title: Orcas Island

text: The name "Orcas" is a shortened form of "Horcasitas," from Juan Vicente de Güemes Padilla Horcasitas y Aguayo, 2nd Count of Revillagigedo, the Viceroy of New Spain who sent an exploration expedition under Francisco de Eliza to the Pacific Northwest in 1791. During the voyage, Eliza explored part of the San Juan Islands. He did not apply the name Orcas specifically to Orcas Island, but rather to part of the archipelago. In 1847, Henry Kellett assigned the name to Orcas Island during his reorganization of the British Admiralty charts. Kellett's work eliminated the patriotically American names that Charles Wilkes had given to many features of the San Juans during the Wilkes Expedition of 1838–1842. Wilkes had named Orcas Island "Hull Island" after Commodore Isaac Hull. Other features of Orcas Island Wilkes named include "Ironsides Inlet" for East Sound and "Guerrier Bay" for West Sound. One of the names Wilkes gave remains: Mount Constitution. Wilkes's names follow a pattern: Hull was the commander of "Old Ironsides" (the ) and won fame after capturing the British warship HMS "Guerriere" in the War of 1812. The islands were first claimed by Spain, then by Britain, who agreed that everything below the 49th parallel was part of the US, in the treaty signed after the War of 1812. The Oregon territory, which then included Washington state and this island, was used jointly by the US and Britain until 1848, but border disputes specifically concerning the San Juan Islands, including the Pig War (1859), were not settled until 1871. The similarity to the name of the orca, which is popularly associated with coastal Washington state, is coincidental.


title: Orcas Island

text: With an area of 57.3 square miles (148.4 km²) and a population of 5,387 (2010 census), Orcas Island is slightly larger, but less populous, than neighboring San Juan Island. It is shaped like a pair of saddlebags, separated by fjord-like Eastsound, and two prominent bays, Westsound and Deer Harbor, on the southwest side. At the island's northern end is the village of Eastsound, the largest population center on Orcas and the second largest in San Juan County.


title: Orcas Island

text: Other, smaller hamlets on the island include Orcas Landing (where the inter-island/mainland ferry lands), West Sound (with Eastsound addresses), Deer Harbor, Rosario (with Eastsound addresses), Olga and Doe Bay. A number of former settlements no longer exist, which were mostly built up around the lime kiln and fruit growing industries.


title: Orcas Island

text: The state supports island access through the Washington State Ferries system. In addition, the island can be accessed through a variety of air, seaplane and sea charter services. Private watercraft can use public docks located near the villages around the island, and various public shoreline access points. During the summer season, there is an island shuttle van that runs from the ferry landing to Eastsound and other points.


title: Orcas Island

text: The Orcas Island School District operates three schools on a single campus: Orcas Island Elementary School housed in the island's historic Nellie S. Milton school building; Orcas Island Middle School; and Orcas Island High School. All of the island's public schools are located in Eastsound.


title: Orcas Island

text: The Orcas Island Public Library is located in Eastsound and serves a population of approximately 6,000 card holders. The Orcas Island Library District is a junior-taxing district that funds the Orcas Island Public Library's operating budget through property taxes. The annual Library Fair sells books donated by Orcas Island residents and visitors, the proceeds of which are donated back to the Library's operating budget.


title: Orcas Island

text: In 2018 Orcas Island Voters approved the creation of San Juan County Public Hospital District #3 (OIHCD) and later elected five Commissioners to the board. OIHCD funds local health care services ensuring care services to locals.


title: Orcas Island

text: The Village Green is located in the center of Eastsound village. The Village Green, with an expansive lawn and shade trees, picnic tables and outdoor performance stage, is the site of community gatherings, music performances, and the weekly farmer’s market.


title: Orcas Island

text: Buck Park is located just north of the school on Mt. Baker Road. The park includes a world-class skateboard park, tennis courts, pickleball courts, baseball/softball and ultimate frisbee fields, soccer pitch, sand volleyball court, a fenced dog off-leash area, a new state-of-the-art running track, and the hub to an network of running trails and walking paths through the Eastsound area.


title: Orcas Island

text: Mount Constitution (elevation 2409 feet/734 meters) is the highest point in the San Juan islands. The mountain is part of Moran State Park, the largest public recreation area in the San Juan Islands, and the largest State Park in Washington. Moran State Park encompasses over 5,000 acres (2,000 ha) of woodland and has several lakes, including Cascade Lake, Mountain Lake, Summit Lake, and Twin Lakes, and numerous waterfalls.


title: Orcas Island

text: Obstruction Pass State Park is an 76-acre park with access to more than a mile of public saltwater shoreline on the south end of Orcas Island, south of Moran State Park.


title: Orcas Island

text: Madrona Point is a traditional burial ground which was controversially sold by the Cemetery Association in 1890. In 1989, the site was purchased out of private ownership for $2.2 million from the Department of the Interior and returned to the Lummi Nation. The tribe agreed to manage the property as an open space open to individuals and groups under a memorandum of understanding with San Juan County. However, the Lummi Nation closed the site in 2007 citing disrespect to the land.


title: Valles Marineris

text: Valles Marineris (; Latin for "Mariner Valleys", named after the "Mariner 9" Mars orbiter of 1971–72 which discovered it) is a system of canyons that runs along the Martian surface east of the Tharsis region. At more than long, wide and up to deep, Valles Marineris is one of the largest canyons of the Solar System, surpassed in length only by the rift valleys of the mid-ocean ridge system of Earth.


title: Valles Marineris

text: Valles Marineris is located along the equator of Mars, on the east side of the Tharsis Bulge, and stretches for nearly a quarter of the planet's circumference. The canyon system starts in the west with Noctis Labyrinthus; proceeding to the east are Tithonium and Ius chasmata, then Melas, Candor and Ophir chasmata, then Coprates Chasma, then Ganges, Capri and Eos chasmata; finally it empties into an outflow channel region containing chaotic terrain that ends in the basin of Chryse Planitia.


title: Valles Marineris

text: It has been recently suggested that Valles Marineris is a large tectonic "crack" in the Martian crust. Most researchers agree that this formed as the crust thickened in the Tharsis region to the west, and was subsequently widened by erosion. Near the eastern flanks of the rift, there appear to be channels that may have been formed by water or carbon dioxide. It has also been proposed that Valles Marineris is a large channel formed by the erosion of lava flowing from the flank of Pavonis Mons.


title: Valles Marineris

text: Theories about the formation of Valles Marineris have changed over the years. Ideas in the 1970s were erosion by water or thermokarst activity, which is the melting of permafrost in glacial climes. Thermokarst activity may have contributed, but erosion by water is a problematic mechanism because liquid water cannot exist in most current Martian surface conditions, which typically experience about 1% of Earth's atmospheric pressure and a temperature range of to . Many scientists however agree that liquid water flowed on the Martian surface in the past, when atmospheric conditions were different. Valles Marineris may have been enlarged by flowing water at that time. Another hypothesis by McCauley in 1972 was that the canyons formed by withdrawal of subsurface magma. Around 1989, a theory of formation by tensional fracturing was proposed. The most agreed upon theory today is that Valles Marineris was formed by rift faults like the East African Rift, later made bigger by erosion and collapsing of the rift walls. It has also been proposed that Valles Marineris was formed by flowing lava.


title: Valles Marineris

text: The formation of Valles Marineris is thought to be closely tied with the formation of the Tharsis Bulge. The Tharsis Bulge was formed from the Noachian to Late Hesperian period of Mars, in three stages. The first stage consisted of a combination of volcanism and isostatic uplift; soon, however, the volcanism loaded the crust to a point at which the crust could no longer support the added weight of Tharsis, leading to widespread graben formation in the elevated regions of Tharsis. Stage two consisted of more volcanism and a loss of isostatic equilibrium; the source regions of the volcanism no longer resided underneath Tharsis, creating a very large load. Finally, the crust failed to hold up Tharsis and radial fractures formed, including at Valles Marineris. Stage three mainly consisted of more volcanism and asteroid impacts. The crust, having already reached its failure point, just stayed in place and younger volcanoes formed. Tharsis volcanism involved very low viscosity magma, forming shield volcanoes similar to those of the Hawaiian Island chain, but, because there is minor or no current active plate tectonics on Mars, the hotspot activity led to very long histories of repeated volcanic eruptions at the same spots, creating some of the largest volcanoes in the solar system, including the biggest, Olympus Mons.


title: Valles Marineris

text: Landslides have left numerous deposits on the floor of Valles Marineris and contributed to widening it. Possible triggers of landslides are quakes caused by tectonic activity or impact events. Both types of events release seismic waves that accelerate the ground at and below the surface. Mars is much less tectonically active than Earth, and marsquakes are unlikely to have provided seismic waves of the required magnitude. Most sizable craters on Mars date to the Late Heavy Bombardment, 4.1 to 3.8 billion years ago (the Noachian period), and are older than the landslide deposits in Valles Marineris. However, three craters (including the crater Oudemans) have been identified, on the basis of their proximity and later dates, as ones whose formation may have caused some of the landslides.


title: Valles Marineris

text: Noctis Labyrinthus, on the western edge of the Valles Marineris Rift System, north of the Syria Planum and east of Pavonis Mons, is a jumbled terrain composed of huge blocks which are heavily fractured. It also contains canyons that run in different directions surrounding large blocks of older terrain. Most of the upper parts of the blocks are composed of younger fractured material thought to be of volcanic origin associated with the Tharsis bulge. The other tops are composed of older fractured material thought also to be volcanic in origin, but differentiated from the younger material by more ruggedness and more impact craters. The sides of the blocks are composed of undivided material thought to be basement rock. The space between the blocks is composed mainly of either rough or smooth floor material. The rough floor material tends to be in the eastern portion of the Noctis Labyrinthus and is thought to be debris from the walls or maybe eolian features covering rough topography and landslides. The smooth floor material is thought to be composed of fluvial or basaltic material and/or eolian features covering an otherwise rough and jumbled terrain. Terrains such as Noctis Labyrinthus are commonly found at the head of outflow channels, like the one explored by the Pathfinder mission and its Sojourner rover. They are interpreted to be a place of downward block faulting associated with the removal of ground fluid in catastrophic flood sequences. The fluid could be either carbon-dioxide ice and gas, water or lava. The hypothesis of lava involvement is associated with a proposal that Noctis Labyrinthus is directly connected to lava tubes on the slope of Pavonis Mons.


title: Valles Marineris

text: Further to the east from Oudemans, Ius and Tithonium chasmata are located parallel to each other, Ius to the south and Tithonium to the north. Ius is the wider of the two, leading to Melas Chasma. Ius has a ridge down the center of it by the name of Geryon Montes, composed of the undivided basement rock. The floor of Ius Chasma is mostly composed of pristine landslide material, not much degraded by cratering or erosion. The southern wall of Ius, and to a lesser extent the northern wall, has many short valleys stretching off roughly perpendicular to the line of the chasmas. These valleys have a stubby theater-headed leading edge very much like features seen on the Colorado Plateau near the Grand Canyon that appear from groundwater sapping. (Theater-headed means that, from above, the head of the valley is a well-defined U-shape). The valley is propagated by the continued erosion and the collapse of the wall. Tithonium Chasma is very similar to Ius, except it is lacking the sapping features on the south side and contains a small portion of material that is similar to the smooth floor features except that it appears to be an ash fall that has been eroded by the wind. Between the two canyons, the surface is composed of younger fractured material - lava flows and faults from crustal extension of the Tharsis Bulge.


title: Valles Marineris

text: The next portion of Valles Marineris to the east are three chasmata, that from south to north are Melas, Candor and Ophir chasmata. Melas is east of Ius, Candor is east of Tithonium and Ophir appears as an oval that runs into Candor. All three chasmata are connected. The floor of Melas Chasma is about 70% younger massive material that is thought to be volcanic ash whipped up by the wind into eolian features. It also contains rough floor material from the erosion of the canyon walls. Also, in these central chasmata there is a portion of the floor that is higher than the rest of the floor, most likely left by the continued dropping of the other floor material. Around the edges of Melas is also a lot of slide material as seen in Ius and Tithonium chasmata.


title: Valles Marineris

text: The material of the floor of the canyon system between Candor and Melas chasmata is grooved. This is interpreted to be alluvial deposits and/or material that has collapsed or contracted by the removal of ice or water. There are also portions of older and younger massive floor material of volcaniclastic origin - only separated in age by crater distribution. Also there is etched massive floor material that is like the younger and older massive material except that it has wind erosion features on it. There are also a few spires of undivided material composed of the same material as the canyon walls.


title: Valles Marineris

text: Further to the east, the canyon system runs into Coprates Chasma, which is very similar to Ius and Tithonium chasmata. Coprates differs from Ius in the eastern end which contains alluvial deposits and eolian material and like Ius, has layered deposits, although the deposits in the Coprates Chasma are much more well defined. These deposits pre-date the Valles Marineris system, suggesting erosion and sedimentary processes later cut by the Valles Marineris system. Newer data from Mars Global Surveyor suggest that the origin of this layering is either just a succession of landslides, one over another, volcanic in origin, or it may be the bottom of a basin of either liquid or solid water ice suggesting that the peripheral canyons of the Valles Marineris system could have been at one time isolated lakes formed from erosional collapse. Another possible source of the layered deposits could be wind-blown, but the diversity of the layers suggests that this material is not dominant. Note that only the upper layers are thin, while the bottom layers are very big, suggesting that the lower layers were composed of mass wasted rock and the upper layers come from another source. Some of this layering may have been transferred to the floor by landslides in which the layers are kept semi-intact, yet the layered section looks highly deformed with thickening and thinning beds that have multitudes of folds in them as seen in MOC image #8405. This complex terrain could also be just eroded sediment from an ancient Martian lake-bed and appear complex because all that we have is an aerial view like a geologic map and not enough elevation data to see if the beds are horizontal.


title: Valles Marineris

text: Near 60° W is the deepest point of the Valles Marineris system (as well as its lowest point by elevation) at below the surrounding plateau. Eastward from here there is about a 0.03 degree slope upward before reaching the outflow channels, which means that if you poured fluid into this part of the canyon, it would form a lake with a depth of before spilling over towards the northern plains.


title: Valles Marineris

text: A field of more than 100 pitted cones on the floor of Coprates Chasma has been interpreted as a set of small igneous cinder or tuff cones, with associated lava flows. Crater dating indicates they are of Middle to Late Amazonian age, about 200 to 400 million years old.


title: Valles Marineris

text: Further to the east lie Eos and Ganges chasmata. Eos Chasma's western floor is mainly composed of an etched massive material composed of either volcanic or eolian deposits later eroded by the Martian wind. The eastern end of the Eos chasma has a large area of streamlined bars and longitudinal striations. This is interpreted to be stream-carved plateau deposits and material transported and deposited by flowing fluid. Ganges Chasma is an offshoot chasma of Eos in a general east–west trend. The floor of Ganges is mainly composed of alluvial deposits from the canyon walls.


title: Valles Marineris

text: East of Eos and Ganges, Valles Marineris empties out into the Chryse region of the northern plains of Mars at an elevation only above the deepest point of Valles Marineris in Melas Chasma. The outflow regions of the northern plains are similar to the terrain seen at the Mars Pathfinder landing site. A terrestrial counterpart of these outflow channels on Earth would be the scablands of eastern Washington. The eastern Washington scablands are a result of repeated catastrophic flooding due to the build-up of an ice dam at the head of Lake Missoula in the Late Pleistocene. The ice dam would block the water for a while, but when it broke, the ice would float on top of the ensuing flood and vast areas would be stripped of topsoil and vegetation, leaving a large barren area of 'teardrop' islands, longitudinal grooves and terraced margins. Many of these features are also seen in Martian outflow channels, but on a larger scale.


title: Valles Marineris

text: The outflow occurs successively through several regions of chaotic terrain, Aurorae Chaos and Hydraotes Chaos, and finally through Simud Valles and Tiu Valles into Chryse Planitia.


title: Bogatyr

text: A bogatyr () or vityaz () is a stock character in medieval East Slavic legends, akin to a Western European knight-errant. Bogatyrs appear mainly in Rus' epic poems—"bylinas". Historically, they came into existence during the reign of Vladimir the Great (Grand Prince of Kiev from 980 to 1015) as part of his elite warriors ("druzhina"), akin to Knights of the Round Table. Tradition describes bogatyrs as warriors of immense strength, courage and bravery, rarely using magic while fighting enemies in order to maintain the "loosely based on historical fact" aspect of bylinas. They are characterized as having resounding voices, with patriotic and religious pursuits, defending Rus' from foreign enemies (especially nomadic Turkic steppe-peoples or Finno-Ugric tribes in the period prior to the Mongol invasions) and their religion. In modern Russian, the word "bogatyr" labels a courageous hero, an athlete or a physically strong man.


title: Bogatyr

text: Its first element is most likely the Indo-Iranian "bhaga" "god, lord" (c.f. bey). A suggestion cited in the "Brockhaus and Efron Encyclopedic Dictionary" derives the word from Sanskrit "baghadhara". Alternatively, Gerard Clauson suggests that "bağatur" was in origin a Hunnic proper name, specifically that of Modu Chanyu.


title: Bogatyr

text: Despite the linguistic research of modern scholars, popular etymology associates the word "bogatyr" with .


title: Bogatyr

text: The first known use of the word in a Russian context occurred in Stanisław Sarnicki's book "Descriptio veteris et novae Poloniae cum divisione ejusdem veteri et nova" ("A description of the Old and the New Poland with the old, and a new division of the same"), printed in 1585 in Cracow (at Aleksy Rodecki's printing house), which states: "Rossi ... de heroibus suis, quos Bohatiros id est semideos vocant, aliis persuadere conantur." ("Russians ... try to convince others about their heroes whom they call Bogatirs, meaning demigods.")


title: Bogatyr

text: The term "vityaz"' comes from Proto-Slavic "*vitędzь", from Proto-Germanic *"wikinga" through a West Germanic intermediary. The earliest attested form is Old English "wicing", "pirate", whence modern English viking. This in turn probably comes from Latin "vicus" with the Germanic suffix "*-inga-", indicating belonging. In Germanic and Latin sources, the word has negative connotations. The circumstances of borrowing, and how it came to mean "hero" in Slavic, remain unclear.


title: Bogatyr

text: Many Rus epic poems, called Bylinas, prominently featured stories about these heroes, as did several chronicles, including the 13th century Galician–Volhynian Chronicle. Some bogatyrs are presumed to be historical figures, while others, like the giant Svyatogor, are purely fictional and possibly descend from Slavic pagan mythology. The epic poems are usually divided into three collections: the Mythological epics, older stories that were told before Kiev-Rus was founded and Christianity was brought to the region, and included magic and the supernatural; the Kievan cycle, that contains the largest number of bogatyrs and their stories (IIya Muromets, Dobrynya Nikitich, and Aloysha Popovich); and the Novgorod cycle, focused on Sadko and Vasily Buslayev, that depicts everyday life in Novgorod.


title: Bogatyr

text: Many of the stories about bogatyrs revolve around the court of Vladimir I of Kiev (958–1015) and are called the Kievan Cycle. The most notable bogatyrs or vityazes served at his court: the trio of Alyosha Popovich, Dobrynya Nikitich and Ilya Muromets. Each of them tends to be known for a certain character trait: Alyosha Popovich for his wits, Dobrynya Nikitich for his courage, and Ilya Muromets for his physical and spiritual power and integrity, and for his dedication to the protection of his homeland and people. Most of those bogatyrs adventures are fictional, and often included fighting dragons, giants and other mythical creatures. However, the bogatyrs themselves were often based on real people. Historical prototypes of both Dobrynya Nikitich (the warlord Dobrynya) and Ilya Muromets are proven to have existed.


title: Bogatyr

text: The Novgorod Republic produced a specific kind of hero, an adventurer rather than a noble warrior. The most prominent examples were Sadko and Vasily Buslayev who became part of the Novgorod Cycle of folk epics.


title: Bogatyr

text: Mythological epics rooted in the supernatural and shamanism, and related to paganism. The most prominent heroes in these epics are Svyatogor and Volkh Vseslavyevich; they are commonly called the "Elder Bogatyrs".


title: Bogatyr

text: Later notable bogatyrs also include those who fought by Alexander Nevsky's side, including Vasily Buslayev and those who fought in the Battle of Kulikovo.


title: Bogatyr

text: Bogatyrs and their heroic tales have influenced many figures in Russian Literature and Art, such Alexander Pushkin, who wrote the 1820 epic fairy tale poem Ruslan and Ludmila, Victor Vasnetsov, and Andrei Ryabushkin whose artworks depict many bogatyrs from the different cycles of folk epics. Bogatyrs are also mentioned in wonder tales in a more playful light as in Foma Berennikov, a story in Aleksandr Afanas'ev's collection of tales called "Russian Fairy Tales" featuring Alyosha Popovich and Ilya Muromets.


title: Bogatyr

text: Red Medusa Animation Studio, based in Russia, created an animated parody of the bogatyrs called "Three Russian Bogaturs," in which the titular characters—strong and tenacious, but not overly bright—prevail against various opponents from fairy tales, pop culture, and modern life.


title: Bogatyr

text: Though not as heavily researched, the female bogatyr or () is a female warrior akin to the Amazons. Many of the more well-known polianitsas are wives to the famous male bogatyrs, such as Nastas'ya Nikulichna, the wife of Dobrynya Nikitich. The female bogatyr matches the men in strength and bravery with stories detailing instances where they save their husbands and outwit the enemy. They are often seen working with the heroes in tales that mention their presence.


title: Caprice Crane

text: Caprice Alexandra Crane (born November 1, 1970, in Hollywood, California) is an American novelist, screenwriter and television writer/producer.


title: Caprice Crane

text: Crane was born in Los Angeles, California, the daughter of radio announcer/television talk show host Les Crane and actress Tina Louise. After she graduated from New York University (NYU) Tisch School of the Arts Film School, MTV hired her to write, produce and music supervise game shows, sports shows, music specials and the MTV Video Music Awards.


title: Caprice Crane

text: Her first novel's title, "Stupid & Contagious" (2006), is taken from the lyrics of the Nirvana song, "Smells Like Teen Spirit." Her second novel, "Forget About It" (2007), was once rumored to be made into a New Line Cinema motion picture starring Scarlett Johansson. Both her first and second books won "Romantic Times" Reader's Choice Awards, two years in a row, in the Mainstream Fiction Chick Lit category.


title: Caprice Crane

text: Her third novel, "Family Affair", was released in October 2009. Her fourth novel, "With a Little Luck," was published on July 26, 2011, by Bantam Books. Crane wrote the original screenplay for the 2011 film "Love, Wedding, Marriage" starring Mandy Moore and Kellan Lutz. Crane's debut young adult novel "Confessions of a Hater" was released in August 2013 with critical praise from "The New York Times". In 2016, Crane co-authored the book "Esther the Wonder Pig: Changing the World One Heart at a Time", published May 31, 2016. "Esther The Wonder Pig" was a "New York Times" Best Seller.


title: Caprice Crane

text: Crane has also worked in staff positions as a writer for TV shows such as CW's "90210" and "Melrose Place". She had a TV pilot based on her novel "Stupid & Contagious" in development for NBC. Crane divides her time between New York and Los Angeles.


title: Machine translation

text: Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another.


title: Machine translation

text: On a basic level, MT performs mechanical substitution of words in one language for words in another, but that alone rarely produces a good translation because recognition of whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalent words in another language, and many words have more than one meaning.


title: Machine translation

text: Solving this problem with corpus statistical and neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies.


title: Machine translation

text: Current machine translation software often allows for customization by domain or profession (such as weather reports), improving output by limiting the scope of allowable substitutions. This technique is particularly effective in domains where formal or formulaic language is used. It follows that machine translation of government and legal documents more readily produces usable output than machine translation of conversation or less standardised text.


title: Machine translation

text: Improved output quality can also be achieved by human intervention: for example, some systems are able to translate more accurately if the user has unambiguously identified which words in the text are proper names. With the assistance of these techniques, MT has proven useful as a tool to assist human translators and, in a very limited number of cases, can even produce output that can be used as is (e.g., weather reports).


title: Machine translation

text: The progress and potential of machine translation have been much debated through its history. Since the 1950s, a number of scholars, first and most notably Yehoshua Bar-Hillel, have questioned the possibility of achieving fully automatic machine translation of high quality.


title: Machine translation

text: The origins of machine translation can be traced back to the work of Al-Kindi, a ninth-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation. The idea of machine translation later appeared in the 17th century. In 1629, René Descartes proposed a universal language, with equivalent ideas in different tongues sharing one symbol.


title: Machine translation

text: The idea of using digital computers for translation of natural languages was proposed as early as 1946 by England's A. D. Booth and Warren Weaver at Rockefeller Foundation at the same time. "The memorandum written by Warren Weaver in 1949 is


title: Machine translation

text: perhaps the single most influential publication in the earliest days of machine translation." Others followed. A demonstration was made in 1954 on the APEXC machine at Birkbeck College (University of London) of a rudimentary translation of English into French. Several papers on the topic were published at the time, and even articles in popular journals (for example an article by Cleave and Zacharov in the September 1955 issue of "Wireless World"). A similar application, also pioneered at Birkbeck College at the time, was reading and composing Braille texts by computer.


title: Machine translation

text: The first researcher in the field, Yehoshua Bar-Hillel, began his research at MIT (1951). A Georgetown University MT research team, led by Professor Michael Zarechnak, followed (1951) with a public demonstration of its Georgetown-IBM experiment system in 1954. MT research programs popped up in Japan and Russia (1955), and the first MT conference was held in London (1956).


title: Machine translation

text: David G. Hays "wrote about computer-assisted language processing as early as 1957" and "was project leader on computational linguistics


title: Machine translation

text: Researchers continued to join the field as the Association for Machine Translation and Computational Linguistics was formed in the U.S. (1962) and the National Academy of Sciences formed the Automatic Language Processing Advisory Committee (ALPAC) to study MT (1964). Real progress was much slower, however, and after the ALPAC report (1966), which found that the ten-year-long research had failed to fulfill expectations, funding was greatly reduced. According to a 1972 report by the Director of Defense Research and Engineering (DDR&E), the feasibility of large-scale MT was reestablished by the success of the Logos MT system in translating military manuals into Vietnamese during that conflict.


title: Machine translation

text: The French Textile Institute also used MT to translate abstracts from and into French, English, German and Spanish (1970); Brigham Young University started a project to translate Mormon texts by automated translation (1971).


title: Machine translation

text: SYSTRAN, which "pioneered the field under contracts from the U.S. government" in the 1960s, was used by Xerox to translate technical manuals (1978). Beginning in the late 1980s, as computational power increased and became less expensive, more interest was shown in statistical models for machine translation. MT became more popular after the advent of computers. SYSTRAN's first implementation system was implemented in 1988 by the online service of the French Postal Service called Minitel. Various computer based translation companies were also launched, including Trados (1984), which was the first to develop and market Translation Memory technology (1989), though this is not the same as MT. The first commercial MT system for Russian / English / German-Ukrainian was developed at Kharkov State University (1991).


title: Machine translation

text: By 1998, "for as little as $29.95" one could "buy a program for translating in one direction between English and a major European language of


title: Machine translation

text: MT on the web started with SYSTRAN offering free translation of small texts (1996) and then providing this via AltaVista Babelfish, which racked up 500,000 requests a day (1997). The second free translation service on the web was Lernout & Hauspie's GlobaLink. "Atlantic Magazine" wrote in 1998 that "Systran's Babelfish and GlobaLink's Comprende" handled


title: Machine translation

text: Franz Josef Och (the future head of Translation Development AT Google) won DARPA's speed MT competition (2003). More innovations during this time included MOSES, the open-source statistical MT engine (2007), a text/SMS translation service for mobiles in Japan (2008), and a mobile phone with built-in speech-to-speech translation functionality for English, Japanese and Chinese (2009). In 2012, Google announced that Google Translate translates roughly enough text to fill 1 million books in one day.


title: Machine translation

text: Behind this ostensibly simple procedure lies a complex cognitive operation. To decode the meaning of the source text in its entirety, the translator must interpret and analyse all the features of the text, a process that requires in-depth knowledge of the grammar, semantics, syntax, idioms, etc., of the source language, as well as the culture of its speakers. The translator needs the same in-depth knowledge to re-encode the meaning in the target language.


title: Machine translation

text: Therein lies the challenge in machine translation: how to program a computer that will "understand" a text as a person does, and that will "create" a new text in the target language that sounds as if it has been written by a person. Unless aided by a 'knowledge base' MT provides only a general, though imperfect, approximation of the original text, getting the "gist" of it (a process called "gisting"). This is sufficient for many purposes, including making best use of the finite and expensive time of a human translator, reserved for those cases in which total accuracy is indispensable.


title: Machine translation

text: Machine translation can use a method based on linguistic rules, which means that words will be translated in a linguistic way – the most suitable (orally speaking) words of the target language will replace the ones in the source language.


title: Machine translation

text: It is often argued that the success of machine translation requires the problem of natural language understanding to be solved first.


title: Machine translation

text: Generally, rule-based methods parse a text, usually creating an intermediary, symbolic representation, from which the text in the target language is generated. According to the nature of the intermediary representation, an approach is described as interlingual machine translation or transfer-based machine translation. These methods require extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules.


title: Machine translation

text: Given enough data, machine translation programs often work well enough for a native speaker of one language to get the approximate meaning of what is written by the other native speaker. The difficulty is getting enough data of the right kind to support the particular method. For example, the large multilingual corpus of data needed for statistical methods to work is not necessary for the grammar-based methods. But then, the grammar methods need a skilled linguist to carefully design the grammar that they use.


title: Machine translation

text: To translate between closely related languages, the technique referred to as rule-based machine translation may be used.


title: Machine translation

text: The rule-based machine translation paradigm includes transfer-based machine translation, interlingual machine translation and dictionary-based machine translation paradigms. This type of translation is used mostly in the creation of dictionaries and grammar programs. Unlike other methods, RBMT involves more information about the linguistics of the source and target languages, using the morphological and syntactic rules and semantic analysis of both languages. The basic approach involves linking the structure of the input sentence with the structure of the output sentence using a parser and an analyzer for the source language, a generator for the target language, and a transfer lexicon for the actual translation. RBMT's biggest downfall is that everything must be made explicit: orthographical variation and erroneous input must be made part of the source language analyser in order to cope with it, and lexical selection rules must be written for all instances of ambiguity. Adapting to new domains in itself is not that hard, as the core grammar is the same across domains, and the domain-specific adjustment is limited to lexical selection adjustment.


title: Machine translation

text: Transfer-based machine translation is similar to interlingual machine translation in that it creates a translation from an intermediate representation that simulates the meaning of the original sentence. Unlike interlingual MT, it depends partially on the language pair involved in the translation.


title: Machine translation

text: Interlingual machine translation is one instance of rule-based machine-translation approaches. In this approach, the source language, i.e. the text to be translated, is transformed into an interlingual language, i.e. a "language neutral" representation that is independent of any language. The target language is then generated out of the interlingua. One of the major advantages of this system is that the interlingua becomes more valuable as the number of target languages it can be turned into increases. However, the only interlingual machine translation system that has been made operational at the commercial level is the KANT system (Nyberg and Mitamura, 1992), which is designed to translate Caterpillar Technical English (CTE) into other languages.


title: Machine translation

text: Machine translation can use a method based on dictionary entries, which means that the words will be translated as they are by a dictionary.


title: Machine translation

text: Statistical machine translation tries to generate translations using statistical methods based on bilingual text corpora, such as the Canadian Hansard corpus, the English-French record of the Canadian parliament and EUROPARL, the record of the European Parliament. Where such corpora are available, good results can be achieved translating similar texts, but such corpora are still rare for many language pairs. The first statistical machine translation software was CANDIDE from IBM. Google used SYSTRAN for several years, but switched to a statistical translation method in October 2007. In 2005, Google improved its internal translation capabilities by using approximately 200 billion words from United Nations materials to train their system; translation accuracy improved. Google Translate and similar statistical translation programs work by detecting patterns in hundreds of millions of documents that have previously been translated by humans and making intelligent guesses based on the findings. Generally, the more human-translated documents available in a given language, the more likely it is that the translation will be of good quality. Newer approaches into Statistical Machine translation such as METIS II and PRESEMT use minimal corpus size and instead focus on derivation of syntactic structure through pattern recognition. With further development, this may allow statistical machine translation to operate off of a monolingual text corpus. SMT's biggest downfall includes it being dependent upon huge amounts of parallel texts, its problems with morphology-rich languages (especially with translating "into" such languages), and its inability to correct singleton errors.


title: Machine translation

text: Example-based machine translation (EBMT) approach was proposed by Makoto Nagao in 1984. Example-based machine translation is based on the idea of analogy. In this approach, the corpus that is used is one that contains texts that have already been translated. Given a sentence that is to be translated, sentences from this corpus are selected that contain similar sub-sentential components. The similar sentences are then used to translate the sub-sentential components of the original sentence into the target language, and these phrases are put together to form a complete translation.


title: Machine translation

text: Hybrid machine translation (HMT) leverages the strengths of statistical and rule-based translation methodologies. Several MT organizations claim a hybrid approach that uses both rules and statistics. The approaches differ in a number of ways:


title: Machine translation

text: More recently, with the advent of Neural MT, a new version of hybrid machine translation is emerging that combines the benefits of rules, statistical and neural machine translation. The approach allows benefitting from pre- and post-processing in a rule guided workflow as well as benefitting from NMT and SMT. The downside is the inherent complexity which makes the approach suitable only for specific use cases.


title: Machine translation

text: A deep learning-based approach to MT, neural machine translation has made rapid progress in recent years, and Google has announced its translation services are now using this technology in preference over its previous statistical methods. A Microsoft team claimed to have reached human parity on WMT-2017 ("EMNLP 2017


title: Machine translation

text: However, many researchers have criticized this claim, rerunning and discussing their experiments; current consensus is that the so-called human parity achieved is not real, being based wholly on limited domains, language pairs, and certain test suites i.e., it lacks statistical significance power. There is still a long journey before NMT reaches real human parity performances.


title: Machine translation

text: To address the idiomatic phrase translation, multi-word expressions, and low-frequency words (also called OOV, or out-of-vocabulary word translation), language-focused linguistic features have been explored in state-of-the-art neural machine translation (NMT) models. For instance, the Chinese character decompositions into radicals and strokes have proven to be helpful for translating multi-word expressions in NMT.


title: Machine translation

text: Word-sense disambiguation concerns finding a suitable translation when a word can have more than one meaning. The problem was first raised in the 1950s by Yehoshua Bar-Hillel. He pointed out that without a "universal encyclopedia", a machine would never be able to distinguish between the two meanings of a word. Today there are numerous approaches designed to overcome this problem. They can be approximately divided into "shallow" approaches and "deep" approaches.


title: Machine translation

text: Shallow approaches assume no knowledge of the text. They simply apply statistical methods to the words surrounding the ambiguous word. Deep approaches presume a comprehensive knowledge of the word. So far, shallow approaches have been more successful.


title: Machine translation

text: Claude Piron, a long-time translator for the United Nations and the World Health Organization, wrote that machine translation, at its best, automates the easier part of a translator's job; the harder and more time-consuming part usually involves doing extensive research to resolve ambiguities in the source text, which the grammatical and lexical exigencies of the target language require to be resolved:


title: Machine translation

text: The ideal deep approach would require the translation software to do all the research necessary for this kind of disambiguation on its own; but this would require a higher degree of AI than has yet been attained. A shallow approach which simply guessed at the sense of the ambiguous English phrase that Piron mentions (based, perhaps, on which kind of prisoner-of-war camp is more often mentioned in a given corpus) would have a reasonable chance of guessing wrong fairly often. A shallow approach that involves "ask the user about each ambiguity" would, by Piron's estimate, only automate about 25% of a professional translator's job, leaving the harder 75% still to be done by a human.


title: Machine translation

text: One of the major pitfalls of MT is its inability to translate non-standard language with the same accuracy as standard language. Heuristic or statistical based MT takes input from various sources in standard form of a language. Rule-based translation, by nature, does not include common non-standard usages. This causes errors in translation from a vernacular source or into colloquial language. Limitations on translation from casual speech present issues in the use of machine translation in mobile devices.


title: Machine translation

text: In information extraction, named entities, in a narrow sense, refer to concrete or abstract entities in the real world such as people, organizations, companies, and places that have a proper name: George Washington, Chicago, Microsoft. It also refers to expressions of time, space and quantity such as 1 July 2011, $500.


title: Machine translation

text: In the sentence "Smith is the president of Fabrionix" both "Smith" and "Fabrionix" are named entities, and can be further qualified via first name or other information; "president" is not, since Smith could have earlier held another position at Fabrionix, e.g. Vice President.


title: Machine translation

text: The term rigid designator is what defines these usages for analysis in statistical machine translation.


title: Machine translation

text: Named entities must first be identified in the text; if not, they may be erroneously translated as common nouns, which would most likely not affect the BLEU rating of the translation but would change the text's human readability. They may be omitted from the output translation, which would also have implications for the text's readability and message.


title: Machine translation

text: Transliteration includes finding the letters in the target language that most closely correspond to the name in the source language. This, however, has been cited as sometimes worsening the quality of translation. For "Southern California" the first word should be translated directly, while the second word should be transliterated. Machines often transliterate both because they treated them as one entity. Words like these are hard for machine translators, even those with a transliteration component, to process.


title: Machine translation

text: Use of a "do-not-translate" list, which has the same end goal – transliteration as opposed to translation. still relies on correct identification of named entities.


title: Machine translation

text: A third approach is a class-based model. Named entities are replaced with a token to represent their "class"; "Ted" and "Erica" would both be replaced with "person" class token. Then the statistical distribution and use of person names, in general, can be analyzed instead of looking at the distributions of "Ted" and "Erica" individually, so that the probability of a given name in a specific language will not affect the assigned probability of a translation. A study by Stanford on improving this area of translation gives the examples that different probabilities will be assigned to "David is going for a walk" and "Ankit is going for a walk" for English as a target language due to the different number of occurrences for each name in the training data. A frustrating outcome of the same study by Stanford (and other attempts to improve named recognition translation) is that many times, a decrease in the BLEU scores for translation will result from the inclusion of methods for named entity translation.


title: Machine translation

text: Some work has been done in the utilization of multiparallel corpora, that is a body of text that has been translated into 3 or more languages. Using these methods, a text that has been translated into 2 or more languages may be utilized in combination to provide a more accurate translation into a third language compared with if just one of those source languages were used alone.


title: Machine translation

text: An ontology is a formal representation of knowledge that includes the concepts (such as objects, processes etc.) in a domain and some relations between them. If the stored information is of linguistic nature, one can speak of a lexicon.


title: Machine translation

text: In NLP, ontologies can be used as a source of knowledge for machine translation systems. With access to a large knowledge base, systems can be enabled to resolve many (especially lexical) ambiguities on their own.


title: Machine translation

text: In the following classic examples, as humans, we are able to interpret the prepositional phrase according to the context because we use our world knowledge, stored in our lexicons:


title: Machine translation

text: A machine translation system initially would not be able to differentiate between the meanings because syntax does not change. With a large enough ontology as a source of knowledge however, the possible interpretations of ambiguous words in a specific context can be reduced.


title: Machine translation

text: Other areas of usage for ontologies within NLP include information retrieval, information extraction and text summarization.


title: Machine translation

text: The ontology generated for the PANGLOSS knowledge-based machine translation system in 1993 may serve as an example of how an ontology for NLP purposes can be compiled:


title: Machine translation

text: While no system provides the holy grail of fully automatic high-quality machine translation of unrestricted text, many fully automated systems produce reasonable output. The quality of machine translation is substantially improved if the domain is restricted and controlled.


title: Machine translation

text: Despite their inherent limitations, MT programs are used around the world. Probably the largest institutional user is the European Commission. The project, for example, coordinated by the University of Gothenburg, received more than 2.375 million euros project support from the EU to create a reliable translation tool that covers a majority of the EU languages. The further development of MT systems comes at a time when budget cuts in human translation may increase the EU's dependency on reliable MT programs. The European Commission contributed 3.072 million euros (via its ISA programme) for the creation of MT@EC, a statistical machine translation program tailored to the administrative needs of the EU, to replace a previous rule-based machine translation system.


title: Machine translation

text: In 2005, Google claimed that promising results were obtained using a proprietary statistical machine translation engine. The statistical translation engine used in the Google language tools for Arabic <-> English and Chinese <-> English had an overall score of 0.4281 over the runner-up IBM's BLEU-4 score of 0.3954 (Summer 2006) in tests conducted by the National Institute for Standards and Technology.


title: Machine translation

text: With the recent focus on terrorism, the military sources in the United States have been investing significant amounts of money in natural language engineering. "In-Q-Tel" (a venture capital fund, largely funded by the US Intelligence Community, to stimulate new technologies through private sector entrepreneurs) brought up companies like Language Weaver. Currently the military community is interested in translation and processing of languages like Arabic, Pashto, and Dari. Within these languages, the focus is on key phrases and quick communication between military members and civilians through the use of mobile phone apps. The Information Processing Technology Office in DARPA hosts programs like TIDES and Babylon translator. US Air Force has awarded a $1 million contract to develop a language translation technology.


title: Machine translation

text: The notable rise of social networking on the web in recent years has created yet another niche for the application of machine translation software – in utilities such as Facebook, or instant messaging clients such as Skype, GoogleTalk, MSN Messenger, etc. – allowing users speaking different languages to communicate with each other. Machine translation applications have also been released for most mobile devices, including mobile telephones, pocket PCs, PDAs, etc. Due to their portability, such instruments have come to be designated as mobile translation tools enabling mobile business networking between partners speaking different languages, or facilitating both foreign language learning and unaccompanied traveling to foreign countries without the need of the intermediation of a human translator.


title: Machine translation

text: Despite being labelled as an unworthy competitor to human translation in 1966 by the Automated Language Processing Advisory Committee put together by the United States government, the quality of machine translation has now been improved to such levels that its application in online collaboration and in the medical field are being investigated. The application of this technology in medical settings where human translators are absent is another topic of research, but difficulties arise due to the importance of accurate translations in medical diagnoses.


title: Machine translation

text: Flaws in machine translation have also been noted for their entertainment value. Two videos uploaded to YouTube in April 2017 involve two Japanese hiragana characters えぐ ("e" and "gu") being repeatedly pasted into Google Translate, with the resulting translations quickly degrading into nonsensical phrases such as "DECEARING EGG" and "Deep-sea squeeze trees", which are then read in increasingly absurd voices; the full-length version of the video currently has 6.9 million views as of March 2022.


title: Machine translation

text: There are many factors that affect how machine translation systems are evaluated. These factors include the intended use of the translation, the nature of the machine translation software, and the nature of the translation process.


title: Machine translation

text: Different programs may work well for different purposes. For example, statistical machine translation (SMT) typically outperforms example-based machine translation (EBMT), but researchers found that when evaluating English to French translation, EBMT performs better. The same concept applies for technical documents, which can be more easily translated by SMT because of their formal language.


title: Machine translation

text: In certain applications, however, e.g., product descriptions written in a controlled language, a dictionary-based machine-translation system has produced satisfactory translations that require no human intervention save for quality inspection.


title: Machine translation

text: There are various means for evaluating the output quality of machine translation systems. The oldest is the use of human judges to assess a translation's quality. Even though human evaluation is time-consuming, it is still the most reliable method to compare different systems such as rule-based and statistical systems. Automated means of evaluation include BLEU, NIST, METEOR, and LEPOR.


title: Machine translation

text: Relying exclusively on unedited machine translation ignores the fact that communication in human language is context-embedded and that it takes a person to comprehend the context of the original text with a reasonable degree of probability. It is certainly true that even purely human-generated translations are prone to error. Therefore, to ensure that a machine-generated translation will be useful to a human being and that publishable-quality translation is achieved, such translations must be reviewed and edited by a human. The late Claude Piron wrote that machine translation, at its best, automates the easier part of a translator's job; the harder and more time-consuming part usually involves doing extensive research to resolve ambiguities in the source text, which the grammatical and lexical exigencies of the target language require to be resolved. Such research is a necessary prelude to the pre-editing necessary in order to provide input for machine-translation software such that the output will not be meaningless.


title: Machine translation

text: In addition to disambiguation problems, decreased accuracy can occur due to varying levels of training data for machine translating programs. Both example-based and statistical machine translation rely on a vast array of real example sentences as a base for translation, and when too many or too few sentences are analyzed accuracy is jeopardized. Researchers found that when a program is trained on 203,529 sentence pairings, accuracy actually decreases. The optimal level of training data seems to be just over 100,000 sentences, possibly because as training data increases, the number of possible sentences increases, making it harder to find an exact translation match.


title: Machine translation

text: Although there have been concerns about machine translation's accuracy, Dr. Ana Nino of the University of Manchester has researched some of the advantages in utilizing machine translation in the classroom. One such pedagogical method is called using "MT as a Bad Model." MT as a Bad Model forces the language learner to identify inconsistencies or incorrect aspects of a translation; in turn, the individual will (hopefully) possess a better grasp of the language. Dr. Nino cites that this teaching tool was implemented in the late 1980s. At the end of various semesters, Dr. Nino was able to obtain survey results from students who had used MT as a Bad Model (as well as other models.) Overwhelmingly, students felt that they had observed improved comprehension, lexical retrieval, and increased confidence in their target language.


title: Machine translation

text: In the early 2000s, options for machine translation between spoken and signed languages were severely limited. It was a common belief that deaf individuals could use traditional translators. However, stress, intonation, pitch, and timing are conveyed much differently in spoken languages compared to signed languages. Therefore, a deaf individual may misinterpret or become confused about the meaning of written text that is based on a spoken language.


title: Machine translation

text: Researchers Zhao, et al. (2000), developed a prototype called TEAM (translation from English to ASL by machine) that completed English to American Sign Language (ASL) translations. The program would first analyze the syntactic, grammatical, and morphological aspects of the English text. Following this step, the program accessed a sign synthesizer, which acted as a dictionary for ASL. This synthesizer housed the process one must follow to complete ASL signs, as well as the meanings of these signs. Once the entire text is analyzed and the signs necessary to complete the translation are located in the synthesizer, a computer generated human appeared and would use ASL to sign the English text to the user.


title: Machine translation

text: Only works that are original are subject to copyright protection, so some scholars claim that machine translation results are not entitled to copyright protection because MT does not involve creativity. The copyright at issue is for a derivative work; the author of the original work in the original language does not lose his rights when a work is translated: a translator must have permission to publish a translation.


title: Gilmore Girls (season 1)

text: The first season of "Gilmore Girls", an American dramedy television series, began airing on October 5, 2000 on The WB. The season concluded on May 10, 2001, after 21 episodes. The season originally aired on Thursdays at 8 pm ET before "Charmed".


title: Gilmore Girls (season 1)

text: The show was first announced for pick-up by The WB for the 2000–2001 season on May 16, 2000, a month after the original filming of the pilot episode in April in the Toronto suburb of Unionville. On March 20, 2001, The WB announced that the show was renewed for a second season.


title: Gilmore Girls (season 1)

text: The first season of Gilmore Girls introduces Lorelai Gilmore (Lauren Graham) and her sixteen-year-old daughter, Rory (Alexis Bledel), as well as the fictional Connecticut town of Stars Hollow and its many quirky inhabitants. The central plot point of the season is Rory's acceptance to Chilton, an elite prep school, and Lorelai's need to borrow money from her parents, Emily (Kelly Bishop) and Richard (Edward Herrmann), in order to fund her daughter's education. Lorelai's parents lend her the money, but on one condition: she and Rory must attend dinner at their home in nearby Hartford every Friday night until the loan is repaid.


title: Gilmore Girls (season 1)

text: Lorelai's relationship with her parents is full of animosity. Not long after giving birth to Rory as a teenager, at the age of 16, she left her parents’ home and moved to Stars Hollow to prevent them from imposing their privileged lifestyle on her daughter. Although still loving her a great deal, her parents continue to resent her for this choice. This results in a significant portion of the conflict throughout the season as Lorelai deals with having her parents in her life on a regular basis for the first time since she was a teenager. It also leads to Lorelai feeling distressed by Rory's positive relationship with her grandparents and obvious interest in their way of life.


title: Gilmore Girls (season 1)

text: In the pilot episode, Rory meets Dean Forester (Jared Padalecki), a new student at Stars Hollow High School who has a crush on her. As the season progresses, she grows to have feelings for him, and they begin dating. Their relationship is briefly interrupted after Dean breaks up with her for not knowing how to respond to his stating that he loves her. Rory professes her love for Dean in the season finale, and they resume their relationship.


title: Gilmore Girls (season 1)

text: The season shows Rory as having strong friendships with both longtime friend Lane Kim (Keiko Agena) and fellow Chilton student Paris Geller (Liza Weil). She has been friends with Lane for over a decade, and the two remain close even when Rory changes schools. When Rory first arrives at Chilton, her relationship with Paris is more that of enemies than friends. However, as the season progresses, the two grow closer, eventually forming a begrudging friendship.


title: Gilmore Girls (season 1)

text: Lorelai has no love interest when the series begins, but she soon develops feelings for Rory's English teacher at Chilton, Max Medina (Scott Cohen). They date for several episodes, but break up when Lorelai begins to feel uncomfortable about how accepting Rory is of having Max in their lives. There is a clear attraction between her and Luke Danes (Scott Patterson), the owner of the local diner, but nothing ever comes of it. Lorelai also briefly reunites with Rory's father, Christopher (David Sutcliffe), but turns him down when he asks her to marry him. Lorelai and Max reunite toward the end of the season, and he proposes in the season finale.


title: Gilmore Girls (season 1)

text: Lorelai is close friends with Sookie St. James (Melissa McCarthy), the chef at the inn she manages. The two plan to eventually open their own inn together.


title: Gilmore Girls (season 1)

text: The season was produced by Warner Bros., Amy Sherman-Palladino and Gavin Polone and was aired on the WB Network in the United States. The series was created by Amy Sherman-Palladino, who acted as an executive producer. Sherman-Palladino served as the seasons show runner.


title: John Joubert (serial killer)

text: John Joseph Joubert IV (July 2, 1963 – July 17, 1996) was an American serial killer executed in Nebraska. He was convicted of murdering three boys in Maine and Nebraska.


title: John Joubert (serial killer)

text: Joubert's parents divorced when he was six years old, he lived with his mother in Lawrence, Massachusetts. He was not allowed to visit his father and grew to hate his controlling mother. In 1974, she moved the family to Portland, Maine.


title: John Joubert (serial killer)

text: In 1971, Joubert's mother moved them out of their former house into a rundown apartment. At this time, he was considered an outcast at school, and sought to compensate for these feelings of isolation by joining the Cub Scouts. It was around this time that his sadistic and homicidal fantasies progressed to the point where he contemplated murdering strangers on the streets, tying and gagging those who resisted him. In one later psychiatric report, he was described as saying that he derived pleasure from the thought of his victims saying "if you are going to do it, get it over with."


title: John Joubert (serial killer)

text: When he was 13, he stabbed a young girl with a pencil and felt sexually stimulated when she cried in pain. The next day, he took a razor blade and slashed another girl as he biked past her. He was never caught for either attack. In another incident, he beat and nearly strangled another boy. He relished the power of bullying, and began to stab or slash others.


title: John Joubert (serial killer)

text: On August 22, 1982, 11-year-old Richard "Ricky" Stetson left home to go jogging on the 3.5 mile long Back Cove Trail in Portland, Maine. When he did not return by dark, his parents called the police. The next day, a motorist discovered the boy's body on the side of Interstate 295. The attacker had attempted to undress him, then stabbed, strangled and bit him. A suspect was arrested for the murder but his teeth did not match the bite mark on Stetson's body, so he was released after a year and a half in custody. No additional leads presented themselves in the case until January 1984.


title: John Joubert (serial killer)

text: Danny Joe Eberle, 13 years old, disappeared while delivering the "Omaha World-Herald" newspaper on Sunday, September 18, 1983, in Bellevue, Nebraska. His brother, who also delivered papers, had not seen him, but he did remember being followed by a white man in a tan car on previous days. It was ascertained that Eberle had delivered only three of the 70 newspapers on his route. At the address of his fourth delivery, his bicycle was discovered along with the rest of the newspapers. There appeared to be no sign of a struggle. Joubert would later describe how he had approached Eberle, drawn a knife, and covered the boy's mouth with his hand. He instructed Eberle to follow him to his truck and drove him to a gravel road outside the town.


title: John Joubert (serial killer)

text: After a three-day search, Eberle's body was discovered in a patch of high grass alongside a gravel road some from his bicycle. He had been stripped to his underwear, his feet and hands had been bound, and his mouth had been sealed with surgical tape. Knife wounds across his body suggested he had been tortured before death. In addition, Joubert had stabbed him nine times. As a kidnapping, the crime came under the jurisdiction of the federal government of the United States, so the FBI was called in.


title: John Joubert (serial killer)

text: The investigation followed several leads, including a young man who was arrested for molesting two young boys approximately a week after the crime. He failed a polygraph test and had a false alibi, but did not fit the profile the FBI had created for the murderer. He was released due to a lack of evidence. Other known pedophiles in the area were questioned, but the case became cold due to a lack of evidence.


title: John Joubert (serial killer)

text: On December 2, 1983, Christopher Walden, age 12, disappeared in Papillion, Nebraska, approximately from where Eberle's body had been found. Witnesses again said they saw a white man in a tan car. Joubert said that he had driven up to Walden as he walked, showed him the sheath of his knife and ordered him into the car.


title: John Joubert (serial killer)

text: After driving to some railway lines out of town, he ordered Walden to strip to his underwear, which he did, but then Walden refused to lie down. After a brief struggle, Joubert overpowered and then stabbed him. Joubert cut Walden's throat so deeply that he had almost been decapitated. Walden's body was found two days later, from the town. Although the crimes were similar, there were differences. Walden had not been bound, had been better concealed, and was thought to have been killed immediately after being abducted.


title: John Joubert (serial killer)

text: On January 11, 1984, a preschool teacher in the area of the murders called police to say that she had seen a young man driving in the area. There are conflicting stories as to what had occurred — whether the car was loitering or just driving around. When the driver saw the teacher writing down his license plate, he stopped and threatened her before fleeing. The car was not tan, but was traced and found to be rented by John Joubert, an enlisted radar technician from Offutt Air Force Base. It turned out that his own car, a tan Chevrolet Nova sedan, was being repaired.


title: John Joubert (serial killer)

text: A search warrant was issued, and rope consistent with that used to bind Danny Joe Eberle was found in his barracks room. The FBI found that the unusual rope had been made for the United States military in South Korea. Under interrogation, Joubert admitted obtaining it from the scoutmaster in the troop in which he was an assistant.


title: John Joubert (serial killer)

text: Robert K. Ressler, the FBI's head profiler at the time, had access to the information about the two boys in Nebraska and worked up a hypothetical description which matched Joubert in every regard. While presenting the case of the two Nebraska boys to a training class at the FBI academy at Quantico, a police officer from Portland, Maine, observed the similarities to a case in his jurisdiction which took place while Joubert had lived there prior to joining the Air Force. Bite mark comparisons proved that Joubert was responsible for the Maine killing in addition to those in Nebraska. Ressler and the Maine investigators came to believe that Joubert joined the military to get away from Maine after the murder of the Stetson boy.


title: John Joubert (serial killer)

text: Further investigation in Maine revealed two crimes between the pencil stabbing of the nine-year-old girl in 1979 and the murder of Stetson in 1982. In 1980, Ressler's investigation revealed that Joubert had slashed a nine-year-old boy and a female teacher in her mid-twenties who both "had been cut rather badly, and were lucky to be alive."


title: John Joubert (serial killer)

text: Joubert then confessed to killing the two boys and, on January 12, was charged with their murders. After initially pleading not guilty, he changed his plea to guilty. There were several psychiatric evaluations performed on Joubert. One characterized him as having obsessive-compulsive disorder, sadistic tendencies, and schizoid personality disorder.


title: John Joubert (serial killer)

text: He was found to have not been psychotic at the time of the crimes. A panel of three judges sentenced him to death for both counts. Joubert was also sentenced to life imprisonment in Maine (which did not have the death penalty) in 1990 for the murder of Ricky Stetson after Joubert's teeth were found to match the bite mark.


title: John Joubert (serial killer)

text: In 1995, Joubert filed a writ of habeas corpus to the United States federal courts over the death sentences. His lawyers argued that the aggravating factor of "exceptional depravity" was unconstitutionally vague. The court agreed and the state of Nebraska appealed to the United States District Court for the District of Nebraska. They overturned the appeal, saying that he had shown sadistic behavior by torturing Eberle and Walden.


title: John Joubert (serial killer)

text: Joubert was executed on July 17, 1996, by the state of Nebraska in the electric chair. He was the second person executed in Nebraska since the death penalty was reintroduced in the state in 1973. Before his execution, Joubert made a final statement in which he apologized for the murders, saying "I just want to say that again I am sorry for what I have done. I do not know if my death will change anything or if it will bring anyone peace. And I just ask the families of Danny Eberle and Christopher Walden and Richard Stetson to please try to find some peace and ask the people of Nebraska to forgive me. That's all." His last meal consisted of pizza with green peppers and onions, strawberry cheesecake and black coffee.


title: John Joubert (serial killer)

text: An appeal to the Nebraska Supreme Court over whether the electric chair in Nebraska is a cruel and unusual punishment revealed that during his execution, Joubert suffered a four-inch brain blister on the top of his head and blistering on both sides of his head above his ears.


title: History of globalization

text: The historical origins of globalization (also known as historical globalization) are the subject of ongoing debate. Though many scholars situate the origins of globalization in the modern era (around the 19th century), others regard it as a phenomenon with a long history, dating back thousands of years (a concept known as archaic globalization). The period in the history of globalization roughly spanning the years between 1600 and 1800 is in turn known as the proto-globalization.


title: History of globalization

text: Perhaps the extreme proponent of a deep historical origin for globalization was Andre Gunder Frank, an economist associated with dependency theory. Frank argued that a form of globalization has been in existence since the rise of trade links between Sumer and the Indus Valley civilization in the third millennium BC. Critics of this idea contend that it rests upon an over-broad definition of globalization.


title: History of globalization

text: Thomas L. Friedman divides the history of globalization into three periods: Globalization 1.0 (1492–1800), Globalization 2.0 (1800–2000) and Globalization 3.0 (2000–present). He states that Globalization 1.0 involved the globalization of countries, Globalization 2.0 involved the globalization of companies and Globalization 3.0 involves the globalization of individuals.


title: History of globalization

text: Even as early as the Prehistoric period, the roots of modern globalization could be found. Territorial expansion by our ancestors to all five continents was a critical component in establishing globalization. The development of agriculture furthered globalization by converting the vast majority of the world's population into a settled lifestyle. However, globalization failed to accelerate due to lack of long-distance interaction and technology. The contemporary process of globalization likely occurred around the middle of the 19th century as increased capital and labor mobility coupled with decreased transport costs led to a smaller world.


title: History of globalization

text: An early form of globalized economics and culture, known as archaic globalization, existed during the Hellenistic Age, when commercialized urban centers were focused around the axis of Greek culture over a wide range that stretched from India to Spain, with such cities as Alexandria, Athens, and Antioch at its center. Trade was widespread during that period, and it is the first time the idea of a cosmopolitan culture (from Greek "Cosmopolis", meaning "world city") emerged. Others have perceived an early form of globalization in the trade links between the Roman Empire, the Parthian Empire, and the Han Dynasty. The increasing articulation of commercial links between these powers inspired the development of the Silk Road, which started in western China, reached the boundaries of the Parthian empire, and continued onwards towards Rome.


title: History of globalization

text: The Islamic Golden Age was also an important early stage of globalization, when Jewish and Muslim traders and explorers established a sustained economy across the Old World resulting in a globalization of crops, trade, knowledge and technology. Globally significant crops such as sugar and cotton became widely cultivated across the Muslim world in this period, while the necessity of learning Arabic and completing the Hajj created a cosmopolitan culture.


title: History of globalization

text: The advent of the Mongol Empire, though destabilizing to the commercial centers of the Middle East and China, greatly facilitated travel along the Silk Road. This permitted travelers and missionaries such as Marco Polo to journey successfully (and profitably) from one end of Eurasia to the other. The Pax Mongolica of the thirteenth century had several other notable globalizing effects. It witnessed the creation of the first international postal service, as well as the rapid transmission of epidemic diseases such as bubonic plague across the newly unified regions of Central Asia. These pre-modern phases of global or hemispheric exchange are sometimes known as archaic globalization. Up to the sixteenth century, however, even the largest systems of international exchange were limited to the Old World.


title: History of globalization

text: The phase is known as proto-globalization. It was characterized by the rise of maritime European empires, in the 15th, 16th and 17th centuries, first the Portuguese and Spanish Empires, and later the Dutch and British Empires. In the 17th century, globalization became also a private business phenomenon when chartered companies like British East India Company (founded in 1600), often described as the first multinational corporation, as well as the Dutch East India Company (founded in 1602) were established.


title: History of globalization

text: The Age of Discovery brought a broad change in globalization, being the first period in which Eurasia and Africa engaged in substantial cultural, material and biologic exchange with the New World. It began in the late 15th century, when the two Kingdoms of the Iberian Peninsula – Portugal and Castile – sent the first exploratory voyages around the Cape of Good Hope and to the Americas, "discovered" in 1492 by Christopher Columbus. Shortly before the turn of the 16th century, Portuguese started establishing trading posts (factories) from Africa to Asia and Brazil, to deal with the trade of local products like slaves, gold, spices and timber, introducing an international business center under a royal monopoly, the House of India.


title: History of globalization

text: Global integration continued with the European colonization of the Americas initiating the Columbian Exchange, the enormous widespread exchange of plants, animals, foods, human populations (including slaves), communicable diseases, and culture between the Eastern and Western hemispheres. It was one of the most significant global events concerning ecology, agriculture, and culture in history. New crops that had come from the Americas via the European seafarers in the 16th century significantly contributed to the world's population growth.


title: History of globalization

text: The 19th century witnessed the advent of globalization approaching its modern form. Industrialization allowed cheap production of household items using economies of scale, while rapid population growth created sustained demand for commodities. Globalization in this period was decisively shaped by nineteenth-century imperialism. After the First and Second Opium Wars, which opened up China to foreign trade, and the completion of the British conquest of India, the vast populations of these regions became ready consumers of European exports. It was in this period that areas of sub-Saharan Africa and the Pacific islands were incorporated into the world system. Meanwhile, the conquest of parts of the globe, notably sub-Saharan Africa, by Europeans yielded valuable natural resources such as rubber, diamonds and coal and helped fuel trade and investment between the European imperial powers, their colonies, and the United States.


title: History of globalization

text: Between the globalization in the 19th and in the 20th there are significant differences. There are two main points on which the differences can be seen. One point is the global trade in this centuries as well as the capital, investment and the economy.


title: History of globalization

text: The global trade in the 20th century shows a higher share of trade in merchant production, a growth of the trade in services and the rise of production and trade by multinational firms.


title: History of globalization

text: The production of merchant goods in the 20th century largely decreased from the levels seen in the 19th century. However, the amount of merchant goods that were produced for the merchandise trade grew.


title: History of globalization

text: The last point that distinguishes the global trade in the 19th century compared to the global trade in the 20th century, is the extent of multinational cooperation. In the 20th century, you can see a "quantum leap" in multinational cooperation compared to the 19th century. Before the 20th century began, there were just Portfolio investment, but no trade-related or production-relation Direct investment.


title: History of globalization

text: Commercial integration has improved since last century, barriers that inhibit trade are lower and transport costs have decreased. Multinational trade contracts and agreements have been signed, like the General Agreement on Tariffs and Trade (GATT), North American Free Trade Agreement (NAFTA), the European Union (EU) has been hugely involved in eliminating tariffs between member states, and the World Trade Organization. From 1890 and up to World War I instability in trade was a problem, but in the post war period there has mostly been economic expansion which leads to stability. Nations have to take care of their own products; they have to make sure that foreign goods do not suffocate their domestic products causing unemployment and maybe social instability. Technological changes have caused lower transporting costs; it takes just a few hours to transport goods between continents to-day, instead of weeks or even months in the nineteenth century.


title: History of globalization

text: By consideration financial crisis one key difference is the monetary regime. In the 19th century it occurred under the fixed exchange rates of the gold standard. But in the 20th century it took place in a regime of managed flexibility. Furthermore, in the 19th century countries had developed effective lenders of last resort, but the same was not true at the periphery and countries there suffered the consequences. A century later there was a domestic safety net in most emerging countries so that banking panics were changed into situations where the debts of an insolvent banking system were taken over by the government. The recovery from banking crisis is another key difference. It has tended to begin earlier in the recent period than in the typical crisis episode a hundred years ago. In the 19th century there were no international rescue packages available to emerging economies. But in the recent period such rescues were a typical component of the financial landscape all over the world.


title: History of globalization

text: The flows information were an important downside in 19th century. Prior to the Transatlantic cable and the Radiotelephone, it used to take very long for information to go from one place to another. So this means that it was very difficult to analyze the information. For instance, it was not so easy to distinguish good and bad credits. Therefore, the information asymmetry played a very important role in international investments. The railway bonds serve as a great example.


title: History of globalization

text: There was also many contracting problems. It was very difficult for companies working overseas to manage their operations in other parts of the world, so this was clearly a big barrier to investment.


title: History of globalization

text: Several macroeconomic factors such as exchange risks and uncertain monetary policies were a big barrier for international investments as well.


title: History of globalization

text: The accounting standards in the U.S. were relatively underdeveloped in the 19th century. The British investors played a very important role in transferring their accounting practices to the new emerging markets.


title: History of globalization

text: The first phase of "modern globalization" began to break down at the beginning of the 20th century, with World War I. The European-dominated network were increasingly confronted with images and stories of ‘others’, thus, then took it upon themselves to take the role of world's guardians of universal law and morality. Racist and unequal practices became also part of their practices in search of materials and resources that from other regions of the world. The increase of world trade before beginning in 1850 right before World War I broke out in 1914 were incentives for bases of direct colonial rule in the global South. Since other European currencies were becoming quite largely circulated, the need to own resource bases became imperative. The novelist VM Yeates criticised the financial forces of globalization as a factor in creating World War I. Financial forces as a factor for creating World War 1 seem to be partly responsible. An example of this would be France's colonial rule over most of Africa during the 20th century. Before World War I broke out, there was no specific aims for the wars in Africa from the French, which left Africans in a “lost” state. Military potential of Africa was first to be emphasized unlike its economic potential...at least at first. France's interest in the military potential of French Africa took a while to be accepted. Africans in the French army were treated with feelings of inferiority from the French. As for the economic incentive for colonial rule came in 1917 when France's was faced with a crisis of food supply. This coming after the outbreak of the war which had left France without the ability to support itself agriculturally since France had a shortage of fertilizers and machinery in 1917.


title: History of globalization

text: Globalization, since World War II, is partly the result of planning by politicians to break down borders hampering trade. Their work led to the Bretton Woods conference, an agreement by the world's leading politicians to lay down the framework for international commerce and finance, and the founding of several international institutions intended to oversee the processes of globalization. Globalization was also driven by the global expansion of multinational corporations based in the United States and Europe, and worldwide exchange of new developments in science, technology and products, with most significant inventions of this time having their origins in the Western world according to Encyclopædia Britannica. Worldwide export of western culture went through the new mass media: film, radio and television and recorded music. Development and growth of international transport and telecommunication played a decisive role in modern globalization.


title: History of globalization

text: These institutions include the International Bank for Reconstruction and Development (the World Bank), and the International Monetary Fund. Globalization has been facilitated by advances in technology which have reduced the costs of trade, and trade negotiation rounds, originally under the auspices of the General Agreement on Tariffs and Trade (GATT), which led to a series of agreements to remove restrictions on free trade.


title: History of globalization

text: Since World War II, barriers to international trade have been considerably lowered through international agreements – GATT. Particular initiatives carried out as a result of GATT and the World Trade Organization (WTO), for which GATT is the foundation, have included:


title: History of globalization

text: Cultural globalization, driven by communication technology and the worldwide marketing of Western cultural industries, was understood at first as a process of homogenization, as the global domination of American culture at the expense of traditional diversity. However, a contrasting trend soon became evident in the emergence of movements protesting against globalization and giving new momentum to the defense of local uniqueness, individuality, and identity.


title: History of globalization

text: The Uruguay Round (1986 to 1994) led to a treaty to create the WTO to mediate trade disputes and set up a uniform platform of trading. Other bilateral and multilateral trade agreements, including sections of Europe's Maastricht Treaty and the North American Free Trade Agreement (NAFTA) have also been signed in pursuit of the goal of reducing tariffs and barriers to trade.


title: History of globalization

text: In the 1990s, the growth of low cost communication networks allowed work done using a computer to be moved to low wage locations for many job types. This included accounting, software development, and engineering design.


title: History of globalization

text: In late 2000s, much of the industrialized world entered into a deep recession. Some analysts say the world is going through a period of deglobalization after years of increasing economic integration. China has recently become the world's largest exporter surpassing Germany.


title: History of globalization

text: Some authors have argued that stretching the beginning of globalization far back in time renders the concept wholly inoperative and useless for political analysis.


title: Matt Watson (YouTuber)

text: Matthew Harris Watson (born February 5, 1996) is an American YouTuber, comedian, musician, podcast host and music video director. He is best known as a co-host of the comedy-variety channel SuperMega (along with its weekly podcast "SuperMegaCast") and a former editor for and member of the Let's Play-orientated web series "Game Grumps". Watson has collaborated with several other entertainers, such as Finn Wolfhard, Markiplier, bbno$ and OneyNG. , SuperMega has over 1 million subscribers and over 385 million total video views.


title: Matt Watson (YouTuber)

text: In 2020, Watson released his music debut with his EP, "OUCH!". His first full-length album, "SEE YOU THERE", was released on November 7, 2022.


title: Matt Watson (YouTuber)

text: Watson was born in Charleston, South Carolina to Ann Watson, a schoolteacher, and Dale Watson, an architectural illustrator.


title: Matt Watson (YouTuber)

text: During his childhood, Watson had a strong interest in art. In middle school, Watson began filming comedy videos of himself and his friends to upload to the then emerging video website YouTube. Throughout his teenage years, he would continue to produce his own content which primarily consisted of sketch comedy, music videos, and animations.


title: Matt Watson (YouTuber)

text: Watson graduated high school from Charleston County School of The Arts in 2014. He attended the University of South Carolina and pursued a degree in business before dropping out after his freshman year and moving to Los Angeles to pursue a career in sketch comedy and video editing instead.


title: Matt Watson (YouTuber)

text: Watson began creating videos in 2008 on his channel Formatt24, where he and his cousin Forest created various sketches. The channel ceased uploading in 2010. In August 2014, Watson began uploading sketches on a new channel called Kids w/ Problems, which would lead him to collaborate with LA-based sketch comedy and music channel Cyndago. After finishing his freshman year of college at The University of South Carolina, Watson moved to Los Angeles in July 2015 to pursue a career in sketch comedy, while also editing videos for the popular YouTuber Markiplier. He lived with fellow comedians Ryan Magee and Daniel Kyre. Watson would later depart Kids w/ Problems and officially join Cyndago on August 10, 2015. The group disbanded one month later following the sudden death of fellow Cyndago member Daniel Kyre. Following these events, Watson returned to Kids w/ Problems with Magee as a permanent co-host.


title: Matt Watson (YouTuber)

text: In 2016, Watson, as well as fellow editor Ryan Magee, stopped working for Fischbach. In a Facebook post, Fischbach stated that the primary reason was that it "was difficult to keep the work and the friendship separate".


title: Matt Watson (YouTuber)

text: On April 12, 2016, Watson and Magee started their own variety comedy channel, SuperMega. SuperMega consists of Let's Plays, sketch comedy, music videos, and a podcast. The duo moved in together to an apartment in Glendale, California, where they spent their days developing the beginning of the channel. Shortly after the channel's conception, the duo started "SuperMegaCast", an hour long free-form comedy podcast where the two converse and joke together. In the summer of 2016, Watson and Magee joined "Game Grumps", where they produced and edited videos for the channel, and occasionally appeared as guests. While working for Game Grumps, Watson and Magee continued to grow SuperMega during their free time, producing comedy videos and collaborating with many creators, such as Finn Wolfhard, OneyPlays, Ian Hecox, Jacksepticeye, Ninja Sex Party, and several others.


title: Matt Watson (YouTuber)

text: On May 3, 2019, the duo left Game Grumps to focus solely on SuperMega. In July 2019, a 2016 video in which Watson and Magee play Pokémon Go at Area 51 went viral after memes surrounding the Storm Area 51 Facebook event became popular. Watson and Magee continued to grow their brand, eventually moving into their own office space dubbed "The SuperMegaPlex", launching a merchandise operation, and growing their podcast. In 2017, SuperMega expanded the scope of their comedy career to include "SuperMega LIVE!", an improv comedy show where they go up in front of a crowd to hang out, tell stories, and do challenges to entertain their fans. The duo performed shows across the United States and Canada, going on to perform in the 2019 Just for Laughs comedy festival.


title: Matt Watson (YouTuber)

text: In 2018, Watson and Magee launched a SuperMega Patreon page, which garnered over 5,000 patrons on launch day, making it one of the most successful launches in Patreon's history.


title: Matt Watson (YouTuber)

text: In 2021, Martins Motorsports announced a partnership with Watson and Magee's channel SuperMega, with the duo specifically serving as the primary sponsor of the #44 Chevrolet Camaro. The #44 Camaro sported SuperMega colors and imagery during the Memorial Day racetrack activities.


title: Matt Watson (YouTuber)

text: Watson and Magee published and released a comedy book, "SuperMega Saves The Troops", on December 7, 2021. They stated they have two sequels planned and in the works.


title: Matt Watson (YouTuber)

text: On May 14, 2022, Watson had a boxing match in iDubbbz's Creator Clash charity event, losing his match against Nathan "Dad" Barnatt in 22 seconds by TKO.


title: Matt Watson (YouTuber)

text: The "SuperMegaCast" is a weekly podcast done by Matt and Ryan, consisting of them talking about current events, recent movies and video games, and stories from their lives. The podcast also frequently hosts guests ranging from close friends and other YouTubers, to artists and celebrities like George Clanton and Max Stanley. "SuperMegaCast" is currently the longest running series on the channel, at over 300 episodes.


title: Matt Watson (YouTuber)

text: Watson himself has featured on a wide array of podcasts, such as comedian Brandon Wardell's podcast "Yeah, But Still" (2 episodes), "Chuckle Sandwich" (2 episodes), Cr1TiKaL's "The Official Podcast", "Podcast About List", the "Misfits Podcast", "Cold Ones", George Clanton's "The Big Stream", and more.


title: Matt Watson (YouTuber)

text: Since 2014, Watson has released various tracks and music videos, mainly consisting of comedic style. While quarantined during the COVID-19 pandemic, Watson produced his first non-comedy EP, "Ouch!", for which he did the instruments, vocals, mixing, and production. On release, The EP's trending spot on Twitter competed for #1 with Big Sean's latest album, Detroit 2, due to SuperMega fans spamming the platform with support. Since the release of "Ouch!", Watson has released two singles, "Bored", for which he directed and produced a music video with fellow director Tucker Prescott, and "Monopoly." He continues to post tracks with either a comedic undertone, a serious nature, or sometimes both. In a review by Nicholas Gaudet of Music Talkers, Gaudet praised "Bored" for its use of jazzy chords, synths, and low bass; as well as stating that it "feels much more confident in its identity" in comparison to "Ouch!". Gaudet would later praise Watson's "Monopoly" for its similar use of a lo-fi style and jazz chords.


title: Matt Watson (YouTuber)

text: In 2022, he released his debut album "See You There" and went on his first solo music tour. Three singles were released ahead of the album, "Ring Pop" featuring Atlanta rapper Father, "Balance" and "Starstud" featuring Sarah Bonito of British indie band Kero Kero Bonito.