the wrong place is a complete waste of time. If you're optimizing a part of code that's taking 1% of your program's run time, you will never speed up your program by more than that 1% even if you speed up the specific part by 10000%. Bottlenecks are usually inner-most loops of the main program loop, you can identify them with [profiling](profiling.md). Generally initialization code that runs only once in a long time doesn't need much optimization -- no one is going to care if a program starts up 1 millisecond faster (but of course in special cases such as launching many processes this may start to matter).
-- **You can almost always trade space (memory usage) for time (CPU demand) and vice versa** and you can also fine-tune this. You typically gain speed by precomputation (look up tables, more demanding on memory) and memory with compression (more demanding on CPU).
+- **You can almost always trade space (memory usage) for time (CPU demand) and vice versa** and you can also fine-tune this. You typically gain speed by precomputation (look up tables, more demanding on memory) and memory with [compression](compression.md) (more demanding on CPU).
 - **[Static](static.md) things are faster and smaller than [dynamic](dynamic.md) things.** This means that things that are somehow fixed/unchangeable are better in terms of performance (and usually also safer and better testable) than things that are allowed to change during [run time](runtime.md) -- for example calling a function directly (e.g. `myVar = myFunc();`) is both faster and requires fewer instructions than calling a function by pointer (e.g. `myVar = myFuncPointer();`): the latter is more flexible but for the price of performance, so if you don't need flexibility (dynamic behavior), use static behavior. This also applies to using [constants](constant.md) (faster/smaller) vs [variables](variable.md), static vs dynamic [typing](typing.md), normal vs dynamic [arrays](array.md) etc.
 - **Be smart, use [math](math.md)**. Example: let's say you want to compute the radius of a zero-centered [bounding sphere](bounding_sphere.md) of an *N*-point [point cloud](point_cloud.md). Naively you might be computing the Euclidean distance (*sqrt(x^2 + y^2 + z^2)*) to each point and taking a maximum of them, however you can just find the maximum of squared distances (*x^2 + y^2 + z^2*) and return a square root of that maximum. This saves you a computation of *N - 1* square roots.
 - **Learn about [dynamic programming](dynamic_programming.md)**.
@@ -19,8 +19,8 @@ These are mainly for [C](c.md), but may be usable in other languages as well.
 - **Use iteration instead of [recursion](recursion.md)** if possible (calling a function costs something).
 - **You can use good-enough [approximations](approximation.md) instead of completely accurate calculations**, e.g. taxicab distance instead of Euclidean distance, and gain speed or memory without trading.
 - **Use quick opt-out conditions**: many times before performing some expensive calculation you can quickly check whether it's even worth performing it and potentially skip it. For example in physics [collision detections](collision_detection.md) you may first quickly check whether the bounding spheres of the bodies collide before running an expensive precise collision detection -- if bounding spheres of objects don't collide, it is not possible for the bodies to collide and so we can skip further collision detection. 
-- **Operations on static data can be accelerated with accelerating structures** ([look-up tables](lut.md) for functions, [indices](indexing.md) for database lookups, spatial grids for collision checking, ...).
-- **Use powers of 2** (1, 2, 4, 8, 16, 32, ...) whenever possible, this is efficient thanks to computers working in binary. Not only may this help nice utilization and alignment of memory, but mainly multiplication and division can be optimized by the compiler to mere bit shifts which is a tremendous speedup.
+- **Operations on static data can be accelerated with accelerating structures** ([look-up tables](lut.md) for functions, [indices](indexing.md) for database lookups, spatial grids for collision checking, various [trees](tree.md) ...).
+- **Use powers of 2** (1, 2, 4, 8, 16, 32, ...) whenever possible, this is efficient thanks to computers working in [binary](binary.md). Not only may this help nice utilization and alignment of memory, but mainly multiplication and division can be optimized by the compiler to mere bit shifts which is a tremendous speedup.
 - **Write [cache-friendly](cache-friendly.md) code** (minimize long jumps in memory).
 - **Compare to [0](zero.md) rather than other values**. There's usually an instruction that just checks the zero flag which is faster than loading and comparing two arbitrary numbers.
 - **Use [bit tricks](bit_hack.md)**, hacks for manipulating binary numbers in clever ways only using very basic operations without which one might naively write complex inefficient code with loops and branches. Example of a simple bit trick is checking if a number is power of two as `!(x & (x - 1)) && x`.
@@ -29,16 +29,17 @@ These are mainly for [C](c.md), but may be usable in other languages as well.
 - **Optimize when you already have a working code**. As [Donald Knuth](knuth.md) put it: "premature optimization is the root of all evil". Nevertheless you should get used to simple nobrainer efficient patterns by default and just write them automatically.
 - **Use your own [caches](cache.md) where they help**, for example if you're frequently working with some database item you better pull it to memory and work with it there, then write it back once you're done (as opposed to communicating with the DB there and back).
 - **[Single compilation unit](single_compilation_unit.md) (one big program without [linking](linking.md)) can help compiler optimize better** because it can see the whole code at once, not just its parts. It will also make your program compile faster.
-- Search literature for **algorithms with better [complexity class](complexity_class.md)** (sorts are a nice example).
+- Search literature for **algorithms with better [complexity class](complexity_class.md)** ([sorts](sorting.md) are a nice example).
 - For the sake of simple computers such as [embedded](embedded.md) platforms **avoid [floating point](floating_point.md)** as that is often painfully slowly emulated in software. Use [fixed point](fixed_point.md), or at least offer it as a [fallback](fallback.md). This also applies to other hardware requirements such as [GPU](gpu.md) or sound cards: while such hardware accelerates your program on computers that have the hardware, making use of it may lead to your program being slower on computers that lack it.
 - **[Early branching](early_branching.md) can create a speed up** (instead of branching inside the loop create two versions of the loop and branch in front of them). This is a kind of space-time tradeoff.
 - **Division can be replaced by multiplication by [reciprocal](reciprocal.md)**, i.e. *x / y = x * 1/y*. The point is that multiplication is usually faster than division. This may not help us when performing a single division by variable value (as we still have to divide 1 by *y*) but it does help when we need to divide many numbers by the same variable number OR when we know the divisor at compile time; we save time by precomputing the reciprocal before a loop or at compile time. Of course this can also easily be done with [fixed point](fixed_point.md) and integers!
-- **Reuse variables to save space**. A warning about this one: readability may suffer, mainstreamers will tell you you're going against "good practice", and some compilers may do this automatically anyway. Be sure to at least make this clear in your comments. Anyway, on a lower level and/or with dumber compilers you can just reuse variables that you used for something else rather than creating a new variable that takes additional RAM; the only prerequisite for "merging" variables is that the variables aren't used at the same time.
-- **What's fast on one platform may be slow on another**. This depends on the instruction set as well as on compiler, operating system, available hardware, [driver](driver.md) implementation and other details. In the end you always need to test on the specific platform to be sure about how fast it will run.
+- **Reuse variables to save space**. A warning about this one: readability may suffer, mainstreamers will tell you you're going against "good practice", and some compilers may do this automatically anyway. Be sure to at least make this clear in your comments. Anyway, on a lower level and/or with dumber compilers you can just reuse variables that you used for something else rather than creating a new variable that takes additional RAM; of course a prerequisite for "merging" variables is that the variables aren't used at the same time.
+- **What's fast on one platform may be slow on another**. This depends on the instruction set as well as on compiler, operating system, available hardware, [driver](driver.md) implementation and other details. In the end you always need to test on the specific platform to be sure about how fast it will run. A good approach is to optimize for the weakest platform you want to support -- if it runs fasts on a weak platform, a "better" platform will most likely still run it fast.
 - **Mental calculation tricks**, e.g. multiplying by one less or more than a power of two is equal to multiplying by power of two and subtracting/adding once, for example *x * 7 = x * 8 - x*; the latter may be faster as a multiplication by power of two (bit shift) and addition/subtraction may be faster than single multiplication, especially on some primitive platform without hardware multiplication. However this needs to be tested on the specific platform. Smart compilers perform these optimizations automatically, but not every compiler is high level and smart.
 - **Else should be the less likely branch**, try to make if conditions so that the if branch is the one with higher probability of being executed -- this can help branch prediction.
 - **You can optimize critical parts of code in [assembly](assembly.md)**, i.e. manually write the assembly code that takes most of the running time of the program, with as few and as inexpensive instructions as possible (but beware, popular compilers are very smart and it's often hard to beat them). But note that such code loses [portability](portability.md)! So ALWAYS have a C (or whatever language you are using) [fallback](fallback.md) code for other platforms, use [ifdefs](ifdef.md) to switch to the fallback version on platforms running on different assembly languages.
 - **[Parallelism](parallelism.md) ([multithreading](multithreading.md), [compute shaders](compute_shader.md), ...) can astronomically accelerate many programs**, it is one of the most effective techniques of speeding up programs -- we can simply perform several computations at once and save a lot of time -- but there are a few notes. Firstly not all problems can be parallelized, some problem are sequential in nature, even though most problems can probably be parallelized to some degree. Secondly it is hard to do, opens the door for many new types of bugs, requires hardware support (software simulated parallelism can't work here of course) and introduces [dependencies](dependency.md); in other words it is huge [bloat](bloat.md), we don't recommend parallelization unless a very, very good reason is given. Optional use of [SIMD](simd.md) instructions can be a reasonable midway to going full parallel computation.
+- **Specialized hardware (e.g. a [GPU](gpu.md)) astronomically accelerates programs**, but as with the previous point, portablity and simplicity greatly suffers, your program becomes bloated and gains dependencies, always consider using specialized hardware and offer software fallbacks.
 
 ## When To Actually Optimize?
 

selflessness.md

@@ -2,7 +2,7 @@
 
 Selflessness means acting with the intent of helping others without harming them, gaining edge over them or taking advantage of them in any way. It is the opposite of [self interest](self_interest.md). Selflessness is the basis of an [ideal society](less_retarded_society.md) and [good technology](lrs.md) (while sadly self interest is the basis of our current dystopian [capitalist](capitalism.md) society).
 
-Selflessness is about the **intent** behind behavior rather than about the result of the behavior; for example being a [vegetarian](vegetarian.md) (or even [vegan](vegan.md)) for ethical reasons (to spare animals of suffering) is selfless while being a vegetarian only because of one's health concerns is not selfless. Similarly if a selfless behavior unpredictably results in harming someone, it is still a selfless behavior as long as the intent behind it was pure. (Note that this does **NOT** at all advocate the "[ends justify the means](ends_justify_the_means.md)" philosophy.)
+Selflessness is about the **intent** behind behavior rather than about the result of the behavior; for example being a [vegetarian](vegetarian.md) (or even [vegan](vegan.md)) for ethical reasons (to spare animals of suffering) is selfless while being a vegetarian only because of one's health concerns is not selfless. Similarly if a selfless behavior unpredictably results in harming someone, it is still a selfless behavior as long as the intent behind it was pure. (Note that this does **NOT** at all advocate the "[ends justify the means](ends_justify_the_means.md)" philosophy which acts with an intent to hurt someone.)
 
 In the real world absolutely pure selflessness may be very hard to find, partly because such behavior by definition seeks no recognition. Acts of sacrificing one's life for another may a lot of times be seen as selfless, but not always (saving one's child in such way may just serve perpetuating own genes, it can also be done to posthumously increase one's fame etc.). An example of high selflessness may perhaps be so called [Langar](langar.md), a big community kitchen run by [Sikhs](sikhism.md) that prepare and serve free [vegetarian](vegetarian.md) food to anyone who comes without differentiating between religious beliefs, skin color, social status, gender etc. Sikhs sometimes also similarly offer a place to stay etc. The mentioned ethical vegetarianism and veganism is another example of selflessness, as well as [LRS](lrs.md) itself, of course.
 

wiki_style.md

@@ -42,7 +42,7 @@ These are some sources you can use for research and gathering information for ar
 - **University theses** (and scientific paper of course): many university theses are publicly accessible and usually nicely sum up topics, bachelor level theses may be better understandable than PhD/master theses.
 - **Slides**: slides from various presentations are actually great resources as they condense the topic into its main points, they filter out the piles of noise.
 - **Wikisource** and **Wikibooks**
-- **[Metapedia](metapedia.md)**
+- **[Metapedia](metapedia.md)**, **[Infogalactic](infogalactic.md)** etc.
 - **[books](book.md)**: Books are still of higher quality than online sources so you can [pirate](piracy.md) some and steal some facts from them.
 - **[Internet Archive](internet_archive.md)**: A lot of things can be found on the old web that today drown in the bloat of shitsites, also Internet Archive has archives of various forums etc.
 - **[YouTube](youtube.md)**: Yes, sadly this is nowadays one of the biggest sources of information which is unfortunately hidden in videos full of ads and retarded zoomers, the information is unindexed. If you are brave enough, you can dig this information out and write it here as a proper text. 

wikipedia.md

@@ -34,7 +34,7 @@ And the bad things are (see also this site: http://digdeeper.club/articles/wikip
 - Wikipedia is **hard to read**. The articles go to great depth and mostly even simple topics are explained with a great deal of highly technical terms so that they can't be well understood by people outside the specific field, even if the topic could be explained simply (Simple English Wikipedia tries to fix this a little bit at least). Editors try to include as much information as possible which too often makes the main point of a topic drown in the blablabla. Wikipedia's style is also very formal and "not [fun](fun.md)" to read, which isn't bad in itself but it just is boring to read. Some alternative encyclopedias such as [Citizendium](citizendium.md) try to offer a more friendly reading style.
 - Wikipedia is **not [public domain](public_domain.md)**. It is licensed under [CC-BY-SA](cc_by_sa.md) which is a [free](free_culture.md) license, but has a few burdening conditions. We belive knowledge shouldn't be owned or burdened by any conditions.
 - Even though there are no ads, there regularly appears **political propaganda**, main page just **hard pushes [feminist](feminism.md) shit** as featured images and articles, there appear popups for LGBT/feminist activism, and of course all articles are littered with [pseudoleftist](pseudoleft.md) propaganda etc.
-- Many articles are bought, there exist companies that offer editing and maintaining certain articles in a way the client desires and of course corporations and politicians take this opportunity -- of course Wikipedia somewhat tries to prevent it but no prevention ever works 100%, so a lot information on Wikipedia is either highly misleading, untrue, censored or downright fabricated.
+- **Many articles are bought**, there exist companies that offer editing and maintaining certain articles in a way the client desires and of course corporations and politicians take this opportunity -- of course Wikipedia somewhat tries to prevent it but no prevention ever works 100%, so a lot information on Wikipedia is either highly misleading, untrue, censored or downright fabricated.
 
 ## Fun And Interesting Pages