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How should I learn guitar? | Guitar is learned best with a teacher and through many hours of practice. In addition, there are many helpful online resources available to learn guitar. | general_qa | 2,646 |
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What is heliocentrism? | Heliocentrism is an astronomical model in which the sun lies at the center, and planets revolve around it. The model was published by Nicolaus Copernicus shortly before his death in 1543, and became one of the most significant events in the history of science. Before the acceptance of heliocentrism, it was widely believed that Earth was the center of the entire universe. | open_qa | 2,652 |
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What position did Manis Lamond play? | Manis Lamond (born 14 September 1966) is a retired soccer player from Papua New Guinea. An international who played as a striker, Lamond played professionally in Australia for Canberra City, Sydney United, A.P.I.A. Leichhardt Tigers, Wollongong City, Marconi Stallions and Newcastle United and in Singapore for Sembawang Rangers. | Manis Lamond was a striker | closed_qa | 2,655 |
Count de Grisly was the first to perform what trick in 1799 | Saw woman in half | open_qa | 2,658 |
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Do i must to hug my wife | Hugging Improves Relationships.
It's a deeper, more intimate level of connection that you don't get from talking. The second reason is that physical touch causes the release of the love hormone oxytocin, which improves bonding and trust and makes people feel closer to one another.
You should hug your spouse every day as an act of showing your love to them. Giving a hug is one of the simplest ways to show your love. Anytime, anywhere a hug can is a healthy reminder to your spouse of why you love them so much. | general_qa | 2,659 |
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Why did the Prix Lupin not take place from 1915 to 1918? | The event was established in 1855, and it was originally called the Prix de l'Empereur. It was initially held at the Champ de Mars, and was transferred to Longchamp in 1857. It was cancelled due to the Franco-Prussian War in 1871, and was renamed the Grande Poule des Produits in 1872.
The race was one of several trials for the Prix du Jockey Club collectively known as the Poules des Produits. The others (listed by their modern titles) were the Prix Daru, the Prix Hocquart, the Prix Noailles and the Prix Greffulhe. Unlike those races, the Grande Poule des Produits had no restrictions based on the nationality of a horse's sire or dam.
The event was renamed in memory of Auguste Lupin (1807–1895), a successful owner-breeder, in 1896.
The Prix Lupin was abandoned throughout World War I, with no running from 1915 to 1918. It was cancelled once during World War II, in 1940. It was run at Le Tremblay over 2,150 metres in 1943, and at Maisons-Laffitte in 1944.
The present system of race grading was introduced in 1971, and the Prix Lupin was classed at Group 1 level.
The race was last run in 2004. It was discontinued after France Galop restructured its Group 1 programme for three-year-olds in 2005. | Due to the first World War | closed_qa | 2,660 |
When was the Tesla Model 3 unit one million sold? | The Tesla Model 3 became the world's all-time best-selling electric car in early 2020, and in June 2021 became the first electric car to pass 1 million global sales. Together with other emerging automotive technologies such as autonomous driving, connected vehicles and shared mobility, electric cars form a future mobility vision called Autonomous, Connected, Electric and Shared (ACES) Mobility. | June 2021 | closed_qa | 2,666 |
Is Yoga effective in losing weight? | Yoga helps burn calories. Specific forms of Yoga like Vinayasa, Ashtanga and Power Yoga help burn more calories since your body is mostly moving throughout the practice.
Being consistent and having a balanced diet goes hand in hand with any form of workout if one wishes to lose weight. Yoga can also help increase muscle mass and tone.
While practicing Yoga, one is constantly focusing on the breathing with each change in posture which helps increases mindfulness as well. Various researches have also shown that yoga also helps in managing stress and improve your mood. | open_qa | 2,668 |
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What is a benefit of salsa dancing? | Salsa dancing is a great form of exercise. It provides a great cardio workout and helps you work on balance and coordination. In addition, it keeps you engaged mentally, making it a workout of the body and the mind. | general_qa | 2,669 |
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On what date was the country of Belize granted independence? | Belize was granted independence from the British Empire on September 21, 1981. | open_qa | 2,671 |
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Given a reference text about Patrick James Mara, tell me what he was known for. | Patrick James Mara (1 February 1942 – 15 January 2016) was an Irish public affairs consultant and politician who served as Senator from July 1981 to October 1981 and May 1982 to December 1982. He was most renowned for being the political adviser to former Taoiseach Charles Haughey. He also served as Press Secretary to Fianna Fáil from 1983 to 1987 and Government Press Secretary from 1987 to 1992.
He was appointed the Fianna Fáil Director of Elections for the 1997, 2002, and 2007 general elections. He was a member of the board of Digicel, the company founded by Denis O'Brien to build mobile networks in the Caribbean.
He was regularly lampooned on the satirical Raidió Teilifís Éireann (RTÉ) radio sketch show Scrap Saturday, which ran from 1989 to 1991. | Patrick James Mara was most known for being a political adviser to Taoiseach Charles Haughey and serving as Press Secretary and Government Press Secretary. | closed_qa | 2,673 |
Why sport cricket is so famous? | Cricket is a very interesting and engaging sport which is celebrated vastly in many nations like India, Australia, England, South Africa etc. Because of the popularity of cricket, it attracts big sponsors and investments globally | open_qa | 2,674 |
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Given this paragraph, which highs school did Drake Maye attend? | Drake Maye was born on August 30, 2002, in Charlotte, North Carolina. He attended and played high school football for Myers Park High School in Charlotte, where he was named MaxPreps North Carolina player of the year. He was a four-star prospect and originally committed to Alabama before flipping to North Carolina. | Based on this text, Drake Maye attended Myers Park High School in Charlotte, North Carolina. | closed_qa | 2,675 |
Why would an NHL team want to lose to be last in the standings? | While winning is ultimately the goal of professional sports teams, in many sports leagues, including the National Hockey League (NHL), teams that are worse get higher draft picks in the upcoming year's entry draft.
Having a higher pick in the entry draft can be very valuable, since it is one of the best ways to get a very talented player on your team. For example, Sidney Crosby, and Connor McDavid, widely considered to be the best players in the NHL were both first overall picks in their drafts. | open_qa | 2,677 |
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What does "time flies" mean? | When we are busy and having fun, our brains perceive time passage differently. Hence the expression time flies. | open_qa | 2,679 |
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What are the pros and cons of denormalizing data sets? | The pro for denormalizing data is to optimize for scan related queries of data and data serving. The con is that denormalization increases data latency due to the re-building of the materialized view. | open_qa | 2,680 |
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Who is the greatest tennis player of all time? | Rafael Nadal | general_qa | 2,681 |
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What are the four major tournaments for the Professional Golfers Association? | The four major tournaments for the Professional Golfers' Association (PGA) Tour are the Masters, the PGA Championship, the US Open, and the British Open. The Masters is the first tournament of the calendar year and is held in April in Augusta, Georgia, USA. The PGA Championship comes second and is held in May followed by the US Open in June and the British Open in July. The PGA Championship, US Open, and British Open are held at different venues each year whereas the Masters tournament is always held at Augusta National Golf Club. The Masters, US Open, and British Open all welcome qualifying amateurs and professionals alike whereas the PGA Championship is limited to professionals only. | open_qa | 2,683 |
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In the series A Song of Ice and Fire, who is the founder of House Grafton? | Gerold Grafton | open_qa | 2,684 |
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How old was Pukeiti when he died? | Pukeiti Pukeiti (c. 1948 - 18 October 2012) was a Cook Islands politician and Member of the Cook Islands Parliament. He was a member of the Cook Islands Party. He represented the electorate of Tamarua.
Pukeiti was elected to Parliament in the 2009 Tamarua by-election following the death of MP Mii Parima. He was re-elected at the 2010 election. | 64 years old. He was born in 1948 and died in 2012, so 2012 - 1948 = 64. | closed_qa | 2,686 |
What can I do to help me sleep better? | Make sure that you turn off your phone at least an hour before bedtime. Avoid eating close to bedtime. Make sure that you allow for enough time to spend in bed: at least 7-9 hours. Avoid drinking alcohol right before bed. Don't rely on substances to help you sleep. Get significant exercise during the day. For most people though, you don't want to exercise right before sleep. Avoid benzodiazepenes as much as possible because they have a significant tendency to lead to dependency and will interfere with sleep. | general_qa | 2,688 |
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Why is it so hard to predict which teams will make the Men's College Basketball Final Four? | Unlike other sports where playoff rounds can be a series of multiple games (such as the NBA, NHL, MLB, etc), the "March Madness" college basketball playoffs features single elimination games for each round, so in a one game playoff, upsets are much more likely than in a 7 game series, where the statistically better team is most like going to win. So, out of the 68 teams that make the tournament, it is hard to predict who will each round. | general_qa | 2,695 |
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Given the following paragraph about politicians, who was the last surviving person to have been a member of the Irish House of Commons? | Sir Thomas Staples, 9th Baronet (31 July 1775 – 14 May 1865) was an Anglo-Irish politician and lawyer. He was the last surviving person to have been a member of the Irish House of Commons, albeit only having been in the House for a short time. | Sir Thomas Staples, 9th Baronet | closed_qa | 2,696 |
What is Milky Way? | The Milky Way is the galaxy that includes the Solar System, with the name describing the galaxy's appearance from Earth: a hazy band of light seen in the night sky formed from stars that cannot be individually distinguished by the naked eye. The term Milky Way is a translation of the Latin via lactea, from the Greek γαλακτικὸς κύκλος (galaktikòs kýklos), meaning "milky circle". From Earth, the Milky Way appears as a band because its disk-shaped structure is viewed from within. Galileo Galilei first resolved the band of light into individual stars with his telescope in 1610. Until the early 1920s, most astronomers thought that the Milky Way contained all the stars in the Universe. Following the 1920 Great Debate between the astronomers Harlow Shapley and Heber Doust Curtis, observations by Edwin Hubble showed that the Milky Way is just one of many galaxies. | Milky Way is the galaxy that includes Solar System in which our planet Earth is located. | closed_qa | 2,698 |
What is the best time of year to visit Lake Tahoe? | The best time to visit Lake Tahoe? The answer depends on your interests (or possibly the interests of the person advising you).
Snow lovers: if you count down the days until the mountain resorts open up, Winter is the time for you. Most resorts open around Thanksgiving and typically close in mid-late Spring. Tahoe has several world-class ski resorts; with Northstar and Palisades being favorites on the North shore, and Heavenly Mountain being the favorite on the South Shore. If flying down the mountain isn't appealing, you can go sledding, snowshoeing or snowmobiling. The snow capped mountains reflected on the deep blue waters of Tahoe make for epic winter sights. There's plenty of joy to be had staying inside, cozying up by the fireplace and simply enjoying the peaceful scenery outside your windows.
Sun Lovers: Tahoe Summers are for you. The Lake: beaches, marinas, restaurants, music and people galore. The lakeside vibe on Tahoe's beaches is casual and fun. Boaters & sailors highly regard Tahoe's famous blue waters. Tahoe is a kayaker's paradise with so many stunning coves to explore. Venture over to Emerald Bay to see where the lake turns from blue to green & visit the historic island in the middle. Hikers and cyclists; when the snow melts, there are countless trails to explore, including long segments of the famous Pacific Rim trail. For those who prefer leisurely strolls, there are some spectacular walking paths right along the lake. Floating down the Truckee River is a must-do for a frolicking day of fun. Campers love Tahoe as well, with many fun campgrounds to visit; some even within a short distance to the bustling streets of Stateline South Shore, where there are casinos, restaurants and music venues. Golfers can rejoice on the world class course along the lake at Edgewood.
In the transition months, the scenery is equally beautiful; and the tourist crowds are much smaller. Some people favorite the Spring and Fall in Tahoe, simply for a more secluded, scenic mountain getaway; catching either the tail end of the snow season or the early warmth glimpses of Summer.
Tahoe is a year-round destination. The best time to visit truly depends on the type of getaway you're seeking. My recommendation: Try all 4 seasons; you may find that it's impossible to pick a favorite! | general_qa | 2,700 |
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How to introduce a new cat to the household if you already have cats? | Confine the new cat to a single room. Make sure the confined cat have access to everything he or she needs, including water, food, bedding, litterbox and toys. Feed your new and existing cats across the closed door, so that the cats can smell each other and associate each other's presence with food and happiness. Use synthetic feline facial pheromone in both the new cat’s room and in the area where the resident cat spends the most time will help to create feelings of familiarity and security within the physical environment. After a while, exchange pieces of bedding between the resident cats and the new cat so that the cats start to recognize each others scents. Slowly allow cats to interact with each other under supervision to ensure the cats build early positive experiences together. | general_qa | 2,701 |
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Which universe we are living today and how large the universe is? | Wow, that's a tough one, currently, we are living in the observational universe, which is 5% of the whole universe from the latest research. The universe we lives is 93 billion light-year in diameter. | general_qa | 2,702 |
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What is the plot of The Count of Monte Cristo? | In Alexandre Dumas' novel "The Count of Monte Cristo," the main character Edmund Dantes is framed and wrongly convicted of a crime he did not commit, by his lover's cousin who secretly wants to marry Edmund's lover. Edmund is sentenced to a prison dungeon where he meets an abby that reveals a hidden treasure should Edmund ever escape. Edmund spends years plotting his escape, retrieval of the treasure, and his revenge on all those who conspired against him. He disguises himself as a Count, then one by one exacts his revenge by influencing his rivals to behave in a manner that will lead to each of their downfalls. While he doesn't directly cause harm to any of his rivals, they all suffer the consequences of their own actions and Edmund comes out victorious. | general_qa | 2,704 |
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Who is the most famous left-handed baseball player? | Babe Ruth | open_qa | 2,705 |
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What are the Chinese dialects that people speak in China? | While most people's native language is Mandarin in China. There are 9 types of dialects which include Wu, Gan, Xiang, Min, Hakka, Yue, Jin, Huizhou ad Pinghua. These dialects share the same Chinese character as Mandarin which means the formal writing is the same. But they all have their own unique pronunciation which makes it hard to understand between the speakers of different dialects. | general_qa | 2,706 |
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In which city is this high school located? | The Instituto de Enseñanza Secundaria Lope de Vega (IES Lope de Vega) is a public high school in Madrid, Spain. It is located in the calle de San Bernardo. It is operated by the regional administration of the Community of Madrid. | Madrid | closed_qa | 2,707 |
What is a newspaper? | A newspaper is a daily printed publication delivered to your house or place of business. It is made our of folded sheets of printed paper, and it contains current and prior day events also called news. You will also find advertisements and different correspondences in it as well. It is a great way to stay up to date with current events, and you will have to pay to get a newspaper subscription delivered daily or weekly. | open_qa | 2,708 |
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What caused the millenium tower to sink in san francisco? | The critics blame the city for allowing Millennium partners to anchor the building into packed sand rather than bedrock. The problem with Millennium tower arose because the 60 to 90-foot-long friction piles supporting it were driven into sandy soil rather than the bedrock, 200 feet down. | open_qa | 2,709 |
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What is the difference between AWD and 4WD? | AWD is a system that without driver intervention, shifts power between the rear and front wheels. This system is typically found on light-duty SUVs or passenger cars. The AWD drive system is designed for mild inclement weather conditions such as light snow, ice and rain. It is not designed for off-roading or severe weather conditions such as heavy snow or mud. This is where the 4WD system comes into the picture.
4WD is a system that includes a transfer case that directly applies power to the rear axle, both front and rear axles and in some cases, only to the front axle. In addition, some 4WD systems include lower gear ratio options, locking hubs and lockers in the axles that force an equal amount of power to each wheel. All this taken together enables a 4WD system to enable a vehicle to navigate through deep snow, mud, over rocks and other obstacles with ease. The 4WD system is most commonly found on trucks, Jeeps and other purpose-built vehicles designed for heavy-duty use, whether for work or pleasure. | open_qa | 2,712 |
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Why do toddlers throw tantrums? | There are many triggers that may cause toddlers to throw a tantrum, such as hunger or exhaustion. But the reason that toddlers often lose control of their emotions and become seemingly inconsolable is that as toddlers develop emotionally, they start to experience new feelings or start to feel things more deeply. When they do not have the communication skills to express these experiences, to manage these experiences, or to ask for help with them, they resort to signaling that they are in distress. | general_qa | 2,716 |
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What are the applications of game theory in NBA basketball? | Game theory studies the strategic interaction of rationale agents. The National Basketball Association (NBA) is the world's premier basketball league, which includes 30 teams across the United States and Canada. An example of game theory in the NBA is the "modern NBA", in which teams play stretch 4s (Power Forwards) and 5s (Centers) who can dribble, pass and shoot rather than simply rebound and dunk. This becomes the "strictly dominate" strategy as this allows the "modern" NBA team to shoot a higher volume of 3 pointers, which has a higher expected value per shot (40 Field Goal % times 3 = 1.2) than 2 pointers (50 Field Goal % times 2 = 1). The Golden State Warriors championship run in the 2010s with Kevin Durant and Draymond Green is a great example of this coaching and player construction strategy. Now nearly all NBA teams employ this strategy, so it is less effective (A Nash (Not Steve Nash!) Equilibrium). | general_qa | 2,717 |
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What is FrieslandCampina? | FrieslandCampina is one of the biggest dairy companies in the world. Their headquaters is in the Netherlands in Amersfoort. Its main brands are Friesche Vlag (or Frisian Flag in Indonesian market), Chocomel, Fristi, Friso, Dutch Lady, Milner, Campina, Landliebe, Optimel, Mona and "Mix'it" | open_qa | 2,718 |
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Who are the Georgia Bulldogs' biggest rival? | Georgia has many traditional geographical rivals. The answer typically depends on who you ask and generally aligns with the age of the Georgia fan. Older fans tend to oppose the Georgia Tech Yellowjackets or Auburn the most as they fondly remember competitive annual matchups in the rivalry games dubbed Clean Old Fashioned Hate or The Deep Souths Oldest Rivalry. GenX and Millennials typically point to the Florida Gators since Florida went on a two decade long run of dominance, going 18-3 in between 1990 and 2010. Tennessee might also garner some votes in this timeframe. Younger fans might point to the multiple National Championship crushing heartbreaks at the hands of Alabama in 2008, 2012, 2015, 2017, and 2018. | general_qa | 2,721 |
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What are the three biggest cities by population in Spain? | The three biggest cities by population in Spain are Madrid, Barcelona, and Valencia. | open_qa | 2,722 |
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I am looking into buying a new monitor, how do I know which one I should buy? | It depends a lot on the use case and how much money you want to spend. First decide on a budget. After that you should decide on what size the monitor should have. Then, within that size and budget range take a look at different features such as resolution, color accuracy, refresh rate and connectivity options. A high resolution is good for work and gaming but also requires a good graphics card. Color accuracy is important if you plan to use the monitor for artistic work, such as editing movies and images. Refresh rate is important if you plan to do gaming, especially online. Connectivity options such as power delivery over USB-C is important if you want to simply connect the monitor with a laptop. | general_qa | 2,726 |
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How would you book the cheapest rental car in a foreign country? | To book the cheapest and best rental car you could start using popular aggregator websites such as Kayak and Expedia to find the best prices from large domestic car rental companies with foreign operations. Next, you can make a search for local car rental companies in the area you are travelling to, and make calls or visit their website. This may require you to speak a local language. Finally, you can utilize alternative car rental companies such as Turo if they are available in the region you are travelling to. | open_qa | 2,727 |
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According to this paragraph, did Frederic Foley hold the patent to the Foley catheter? | Foley first described the use of a self-retaining balloon catheter in 1929, to be used to achieve hemostasis after cystoscopic prostatectomy. He worked on development of this design for use as an indwelling urinary catheter, to provide continuous drainage of the bladder, in the 1930s. His design incorporated an inflatable balloon towards the tip of the tube which could be inflated inside the bladder to retain the catheter without external taping or strapping. He demonstrated this to the American Urologists Society in 1935, and published a paper describing it in 1937. While he was still developing his catheter, a patent was issued to Paul Raiche of the Davol Rubber Company of Providence, Rhode Island in 1936. Four months later, in October 1936, Foley applied for the patent, and was awarded this after appearing before the patent office Board of Appeals. Raiche appealed this decision in court, and it was overturned, returning the patent to Raiche. A further request for a hearing made by Foley was refused, and so the patent stayed with Raiche.
https://en.wikipedia.org/wiki/Frederic_Foley | According to this paragraph, Frederic Foley applied for the patent but it was ultimately awarded to Paul Riache instead. | closed_qa | 2,728 |
What is a genome-wide association study (GWAS)? | In genomics, a genome-wide association study (GWA study, or GWAS), is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms.
When applied to human data, GWA studies compare the DNA of participants having varying phenotypes for a particular trait or disease. These participants may be people with a disease (cases) and similar people without the disease (controls), or they may be people with different phenotypes for a particular trait, for example blood pressure. This approach is known as phenotype-first, in which the participants are classified first by their clinical manifestation(s), as opposed to genotype-first. Each person gives a sample of DNA, from which millions of genetic variants are read using SNP arrays. If there is significant statistical evidence that one type of the variant (one allele) is more frequent in people with the disease, the variant is said to be associated with the disease. The associated SNPs are then considered to mark a region of the human genome that may influence the risk of disease.
GWA studies investigate the entire genome, in contrast to methods that specifically test a small number of pre-specified genetic regions. Hence, GWAS is a non-candidate-driven approach, in contrast to gene-specific candidate-driven studies. GWA studies identify SNPs and other variants in DNA associated with a disease, but they cannot on their own specify which genes are causal.
The first successful GWAS published in 2002 studied myocardial infarction. This study design was then implemented in the landmark GWA 2005 study investigating patients with age-related macular degeneration, and found two SNPs with significantly altered allele frequency compared to healthy controls. As of 2017, over 3,000 human GWA studies have examined over 1,800 diseases and traits, and thousands of SNP associations have been found. Except in the case of rare genetic diseases, these associations are very weak, but while they may not explain much of the risk, they provide insight into genes and pathways that can be important. | open_qa | 2,734 |
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Given this paragraph about time travel, how practical is it | Time travel is the concept of movement between certain points in time, analogous to movement between different points in space by an object or a person, typically with the use of a hypothetical device known as a time machine. Time travel is a widely recognized concept in philosophy and fiction, particularly science fiction. The idea of a time machine was popularized by H. G. Wells' 1895 novel The Time Machine. | Yes, time travel is indeed a real thing. But it's not quite what you've probably seen in the movies. Under certain conditions, it is possible to experience time passing at a different rate than 1 second per second. And there are important reasons why we need to understand this real-world form of time travel. | closed_qa | 2,735 |
How is plastic made? | Plastic is made from oil, natural gas and even plant oils during refining of these oils into other products like gasoline. Ethane and propane are created when treated with heat during a refinery process called cracking. This turns the Ethane and propane into ethylene and propylene which are used with other chemical ingredients to create polymers that are the base of what plastic is made out of. | open_qa | 2,740 |
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What is the route to eternal happiness? | Being at peace with oneself is the route to happiness. When our minds are not running after material goals but instead being comfortable in the current and now, that's what leads to sustained happiness. Else one is running after temporal happiness, which come in the form of something that satisfies us in the moment but us not sustaining - e.g. watching TV or eating good food. Eternal happiness comes from the state of mind and not from achieving a goal we are conditioned towards | open_qa | 2,742 |
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what makes the Sun bright ? | The sun is a huge massive sphere of gas and it is powered by the energy released by turning hydrogen to helium at its core. This process is called nuclear fusion reaction. Nuclear fusion involves two or more nuclei combining together to form one or more different atomic nuclei. Nuclear fusion releases termendous amount of energy in the form of light and heat. | open_qa | 2,744 |
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What does "digital nomads" mean? | Digital nomads are professionals who use technology and the internet to do their jobs while traveling and living a nomadic life. Digital nomads work remotely, instead of going to a company's office or headquarters. | open_qa | 2,746 |
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Why are plants green? | Parts of a plant that are green, such as leaves, are green because they contain chlorophyll. Chlorophyll absorbs light energy (but less so green light than red or blue) and helps convert that energy into food for the plant as part of photosynthesis.
A more whimsical answer, which is not scientifically accurate, is that plants need both sunlight (which is yellow) and water (which is blue) to live and yellow plus blue makes green. | general_qa | 2,747 |
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Who is Evelyn Quan Wang in the move "Everything Everywhere All at Once"? | Evelyn Quan Wang is a middle-aged Chinese American immigrant who runs a laundromat with her husband, Waymond; two decades earlier, they eloped to the United States and had a daughter, Joy. The laundromat is being audited by the Internal Revenue Service (IRS), Waymond is trying to serve Evelyn divorce papers in an attempt to get her attention so they can talk things out regarding their marriage, Evelyn's demanding father (referred to as Gong Gong, Cantonese for 'grandfather') is visiting for her Chinese New Year party, and Evelyn is reluctant to accept Joy's lesbian relationship with her non-Chinese girlfriend Becky (only introducing Becky to Gong Gong as Joy's "very good friend"). | Evelyn Quan Wang is a middle-aged Chinese American immigrant who runs a laundromat with her husband, Waymond. | closed_qa | 2,748 |
Given this paragraph, which was built first Disneyland or Disney World? | Designed to supplement Disneyland in Anaheim, California, which had opened in 1955, the complex was developed by Walt Disney in the 1960s. "The Florida Project", as it was known, was intended to present a distinct vision with its own diverse set of attractions. Walt Disney's original plans also called for the inclusion of an "Experimental Prototype Community of Tomorrow" (EPCOT), a planned community intended to serve as a testbed for new city-living innovations. Walt Disney died on December 15, 1966, during the initial planning of the complex. After his death, the company wrestled with the idea of whether to bring the Disney World project to fruition; however, Walt's older brother, Roy O. Disney, came out of retirement to make sure Walt's biggest dream was realized. Construction started in 1967, with the company instead building a resort similar to Disneyland, abandoning the experimental concepts for a planned community. The Magic Kingdom was the first theme park to open in the complex, in 1971, followed by Epcot (1982), Disney's Hollywood Studios (1989), and Disney's Animal Kingdom (1998). It was Roy who insisted the name of the entire complex be changed from Disney World to Walt Disney World, ensuring that people would remember that the project was Walt's dream. | According to this text, Disneyland was built first in 1955, with Disney World construction starting later in 1967 and first opening in 1971. | closed_qa | 2,749 |
What number octane gas should be used for combustion engines in vehicles? | Manufacturers list the minimal octane to be used on specific vehicles in the owners manual. Always check the manual to be sure the proper fuel is being used. An octane number such as 87, 91, 93 indicates the amount of heat tolerance of the fuel before igniting inside the engine cylinder. The higher the octane number, the higher heat tolerance. If you use the wrong octane in a vehicle, such as using 87, rather than 93 for a high performing turbo or supercharged vehicle, the engine could produce knock or pre-detonation. Knock occurs when the timing of of the air and fuel mixture in the cylinder explodes too early and can cause serious damage to the engine components. Knock is also something you can hear and feel and can be noticed by the driver. Having the detonation of the air and fuel, produced by the spark plug that is intended from the factory is optimal for the longevity of the vehicle. | open_qa | 2,750 |
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Who is the most sensational player in MLB today? | Shohei Ohtani | open_qa | 2,753 |
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What is I Liq Chuan? | Sam F.S. Chin (Chin Fan Siong, 曾帆祥, born August 1, 1954) is the Grandmaster and Gatekeeper of the martial art called I Liq Chuan, and also known as "the Martial Art of Awareness". Chin developed the grading system for this system.
Chin was trained since childhood by his father, Chin Lik Keong, founder of I Liq Chuan, and in 1978, he won the state heavy weight kickboxing championships of Selangor (Malaysia). In August 2009 Chin was officially named the Gate Keeper and Lineage Holder of the I Liq Chuan. He is also the founder and President of Chin Family I Liq Chuan Association that supports the martial art's growth.
Chin has taught workshops worldwide , written two books on his family's martial art, co-authored articles, and produced a series of DVDs. Chin was interviewed by Jess O'Brien for his 2007 book "Nei Jia Quan: Internal Martial Arts".
In August 2009, Chin was also recognized by the USA Wushu Kung-Fu Federation as a Hall of Fame Outstanding Master. In 2014, he was written about by Ashe Higgs in Kung Fu Tai Chi Magazine "Finding the Center: I Liq Chuan’s Three Essential Qualities for Offense and Defense as One". Chin was also the subject of the 2016 CCTV Documentary "Kung Fu Abroad: I Liq Chuan 中央电视台《功夫在外》纪录片".
On November 15, 2017 Sam Chin became an honorary professor at the University of Plovdiv, Bulgaria in recognition of his lifetime of achievement in spreading I Liq Chuan. | I Liq Chuan is a style of martial art founded by Chin Lik Keong from Malaysia that is also known as the "Martial Art of Awareness". | closed_qa | 2,754 |
When was the Victorian Football League renamed to the Australian Football League? | 1990 | open_qa | 2,756 |
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The Bacillus Calmette-Guerin (BCG) vaccine is administered to Indian children soon after birth to protect them against which disease? | The Bacillus Calmette-Guerin (BCG) vaccine is administered to Indian children soon after birth to protect them against Tuberculosis | open_qa | 2,757 |
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What is industrial espionage? | Industrial espionage, economic espionage, corporate spying, or corporate espionage is a form of espionage conducted for commercial purposes instead of purely national security.
While political espionage is conducted or orchestrated by governments and is international in scope, industrial or corporate espionage is more often national and occurs between companies or corporations. | open_qa | 2,758 |
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Given a reference text about Kostas Georgakis, when did he go to Italy and what did he do there? | Kostas Georgakis (Greek: Κώστας Γεωργάκης) (23 August 1948 – 19 September 1970) was a Greek student of geology, who in the early hours of 19 September 1970, set himself ablaze in Matteotti square in Genoa in a fatal protest against the dictatorial regime of Georgios Papadopoulos.
Early life
Georgakis grew up in Corfu in a family of five. His father was a self-employed tailor of modest means. Both his father and grandfather distinguished themselves in the major wars that Greece fought in the 20th century. He attended the second lyceum in Corfu where he excelled in his studies. In August 1967, a few months after the 21 April coup in Greece, Georgakis went to Italy to study as a geologist in Genoa. He received 5,000 drachmas per month from his father and this, according to friends' testimony, made him feel guilty for the financial burden his family endured so that he could attend a university. In Italy he met Rosanna, an Italian girl of the same age and they got engaged. In 1968 Georgakis became a member of the Center Union party of Georgios Papandreou. | Kostas Georgakis went to Genoa, Italy in 1967 to study geology. | closed_qa | 2,760 |
What is a Roth 401(k)? | In the United States, a 401(k) plan is an employer-sponsored, defined-contribution, personal pension (savings) account, as defined in subsection 401(k) of the U.S. Internal Revenue Code. Periodical employee contributions come directly out of their paychecks, and may be matched by the employer. This legal option is what makes 401(k) plans attractive to employees, and many employers offer this option to their (full-time) workers.
There are two types: traditional and Roth 401(k). For Roth accounts, contributions and withdrawals have no impact on income tax. For traditional accounts, contributions may be deducted from taxable income and withdrawals are added to taxable income. There are limits to contributions, rules governing withdrawals and possible penalties.
The benefit of the Roth account is from tax-free capital gains. The net benefit of the traditional account is the sum of (1) a possible bonus (or penalty) from withdrawals at tax rates lower (or higher) than at contribution, and (2) the impact on qualification for other income-tested programs from contributions and withdrawals reducing and adding to taxable income, minus the consequences of capital gains being taxed at regular income rates. | Roth 401(k) is a type of 401(k) where accounts, contributions, and withdrawals have no impact on income tax. The benefit of the Roth account is that the capital gains are tax-free.
In the United States, a 401(k) plan is an employer-sponsored, defined-contribution, personal pension (savings) account, as defined in subsection 401(k) of the U.S. Internal Revenue Code. Periodical employee contributions come directly out of their paychecks and may be matched by the employer. | closed_qa | 2,761 |
Who was the mascot of 13th South Asian Games (SAG) | A pair of blackbucks | open_qa | 2,763 |
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What are the words of House Buckwell? | "Pride and Purpose" | open_qa | 2,764 |
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What are the pros and cons of charging your Tesla at home? | The most convenient way to charge your EV is to charge it at home overnight while you sleep. Home chargers tend to be slow chargers which reach around 3.6 - 7 kW, although you can also charge using your home’s plug sockets which charge at speeds of around 2.3 kW.
Pros
Charging your Tesla Model Y at home overnight is probably the cheapest, most cost-efficient way to charge your EV. This is because off-peak energy prices are significantly cheaper than peak charging. Model Ys come with an adapter wire, allowing you to charge your EV using your home's plugs easily.
If you're interested in charging at home, installing a home charging unit could be worth your time. Over time this could save you money. There are grants available to help you afford a home charger.
The OZEV Chargepoint Grant is up to £350 or 75% off the fully installed charge point cost if specifics are met. There is also the Scottish EST Domestic Chargepoint Grant which gives you up to £300 and can be used alongside the OZEV Chargepoint Grant.
Cons
Home chargers rarely exceed speeds of 7 kW. This means charging the Tesla Model Y's large battery would take a long time. If you don't invest in a home charging station, it might also be risky to home charge as the 3-pin plug can damage your home's wiring.
If you choose to charge during the day, it can also get quite expensive and may not compare favourably with public charging stations, despite being much slower. | open_qa | 2,767 |
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Give me a one line summary of this: "Gale gave me a sense of security I’d lacked since my father’s death. His companionship replaced the long solitary hours in the woods. I became a much better hunter when I didn’t have to look over my shoulder constantly, when someone was watching my back…Being out in the woods with Gale…sometimes I was actually happy.” | Gale made me feel secure and happy. | general_qa | 2,768 |
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Name some popular breakfast foods in the United States | In the United States of America popular breakfasts include bacon and eggs, waffles, French toast, cereal and pancakes | open_qa | 2,769 |
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What is the best bicycle for me? | The best bicycle depends on your goals, experience, budget, and physical characteristics such as height, weight, etc. You should ensure that the bicycle you select fits into those requirements. Once you have an idea of what those requirements are, take a look at options and you should be able to make an informed decision. | general_qa | 2,772 |
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Given a reference text about Ihor Lapin, tell me what he did before the war. | Ihor Lapin (born 28 May 1969 in Ivanychi) is a Ukrainian lawyer and politician who is a former (2014-2019) Member of the Parliament of Ukraine.
During the War in Donbass (eastern Ukraine) he was commander of the 2nd assault squadron "West" of the 24th Battalion of Territorial Defense "Aidar" of the Armed Forces of Ukraine, formed mainly from volunteers from Volyn Region.
In the Russian-Ukrainian war, he was the commander of the Special Forces Battalion of the First Separate Special Forces Brigade, named after Ivan Bohun.
Before the war, he worked as a lawyer, and was a member of the Bar Qualification-Disciplinary Commission of Volyn Region. | Before the war, Ihor Lapin was a lawyer and a member of the Bar Qualification-Disciplinary Commission. | closed_qa | 2,774 |
What is a jet engine? | A jet engine is a reaction engine used for propulsion, most commonly in airplanes. It works by compressing and discharging heated gas, and follows Newton's third law of motion. Most jet engine used in airplanes are breathing axial flow gas turbines. These gas turbines are powered using aviation turbine fuel (avtur) or more commonly called jet fuel. The gas turbines have at least three stages: a compressor, a combustor, and a turbine. | general_qa | 2,776 |
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What are the best types of questions to ask during a job interview? | The best types of questions to ask during an interview will depend on the position being filled, the required experience and expertise, and the specific skill set sought. It is important to ask background questions to understand the candidate’s current role and responsibilities, as well as their ideal next job. Behavioral questions are also quite useful during an interview. Behavioral questions ask a candidate to describe how they would respond in a specific situation and can be tailored to the skills and experience sought. For example, it is useful to describe a situation the candidate is likely to encounter at the potential new job and ask them to describe how they would handle the situation. This will help you identify whether the candidate has the skills and experience to address some of the day-to-day work at your company. It is a good idea to ask multiple behavioral questions during each interview and to ask all candidates for that role the same questions. | general_qa | 2,778 |
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Where was 52nd International Film Festival of India held ? | Goa (Nov 20 to Nov 28) | open_qa | 2,780 |
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In the series A Song of Ice and Fire, who is the founder of House Lannister? | Lann the Clever | open_qa | 2,781 |
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Given this paragraph about magnesium, what is the atomic number of magnesium? | Magnesium is a chemical element with the symbol Mg and atomic number 12. It is a shiny gray metal having a low density, low melting point and high chemical reactivity. Like the other alkaline earth metals (group 2 of the periodic table) it occurs naturally only in combination with other elements and it almost always has an oxidation state of +2. It reacts readily with air to form a thin passivation coating of magnesium oxide that inhibits further corrosion of the metal. The free metal burns with a brilliant-white light. The metal is obtained mainly by electrolysis of magnesium salts obtained from brine. It is less dense than aluminium and is used primarily as a component in strong and lightweight alloys that contain aluminium. | The atomic number of magnesium is 12. | closed_qa | 2,782 |
Why would anyone go river rafting? | River rafting offers an opportunity to see nature from a new point of view. You enjoy scenery a the pace of the river current, whether on flat water, through gentle riffles or in whitewater. The flora and fauna that you see will vary wildly depending on the ecosystem and area of the river you float. For example, in Oregon alone you can raft rivers flowing down in conditions ranging from semi desert to deep forest. | general_qa | 2,783 |
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What is the Shy Plant? | The scientific name of the shy plant also known as the shame plant is Mimosa pudica, which means shy, bashful, and sensitive. The structures of the shy plant are interesting; it has an herbaceous stem. As well as a dicot on a monocot stem. It has beautiful flowers and leaves that are green, and they are thigmotropism negative. When the shy plant's leaves are touched, they curl up. The Shy plant needs direct sunlight, and 70 to 80 degrees indoors is a good place for it. When the need to water comes, the soil must be 50% dry. The medical value of the Shy plant is great. It helps with Hemorrhoids, infections, sores, and sinuses. | general_qa | 2,784 |
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What is 'karma' according to Buddhism? | Karma is a central and fundamental aspect of Buddhist doctrine common to all traditions of Buddhism. The Buddhist concept of Karma is a natural process that operates with all our volitional actions and which does not need an external agency or power that sits in judgement.
Karma in Buddhism should not be considered as moral justice, or a method of reward and punishment, that needs an external body or authority to decide whom or what should be punished and rewarded. It is believed that Gautama Buddha attained complete insight into how the process of Karma works during the night of his full enlightenment when, through the divine eye (dibbacakku), Buddha saw how other beings die and are reborn in happy and unhappy states according to their Karma.
According to the Cula-kammavibhanga sutta of the Majima Nikava (collection of the middle length discourses of the Buddha), a young brahmin by the name of Subha had approached the Buddha and inquired as to why there was so much inequality among human beings in terms of being short-lived or long-lived, sickly or healthy, ugly or beautiful, powerful or powerless, poor or rich, low-born or high-born, ignorant or intelligent, etc. Buddha had then explained that:
"all living beings are the owners of their actions, heirs to their actions, they originate from their actions, they are related through their actions, they have their actions as their refuge and that it is action or Karma that distinguishes beings as inferior and superior
The word Karma in Pali, and karma in Sanskrit, means action but encompasses only actions that are intentional, volitional and willful and which will lead to consequences sooner or later. The mind (citta) by itself cannot perform or direct any mental, verbal or physical action and it is the intention, will, mental effort or volition (cetana) that directs any mental, verbal or physical action.
Thus the Buddha declared:
"Cetanaham bhikkhave kammam vadami
Cetayitva kammam karoti, kayena, vacaya, manasa"
"It is volition that I call Karma, by volition one performs Karma through body, word or mind." | open_qa | 2,786 |
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Give me a summary about St Paul's Cathedral | St Paul's Cathedral is an Anglican cathedral in London and is the seat of the Bishop of London. The cathedral serves as the mother church of the Diocese of London. It is on Ludgate Hill at the highest point of the City of London and is a Grade I listed building. Its dedication to Paul the Apostle dates back to the original church on this site, founded in AD 604. The present structure, dating from the late 17th century, was designed in the English Baroque style by Sir Christopher Wren. Its construction, completed in Wren's lifetime, was part of a major rebuilding programme in the city after the Great Fire of London. The earlier Gothic cathedral (Old St Paul's Cathedral), largely destroyed in the Great Fire, was a central focus for medieval and early modern London, including Paul's walk and St Paul's Churchyard, being the site of St Paul's Cross.
The cathedral is one of the most famous and recognisable sights of London. Its dome, surrounded by the spires of Wren's City churches, has dominated the skyline for over 300 years. At 365 ft (111 m) high, it was the tallest building in London from 1710 to 1963. The dome is still one of the highest in the world. St Paul's is the second-largest church building in area in the United Kingdom, after Liverpool Cathedral. | open_qa | 2,787 |
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Why should people drink water? | The body is composed of anywhere between 55-75% water and many bodily functions rely on being sufficiently hydrated. One of the best ways to stay hydrated is to drink water. Drinking water has many benefits such as helping regulate your body temperature, protecting your joints and organs and keeping your skin healthy and clear. | general_qa | 2,789 |
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Why are people afraid of sharks? | Many people are afraid of sharks from irrational fear from media, and from losing control. Only about 80 humans are attacked by sharks each year, with a very low death rate. Galeophobia is the term used for being afraid of sharks. | general_qa | 2,791 |
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Given these paragraphs about Large language models, what are some examples of emergent abilities? | A large language model (LLM) is a language model consisting of a neural network with many parameters (typically billions of weights or more), trained on large quantities of unlabelled text using self-supervised learning. LLMs emerged around 2018 and perform well at a wide variety of tasks. This has shifted the focus of natural language processing research away from the previous paradigm of training specialized supervised models for specific tasks.
Properties
Though the term large language model has no formal definition, it often refers to deep learning models having a parameter count on the order of billions or more. LLMs are general purpose models which excel at a wide range of tasks, as opposed to being trained for one specific task (such as sentiment analysis, named entity recognition, or mathematical reasoning). The skill with which they accomplish tasks, and the range of tasks at which they are capable, seems to be a function of the amount of resources (data, parameter-size, computing power) devoted to them, in a way that is not dependent on additional breakthroughs in design.
Though trained on simple tasks along the lines of predicting the next word in a sentence, neural language models with sufficient training and parameter counts are found to capture much of the syntax and semantics of human language. In addition, large language models demonstrate considerable general knowledge about the world, and are able to "memorize" a great quantity of facts during training.
Hallucinations
Main article: Hallucination (artificial intelligence)
In artificial intelligence in general, and in large language models in particular, a "hallucination" is a confident response that does not seem to be justified by the model's training data.
Emergent abilities
On a number of natural language benchmarks involving tasks such as question answering, models perform no better than random chance until they reach a certain scale (in this case, measured by training computation), at which point their performance sharply increases. These are examples of emergent abilities.
Unpredictable abilities that have been observed in large language models but that were not present in simpler models (and that were not explicitly designed into the model) are usually called "emergent abilities". Researchers note that such abilities "cannot be predicted simply by extrapolating the performance of smaller models". These abilities are discovered rather than programmed-in or designed, in some cases only after the LLM has been publicly deployed. Hundreds of emergent abilities have been described. Examples include multi-step arithmetic, taking college-level exams, identifying the intended meaning of a word, chain-of-thought prompting, decoding the International Phonetic Alphabet, unscrambling a word’s letters, identifying offensive content in paragraphs of Hinglish (a combination of Hindi and English), and generating a similar English equivalent of Kiswahili proverbs.
Architecture and training
Large language models have most commonly used the transformer architecture, which, since 2018, has become the standard deep learning technique for sequential data (previously, recurrent architectures such as the LSTM were most common). LLMs are trained in an unsupervised manner on unannotated text. A left-to-right transformer is trained to maximize the probability assigned to the next word in the training data, given the previous context. Alternatively, an LLM may use a bidirectional transformer (as in the example of BERT), which assigns a probability distribution over words given access to both preceding and following context. In addition to the task of predicting the next word or "filling in the blanks", LLMs may be trained on auxiliary tasks which test their understanding of the data distribution such as Next Sentence Prediction (NSP), in which pairs of sentences are presented and the model must predict whether they appear side-by-side in the training corpus.
The earliest LLMs were trained on corpora having on the order of billions of words. The first model in OpenAI's GPT series was trained in 2018 on BookCorpus, consisting of 985 million words. In the same year, BERT was trained on a combination of BookCorpus and English Wikipedia, totalling 3.3 billion words. In the years since then, training corpora for LLMs have increased by orders of magnitude, reaching up to hundreds of billions or trillions of tokens.
LLMs are computationally expensive to train. A 2020 study estimated the cost of training a 1.5 billion parameter model (1-2 orders of magnitude smaller than the state of the art at the time) at $1.6 million.
A 2020 analysis found that neural language models' capability (as measured by training loss) increased smoothly in a power law relationship with number of parameters, quantity of training data, and computation used for training. These relationships were tested over a wide range of values (up to seven orders of magnitude) and no attenuation of the relationship was observed at the highest end of the range (including for network sizes up to trillions of parameters).
Application to downstream tasks
Between 2018 and 2020, the standard method for harnessing an LLM for a specific natural language processing (NLP) task was to fine tune the model with additional task-specific training. It has subsequently been found that more powerful LLMs such as GPT-3 can solve tasks without additional training via "prompting" techniques, in which the problem to be solved is presented to the model as a text prompt, possibly with some textual examples of similar problems and their solutions.
Fine-tuning
Main article: Fine-tuning (machine learning)
Fine-tuning is the practice of modifying an existing pretrained language model by training it (in a supervised fashion) on a specific task (e.g. sentiment analysis, named entity recognition, or part-of-speech tagging). It is a form of transfer learning. It generally involves the introduction of a new set of weights connecting the final layer of the language model to the output of the downstream task. The original weights of the language model may be "frozen", such that only the new layer of weights connecting them to the output are learned during training. Alternatively, the original weights may receive small updates (possibly with earlier layers frozen).
Prompting
See also: Prompt engineering and Few-shot learning (natural language processing)
In the prompting paradigm, popularized by GPT-3, the problem to be solved is formulated via a text prompt, which the model must solve by providing a completion (via inference). In "few-shot prompting", the prompt includes a small number of examples of similar (problem, solution) pairs. For example, a sentiment analysis task of labelling the sentiment of a movie review could be prompted as follows:
Review: This movie stinks.
Sentiment: negative
Review: This movie is fantastic!
Sentiment:
If the model outputs "positive", then it has correctly solved the task. In zero-shot prompting, no solve examples are provided. An example of a zero-shot prompt for the same sentiment analysis task would be "The sentiment associated with the movie review 'This movie is fantastic!' is".
Few-shot performance of LLMs has been shown to achieve competitive results on NLP tasks, sometimes surpassing prior state-of-the-art fine-tuning approaches. Examples of such NLP tasks are translation, question answering, cloze tasks, unscrambling words, and using a novel word in a sentence. The creation and optimisation of such prompts is called prompt engineering.
Instruction tuning
Instruction tuning is a form of fine-tuning designed to facilitate more natural and accurate zero-shot prompting interactions. Given a text input, a pretrained language model will generate a completion which matches the distribution of text on which it was trained. A naive language model given the prompt "Write an essay about the main themes of Hamlet." might provide a completion such as "A late penalty of 10% per day will be applied to submissions received after March 17." In instruction tuning, the language model is trained on many examples of tasks formulated as natural language instructions, along with appropriate responses. Various techniques for instruction tuning have been applied in practice. OpenAI's InstructGPT protocol involves supervised fine-tuning on a dataset of human-generated (prompt, response) pairs, followed by reinforcement learning from human feedback (RLHF), in which a reward function was learned based on a dataset of human preferences. Another technique, "self-instruct", fine-tunes the language model on a training set of examples which are themselves generated by an LLM (bootstrapped from a small initial set of human-generated examples).
https://en.wikipedia.org/wiki/Large_language_model | Examples include multi-step arithmetic, taking college-level exams, identifying the intended meaning of a word, chain-of-thought prompting, decoding the International Phonetic Alphabet, unscrambling a word’s letters, identifying offensive content in paragraphs of Hinglish (a combination of Hindi and English), and generating a similar English equivalent of Kiswahili proverbs. | closed_qa | 2,792 |
What is the difference between coffee and espresso? | Espresso is a type of coffee. More specifically, it's a method of brewing coffee that uses high water pressure and finely ground beans to make a small, concentrated shot. Espresso has a top layer of foam known as the crema, which is a by-product of the high-pressure extraction process.
When ordering a "coffee" in America, you will most likely get a drip coffee which is also a type of coffee. When you order un caffè (a coffee) in Italy, you will most likely receive an espresso. | open_qa | 2,794 |
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How do you make wine? | Wine is made from grapes. You first need to harvest or collect the grapes and then take them off the stem. Next you need to crush the grapes and get as much juice out of them as possible. Then you let the grapes ferment for many weeks or months and during the fermentation process alcohol will be released. Then you can siphon the wine in the barrels or let the wine age longer and then get it ready for bottling or corking / capping. | open_qa | 2,795 |
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How do archaeologist use stratigraphy? | Stratigraphy is very important for archaeologists and is used to interpret time and space within a site. In general, the soil horizons near the top are the most recent and those lower down are older. Stratigraphy can help archaeologist determine how old a site is as well as different events that might have taken place at the site. | open_qa | 2,796 |
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is diners drive-ins and dives the best food network show? | It depends what you are looking for! If you are interested in learning about new foods in predominantly US locations that are generally affordable without a competitive element then diners drive-ins and dives, or triple D, may be great for you. Given how many years the show has been on air it is almost impossible to watch a repeat and you usually find something interesting to pay attention to. While it's not competitive, you can definitely see which restaurants make the host super excited versus not. It is a great show to decompress from work or stress before going to bed. | general_qa | 2,797 |
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What is meant by the saying “break a leg”? | “Break a leg” is a way to wish someone good luck, especially before a performance. | open_qa | 2,802 |
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What is Megan Rapinoe's soccer jersey number? | 15 | open_qa | 2,804 |
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Does Grigorievna Nazarenko live in Moscow? | Professor Tatyana Grigorievna Nazarenko is one of the leading Russian contemporary painters who has set new directions in Russian Art and Painting starting from the 1970s. She was born in Moscow where she still lives and works. | Yes, she lives in Moscow | closed_qa | 2,805 |
Given a reference text about the Falcons, how many Super Bowls have they won in their history? | The Atlanta Falcons are a professional American football team based in Atlanta. The Falcons compete in the National Football League (NFL) as a member club of the league's National Football Conference (NFC) South division. The Falcons were founded on June 30, 1965, and joined the NFL in 1966 as an expansion team, after the NFL offered then-owner Rankin Smith a franchise to keep him from joining the rival American Football League (AFL).
In their 55 years of existence, the Falcons have compiled a record of 379–487–6 (369–473–6 in the regular season and 10–14 in the playoffs), winning division championships in 1980, 1998, 2004, 2010, 2012, and 2016. The Falcons have appeared in two Super Bowls, the first during the 1998 season in Super Bowl XXXIII, where they lost to the Denver Broncos 34–19, and the second 18 years later, a 34–28 overtime loss to the New England Patriots in Super Bowl LI.
The Falcons' current home field is Mercedes-Benz Stadium, which opened for the 2017 season; the team's headquarters and practice facilities are located at a 50-acre (20 ha) site in Flowery Branch, northeast of Atlanta in Hall County. | Although the falcons have been to two Super Bowl games in their history, they have not won a Super Bowl yet. | closed_qa | 2,806 |
Who was Bhagat Singh? | Bhagat Singh was a freedom fighter born in undivided India on 27th September 1907 and was hanged to death by the British Empire at a young age of 23 years on 23rd March 1931. | open_qa | 2,809 |
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Who are the contenders for the World Chess Championship in 2023? | Ian Nepomniachtchi from Russia up against Ding Liren from China | open_qa | 2,812 |
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What are the main differences between traditional fishing with a spinning rod or baitcasting rod and fly fishing? | The main differences between the two methods of fishing are the types of lures that are used and in the way the lure is delivered by a cast of the rod. In traditional or spin fishing, the lure itself is weighted and this weight provides the leverage necessary to cast out into the water. In contrast, fly fishing the lures are typically called flies and are very light. Because they are so light, a heavier line is used and the weight of the line is what allows the fly to be cast out and delivered to the water. Spin fishing lures are often measured in ounces of weight and are often made of metal or plastic. They can range in size and design depending on the target species of fish. Fly fishing flies are typically very lightweight hairs, threads, or other materials tied to a hook. The fly fishing line weights are measured in grains. | general_qa | 2,813 |
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What is Noether's theorem and how does it relate symmetries to conserved quantities? | Emmy Noether proposed a theorem that states that for every symmetry in physics, there is a conserved quantity. For example, for the symmetry that the laws of physics are unchanged by a translation in space, a rotation in space, or an offset in time, the corresponding conserved quantities are linear momentum, angular momentum, and the conservation of energy. | open_qa | 2,816 |
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Why do people like living in California? | California has the highest population of any U.S. state. Many people like living there because of its relatively mild climate and easy access to National and State Parks. Others enjoy living in California because it provides strong human rights protections to minority groups. California is a very large state and has a varied geography. As a result, people who want to live in coastal, forested, desert, or mountain environments can all find a location they like. | general_qa | 2,817 |
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What is powerlifting? | Powerlifting is a strength sport which consists of having three attempts at lifting a maximal weight on three separate lifts using a barbell with weight plates. The three lifts are typically the squat, deadlift and bench press. | open_qa | 2,819 |
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In the United States, what type of degree is typically earned before starting graduate school? | A Bachelors degree is earned before commencing grad school | open_qa | 2,820 |
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What is the difference between Eczema and Atopic Dermatitis? | Eczema is a general term for chronic conditions of skin inflammation whereas Atopic Dermatitis is a specific type of Eczema. | open_qa | 2,823 |
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Why does a US $20 bill have a vertical strip on it when held to light? | Paper money has counterfeit measures to ensure it is very difficult to duplicate/fake | open_qa | 2,824 |
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Tell me about the Boxer dog | The Boxer was originally bred in Germany as a working breed. They are considered great family dogs. | open_qa | 2,825 |
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What is an API? | An application programming interface (API) is a way for two or more computer programs to communicate with each other. It is a type of software interface, offering a service to other pieces of software. | open_qa | 2,827 |
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What is Sensory processing disorder? | Sensory processing disorder (SPD, formerly known as sensory integration dysfunction) is a condition in which multisensory input is not adequately processed in order to provide appropriate responses to the demands of the environment. Sensory processing disorder is present in many people with autism spectrum disorder and attention deficit hyperactivity disorder. Individuals with SPD may inadequately process visual, auditory, olfactory (smell), gustatory (taste), tactile (touch), vestibular (balance), proprioception (body awareness), and interoception (internal body senses) sensory stimuli.
Sensory integration was defined by occupational therapist Anna Jean Ayres in 1972 as "the neurological process that organizes sensation from one's own body and from the environment and makes it possible to use the body effectively within the environment".Sensory processing disorder has been characterized as the source of significant problems in organizing sensation coming from the body and the environment and is manifested by difficulties in the performance in one or more of the main areas of life: productivity, leisure and play or activities of daily living.
Sources debate whether SPD is an independent disorder or represents the observed symptoms of various other, more well-established, disorders.SPD is not included in the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association, and the American Academy of Pediatrics has recommended in 2012 that pediatricians not use SPD as a stand-alone diagnosis. | Sensory processing disorder (SPD, formerly known as sensory integration dysfunction) is a condition in which multisensory input is not adequately processed to provide appropriate responses to the demands of the environment. Sensory processing disorder is present in many people with autism spectrum disorder and attention deficit hyperactivity disorder. Individuals with SPD may inadequately process visual, auditory, olfactory (smell), gustatory (taste), tactile (touch), vestibular (balance), proprioception (body awareness), and interoception (internal body senses) sensory stimuli. | closed_qa | 2,828 |
What is a weed wacker? | A weed wacker is a stringed trimmer that is powered by a better or by gasoline. The string spins at a very fast circular velocity for cutting. It is used for cutting weeds, grass and making the edge of lawns look uniform. Its important to where proper safety equipment when using a weed wacker to prevent injury to your legs from spinning plastic string. | open_qa | 2,829 |
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Why is the World Cup the best sporting competition? | The World Cup is a global event that happens only once every four years. It always has a Host(s) Nation, which is the only team that automatically qualifies for the tournament. Various tournaments lead up to the event, leading to the qualification for the World Cup. From there, FIFA will rank the qualifiers in different tiers and draw them via lottery into "Groups" together.
The Qualification process is available to all teams across the globe. Regionally-based tournaments hosted by the likes of CONACAF, UEFA, CAF, CONMEBOl, etc lead up to the World Cup Tournament.
Once the Groups are drawn via lottery together, all Four teams (from different regions). They play against each other and the two teams with the highest total points will advance to the elimination rounds, which include a round of 16, Quarterfinals, Semifinals, and the Final. Once the elimination round begins they are single elimination matches the loser is out of the tournament and the winner advances to the next round. | open_qa | 2,830 |
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