explain xkcd - User contributions [en]

1903: Bun Trend

2022-09-25T08:28:52Z

IndigoFenix: /* Explanation */

{{comic
| number = 1903
| date = October 16, 2017
| title = Bun Trend
| image = bun_trend.png
| titletext = Our experts have characterized the ecological impact of this trend as "adorable."
}}

==Explanation==

In this comic, [[Beret Guy]] takes his bun shenanigans to the state government, reporting to the governor that the number of buns around the capitol has shown a rapid increase. The governor is confused, then finally comes to grasp that Beret Guy is talking about {{w|rabbit}}s, lots of which can be seen if he would just go outside (by the way, there is a ''small'' one '''RIGHT NOW'''!).

Elections in the United States often have a blank spot on the ballot for the voter to write the name of a {{w|write-in candidate}}. Beret Guy thinks he works for the governor because he wrote his name in on the ballot. This does not mean that he actually works for the governor.{{Citation needed}}

The governor finally takes appropriate action by calling security, and Beret Guy confronts his fate with poise and honor. Indeed, the readiness with which he accepts his removal almost seems to suggest that he doesn't belong, which would be an unusual level of awareness for his character. Alternatively, Beret Guy might have misinterpreted the governor's request for security as a question of whether he works in security, or simply ignorance.

Beret Guy's uncertain position in the government is very similar to the way he treats and operates his business.

"Buns" have been mentioned previously in [[1682: Bun]] and [[1871: Bun Alert]].

It is likely that Beret Guy is using the aforementioned Bun Alert app to measure the rabbit population. If this is the case, the recent increase in alerts may simply represent an increase in people using the app, rather than an actual increase in the rabbit population - a common fallacy. One simple way of correcting for this is to divide the total alerts by the number of active users during each interval; a change in this value would indicate that the bun population is actually changing.

In countries where rabbits are an invasive species or crop-destroying pests, an increase in rabbit populations may be of concern. In the title text, however, experts characterize the ecological impact of a large number of bunnies as "adorable" instead of giving information on how the rabbits are affecting the environment.

==Transcript==
:[Beret Guy holds a stick and points at a board next to him. The board contains a picture of a rabbit, a data point graph, and other notes.]
:Beret Guy: Good morning, Governor. Our tracking systems show a rapid increase in the number of buns around the Capitol.

:[Hairy is sitting at an office desk and facing Beret Guy in a frameless panel.]
:Hairy: Buns?
:Beret Guy: Yes; there's been a long-term upward trend, but it has accelerated recently.
:Hairy: The trend in... rabbits.
:Beret Guy: Yes.

:[Beret Guy takes out his phone.]
:Hairy: So... so what?
:Beret Guy: So if you want to see some buns, there are lots of them outside!
:[Beret Guy's phone vibrates]
:Phone: ''beep!''
:Beret Guy: Ooh!
:Beret Guy: There's a small one right now!

:[Zoom-in on Beret Guy.]
:Hairy (offscreen): Do you... actually ''work'' for me?
:Beret Guy: Almost certainly. We had an election, right? I wrote my name in on the thing.
:Hairy (offscreen): Security?
:Beret Guy: It's been an honor to serve.

{{comic discussion}}

[[Category:Comics featuring Hairy]]
[[Category:Comics featuring Beret Guy]]
[[Category:Animals]]
[[Category:Buns]]
[[Category:Beret Guy's Business]]

2502: Every Data Table

2021-08-14T17:35:33Z

IndigoFenix: /* Explanation */

{{comic
| number = 2502
| date = August 13, 2021
| title = Every Data Table
| image = every data table.png
| titletext = "I'm hoping 2022 is relatively normal because I don't know what symbol comes after the asterisk and the dagger."
| imagesize =
}}

==Explanation==
{{incomplete|Created by a TRIPLE DAGGER. Do NOT delete this tag too soon.}}
This comic is another entry in a [[:Category:COVID-19|series of comics]] related to the {{w|COVID-19 pandemic|2020-21 pandemic}} of the {{w|SARS-CoV-2}} virus, which causes {{w|COVID-19}}.

The COVID pandemic has had a large impact on the entire world and one way this can be seen is through strange stats resulting from the effects of the pandemic. Various statistics such as employment statistics, spending power, holiday miles, pet ownerships, births (or at least conceptions) and — naturally — deaths may have been either grossly suppressed/increased for the majority of 2020, and for 2021 may have hardly recovered, partially recovered, renormalised, bounced back with a vengeance or be over-compensated for in the effort to catch up.

It is hard to know what 2022 might be like. Nothing (at the time of this comic being published) is exactly back to normal and proper recovery or the resulting compensatory readjustment may not have concluded in time for 2022 to reflect the trends expected based upon pre-2020 figures, and the additional further years that future statistics will record.

As an example, the cycles of Summer and Winter Olympics/Paralympics has been disrupted due to the 2020 Summer Olympics being postponed to 2021, thus causing the next Winter Olympics to be only half a year away (in early 2022) and the next Summer Olympics/Paralympics to be 3 years away (in 2024). This has not occurred since the 1990s (when both of the Winter Games were shifted away from the Summer Games' years), or the 1940s (the last major interruption in the main Summer Olympic cycle).

Sometimes punctuation such as an asterisk (*) or a dagger (†, also called an obelus or obelisk) is used to denote an unusual entry in a table to be explained in a footnote with a matching symbol. Common symbols that are used if the first two are taken include multiple symbols (such as †† or ***), or a series of further symbols such as a double dagger (‡), the section symbol/silcrow (§), the parallel/double-pipe (‖) and the paragraph symbol/pilcrow (¶). Alternately you can start and continue with superscript numbers (¹, ², ³ ...), especially when you expect to commonly need {{w|Terry Pratchett|multiple}} and/or {{w|Randall Munroe|nested}} footnotes on each page, or gather them as endnotes, a whole chapter at a time.

It is also possible that the symbols themselves may be acknowledging the cause of the impacts; the asterisk (*) resembles a spiked coronavirus, and the dagger (†) resembles a hypodermic needle used for a vaccine.

The author, however, seems to have forgotten the potential monkey's paw nature of his wish. Relative is a relative term. It could well be that the whole pandemic thing becomes the new normal, thus removing the necessity of using symbols to delineate such years.

== Transcript ==

:2017........ (scribble)
:2018....... (scribble)
:2019....... (scribble)
:2020*...... (scribble)
:2021†...... (scribble)
:2022....... (scribble)
:2023....... (scribble)
:2024....... (scribble)

:[Caption under the panel:]
:Every data table from now on

{{comic discussion}}

[[Category:COVID-19]]
[[Category:Statistics]]

Talk:2145: Heists And Escapes

2019-05-05T19:29:04Z

IndigoFenix:

The real-life battle of Alesia was appparently the opposite of Winterfell, insofar as where the "rattling" happens. [[Special:Contributions/198.41.230.244|198.41.230.244]] 21:37, 3 May 2019 (UTC)
:I think that title text theory it's also a reference to the [[wikipedia:Tommy_Westphall#The_Tommy_Westphall_Universe_Hypothesis|Tommy Westphall universe hypothesis]]. --[[User:Valepert|valepert]] ([[User talk:Valepert|talk]]) 21:48, 3 May 2019 (UTC)

I'm pretty sure that "Kevin McCallister's Subconscious" is an Inception reference. [[User:LegionMammal978|LegionMammal978]] ([[User talk:LegionMammal978|talk]]) 22:44, 3 May 2019 (UTC)
: I've out of reflex hafe read that Kenny is dead, instead.[[User:Gunterkoenigsmann|Gunterkoenigsmann]] ([[User talk:Gunterkoenigsmann|talk]]) 05:08, 4 May 2019 (UTC)
:"Kevin McCallister" is the name of the lead character in the Home Alone movies, played by Macaulay Culkin.
:[[User:ProphetZarquon|ProphetZarquon]] ([[User talk:ProphetZarquon|talk]]) 17:21, 4 May 2019 (UTC)

I'm guessing that Randall also watches Game of Thrones. Also should we add a GoT or ASoIaF category? It's been referenced in several comics in the past. [[User:Herobrine|Herobrine]] ([[User talk:Herobrine|talk]]) 00:32, 4 May 2019 (UTC)
:Yes please?
:[[User:ProphetZarquon|ProphetZarquon]] ([[User talk:ProphetZarquon|talk]]) 17:16, 4 May 2019 (UTC)

inb4 crazy anti-semitic conspiracy theorist vandalises the page [[User:RandomIsocahedron|RandomIsocahedron]] ([[User talk:RandomIsocahedron|talk]]) 00:56, 4 May 2019 (UTC)
:For the most part he only vandalized comics related to space or science, there's no reason for him to vandalize this page. Besides he hasn't vandalized any pages recently either, I think he got tired of constantly having to type in a CAPTCHA to vandalize pages only to have it reverted almost instantly by us. [[User:Herobrine|Herobrine]] ([[User talk:Herobrine|talk]]) 01:50, 4 May 2019 (UTC)
::Can confirm, CAPTCHAs suck. {{unsigned ip|162.158.146.166}}

Dude, spoiler alert?! [[Special:Contributions/162.158.62.15|162.158.62.15]] 19:19, 4 May 2019 (UTC)

Anyone else get the feeling that Randall is taunting us explainxkcders with the last part of the title text on this one? [[Special:Contributions/172.68.133.54|172.68.133.54]] 21:43, 4 May 2019 (UTC)
:Maybe, but that kind of absurdist humour involving combining different stories is fairly common on xkcd. [[User:RandomIsocahedron|RandomIsocahedron]] ([[User talk:RandomIsocahedron|talk]]) 00:31, 5 May 2019 (UTC)
::Well, let's try. The protagonists are stuck in a room, surrounded by the dead. Kevin is among the dead, and he is the only one who knows how to break into the vault. In order to get into the vault after escaping their room, they must first enter Zombie Kevin's mind and at the same time rescue his soul from Hell, escaping from the land of the dead across the River Styx. They must then reunite their souls with their minds and their minds with their bodies, use the resurrected Kevin to enter the vault, and finally escape, whereupon they find that the whole setup was in fact a staged TV show - except for the descent into Hell, which was actually real. [[User:IndigoFenix|IndigoFenix]] ([[User talk:IndigoFenix|talk]]) 20:28, 5 May 2019 (UTC)

I would argue that the middle room at the battle of Winterfell is not necessarily the keep but just a reference to the castle of Winterfell as a whole.[[Special:Contributions/162.158.89.157|162.158.89.157]] 06:23, 5 May 2019 (UTC)
:The mention of this "middle room" here and in the explanation is quite confusing. In the comic, there's an outer room and an inner room (I'm guessing this is the crypt), but what does the term middle room refer to? Could someone with knowledge of GoT please change this section so it makes sense in terms of two rooms instead of a middle room that doesn't exist? [[User:Ianrbibtitlht|Ianrbibtitlht]] ([[User talk:Ianrbibtitlht|talk]]) 14:33, 5 May 2019 (UTC)

2097: Thor Tools

2019-01-14T15:58:45Z

IndigoFenix:

{{comic
| number = 2097
| date = January 11, 2019
| title = Thor Tools
| image = thor_tools.png
| titletext = CORRECTION: After careful evaluation, we have determined that the axis label on this chart was printed backward.
}}

==Explanation==
{{incomplete|Add a list of the tools in the comic. Do NOT delete this tag too soon.}}

In Norse mythology, {{w|Thor}} is (in Scandinavian languages) the name of a god of thunder and lightning. His signature weapon is a magic hammer called {{w|Mjölnir}}. In popular culture, he might be best known for his role in {{w|Thor (Marvel Comics)|Marvel comics and films}}, which his appearance here seems to be referencing. In the Marvel Cinematic Universe movie, Avengers: Infinity War, Thor also wields an axe named Stormbreaker.

Although this hammer was historically a weapon, this comic interprets it as it would more commonly be interpeted today -- as a tool. The comic is listing various hand tools in order of utility and viability as Thor's weapon, besides his actual, enchanted hammer. Hammers are heavy, blunt, and can do large amounts of damage to an opponent, whereas a hand plane is sharp, but only in one place, and will only inflict surface wounds.

Some of these tools require power, which would generally require Thor to stay near an outlet or keep a battery charging, such as the circular saw, or Dremel. However, being the god of lightning may allow him to circumvent this, by producing electricity for the direct current (D.C.) tools, although he would need an inverter to convert the lightning (D.C.) to alternating current (A.C.) for the tools requiring it. Thor would also need compressed air for the nail gun or jackhammer, only allowing Thor so many shots before reloading the air tank at an outlet, or via a concentrated wind storm.

The nail gun and staple gun would also require nails or staples respectively to function as a weapon. Although Mjölnir is believed to return to Thor if thrown, it's not clear how similar system could work with nails and staples.

The usefulness of the nail gun as a weapon might depend on whether it was an older one that can be bump-fired or a newer one that requires a separate trigger pull for each nail.

In the title text, [[Randall]] writes that the order of the axis label should be reversed, making the plane the best tool and Mjölnir the worst. Considering that the title of the comic is "Thor Tools" ("tools", instead of "weapons"), the argument seems to be that a hammer is less useful than the rest, by seeing them as tools and not as weapons.

A few other interpretations of this could be:
* Randall proposes that Thor armed with a plane or digital calipers would be much more fearsome than with a hammer.
* The "value" of the more strange-seeming items would be much higher than his traditional hammer, perhaps more gory or more humorous.
* Thor tends to cause collateral damage, and would cause less with a plane or calipers.
* "Best" and "worst" are to be interpreted for Thor's enemies rather than Thor himself.
* Randall might just find the idea of Thor wielding a Plane as a weapon to be really funny.

The title may be a reference to Gary Larson's ''The Far Side'' comic, ''Cow Tools''.

===List of tools===

All shown tools are explained below:
;Hammer
:A {{w|hammer}} ''is a tool consisting of a weighted "head" fixed to a long handle that is swung to deliver an impact to a small area of an object''. Thor was a hammer-wielding god and produced the lighting by using this tool. A {{w|war hammer}} was an actual blunt weapon used for combat in medieval times, and is the original Thor's attribute. There exists a variety of craftsman's hammers designed for specific purposes which can be used as weapons of opportunity to various degrees, depending on the tool's size, weight and material.
;Axe
:An {{w|axe}} or just ax is another old human tool used to split and cut wood, but it also was used as a dangerous weapon in the medieval times. The battle-axes of old were of considerably different design than the woodworking ones, being lighter and having thinner and wider blades. Even though, a woodworking axe could be a formidable weapon of opportunity.
;Claw hammer
:A {{w|claw hammer}} is a hammer tool primarily used for driving nails into other objects, but also for pulling nails from them. This item seems a bit redundant in the presence of a general hammer on the axis, but could be seen as more scary because it has a pointed, curved and split back head (used for pulling nails). In fact, the usefulness of its back head for combat is debatable at least. On the other hand, it is smaller and lighter than some other craftman's hammers, and less scary than a true war hammer, so its place on the axis may be justified.
;Circular saw
:A {{w|circular saw}} is using a, mostly electric powered, fast-revolving toothed disc to cut materials. A stationary version is called a ''table saw'' but the figure of Thor drawn above presents him using a lighter hand-held version making a buzzing sound. Since the power of the saw is far beyond the human power it is quite a dangerous tool and could be fatal to the user himself. However, it would be rather unwieldy in combat, as it is quite heavy and bulky, and usually requires both hands to operate. Also, electric circular saw would be limited by its cord length, however cordless (battery-operated) saws exist today. This item could be a mock reference to a common trope in horror movies or computer games, when a {{w|chainsaw}} (not a circular saw) is used a weapon.
;Shovel
:A {{w|shovel}} is also a historic tool. It can be used to dig into the ground, move snow or dirt, harvest, and much more. Because it has a relatively thin, sharp metal blade at the end of a pole, it can be used as a weapon of opportunity. Indeed, a small (sometimes foldable), sturdy {{w|Entrenching tool|spade}} was and still is a standard issue item for an infantryman in some countries, intended mainly for entrenching work, but also usable as a weapon – and the soldiers are trained to use it as such, sometimes to a high skill, specifically among special forces. It is rumored that Russian Spetznaz operators are specifically trained to use their spades as throwing weapons. It is therefore more useful in combat than a circular saw – but may be seen as less scary.
;Jackhammer
:A {{w|jackhammer}} is a power tool used to drill and crush hard but brittle materials like stone, concrete etc. It has heavy body with a protruding shaft that makes hard and rapid back-and-forth (and optionally also rotary) movements that drive an implement (a drill, a chisel etc.) into the worked material. Like the circular saw jackhammer is a tool that is powered far beyond single human capabilities. Most jackhammers are very heavy and can be reasonably used only in a facing-down position to work on floors, pavements and other near-horizontal surfaces, nullifying combat application. However, since Thor is purportedly very strong, he may be able to hold it horizontally for some combat...
;Socket wrench
:A handle attached to a {{w|socket wrench}} is mostly used to tighten bolts or nuts. But since it is quite heavy and resembles a hammer it could also be used in a similar fashion. It may be a self-reference to [[538: Security|comic 538]].
;Bolt cutters
:{{w|Bolt cutters}} are cutters with very long handles, typically 2 or 3 feet long, and comparatively tiny jaws. The length of the handles provides the user enough mechanical advantage to sheer through things like bolts, chain links, and lock shackles. Although this tool can cut some fairly tough objects, its usefulness in combat is limited – as far as the cutting action goes at least. On the other hand they are quite heavy and can be used as a blunt weapon.
;Hacksaw
:A {{w|hacksaw}} is a type of hand saw with very small teeth. Hacksaws are well suited to cutting materials like metal and plastic, where the larger teeth of a wood saw would tend to bind or damage the material around the cut. Hacksaw blades are fairly unlikely to seriously injure people, though a hacksaw may be useful against metal baddies like Ultron.
;Nail gun
:A {{w|nail gun}} is a tool for driving nails or other fasteners into various materials ranging from soft wood to hard concrete by a single powerful "shot" to the nail being driven. There are models powered by compressed air, electricity (several types of mechanisms) or explosive charges similar to firearm ammunition (most often compatible with {{w|.22 Short}} blank cartridges). They are normally used by slightly pushing the "nozzle" against an object, disengaging a safety nose contact mechanism, and pulling the trigger. These are quite dangerous tools and can be potentially modified – by removing safety mechanisms – to act similarly to a handgun, shooting nails as high-speed projectiles. It's place in the middle of the axis seems not right compared to the work hazard level of other tools placed left of it. If safety mechanisms are left intact, a nail gun would need to be used in close combat by pressing it against an opponent which would make it difficult to apply, but if applied successfully it would inflict grievous wounds.
;Staple gun
: A {{w|staple gun}} is a tool used to drive {{w|Staple (fastener)|staples}} (C-shaped pieces of hard wire) into relatively soft materials such as wood, plastics and light masonry in order to fix something to them. There exist spring-loaded hand-operated staple guns as well as power ones utilizing either electricity or compressed air. The power discharged during staple action is a lot less than that of a nail gun and would inflict minor skin wounds at most. If one manages to eject a staple into the air (not against an object) it won't travel very far. A figure of Thor is drawn above the axis showing him using a staple gun this way, with staples falling short onto the ground. The gun held by Thor makes ''kachunk'' sounds characteristic for a spring-loaded version of the tool.
;Coping saw
;Screwdriver (flat)
:A (flat) {{w|screwdriver}} is a metal rod with a handle, flattened and ground at the other end to form a fairly sharp but short edge perpendicular to the rod. It is normally used to drive {{w|Screw|screws}} into a material, by putting the edge into a groove on the screw's head and turning it while pressing firmly. It is not very dangerous normally, but many people have cut their fingers while driving screws in. It could potentially be used as a stabbing weapon similarly to a dagger, but much less effectively, or alternatively the heavy handle may be used as a bludgeon, though the smooth rod would be difficult to grip. Some nations seem to regard it so much dangerous as to ban its possession in public along knives.
;Ball-peen hammer
;Screwdriver (Phillips)
:Similar to a flat screwdriver, but with a cross-shaped tip, designed to drive screws with matching cross-shaped heads. While a Phillips screwdriver could potentially be used as an improvised weapon to stab or strike like a flat screwdriver, the blunter, cross shape is less likely to inflict cutting injury, likely leading to its lower position on the list.
;Awl
:An {{w|Stitching awl|awl}} is a hand tool, basically a rather short, thin, sharp (sometimes curved) spike with a handle. It is used for punching holes through soft material (leather, fabrics) or to {{w|Scratch awl|mark points}} or lines on wood or metal to assist further work such as cutting or drilling. In a pinch, it could be used as a stabbing weapon like a dagger, but a screwdriver is more sturdy for such purpose.
;Digital Caliper
:{{w|Digital calipers}} are an instrument for precisely measuring the dimensions of small objects. Typically, digital calipers can measure inner diameters, outer diameters, and depth. The reason they are considered more formidable than Dremels and planes is likely how supprisingly sharp the calipers are. They need to be sharp to make accurate measurements, but it is not uncommon for people to cut themselves while using a digital caliper.
;Dremel
:Dremel is a brand name (often used in a generic sense) of small {{w|Die grinder|rotary power tools}} that can be used in precise work involving small objects such as engraving, milling, drilling, grinding, cutting, polishing etc. It consists of a relatively small and lightweight body housing a high-speed electric motor driving a shaft equipped with a {{w|Chuck (engineering)|chuck}}. Various implements can be fixed to the chuck – drills, milling cutters of various shapes, small cutting disks, grinding stones, brushes, soft polishing disks etc. Typically the tool is used handheld against an object held in a vice. It can also be mounted in a stand with a {{w|flexible shaft}} attached, at the other end of which an implement is fixed in a chuck, allowing for still more precise work. A Dremel would be rather useless in combat, effecting in superficial wounds only. It could be seen as a baby circular saw, therefore much less scary and placed much more to the right of the scale. However, it is still a heavy object with a firm grip, and could plausibly be wielded as a bludgeon, making it slightly more effective than a plane.
;Plane
:A {{w|Plane_(tool)|hand plane}} is a tool for shaping wood using muscle power to force the cutting blade over the wood surface. It is designed to scrape layers of wood off the surface. While a plane does have a sharp edge and can cause painful injuries if misused, its awkward shape and the small size of the cutting edge would make it impractical to wield and nearly useless as a combat weapon, even for bludgeoning. A hand plane could plausibly be used as a particularly brutal ''torture'' device on a restrained victim, but as Thor is typically depicted as an honorable and heroic character it is unlikely that he would use one in this manner.

==Transcript==

:[A wide image is shown in a single frame.]
:Hand tools Thor could have ended up with
:[Below is a small centered horizontal line with arrows at both ends, labeled "Best" to the left and "Worst" on the right.]

:[The rest of the image shows an other horizontal line in the middle, also with arrows at both ends, covering the full width. Items are marked by a dot with a text above or below, and sometimes a figure wearing a winged helmet, above the line, uses a tool mentioned below:]
:Hammer
:Axe
:Claw hammer
:Circular saw
:[Above, the winged helmet guy uses a circular saw:]
:''Bzzzz zzzz''
:Shovel
:Jackhammer
:Socket wrench
:[Above, the winged helmet guy spins the socket of a socket wrench with a tiny sound.]
:Bolt cutters
:Hacksaw
:Nail gun
:Staple gun
:[Above, the winged helmet guy fires staples into the ground in front of him:]
:''Kachunk kachunk''
:Coping saw
:Screwdriver (flat)
:Ball-peen hammer
:Screwdriver (Phillips)
:Awl
:Digital Caliper
:Dremel
:[Above, the winged helmet guy shows a running Dremel to the left:]
:''Bzzzzz''
:Plane

{{comic discussion}}

2097: Thor Tools

2019-01-14T15:50:56Z

IndigoFenix: /* List of tools */

{{comic
| number = 2097
| date = January 11, 2019
| title = Thor Tools
| image = thor_tools.png
| titletext = CORRECTION: After careful evaluation, we have determined that the axis label on this chart was printed backward.
}}

==Explanation==
{{incomplete|Add a list of the tools in the comic. Do NOT delete this tag too soon.}}

In Norse mythology, {{w|Thor}} is (in Scandinavian languages) the name of a god of thunder and lightning. His signature weapon is a magic hammer called {{w|Mjölnir}}. In popular culture, he might be best known for his role in {{w|Thor (Marvel Comics)|Marvel comics and films}}, which his appearance here seems to be referencing. In the Marvel Cinematic Universe movie, Avengers: Infinity War, Thor also wields an axe named Stormbreaker.

Although this hammer was historically a weapon, this comic interprets it as it would more commonly be interpeted today -- as a tool. The comic is listing various hand tools in order of utility and viability as Thor's weapon, besides his actual, enchanted hammer. Hammers are heavy, blunt, and can do large amounts of damage to an opponent, whereas a hand plane is sharp, but only in one place, and will only inflict surface wounds.

Some of these tools require power, which would generally require Thor to stay near an outlet or keep a battery charging, such as the circular saw, or Dremel. However, being the god of lightning may allow him to circumvent this, by producing electricity for the direct current (D.C.) tools, although he would need an inverter to convert the lightning (D.C.) to alternating current (A.C.) for the tools requiring it. Thor would also need compressed air for the nail gun or jackhammer, only allowing Thor so many shots before reloading the air tank at an outlet, or via a concentrated wind storm.

The nail gun and staple gun would also require nails or staples respectively to function as a weapon. Although Mjölnir is believed to return to Thor if thrown, it's not clear how similar system could work with nails and staples.

The usefulness of the nail gun as a weapon might depend on whether it was an older one that can be bump-fired or a newer one that requires a separate trigger pull for each nail.

In the title text, [[Randall]] writes that the order of the axis label should be reversed, making the plane the best tool and Mjölnir the worst. Considering that the title of the comic is "Thor Tools" ("tools", instead of "weapons"), the argument seems to be that a hammer is less useful than the rest, by seeing them as tools and not as weapons.

A few other interpretations of this could be:
* Randall proposes that Thor armed with a plane or digital calipers would be much more fearsome than with a hammer.
* The "value" of the more strange-seeming items would be much higher than his traditional hammer, perhaps more gory or more humorous.
* Thor tends to cause collateral damage, and would cause less with a plane or calipers.
* "Best" and "worst" are to be interpreted for Thor's enemies rather than Thor himself.
* Randall might just find the idea of Thor wielding a Plane as a weapon to be really funny.

The title may be a reference to Gary Larson's ''The Far Side'' comic, ''Cow Tools''.

===List of tools===

All shown tools are explained below:
;Hammer
:A {{w|hammer}} ''is a tool consisting of a weighted "head" fixed to a long handle that is swung to deliver an impact to a small area of an object''. Thor was a hammer-wielding god and produced the lighting by using this tool. A {{w|war hammer}} was an actual blunt weapon used for combat in medieval times, and is the original Thor's attribute. There exists a variety of craftsman's hammers designed for specific purposes which can be used as weapons of opportunity to various degrees, depending on the tool's size, weight and material.
;Axe
:An {{w|axe}} or just ax is another old human tool used to split and cut wood, but it also was used as a dangerous weapon in the medieval times. The battle-axes of old were of considerably different design than the woodworking ones, being lighter and having thinner and wider blades. Even though, a woodworking axe could be a formidable weapon of opportunity.
;Claw hammer
:A {{w|claw hammer}} is a hammer tool primarily used for driving nails into other objects, but also for pulling nails from them. This item seems a bit redundant in the presence of a general hammer on the axis, but could be seen as more scary because it has a pointed, curved and split back head (used for pulling nails). In fact, the usefulness of its back head for combat is debatable at least. On the other hand, it is smaller and lighter than some other craftman's hammers, and less scary than a true war hammer, so its place on the axis may be justified.
;Circular saw
:A {{w|circular saw}} is using a, mostly electric powered, fast-revolving toothed disc to cut materials. A stationary version is called a ''table saw'' but the figure of Thor drawn above presents him using a lighter hand-held version making a buzzing sound. Since the power of the saw is far beyond the human power it is quite a dangerous tool and could be fatal to the user himself. However, it would be rather unwieldy in combat, as it is quite heavy and bulky, and usually requires both hands to operate. Also, electric circular saw would be limited by its cord length, however cordless (battery-operated) saws exist today. This item could be a mock reference to a common trope in horror movies or computer games, when a {{w|chainsaw}} (not a circular saw) is used a weapon.
;Shovel
:A {{w|shovel}} is also a historic tool. It can be used to dig into the ground, move snow or dirt, harvest, and much more. Because it has a relatively thin, sharp metal blade at the end of a pole, it can be used as a weapon of opportunity. Indeed, a small (sometimes foldable), sturdy {{w|Entrenching tool|spade}} was and still is a standard issue item for an infantryman in some countries, intended mainly for entrenching work, but also usable as a weapon – and the soldiers are trained to use it as such, sometimes to a high skill, specifically among special forces. It is rumored that Russian Spetznaz operators are specifically trained to use their spades as throwing weapons. It is therefore more useful in combat than a circular saw – but may be seen as less scary.
;Jackhammer
:A {{w|jackhammer}} is a power tool used to drill and crush hard but brittle materials like stone, concrete etc. It has heavy body with a protruding shaft that makes hard and rapid back-and-forth (and optionally also rotary) movements that drive an implement (a drill, a chisel etc.) into the worked material. Like the circular saw jackhammer is a tool that is powered far beyond single human capabilities. Most jackhammers are very heavy and can be reasonably used only in a facing-down position to work on floors, pavements and other near-horizontal surfaces, nullifying combat application. However, since Thor is purportedly very strong, he may be able to hold it horizontally for some combat...
;Socket wrench
:A handle attached to a {{w|socket wrench}} is mostly used to tighten bolts or nuts. But since it is quite heavy and resembles a hammer it could also be used in a similar fashion. It may be a self-reference to [[538: Security|comic 538]].
;Bolt cutters
:{{w|Bolt cutters}} are cutters with very long handles, typically 2 or 3 feet long, and comparatively tiny jaws. The length of the handles provides the user enough mechanical advantage to sheer through things like bolts, chain links, and lock shackles. Although this tool can cut some fairly tough objects, its usefulness in combat is limited – as far as the cutting action goes at least. On the other hand they are quite heavy and can be used as a blunt weapon.
;Hacksaw
:A {{w|hacksaw}} is a type of hand saw with very small teeth. Hacksaws are well suited to cutting materials like metal and plastic, where the larger teeth of a wood saw would tend to bind or damage the material around the cut. Hacksaw blades are fairly unlikely to seriously injure people, though a hacksaw may be useful against metal baddies like Ultron.
;Nail gun
:A {{w|nail gun}} is a tool for driving nails or other fasteners into various materials ranging from soft wood to hard concrete by a single powerful "shot" to the nail being driven. There are models powered by compressed air, electricity (several types of mechanisms) or explosive charges similar to firearm ammunition (most often compatible with {{w|.22 Short}} blank cartridges). They are normally used by slightly pushing the "nozzle" against an object, disengaging a safety nose contact mechanism, and pulling the trigger. These are quite dangerous tools and can be potentially modified – by removing safety mechanisms – to act similarly to a handgun, shooting nails as high-speed projectiles. It's place in the middle of the axis seems not right compared to the work hazard level of other tools placed left of it. If safety mechanisms are left intact, a nail gun would need to be used in close combat by pressing it against an opponent which would make it difficult to apply, but if applied successfully it would inflict grievous wounds.
;Staple gun
: A {{w|staple gun}} is a tool used to drive {{w|Staple (fastener)|staples}} (C-shaped pieces of hard wire) into relatively soft materials such as wood, plastics and light masonry in order to fix something to them. There exist spring-loaded hand-operated staple guns as well as power ones utilizing either electricity or compressed air. The power discharged during staple action is a lot less than that of a nail gun and would inflict minor skin wounds at most. If one manages to eject a staple into the air (not against an object) it won't travel very far. A figure of Thor is drawn above the axis showing him using a staple gun this way, with staples falling short onto the ground. The gun held by Thor makes ''kachunk'' sounds characteristic for a spring-loaded version of the tool.
;Coping saw
;Screwdriver (flat)
:A (flat) {{w|screwdriver}} is a metal rod with a handle, flattened and ground at the other end to form a fairly sharp but short edge perpendicular to the rod. It is normally used to drive {{w|Screw|screws}} into a material, by putting the edge into a groove on the screw's head and turning it while pressing firmly. It is not very dangerous normally, but many people have cut their fingers while driving screws in. It could potentially be used as a stabbing weapon similarly to a dagger, but much less effectively, or alternatively the heavy handle may be used as a bludgeon, though the smooth rod would be difficult to grip. Some nations seem to regard it so much dangerous as to ban its possession in public along knives.
;Ball-peen hammer
;Screwdriver (Phillips)
:Similar to a flat screwdriver, but with a cross-shaped tip, designed to drive screws with matching cross-shaped heads. While a Phillips screwdriver could potentially be used as an improvised weapon to stab or strike like a flat screwdriver, the blunter, cross shape is less likely to inflict cutting injury, likely leading to its lower position on the list.
;Awl
:An {{w|Stitching awl|awl}} is a hand tool, basically a rather short, thin, sharp (sometimes curved) spike with a handle. It is used for punching holes through soft material (leather, fabrics) or to {{w|Scratch awl|mark points}} or lines on wood or metal to assist further work such as cutting or drilling. In a pinch, it could be used as a stabbing weapon like a dagger, but a screwdriver is more sturdy for such purpose.
;Digital Caliper
:{{w|Digital calipers}} are an instrument for precisely measuring the dimensions of small objects. Typically, digital calipers can measure inner diameters, outer diameters, and depth. The reason they are considered more formidable than Dremels and planes is likely how supprisingly sharp the calipers are. They need to be sharp to make accurate measurements, but it is not uncommon for people to cut themselves while using a digital caliper.
;Dremel
:Dremel is a brand name (often used in a generic sense) of small {{w|Die grinder|rotary power tools}} that can be used in precise work involving small objects such as engraving, milling, drilling, grinding, cutting, polishing etc. It consists of a relatively small and lightweight body housing a high-speed electric motor driving a shaft equipped with a {{w|Chuck (engineering)|chuck}}. Various implements can be fixed to the chuck – drills, milling cutters of various shapes, small cutting disks, grinding stones, brushes, soft polishing disks etc. Typically the tool is used handheld against an object held in a vice. It can also be mounted in a stand with a {{w|flexible shaft}} attached, at the other end of which an implement is fixed in a chuck, allowing for still more precise work. A Dremel would be rather useless in combat, effecting in superficial wounds only. It could be seen as a baby circular saw, therefore much less scary and placed much more to the right of the scale.
;Plane
:A {{w|Plane_(tool)|hand plane}} is a tool for shaping wood using muscle power to force the cutting blade over the wood surface. It is designed to scrape layers of wood off the surface. While a plane does have a sharp edge and can cause painful injuries if misused, its awkward shape and the small size of the cutting edge would make it impractical to wield and nearly useless as a combat weapon.

==Transcript==

:[A wide image is shown in a single frame.]
:Hand tools Thor could have ended up with
:[Below is a small centered horizontal line with arrows at both ends, labeled "Best" to the left and "Worst" on the right.]

:[The rest of the image shows an other horizontal line in the middle, also with arrows at both ends, covering the full width. Items are marked by a dot with a text above or below, and sometimes a figure wearing a winged helmet, above the line, uses a tool mentioned below:]
:Hammer
:Axe
:Claw hammer
:Circular saw
:[Above, the winged helmet guy uses a circular saw:]
:''Bzzzz zzzz''
:Shovel
:Jackhammer
:Socket wrench
:[Above, the winged helmet guy spins the socket of a socket wrench with a tiny sound.]
:Bolt cutters
:Hacksaw
:Nail gun
:Staple gun
:[Above, the winged helmet guy fires staples into the ground in front of him:]
:''Kachunk kachunk''
:Coping saw
:Screwdriver (flat)
:Ball-peen hammer
:Screwdriver (Phillips)
:Awl
:Digital Caliper
:Dremel
:[Above, the winged helmet guy shows a running Dremel to the left:]
:''Bzzzzz''
:Plane

{{comic discussion}}

1991: Research Areas by Size and Countedness

2018-05-09T22:28:18Z

IndigoFenix:

{{comic
| number = 1991
| date = May 9, 2018
| title = Research Areas by Size and Countedness
| image = research_areas_by_size_and_countedness.png
| titletext = Mathematicians give a third answer on the vertical axis, "That question is poorly defined, but we have a sub-field devoted to every plausible version of it."
}}

==Explanation==
{{incomplete|The tables needs to be filled in. Title text not explained. Do NOT delete this tag too soon.}}

This comic is a [[:Category:Scatter plots|scatter plot]] that ranks different research fields according to the precision of the knowledge of the number of the studied object (vertical axis) vs. how large (the size of) the studied object is on the horizontal axis.

For instance the number of presidents is well known, so the study of their history is at the top of the Y-axis. This study is placed close to the Y-axis as the size of a president is about midway in size between the two extremes of the X-axis, elementary particles to the left (small) and the entire cosmos (cosmology) to the right (big).

On the X-axis Presidents are close to the middle. Both presidents and other larger life forms (as a research area) including extinct animals (paleontology) and exobiology are all close to the the same central position just right of the Y-axis, with smaller animals like birds and insects just to the left of the Y-axis. But where the number of presidents is well known, then the number of exoplanet life forms (exobiology) is completely unknown and thus it will be found at the very bottom of the Y-axis, since we have no idea if there are life elsewhere and if so how many places will it be and how varied.

The 19 research areas are listed and explained in the [[#Tables of research areas|tables]] below.

In the title text the mathematicians give a third answer...?

==Tables of research areas==

===Upper left quadrant===
*This is the section with the small items with count known.

{| class = "wikitable"
! Research field
! Size
! Knowledge of #
! Explanation
|-
|{{w|Elementary particle physics}}
| The smallest subjects that we have actually detected are the {{w|elementary particles}}. These may be made of smaller {{w|String theory|strings}} but if so these have still not been detected.
| We have a fairly good estimate of how many elementary particles there are. There could be some uncertainty though, so it is not at the very top.
|Elementary particle physics is concerned with the study of subatomic particles (the smallest things that can exist), of which there are 17. Most notably, until recently it was uncertain whether the {{w|Higgs boson}} was one of the elementary particles, but scientists have a "pretty good estimate" because the mathematical models don't predict the existence of many other particles
|-
|{{w|Dentistry}}
|
|
|Dentistry is the study of teeth (pretty small). Humans grow 32 teeth, which is a "pretty good estimate" since it is very rare for {{w|Hyperdontia|more than 32 teeth to grow}} and it is rather common for {{w|wisdom teeth}} to be surgically extracted
|-
|{{w|Shakespeare}} studies
|
|
|Shakespeare studies is concerned with the works of William Shakespeare (each book is pretty small). Generally, 36 plays are attributed to him, but between 1 and 3 additional plays are considered "lost" (i.e. at some point between being first published or performed and scholars seriously studying Shakespeare, all known copies, references, and fragments were destroyed, making it impossible to determine whether Shakespeare actually wrote them or whether they actually existed as separate plays), and {{w|Shakespeare apocrypha|some 20 more}} are believed to have been written by him, but not signed. To make matters worse, some plays that ''were'' published or performed under Shakespeare's name are believed to have been written as collaborations (not fully by him) or mis-attributed (we don't know who wrote them but, everyone says it was him).
|-
|{{w|Ornithology}}
|
|
|Ornithology studies birds (birds tend to be small, even the largest known bird, the {{w|Condor}}, stands smaller than the average human, with non-flying avians such as the {{w|ostrich}} generally not considered birds). As with all animal classifications, we aren't really certain how many species there are, and are [https://www.amnh.org/about-the-museum/press-center/new-study-doubles-the-estimate-of-bird-species-in-the-world constantly revising the figure], but all estimates remain in the low thousands, so we do have a "pretty good estimate"
|-
|Ancient {{w|literature}}
|
|
|While it is fairly straightforward to look up how many books [http://www.proquest.com/products-services/Books-in-Print.html are currently in print], or how many books [https://mashable.com/2010/08/05/number-of-books-in-the-world/ all currently printed information would fit into if bound into equal-length volumes], and then limiting those estimates to those that date before a specific year, counting how many books from the period of interest haven't survived to the present day (books that were "{{w|lost work|lost}}" either by deliberate discontinuation, or accidental destruction such as in the {{w|Destruction of the Library of Alexandria|Library of Alexandria}}) is a bit more difficult. However, because we know the work existed (it is mentioned by name in some other text), we have "pretty good estimate" that the number of lost works is "only" in the tens of thousands, as is the number of surviving works.
|}

===Upper right quadrant===
*This is the section with the big items with count known.

{| class = "wikitable"
! Research field
! Size
! Knowledge of #
! Explanation
|-
|{{w|Marine Mammol}}ogy
|
|
|Marine mammals are the largest extant animals. The US Government [http://www.nmfs.noaa.gov/pr/species/mammals/ recognizes] 119 marine mammals. However, what constitutes each species is [https://www.marinemammalscience.org/species-information/list-marine-mammal-species-subspecies/ constantly being revised], with new studies indicating either that what use to be considered a subspecies is actually a separate species, or that what use to be considered a subspecies is actually a separate species. As the depths of the ocean are further explored, species that were outright unknown are spotted and need to be classified. However, since marine mammals breathe air, they have to come to the surface where we can see them, so we're pretty sure that we've spotted them all.
|-
|{{w|List_of_Presidents_of_the_United_States|Presidential History}}
|
|
|Presidents are generally considered "big" men in history. Therefore, each one is fairly well known and documented. There is, however, some discussion on how many presidents there have been in the history of the United States, since prior to the {{w|Twenty-fifth Amendment to the United States Constitution|25th amendment}}, it was unspecified whether vice presidents counted as presidents during the President's absence. Most notably, this ambiguity is the reason {{w|David Rice Atchison}}'s tombstone is inscribed with the words "President of the United States for one day".
|-
|{{w|Railway}} Engineering
|
|
|A railway can span anywhere from a few hundred feet, to thousands of miles, so they're pretty big. The type of a railway is generally given by its {{w|track gauge}}, which are defined as "standard" (whatever you're currently using), "narrow" (rails closer together than whatever you're using) and "broad" (rails farther apart than whatever you're using). Since what is standard varies from country to country, and indeed from line to line, how many kinds of "narrow" gauge and "broad" gauge exist depend on who you ask.
|-
|{{w|Geology}}
|
|
|Geology is generally considered the study of rocks (small rocks being considered fragments of mountain layers, so what counts as a "rock" for a geologist can be pretty big). There is no universally agreed upon number to how many {{w|List of rock types|types of rock}} there are, but all geologists agree they can be grouped into igneous, metamorphic, and sedimentary rock.
|-
|{{w|Cosmology}}
| As this encompasses (at least) all of the visible parts of the universe (we live in) there can be no other "items" to study that would be larger.
| There are only one visible univrese, but there could be multiverses/parallel universes, and also an infinite universe beyond the borders of our own part of this universe' event horizon. So it depends on who you ask if they say there is one of and infinite number of universes to study, thus it is placed close to the middle of the two extremes,
|Cosmology is the study of the universe. There is an asterisk with the note "Depends on who you ask", relating to the estimate of how many universes there are. While it might seem obvious that there is only one universe, some branches of physics believe that our universe is part of a {{w|multiverse}}, and this remains an open and contested subject in the field.
|}

===Lower left quadrant===
*This is the section with the small items with count unknown.

{| class = "wikitable"
! Research field
! Size
! Knowledge of #
! Explanation
|-
|{{w|Mycology}}
|
|
|Mycology is the study of fungi (since fungi tend to grow flat -- excepting for mushrooms, which are their sexual organs, and do not exceed a foot in height (see [http://www.isciencetimes.com/articles/5740/20130729/giant-fungus-china-mushroom-world-s-largest-size.htm World's Largest mushrooms] -- mushrooms are generally considered small). It is a lot harder to discern which species a fungus is, and therefore classify it, so we "have no idea" how many kinds of fungi there are. Studies [https://www.ncbi.nlm.nih.gov/pubmed/21613136 vary wildly] between about 70,000 to over 5,000,000
|-
|Entymology
|
|
|It is unclear whether [[Randall]] means {{w|entomology}} or {{w|etymology}} (probably neither; it's likely that this wasn't a mistake). In either case, [https://www.ncbi.nlm.nih.gov/pubmed/28938083 estimates for insects] (entomology) vary from less than 1,000,000 to 30,000,000; and [https://www.quora.com/How-many-root-words-are-there-in-the-English-language estimates for root words] (etymology) reaching hundreds of thousands.
|-
|{{w|Microbiology}}
|
|
|Microbiology studies microscopic (too small to see) organisms, of which some 1,400 are known and "estimates for the total number of microbial species vary wildly, from as low as 120,000 to tens of millions and higher", according to [https://www.quora.com/How-many-root-words-are-there-in-the-English-language Nature magazine].
|-
|{{w|Pharmacology}}
|
|
|The number of drugs (pharmaceuticals) discovered and synthesized is not tallied, according to [https://www.raps.org/regulatory-focus%E2%84%A2/news-articles/2014/10/how-many-drugs-has-fda-approved-in-its-entire-history-new-paper-explains recent studies], but an estimate can be obtained by seeing how many have passed through the {{w|Food and Drug Administration|U.S. FDA}} (1,453). Many home remedies, which might technically qualify as drugs, have not been approved because {{w|Novelty (patent)|"everybody knows that"}}, as well as many solely recreational drugs since regulation might result in outlawing. Because of this, "we have no idea" how many drugs truly exist. Since drugs are extremely powerful molecules that are only administered in choice amounts, they are generally perceived as small.
|}

===Lower right quadrant===
*This is the section with the big items with count unknown.

{| class = "wikitable"
! Research field
! Size
! Knowledge of #
! Explanation
|-
|{{w|Botany}}
|
|
|
|-
|{{w|Paleontology}}
|Paleontologists study fossils, which range in size from very small to very large. When most people think of paleontologists though, they tend to think of them as studying large animals such as dinosaurs.
|
|
|-
|{{w|Black Hole}} Astronomy
|Compared to most astronomical objects, black holes are fairly small. However, most of them (that we are able to detect) are still larger than the Earth, so they would still fall on the "big" end of this chart. Alternatively, Randall may be referring to their mass, which is on the scale of stars.
|
|
|-
|{{w|Exobiology}}
|
|
|
|-
|{{w|Theology}}
|It is placed at a scale as large as the universe (cosmology) as it should encompass the entire creation. For those not believing in gods it could also be seen as studying something as small as the human brain that has created all the gods in our image. But Randall has chosen to place it in the big section.
|As no one really can know anything about theology as it is a study based on fairy tales it is at the bottom of the we have no idea scale. Generally applicable to anything with religiopn, but also here in relation to how many gods are there/how many religions.
|As far as "number of gods" is concerned, theological beliefs range from atheism (zero gods) to animism (an individual god in every single living or non-living thing that exists). A range from zero to near-infinite is an extremely broad estimate, placing it firmly on the "we have no idea" side of the diagram.
|}

==Transcript==
:[An X-Y scatter plot of research areas, written in gray font, where both axes have arrows in both ends. At the end of each arrow is a label. Above the left part of the X-axis there is a line which goes to a text about the meaning of the X-axis. Similarly there is a line to from the top of the Y-axis to a questions “asked” to those that study the given subject, their answers being somewhere between the two labels on the Y axis.]

:[The X-axis from left to right, text first and then labels:]
:Size of the thing you study
:Small
:Big

:[The Y-axis from top to bottom, question first and then labels:]
:"That thing you study - how many of them are there?"
:"We have a pretty good estimate."
:"We have no idea"

:[The research areas names are listed here below by sorting them into the four quadrants from top left to bottom right. In each quadrant the areas are listed after most left first, and then top to bottom for those at the same x position.]

:[Upper left quadrant (Small & count known):]
:Elementary particle physics
:Dentistry
:Shakespeare studies
:Ornithology
:Ancient Literature

:[Upper right quadrant (Big & count known):]
:Presidential History
:Marine Mammology
:Railway Engineering
:Geology
:Cosmology*
:(*Depends who you ask)

:[Lower left quadrant (Small & count unknown):]
:Pharmacology
:Microbiology
:Entymology
:Mycology

:[Upper right quadrant (Big & count unknown):]
:Botany
:Paleontology
:Exobiology
:Black Hole Astronomy
:Theology

{{comic discussion}}

[[Category:Scatter plots]]
[[Category:Rankings]]
[[Category:Science]]
[[Category:Physics]]
[[Category:Astronomy]]
[[Category:Math]] 
[[Category:Fiction]] 
[[Category:Religion]] 
[[Category:Animals]] 
[[Category:Exoplanets]] 
[[Category:Politics]]

1878: Earth Orbital Diagram

2017-08-18T14:58:54Z

IndigoFenix: /* Explanation */

{{comic
| number = 1878
| date = August 18, 2017
| title = Earth Orbital Diagram
| image = earth_orbital_diagram.png
| titletext = You shouldn't look directly at a partial eclipse because of the damage that can be caused by improperly aligning the solar-lunar orbital plane with the orbital bones around your eye.
}}

==Explanation==
{{incomplete|Created by a BOT - Please change this comment when editing this page. Do NOT delete this tag too soon.}}
This comic is the third consecutive comic published in the week before the {{w|solar eclipse}} occurring on Monday, {{w|Solar eclipse of August 21, 2017|August 21, 2017}} which is a total solar eclipse and visible in totality within a band across the {{w|contiguous United States}} from west to east. The other comics are [[1876: Eclipse Searches]] and [[1877: Eclipse Science]].

The comic claims that the reason that eclipses don't happen every month is simple to understand by looking at an orbital diagram. Ironically, the cartoon has so many parts and labels which make it far more difficult to understand than is implied. Many of the terms used are also incorrect and have nothing to do with orbital mechanics.

All these labels are complicated words, some are somewhat related to orbital mechanics ("equinox", "perihelion") while some are just latin sounding nouns. Moreover, many of the labels provided are kludged, obfuscated, or simply made up. Compare/contrast with the standard {{w|Kepler orbit|Kepler Orbit}} diagram. Most easily recognizable are the "Dimples of Venus," referring to axis-intersection points in the diagram on Earth.

The reason why eclipses do not occur every month is because the Moon and Earth do not orbit on a single plane; the moon's orbit has an angle, or ''inclination'' of about 5.145 degrees relative to the ''ecliptic plane'' and therefore only rarely passes directly between the Earth and the Sun. This fact is evident from this diagram and is correctly labeled with the simple Greek letter "theta"; the remaining labels do not contribute to this explanation and exist only to distract or misinform the reader.

{| class=wikitable
! Word used in the comics
! Meaning of word used
! Actual astronomical term
! Meaning of actual term

|-
| {{w|Declension}}
| Inflection of nouns in a language.
| Inclination
| The "tilt" of an orbit

|-
| Perihelix
| Portmanteau of helix and perihelion
| Perihelion
| Lowest point in a solar orbit

|}

==Transcript==
{{incomplete transcript|Do NOT delete this tag too soon.}}
:[An orbital map of the Earth is shown. The Sun is in the center, the Earth is at the right bottom, and the Moon is left below the Earth.]
:'''Why isn't there an eclipse every month?'''
:This is a common question! The answer is made clear b a quick look at the Earth's orbital diagram:

:[Label Sun:]
:Solar plexus

:[Labels Earth's orbit (beginning at the Earth counter clockwise):]
:Perihelix, Declension, Obsequity, Hypothecate, Enceliopsip, Equinox (''Solstice'' in British English)

:[Two angles in the plane are labeled as:]
:Determinant of the date of Easter, Arctangent

:[The plane of the Moon is pictured in a small angel to the Earth's plane and named Astral Plane. The labels at the Moons path are:]
:Tropopause, Prolapse, Dimples of Venus, Errata.

{{comic discussion}}

[[Category:Astronomy]]

1878: Earth Orbital Diagram

2017-08-18T14:48:55Z

IndigoFenix: /* Explanation */

{{comic
| number = 1878
| date = August 18, 2017
| title = Earth Orbital Diagram
| image = earth_orbital_diagram.png
| titletext = You shouldn't look directly at a partial eclipse because of the damage that can be caused by improperly aligning the solar-lunar orbital plane with the orbital bones around your eye.
}}

==Explanation==
{{incomplete|Created by a BOT - Please change this comment when editing this page. Do NOT delete this tag too soon.}}

Moreover, many of the labels provided are kludged, obfuscated, or simply made up. Compare/contrast with the standard {{w|Kepler orbit|Kepler Orbit}} diagram. Most easily recognizable are the "Dimples of Venus," referring to axis-intersection points in the diagram on Earth.

=== Explanation ===

{| class=wikitable
! Word used in the comics
! Meaning
! Actual astronomical term

|-
| {{w|Declension}}
| Inflection of nouns in a language.
| Inclination

|}

This comic is the third consecutive comic published in the week before the {{w|solar eclipse}} occurring on Monday, {{w|Solar eclipse of August 21, 2017|August 21, 2017}} which is a total solar eclipse and visible in totality within a band across the {{w|contiguous United States}} from west to east. The other comics are [[1876: Eclipse Searches]] and [[1877: Eclipse Science]].

The comic claims that the reason that eclipses don't happen every month is simple to understand by looking at an orbital diagram. Ironically, the cartoon has so many parts and labels which make it far more difficult to understand than is implied. Many of the terms used are also incorrect and have nothing to do with orbital mechanics.

All these labels are complicated words, some are somewhat related to orbital mechanics ("equinox", "perihelion") while some are just latin sounding nouns.

The reason why eclipses do not occur every month is because the Moon and Earth do not orbit on a single plane; the moon's orbit has an angle, or ''inclination'' of about 5.145 degrees relative to the ''ecliptic plane'' and therefore only rarely passes directly between the Earth and the Sun. This fact is evident from this diagram, although the numerous labels do not contribute to this explanation and in fact exist only to distract or misinform the reader.

==Transcript==
{{incomplete transcript|Do NOT delete this tag too soon.}}

{{comic discussion}}

[[Category:Astronomy]]

1878: Earth Orbital Diagram

2017-08-18T14:45:40Z

IndigoFenix: /* Explanation */

1864: City Nicknames

2017-07-17T19:29:03Z

IndigoFenix: /* Nicknames and Demonyms */ Added "Honey Badgers" as a possible inspiration for "Honey Barons"

{{comic
| number = 1864
| date = July 17, 2017
| title = City Nicknames
| image = city_nicknames.png
| titletext = This place has so many demonyms. Northlanders. Fair Folk. Honey Barons. Lake Dwellers. Treasurers. Swamp Watchers. Dream Farmers. Wellfolk. Rockeaters. Forgotten Royals. Remote Clients. Barrow-Clerks. The People of Land and Sky.
}}

==Explanation==
{{incomplete|stub}}

Cities often have official or unofficial nicknames. For instance, [[wikipedia:St._Louis|St. Louis, Missouri]], is known as "Gateway to the West" among several other nicknames. The nicknames typically invoke some historical or geographic feature of the city, but can sometime be opaque to those not familiar with the city. [https://www.into-asia.com/bangkok/introduction/fullname.php The full, formal name of Bangkok] includes a long list of superlatives translating as "The city of angels, the great city, the residence of the Emerald Buddha, the impregnable city (of Ayutthaya) of God Indra, the grand capital of the world endowed with nine precious gems, the happy city, abounding in an enormous Royal Palace that resembles the heavenly abode where reigns the reincarnated god, a city given by Indra and built by Vishnukarn."

[[Black Hat]] appears to believe they are near [[wikipedia:New York City|New York City]], despite the skyline being clearly recognizable as St. Louis due to the [[wikipedia:Gateway Arch|Gateway Arch]]. However, the nickname he gives is neither a common New York nickname (such as "[[wikipedia: List of nicknames of New York City|The Big Apple]]") nor a St. Louis nickname. [[Megan]] tries to correct him, but it becomes clear that Black Hat is making up nicknames. Many of his suggestions are puns for real nicknames of other places.

The title text contains made up [[wikipedia:Demonym|demonyms]] in the same pattern. A demonym is a word for the people who live in a particular place. They are typically derived from the name of the place (e.g. "St. Louisan" for people from St. Louis), but some regions have an [[wikipedia:Demonym#Informal|informal demonym]] that can be used colloquially by those familiar with the place to refer to its residents.

===Nicknames and Demonyms===

{| class=wikitable
! City nickname in comic
! Reference
! Explanation

|-
| The Hot Tamale
| {{w|Hot Tamales}}
| Possibly a reference to the term [https://www.urbandictionary.com/define.php?term=big%20enchilada/ The big enchilada.]

|-
| The Winged City
| The Windy City
| Chicago. Possibly also [http://www.airport-technology.com/projects/incheon-international-airport/ Incheon International Airport (ICA/RKSI), South Korea]

|-
| The Gold Trombone
|
| Possibly a reference to the gold standard.

|-
| Castleopolis
| {{w|Cassopolis}}
| {{w|Polis}} (from the Greek πόλις for city) is commonly used as a suffix for city names, like {{w|Minneapolis}} or {{w|Alexandroupolis}}; {{w|Metropolis}} can either be a type of city, or one of the real or fictional cities bearing the name. Appended to the base word "Castle", this would be the "Castle city".

|-
| The Kissing Kingdom
|
|

|-
| Sandland
|
| {{w|Sandland}} is a village in northern Norway, most likely coincidentally.

|-
| The High Place
|Denver
|Denver is known as the Mile High City

|-
| Ol' Ironhook
| {{w|Old Ironsides}}
| A nickname for the USS Constitution (docked in Charlestown, MA). Possibly a conflation of Old Kinderhook (a nickname for US President Martin Van Buren) with Old Ironsides (a nickname for English Lord Protector Oliver Cromwell).
|-
| The Thousand Spires || The City of a Hundred Spires / City of Dreaming Spires|| Prague / Oxford
|-
| The Graveyard of Kings || The Graveyard of Champions || Court 2 at Wimbledon, where former champions are often defeated (the playing environment is very different from Centre Court and Court One, which are larger and where games involving highly-ranked players are preferentially located). The comic was released one day after the 2017 Wimbledon Championships were finished.
|-
| Bloomtown || [[wikipedia: Boomtown|Boomtown]] || Generic term for a town undergoing rapid growth. Used in the 2002 TV series of the same name as a nickname for Los Angeles. Might also be referring to [[wikipedia:Bloom County|Bloom County]], a comic by [[wikipedia:Berkeley Breathed|Berkeley Breathed]], or Dublin, as the setting for Ulysses by James Joyce.
|-
| Lantern City USA || {{w|Tree City USA}} || A designation supporting municipalities that showcase urban forestry, in connection with Arbor Day.
|-
| The City of Many Daughters || ||
|-
| Big Mauve || [[wikipedia: Big_Red_(drink)|Big Red Soda]] || Big Red Soda. The Dartmouth football team is the Big Green.
|-
| The Glass Cradle || [[wikipedia:The Glass Menagerie|The Glass Menagerie]] || A play by Tennessee Williams
|-
| The Road Source ||{{w|Rome}} || From the saying that {{w|All Roads Lead to Rome}}
|-
| London Prime || London || In the DC comics, to incorporate multiple continuties, there were multiple universes. London Prime would be "real London" on Earth Prime. Various cities named {{w|New London}} in the United States and elsewhere are imagined as London in alternate continuities.
|-
| Hamtown || {{w|Hamburg}} {{w|Toronto}} || The German word ''Burg'' means castle or fort and is often used as suffix for town names. The origin of the prefix ''Ham'' is uncertain, but the food {{w|Hamburger}} derives from this city and ''Hamburger'' in German is the demonym of Hamburg. Toronto sometimes nicknamed Hogtown.
|-
| The Salad Bowl || || A theory of cultural integration in the US, one that stands in contrast to the older 'Melting Pot' theory. Could also refer to the [[wikipedia: Dust Bowl|Dust Bowl]]
|-
| God's Boudoir || || Humorous reference similar to "God's Waiting Room" used for the state of Florida, where many elderly retire then expire.
|-
| The Glittering Swamp || [[wikipedia:Great Dismal Swamp|The Great Dismal Swamp ]] || A large swamp in Virginia and North Carolina.
|-
| The Steel Forest || The Concrete Jungle || The Concrete Jungle is a name often given to New York's Manhattan area. There was also a book and movie entitled The Petrified Forest.
|-
| The Mobius Strip || The Strip || The Strip is a shortened and commonly used name for the Las Vegas Strip, the main area of hotels and casinos in Las Vegas, Nevada. A {{w|Mobius strip}} is a one-sided piece of paper created by rotating the short edge of the strip 180 degrees and attaching it to the other short edge. The Vegas strip has more or less only one side as well.
|-
| The Land of Trains and Fog || || In the webcomic [[wikipedia:Homestuck | Homestuck]] many events take place on various planets named in the format "The Land of X and Y", e.g. "The Land of Light and Rain". The novel by George R.R. Martin, which was made into ''Game of Thrones'', was called ''A Song of Ice and Fire''.
|-
| The Meeting Place || ||
|-
| The Dark Star || || Dark Star is a 1974 science fiction comedy film.
|-
| The Walled Garden || {{w|Walled garden (technology)}} || A walled garden is a virtual environment where the user can only view content that is published or permitted by the proprietor, e.g. AOL or Facebook. This could also be a reference to walled cities, e.g. from the Middle Ages, or the {{w|Kowloon Walled City}} in the modern era. The Secret Garden was a book.
|-
| Skin City || [[wikipedia:Sin City (description)|Sin City]] || Generic term for a city well known for gambling, drugs, or other vices. Also Las Vegas.
|-
| The Horse Rotary || ||
|-
| Turkeytown || Turkeytown || A town in Lincoln County, Kentucky
|-
| The Naked Towers || || The Naked City was a television series. The Two Towers is a book by Tolkien, and Naked Lunch is a book by Burroughs
|-
| The Meta-City || Metacity || A term for a heterogenous, sprawling urban center with multiple dense centers, such as Tokyo or New York City. Metacity was also the window manager in the Linux GNOME 2 desktop.
|-
| The Urban Orb || || The screenname of a Let's Player on Youtube and Twitch.
|-
| The City of Angles || City of Angels || Los Angeles. Also, the titular City of Angles in the web novel [http://stefangagne.com/cityofangles/ City of Angles].
|-
| The Big Wheel || [http://www.imdb.com/title/tt0041179/ The Big Wheel] || A 1949 movie about a race car driver. Alternatively, a child's plastic tricycle with an oversized front wheel.
|-
| Bird City USA || || A program started by the Audubon Society.
|-
| The City of Seven Crowns || City of Seven Hills || Rome
|-
| Hilltopia ||The Hilltop || May be reference to The Hilltop in AMC's The Walking Dead
|-
| Bug City || || A nickname for the bug-infested Chicago in the roleplaying game Shadowrun. Also, a sourcebook for the game.
|-
| The Bottomless Cup || || There are many mentions of Bottomless Pits in stories.
|-
| Lorde's Fen || Lord's Fen || [[wikipedia:Lorde| Lorde]] is a musical artist from Herne Bay, New Zealand - an area near Waitemata Harbour. A [[wikipedia:Fen| Fen]] is a type of wetland, which could loosely connect to Herne Bay.
|-
| The Last Town || || The third book in the Wayward Pines series.
|-
| The Empty Set || || The concert hall in the video game Transistor. In mathematics, the {{w|empty set}} refers to an unique set with no elements, often notated as "{}" or "∅".
|-
| Ghost Harbor || || The name for a brewing company in North Carolina.
|}

{| class=wikitable
! Demonym in comic
! Reference
! Explanation
|-
| Northlanders || Highlanders || Maybe a reference to the people of the {{w|Scottish Highlands}}, with a similar demonym. The "High" in "Highlands" is a reference to the mountainous landscape, not the geographical position.
|-
| Fair Folk || || The elves in ''The Lord of the Rings'' are referred to as the 'fair folk'. The fair folk is also more generally used as a name for fairies in folklore.
|-
| Honey Barons || [[wikipedia: Robber_baron_(industrialist) | Robber Barons]], [[wikipedia: Honey_badger | Honey Badgers]] || Possibly a play on The Robber Barons, a group of powerful industrialists in the late 1800's known for questionable business ethics, and honey badgers, animals known for their tough skin, bad tempers, and tenacity.
|-
| Lake Dwellers || ||
|-
| Treasurers || || A {{w|treasurer}} is a person in charge of running the treasury of an organization, for example a governmental department. The Auditors were characters in the Pratchett Discworld books who wanted to simplify the universe by destroying it.
|-
| Swamp Watchers || ||
|-
| Dream Farmers || ||
|-
| Wellfolk || Werefolk || The were folk were people who could change into animals: e.g. werewolves.
|-
| Rockeaters || [[Wikipedia:List_of_The_Neverending_Story_characters#Pyornkrachzark_and_the_other_messengers| Rockbiter]] || In the Never Ending Story, Pyornkrachzark, more commonly known as "Rock Biter" is a large creature made completely of stone, named due to their diet of rocks.
|-
| Forgotten Royals || [[wikipedia:Forgotten Realms | Forgotten Realms]] || Royalty from D&D campaign setting
|-
| Remote Clients || [[wikipedia:Remote_computer|Remote computer client]] || In computing, a remote client is a program used to access a computer or service over the internet.
|-
| Barrow-Clerks || [http://lotr.wikia.com/wiki/Barrow-wights Barrow-wights] || Creatures in "The Lord of the Rings" that resemble wraiths. The Hobbits come across them in the [http://lotr.wikia.com/wiki/Barrow-downs Barrow-downs].
|-
| The People of Land and Sky || [[wikipedia:Sea_Peoples|Sea Peoples]] ||
|}

==Transcript==
{{incomplete transcript|Do NOT delete this tag too soon.}}
:[Black Hat, Megan, and Ponytail are standing on a hill overlooking a city. The Gateway Arch is visible, as well as a number of skyscrapers in the skyline.]
:Black Hat: Ah, New York. The Hot Tamale.
:Megan: This is St. Louis. Also, that's not–
:Black Hat: The Winged City. The Gold Trombone. Castleopolis.
:Megan: It's none of those.

:[Close-up of Black Hat]
:Black Hat: The Kissing Kingdom. Sandland. The High Place. Ol' Ironhook.
:Megan (off-panel): Still wrong.
:Black Hat: The Thousand Spires. The Graveyard of Kings. Bloomtown. Lantern City USA.
:Megan (off-panel): Please stop.

:[Black Hat, Megan, and Ponytail are walking]
:Black Hat: The City of Many Daughters. Big Mauve. The Glass Cradle. The Road Source. London Prime. Hamtown. The Salad Bowl. God's Boudoir. The Glittering Swamp. The Steel Forest. The Mobius Strip. The Land of Trains and Fog. The Meeting Place. The Dark Star. The Walled Garden. Skin City. The Horse Rotary. Turkeytown. The Naked Towers. The Meta-City. The Urban Orb. The City of Angles. The Big Wheel. Bird City USA. The City of Seven Crowns. Hilltopia. Bug City. The Bottomless Cup. [Text size getting smaller] Lorde's Fen. The Last Town. The Empty Set. Ghost Harbor.
:Megan: How long does this last?
:Ponytail: No city has ever let him stay long enough to find out.

{{comic discussion}}
[[Category:Comics featuring Black Hat]]
[[Category:Comics featuring Megan]]
[[Category:Comics featuring Ponytail]]

1838: Machine Learning

2017-05-21T19:07:31Z

IndigoFenix: /* Neural networks */

{{comic
| number = 1838
| date = May 17, 2017
| title = Machine Learning
| image = machine_learning.png
| titletext = The pile gets soaked with data and starts to get mushy over time, so it's technically recurrent.
}}

==Explanation==
{{incomplete|Work in progress. <s>This explanation is an attempt at {{w|design by committee|machine learning by committee}}.</s>}}

{{w|Machine learning}} is a method employed in automation of complex tasks. It usually involves creation of algorithms that deal with statistical analysis of data and pattern recognition to generate output. The validity/accuracy of the output can be used to give feedback to make changes to the system, usually making future results statistically better.

Pinball stands atop his machine learning system, which consists of a pile of mathematical functions with an input funnel (labelled "data") at one end, an output box (labelled "answers") at the other, and a whole mess of mathematical functions in between. As Pinball explains to the incredulous Cueball, data enters through the funnel, undergoes an incomprehensible process of linear algebra, and comes out as answers. Pinball appears to be a functional part of this system himself, as he stands atop the pile stirring it with a paddle. Pinball's machine learning system is probably very inefficient, as he is integral to both the mechanical part (repeated stirring) and the learning part (making the answers look "right").

The main joke is that, despite this description being too vague and giving no intuition or details into the system, it is close to the level of understanding most machine learning experts have of the most popular class of techniques in machine learning, namely support vector machines. 

====Composting====
This comic compares a machine learning system to a compost pile. {{w|Composting}} is the process of taking organic matter, such as food and yard waste, and allowing it to decompose into a form that serves as fertilizer. A common method of composting is to mound the organic matter in a pile with a certain amount of moisture, then "stirring" the pile occasionally to move the less-decomposed material from the top to the interior of the pile, where it will decompose faster.

In large-scale composting operations, the raw organic matter added to the pile is referred to as "input". This cartoon implies a play on the term "input", comparing a compost input to a data input.

====Machine learning====
''One of the most popular paradigms of machine learning is that of supervised learning, where a function mapping an input to an output is learned from several input-output pairs, e.g. a function mapping images of faces to people names, from a dataset of static labelled images. Classic machine learning techniques like regression, or logistic regression, have understandable parameters, and provable algorithms, but require significant engineering in the pre-processing step and don't perform very well for data like images or natural text. Deep learning techniques, on the other hand, require very little pre-processing, but require the data to be run through several steps of linear algebra, where essentially in each step the output of the previous step is multiplied with a matrix and sent to the the next step. This multi-step process has proven to be very successful for image and text data, but the structure of the parameters, arranged as a matrix for each step, allows for very little interpretation, and can only be described as "data going through a pile of linear algebra".''

The method of training such deep neural networks is via gradient descent, which can be viewed as "stirring the pile of linear algebra until the answers start looking right".

The title text refers to recurrent neural networks, which are a useful class of deep neural networks for dealing with sequence data like speech or text.

====Neural networks====
This comic satirizes machine learning, more specifically neural networks. In its most basic form, a neural network takes data and results and strengthens connections that give the right answer and weakens ones that don't, until the results "look right". Neural networks are extremely data-dependent, and make remarkably few guarantees when compared to most other computing techniques, thus the joke.

''Recently, other forms of neural networks, such as LSTMs, feed old sequence data back into the network with some delay, making it recurrent. The title text calls this the pile "getting mushy". The title text is also be a pun based on how Pinball is going through the data. Instead of using a shovel, he is using a canoe paddle. Canoes can be used on rivers, and rivers by definition have currents. Thus, a recurrent data could, in this situation, mean data treated as if it were part of a river.''

Neural networks are programs that attempt to emulate a living brain - unlike traditional code, where the logic is written by a human programmer, a neural network looks for patterns between particular sets of inputs and particular outputs, strengthening connections that lead to "right" answers. Beyond creating the initial parameters of the network, as well as its inputs and outputs, teaching a neural network is less like programming and more like "training" - continually feeding the computer input-output pairs until the computer "learns" how to turn an input into an output, creating its ''own'' logical path. Google uses neural networks to analyze images, since it is extremely difficult to find a human-readable set of equations that could tell you, for instance, whether or not a [[https://explainxkcd.com/1425/ particular set of pixels represents a picture of a bird]].

One of the main criticisms of neural networks is that, while they do seem to ''work'', it is nearly impossible to examine the step-by-step process an actual trained neural network goes through to turn a given input into a given output, since the logic used by the program is effectively a "black box" that is meaningful only to the computer itself. When traditional code gives wrong answers, a programmer can look at the code's source and analyze its path of logic to find the source of the error. When a neural network gives wrong answers, the only solution is to train the network more ("stir the pile") until the answers start looking right.

In the above example, one might create a neural network that is intended to analyze pictures, then give it thousands of pictures of birds of different species and taken from different angles, as well as thousands of pictures of things that are not birds, and tell it which are birds and which are not until the program figures out the pattern well enough to recognize pictures of birds on its own. However, even when the program works, it will not be possible to look at the code to understand ''how'' the program recognizes birds - it just ''does''. If it starts mistyping images, the only way to figure out what is wrong is to look at a possible bias of the training images - perhaps the images left out pictures of birds viewed from above, or those of a particular unusual color, or those making a particular pose. To fix it, it must be sent back to training.

==Transcript==

[Cueball Prime, holds a canoe paddle at his side and stands on top of a "big pile of linear algebra" containing a funnel labeled "data" and box labeled "answers". Cueball II stands to the left side of the panel.)]

Cueball II: This is your machine learning system?

Cueball Prime: Yup! You pour the data into this big pile of linear algebra, then collect the answers on the other side.

Cueball II: What if the answers are wrong?

Cueball Prime: Just stir the pile until they start looking right.

{{comic discussion}}

1838: Machine Learning

2017-05-21T19:06:33Z

IndigoFenix: /* Neural networks */

{{comic
| number = 1838
| date = May 17, 2017
| title = Machine Learning
| image = machine_learning.png
| titletext = The pile gets soaked with data and starts to get mushy over time, so it's technically recurrent.
}}

==Explanation==
{{incomplete|Work in progress. <s>This explanation is an attempt at {{w|design by committee|machine learning by committee}}.</s>}}

{{w|Machine learning}} is a method employed in automation of complex tasks. It usually involves creation of algorithms that deal with statistical analysis of data and pattern recognition to generate output. The validity/accuracy of the output can be used to give feedback to make changes to the system, usually making future results statistically better.

Pinball stands atop his machine learning system, which consists of a pile of mathematical functions with an input funnel (labelled "data") at one end, an output box (labelled "answers") at the other, and a whole mess of mathematical functions in between. As Pinball explains to the incredulous Cueball, data enters through the funnel, undergoes an incomprehensible process of linear algebra, and comes out as answers. Pinball appears to be a functional part of this system himself, as he stands atop the pile stirring it with a paddle. Pinball's machine learning system is probably very inefficient, as he is integral to both the mechanical part (repeated stirring) and the learning part (making the answers look "right").

The main joke is that, despite this description being too vague and giving no intuition or details into the system, it is close to the level of understanding most machine learning experts have of the most popular class of techniques in machine learning, namely support vector machines. 

====Composting====
This comic compares a machine learning system to a compost pile. {{w|Composting}} is the process of taking organic matter, such as food and yard waste, and allowing it to decompose into a form that serves as fertilizer. A common method of composting is to mound the organic matter in a pile with a certain amount of moisture, then "stirring" the pile occasionally to move the less-decomposed material from the top to the interior of the pile, where it will decompose faster.

In large-scale composting operations, the raw organic matter added to the pile is referred to as "input". This cartoon implies a play on the term "input", comparing a compost input to a data input.

====Machine learning====
''One of the most popular paradigms of machine learning is that of supervised learning, where a function mapping an input to an output is learned from several input-output pairs, e.g. a function mapping images of faces to people names, from a dataset of static labelled images. Classic machine learning techniques like regression, or logistic regression, have understandable parameters, and provable algorithms, but require significant engineering in the pre-processing step and don't perform very well for data like images or natural text. Deep learning techniques, on the other hand, require very little pre-processing, but require the data to be run through several steps of linear algebra, where essentially in each step the output of the previous step is multiplied with a matrix and sent to the the next step. This multi-step process has proven to be very successful for image and text data, but the structure of the parameters, arranged as a matrix for each step, allows for very little interpretation, and can only be described as "data going through a pile of linear algebra".''

The method of training such deep neural networks is via gradient descent, which can be viewed as "stirring the pile of linear algebra until the answers start looking right".

The title text refers to recurrent neural networks, which are a useful class of deep neural networks for dealing with sequence data like speech or text.

====Neural networks====
This comic satirizes machine learning, more specifically neural networks. In its most basic form, a neural network takes data and results and strengthens connections that give the right answer and weakens ones that don't, until the results "look right". Neural networks are extremely data-dependent, and make remarkably few guarantees when compared to most other computing techniques, thus the joke.

''Recently, other forms of neural networks, such as LSTMs, feed old sequence data back into the network with some delay, making it recurrent. The title text calls this the pile "getting mushy". The title text is also be a pun based on how Pinball is going through the data. Instead of using a shovel, he is using a canoe paddle. Canoes can be used on rivers, and rivers by definition have currents. Thus, a recurrent data could, in this situation, mean data treated as if it were part of a river.''

Neural networks are programs that attempt to emulate a living brain - unlike traditional code, where the logic is written by a human programmer, a neural network looks for patterns between particular sets of inputs and particular outputs, strengthening connections that lead to "right" answers. Beyond creating the initial parameters of the network, as well as its inputs and outputs, teaching a neural network is less like programming and more like "training" - continually feeding the computer input-output pairs until the computer "learns" how to turn an input into an output, creating its ''own'' logical path. Google uses neural networks to analyze images, since it is extremely difficult to find a human-readable set of equations that could tell you, for instance, whether or not a [[particular set of pixels represents a picture of a bird]](https://explainxkcd.com/1425/).

One of the main criticisms of neural networks is that, while they do seem to ''work'', it is nearly impossible to examine the step-by-step process an actual trained neural network goes through to turn a given input into a given output, since the logic used by the program is effectively a "black box" that is meaningful only to the computer itself. When traditional code gives wrong answers, a programmer can look at the code's source and analyze its path of logic to find the source of the error. When a neural network gives wrong answers, the only solution is to train the network more ("stir the pile") until the answers start looking right.

In the above example, one might create a neural network that is intended to analyze pictures, then give it thousands of pictures of birds of different species and taken from different angles, as well as thousands of pictures of things that are not birds, and tell it which are birds and which are not until the program figures out the pattern well enough to recognize pictures of birds on its own. However, even when the program works, it will not be possible to look at the code to understand ''how'' the program recognizes birds - it just ''does''. If it starts mistyping images, the only way to figure out what is wrong is to look at a possible bias of the training images - perhaps the images left out pictures of birds viewed from above, or those of a particular unusual color, or those making a particular pose. To fix it, it must be sent back to training.

==Transcript==

[Cueball Prime, holds a canoe paddle at his side and stands on top of a "big pile of linear algebra" containing a funnel labeled "data" and box labeled "answers". Cueball II stands to the left side of the panel.)]

Cueball II: This is your machine learning system?

Cueball Prime: Yup! You pour the data into this big pile of linear algebra, then collect the answers on the other side.

Cueball II: What if the answers are wrong?

Cueball Prime: Just stir the pile until they start looking right.

{{comic discussion}}

1838: Machine Learning

2017-05-21T18:40:04Z

IndigoFenix: /* Neural networks */

{{comic
| number = 1838
| date = May 17, 2017
| title = Machine Learning
| image = machine_learning.png
| titletext = The pile gets soaked with data and starts to get mushy over time, so it's technically recurrent.
}}

==Explanation==
{{incomplete|Work in progress. <s>This explanation is an attempt at {{w|design by committee|machine learning by committee}}.</s>}}

{{w|Machine learning}} is a method employed in automation of complex tasks. It usually involves creation of algorithms that deal with statistical analysis of data and pattern recognition to generate output. The validity/accuracy of the output can be used to give feedback to make changes to the system, usually making future results statistically better.

Pinball stands atop his machine learning system, which consists of a pile of mathematical functions with an input funnel (labelled "data") at one end, an output box (labelled "answers") at the other, and a whole mess of mathematical functions in between. As Pinball explains to the incredulous Cueball, data enters through the funnel, undergoes an incomprehensible process of linear algebra, and comes out as answers. Pinball appears to be a functional part of this system himself, as he stands atop the pile stirring it with a paddle. Pinball's machine learning system is probably very inefficient, as he is integral to both the mechanical part (repeated stirring) and the learning part (making the answers look "right").

The main joke is that, despite this description being too vague and giving no intuition or details into the system, it is close to the level of understanding most machine learning experts have of the most popular class of techniques in machine learning, namely support vector machines. 

====Composting====
This comic compares a machine learning system to a compost pile. {{w|Composting}} is the process of taking organic matter, such as food and yard waste, and allowing it to decompose into a form that serves as fertilizer. A common method of composting is to mound the organic matter in a pile with a certain amount of moisture, then "stirring" the pile occasionally to move the less-decomposed material from the top to the interior of the pile, where it will decompose faster.

In large-scale composting operations, the raw organic matter added to the pile is referred to as "input". This cartoon implies a play on the term "input", comparing a compost input to a data input.

====Machine learning====
''One of the most popular paradigms of machine learning is that of supervised learning, where a function mapping an input to an output is learned from several input-output pairs, e.g. a function mapping images of faces to people names, from a dataset of static labelled images. Classic machine learning techniques like regression, or logistic regression, have understandable parameters, and provable algorithms, but require significant engineering in the pre-processing step and don't perform very well for data like images or natural text. Deep learning techniques, on the other hand, require very little pre-processing, but require the data to be run through several steps of linear algebra, where essentially in each step the output of the previous step is multiplied with a matrix and sent to the the next step. This multi-step process has proven to be very successful for image and text data, but the structure of the parameters, arranged as a matrix for each step, allows for very little interpretation, and can only be described as "data going through a pile of linear algebra".''

The method of training such deep neural networks is via gradient descent, which can be viewed as "stirring the pile of linear algebra until the answers start looking right".

The title text refers to recurrent neural networks, which are a useful class of deep neural networks for dealing with sequence data like speech or text.

====Neural networks====
This comic satirizes machine learning, more specifically neural networks. In its most basic form, a neural network takes data and results and strengthens connections that give the right answer and weakens ones that don't, until the results "look right". Neural networks are extremely data-dependent, and make remarkably few guarantees when compared to most other computing techniques, thus the joke.

''Recently, other forms of neural networks, such as LSTMs, feed old sequence data back into the network with some delay, making it recurrent. The title text calls this the pile "getting mushy". The title text is also be a pun based on how Pinball is going through the data. Instead of using a shovel, he is using a canoe paddle. Canoes can be used on rivers, and rivers by definition have currents. Thus, a recurrent data could, in this situation, mean data treated as if it were part of a river.''

Neural networks are programs that attempt to emulate a living brain - unlike traditional code, where the logic is written by a human programmer, a neural network looks for patterns between particular sets of inputs and particular outputs, strengthening connections that lead to "right" answers. Beyond creating the initial parameters of the network, as well as its inputs and outputs, teaching a neural network is less like programming and more like "training" - continually feeding the computer input-output pairs until the computer "learns" how to turn an input into an output, creating its ''own'' logical path. Google uses neural networks, for instance, to analyze images and figure out their relationships to search terms.

One of the main criticisms of neural networks is that, while they do seem to ''work'', it is nearly impossible to examine the step-by-step process an actual trained neural network goes through to turn a given input into a given output, since the logic used by the program is effectively a "black box" that is meaningful only to the computer itself. When traditional code gives wrong answers, a programmer can look at the code's source and analyze its path of logic to find the source of the error. When a neural network gives wrong answers, the only solution is to train the network more ("stir the pile") until the answers start looking right.

==Transcript==

[Cueball Prime, holds a canoe paddle at his side and stands on top of a "big pile of linear algebra" containing a funnel labeled "data" and box labeled "answers". Cueball II stands to the left side of the panel.)]

Cueball II: This is your machine learning system?

Cueball Prime: Yup! You pour the data into this big pile of linear algebra, then collect the answers on the other side.

Cueball II: What if the answers are wrong?

Cueball Prime: Just stir the pile until they start looking right.

{{comic discussion}}

1838: Machine Learning

2017-05-21T18:32:46Z

IndigoFenix: /* Neural networks */

{{comic
| number = 1838
| date = May 17, 2017
| title = Machine Learning
| image = machine_learning.png
| titletext = The pile gets soaked with data and starts to get mushy over time, so it's technically recurrent.
}}

==Explanation==
{{incomplete|Work in progress. <s>This explanation is an attempt at {{w|design by committee|machine learning by committee}}.</s>}}

{{w|Machine learning}} is a method employed in automation of complex tasks. It usually involves creation of algorithms that deal with statistical analysis of data and pattern recognition to generate output. The validity/accuracy of the output can be used to give feedback to make changes to the system, usually making future results statistically better.

Pinball stands atop his machine learning system, which consists of a pile of mathematical functions with an input funnel (labelled "data") at one end, an output box (labelled "answers") at the other, and a whole mess of mathematical functions in between. As Pinball explains to the incredulous Cueball, data enters through the funnel, undergoes an incomprehensible process of linear algebra, and comes out as answers. Pinball appears to be a functional part of this system himself, as he stands atop the pile stirring it with a paddle. Pinball's machine learning system is probably very inefficient, as he is integral to both the mechanical part (repeated stirring) and the learning part (making the answers look "right").

The main joke is that, despite this description being too vague and giving no intuition or details into the system, it is close to the level of understanding most machine learning experts have of the most popular class of techniques in machine learning, namely support vector machines. 

====Composting====
This comic compares a machine learning system to a compost pile. {{w|Composting}} is the process of taking organic matter, such as food and yard waste, and allowing it to decompose into a form that serves as fertilizer. A common method of composting is to mound the organic matter in a pile with a certain amount of moisture, then "stirring" the pile occasionally to move the less-decomposed material from the top to the interior of the pile, where it will decompose faster.

In large-scale composting operations, the raw organic matter added to the pile is referred to as "input". This cartoon implies a play on the term "input", comparing a compost input to a data input.

====Machine learning====
''One of the most popular paradigms of machine learning is that of supervised learning, where a function mapping an input to an output is learned from several input-output pairs, e.g. a function mapping images of faces to people names, from a dataset of static labelled images. Classic machine learning techniques like regression, or logistic regression, have understandable parameters, and provable algorithms, but require significant engineering in the pre-processing step and don't perform very well for data like images or natural text. Deep learning techniques, on the other hand, require very little pre-processing, but require the data to be run through several steps of linear algebra, where essentially in each step the output of the previous step is multiplied with a matrix and sent to the the next step. This multi-step process has proven to be very successful for image and text data, but the structure of the parameters, arranged as a matrix for each step, allows for very little interpretation, and can only be described as "data going through a pile of linear algebra".''

The method of training such deep neural networks is via gradient descent, which can be viewed as "stirring the pile of linear algebra until the answers start looking right".

The title text refers to recurrent neural networks, which are a useful class of deep neural networks for dealing with sequence data like speech or text.

====Neural networks====
This comic satirizes machine learning, more specifically neural networks. In its most basic form, a neural network takes data and results and strengthens connections that give the right answer and weakens ones that don't, until the results "look right". Neural networks are extremely data-dependent, and make remarkably few guarantees when compared to most other computing techniques, thus the joke.

''Recently, other forms of neural networks, such as LSTMs, feed old sequence data back into the network with some delay, making it recurrent. The title text calls this the pile "getting mushy". The title text is also be a pun based on how Pinball is going through the data. Instead of using a shovel, he is using a canoe paddle. Canoes can be used on rivers, and rivers by definition have currents. Thus, a recurrent data could, in this situation, mean data treated as if it were part of a river.''

Neural networks are programs that attempt to emulate a living brain - unlike traditional code, which is written by a human programmer, a neural network looks for patterns between particular inputs and particular outputs, strengthening connections that lead to "right" answers. Beyond creating the initial parameters, inputs and outputs, teaching a neural network is less like programming and more like "training" - continually feeding the computer input-output pairs until the computer "learns" how to turn an input into an output. Google uses neural networks, for instance, to analyze images and figure out their relationships to search terms.

One of the main criticisms of neural networks is that, while they do seem to ''work'', it is nearly impossible to examine the step-by-step process a trained neural network goes through to turn a given input into a given output, since the learning process is effectively a "black box" that is meaningful only to the computer itself. When traditional code gives wrong answers, a programmer can look at the code's source and analyze its path of logic to find the source of the error. When a neural network gives wrong answers, the only solution is to train the network ("stir the pile") until the answers start looking right.

==Transcript==

[Cueball Prime, holds a canoe paddle at his side and stands on top of a "big pile of linear algebra" containing a funnel labeled "data" and box labeled "answers". Cueball II stands to the left side of the panel.)]

Cueball II: This is your machine learning system?

Cueball Prime: Yup! You pour the data into this big pile of linear algebra, then collect the answers on the other side.

Cueball II: What if the answers are wrong?

Cueball Prime: Just stir the pile until they start looking right.

{{comic discussion}}

1838: Machine Learning

2017-05-21T18:28:58Z

IndigoFenix:

{{comic
| number = 1838
| date = May 17, 2017
| title = Machine Learning
| image = machine_learning.png
| titletext = The pile gets soaked with data and starts to get mushy over time, so it's technically recurrent.
}}

==Explanation==
{{incomplete|Work in progress. <s>This explanation is an attempt at {{w|design by committee|machine learning by committee}}.</s>}}

{{w|Machine learning}} is a method employed in automation of complex tasks. It usually involves creation of algorithms that deal with statistical analysis of data and pattern recognition to generate output. The validity/accuracy of the output can be used to give feedback to make changes to the system, usually making future results statistically better.

Pinball stands atop his machine learning system, which consists of a pile of mathematical functions with an input funnel (labelled "data") at one end, an output box (labelled "answers") at the other, and a whole mess of mathematical functions in between. As Pinball explains to the incredulous Cueball, data enters through the funnel, undergoes an incomprehensible process of linear algebra, and comes out as answers. Pinball appears to be a functional part of this system himself, as he stands atop the pile stirring it with a paddle. Pinball's machine learning system is probably very inefficient, as he is integral to both the mechanical part (repeated stirring) and the learning part (making the answers look "right").

The main joke is that, despite this description being too vague and giving no intuition or details into the system, it is close to the level of understanding most machine learning experts have of the most popular class of techniques in machine learning, namely support vector machines. 

====Composting====
This comic compares a machine learning system to a compost pile. {{w|Composting}} is the process of taking organic matter, such as food and yard waste, and allowing it to decompose into a form that serves as fertilizer. A common method of composting is to mound the organic matter in a pile with a certain amount of moisture, then "stirring" the pile occasionally to move the less-decomposed material from the top to the interior of the pile, where it will decompose faster.

In large-scale composting operations, the raw organic matter added to the pile is referred to as "input". This cartoon implies a play on the term "input", comparing a compost input to a data input.

====Machine learning====
''One of the most popular paradigms of machine learning is that of supervised learning, where a function mapping an input to an output is learned from several input-output pairs, e.g. a function mapping images of faces to people names, from a dataset of static labelled images. Classic machine learning techniques like regression, or logistic regression, have understandable parameters, and provable algorithms, but require significant engineering in the pre-processing step and don't perform very well for data like images or natural text. Deep learning techniques, on the other hand, require very little pre-processing, but require the data to be run through several steps of linear algebra, where essentially in each step the output of the previous step is multiplied with a matrix and sent to the the next step. This multi-step process has proven to be very successful for image and text data, but the structure of the parameters, arranged as a matrix for each step, allows for very little interpretation, and can only be described as "data going through a pile of linear algebra".''

The method of training such deep neural networks is via gradient descent, which can be viewed as "stirring the pile of linear algebra until the answers start looking right".

The title text refers to recurrent neural networks, which are a useful class of deep neural networks for dealing with sequence data like speech or text.

====Neural networks====
This comic satirizes machine learning, more specifically neural networks. In its most basic form, a neural network takes data and results and strengthens connections that give the right answer and weakens ones that don't, until the results "look right". Neural networks are extremely data-dependent, and make remarkably few guarantees when compared to most other computing techniques, thus the joke.

''Recently, other forms of neural networks, such as LSTMs, feed old sequence data back into the network with some delay, making it recurrent. The title text calls this the pile "getting mushy". The title text is also be a pun based on how Pinball is going through the data. Instead of using a shovel, he is using a canoe paddle. Canoes can be used on rivers, and rivers by definition have currents. Thus, a recurrent data could, in this situation, mean data treated as if it were part of a river.''

Neural networks are programs that attempt to emulate a living brain - unlike traditional code, which is written by a human programmer, a neural network looks for patterns between particular inputs and particular outputs, strengthening connections that lead to "right" answers. Beyond creating the initial parameters, inputs and outputs, teaching a neural network is less like programming and more like "training" - continually feeding the computer input-output pairs until the computer "learns" how to turn an input into an output. Google uses neural networks, for instance, to figure out relationships between different search terms by analyzing the links users are likely to click after entering a search term.

One of the main criticisms of neural networks is that, while they do seem to ''work'', it is nearly impossible to examine the step-by-step process a trained neural network goes through to turn a given input into a given output, since the learning process is effectively a "black box" that is meaningful only to the computer itself. When traditional code gives wrong answers, a programmer can look at the code's source and analyze its path of logic to find the source of the error. When a neural network gives wrong answers, the only solution is to train the network ("stir the pile") until the answers start looking right.

==Transcript==

[Cueball Prime, holds a canoe paddle at his side and stands on top of a "big pile of linear algebra" containing a funnel labeled "data" and box labeled "answers". Cueball II stands to the left side of the panel.)]

Cueball II: This is your machine learning system?

Cueball Prime: Yup! You pour the data into this big pile of linear algebra, then collect the answers on the other side.

Cueball II: What if the answers are wrong?

Cueball Prime: Just stir the pile until they start looking right.

{{comic discussion}}

Talk:1787: Voice Commands

2017-01-21T18:31:20Z

IndigoFenix:

http://wbic16.xedoloh.com/dvorak.html converts "svat ussupd ;dlh a kdbk" to "okay google send a text"--[[Special:Contributions/162.158.75.10|162.158.75.10]] 16:38, 18 January 2017 (UTC)
:Well that's a much easier way of converting it than my method of looking at two keyboards. [[Special:Contributions/162.158.255.58|162.158.255.58]] 16:42, 18 January 2017 (UTC)

:I think that's just for US keyboards. I get different results trying that on a UK QWERTY keyboard [[User:Jdluk|Jdluk]] ([[User talk:Jdluk|talk]]) 16:56, 18 January 2017 (UTC)

:The opposite way of typing QWERTY on Dvorak gives the even less pronounceable "RTAF IRRIN. O.BE A Y.QY". –''TisTheAlmondTavern'', 12:38, 19 January 2017 (UTC)

The QWERTY layout is to slow typists down is an enduring myth. In the early days there were typing competitions (with big prizes) to find the fastest typist and fastest machine. This was won by QWERTY in the English world and AZERTY in the French one. Other languages may vary.

The avoid a clash reason (as users of manual machines know) is shown up by the common Left Right Left sequence of "the" and the many letter pairs in English of "er" which are adjacent left fingers and often caused me jams!

Other layouts and designs may have benefits, but will never become the default - a bit like Esperanto methinks ;-) [[User:RIIW - Ponder it|RIIW - Ponder it]] ([[User talk:RIIW - Ponder it|talk]]) 18:31, 18 January 2017 (UTC)

: "In the early days" typewriters would jam easily, so ''of course'' a layout that for the most part avoided that would be fastest way back then. Just because the layout ''still'' had jamming problems doesn't mean it wouldn't come out on top. Touchtyping (a more recent development than QWERTY) makes QWERTY uncomfortable to use at speed, but the pretty much random nature of the layout makes life easier for spell checking software (a more recent development than Dvorak) than Dvorak. [[Special:Contributions/198.41.238.16|198.41.238.16]] 23:43, 18 January 2017 (UTC)

* It's not really a contradiction. The QWERTY layout was not to ''slow down'' typists exactly, but to reduce the likelihood of a typist hitting two ''adjacent'' keys in quick succession, since this is what caused jams. To do this, it placed letters that are frequently found next to each other in different parts of the keyboard. However, this is ''also'' more efficient, because it causes the typist to frequently switch hands with each key press, giving the unused hand a chance to move into position for the next key, and makes typos less frequent. Try to quickly type "western" (mostly the left hand) and then try to quickly type "landing" (alternating hands).

I have only typed Dvorak since 1991, currently on a TypeMatrix 2030DV. Since I have pretty much forgotten Qwerty, I had to look at my wife's laptop to find the letters. Back and forth looking at the comic, it took me a minute to translate that in Notepad. ;-) I can do about 90 wpm in DV. Friends don't let friends type Qwerty!
[[User:TrueFalcon|TrueFalcon]] ([[User talk:TrueFalcon|talk]]) 17:10, 18 January 2017 (UTC)
* Dvorak? pfft. I use butterflies [[Special:Contributions/108.162.245.160|108.162.245.160]] 23:52, 18 January 2017 (UTC)
* As a fellow Dvorak user, I think comments like these are the reason we keep getting comics about us. [[Special:Contributions/162.158.69.177|162.158.69.177]] 18:03, 18 January 2017 (UTC)
** I can practically guarantee it. Especially since actual studies on the subject suggest it's more ability and practice that improve typing speed rather than what layout is used. --[[User:KingStarscream|KingStarscream]] ([[User talk:KingStarscream|talk]]) 20:16, 18 January 2017 (UTC)
** Case in point: I wasn't born until 1988 so I have less experience than OP, but I type about 100 WPM in QWERTY. What does that say about Dvorak? --[[User:PsyMar|PsyMar]] ([[User talk:PsyMar|talk]]) 03:06, 20 January 2017 (UTC)
** Yeah, I hit roughly 80 or 85 at my best in Dvorak, but it's only because I couldn't type Qwerty at all. I switched so I would have to stop looking at the keys when I typed, and that's the only benefit it's ever actually afforded me, aside from potentially averting some wrist strain when I write a lot in short time periods. [[Special:Contributions/162.158.69.177|162.158.69.177]] 13:28, 20 January 2017 (UTC)

The hovertext should say "vocal cords," right? Not "chords"? [[Special:Contributions/173.245.50.222|173.245.50.222]] 18:20, 18 January 2017 (UTC)

: I've heard there ''are'' people who can sing more than one note at a time - a real vocal chord. [[Special:Contributions/198.41.238.16|198.41.238.16]] 23:47, 18 January 2017 (UTC)

:I suppose it might be a deliberate error, but, yes, "vocal chords" is incorrect: it should be "vocal cords" (i.e. strings), or even more correctly [https://en.wikipedia.org/wiki/Vocal_folds vocal folds]. [[Special:Contributions/141.101.99.173|141.101.99.173]] 09:27, 19 January 2017 (UTC)

: A stenograph (as used by a court stenographer) is a keyboard where one presses several keys at a time, called a chord, so I think the hover text 'vocal chord' is a play on the idea of vocalising several 'keys' at once --[[Special:Contributions/141.101.107.126|141.101.107.126]] 13:01, 19 January 2017 (UTC)

: The OED lists "chord" as a variant of "cord" for anatomical purposes. Both are allowable and neither is unusual. https://en.oxforddictionaries.com/definition/chord [[Special:Contributions/108.162.219.106|108.162.219.106]] 18:48, 20 January 2017 (UTC)

The layout was intended to reduce jams, and was likely a trial and error process in development. The layout does in effect slow down the people of the day some, as for instance so many words are typed by left hand only, but this is likely unintentional. Notice that keys like the "I" and "O" are "together", but in fact are separated by three other key linkages, "K""," and "9", so pressing those didn't cause a jam as frequently when pressed in rapid succession, but nevertheless would have been faster had they been on opposite sides of the keyboard. Another point is that keyboarding was still visual at the time, so this keyboard mechanism never took into account the touch typing method that was developed a decade or so later. [[Special:Contributions/172.68.38.10|172.68.38.10]] 19:27, 18 January 2017 (UTC)

Is this an appropriate time to mention the advantages of MessageEase? No? Nevermind then. {{unsigned ip|162.158.114.82}}

I enjoyed MessageEase until I discovered Multiling O. It’s much more customizable. [[Special:Contributions/108.162.245.172|108.162.245.172]] 22:33, 19 January 2017 (UTC)

Bah. Everyone knows saying it in the original Klingon is much more efficient. --[[Special:Contributions/108.162.238.11|108.162.238.11]] 14:18, 19 January 2017 (UTC)

Can we remove that last paragraph? It seems irrelevant to the explanation - as do a few other interludes that seem to only contribute to the opinions of the authors.
[[Special:Contributions/162.158.214.82|162.158.214.82]] 14:55, 19 January 2017 (UTC)
: It would be safer to say which paragraph you mean, or multiple people might follow your suggestion and remove multiple paragraphs --[[User:OliReading|OliReading]] ([[User talk:OliReading|talk]]) 00:18, 20 January 2017 (UTC)

Please don't use the abomination "substituted with." That's what people used when they can't decide whether A is substituted for B or replaced with B, so they split the difference. [[User:Gmcgath|Gmcgath]] ([[User talk:Gmcgath|talk]]) 12:35, 20 January 2017 (UTC)