{"success":true,"data":{"query":"Texas Place History","limit":10,"count":10,"sources":["wiki_artificial_intelligence.hat","wiki_real_estate.hat","wiki_dallas.hat","web_1779060041.hat"],"synced":[],"results":[{"source":"wiki_artificial_intelligence.hat","text":"ARTICLE: Artificial intelligence\nArtificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.\nHigh-profile applications of AI include advanced web search engines, chatbots, virtual assistants, autonomous vehicles, and play and analysis in strategy games (e.g., chess and Go). Since the 2020s, generative AI has become widely available to generate images, audio, and videos from text prompts.\nThe traditional goals of AI research include learning, reasoning, knowledge representation, planning, natural language processing, and perception, as well as support for robotics. To reach these goals, AI researchers have used techniques including state space search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics. AI also draws upon psychology, linguistics, philosophy, neuroscience, and other fields. Some companies, such as OpenAI, Google DeepMind and Meta, aim to create artificial general intelligence (AGI) – AI that can complete virtually any cognitive task at least as well as a human.\nArtificial intelligence was founded as an academic discipline in 1956, and the field went through multiple cycles of optimism throughout its history, followed by periods of disappointment and loss of funding, known as AI winters. Funding and interest increased substantially after 2012, when graphics processing units began being used to accelerate neural networks, and deep learning outperformed previous AI techniques. This growth accelerated further after 2017 with the transformer architecture. In the 2020s, an AI boom has coincided with advances in generative AI, which allowed for the creation and modification of media. In addition to AI safety and unintended consequences and harms from the use of AI, ethical concerns, AI's long-term effects, and potential existential risks have prompted discussions of AI regulation.","score":85.54123158795183,"links":[]},{"source":"wiki_artificial_intelligence.hat","text":"Algorithmic bias and fairness\nMachine learning applications can be biased if they learn from biased data. The developers may not be aware that the bias exists. Discriminatory behavior by some LLMs can be observed in their output. Bias can be introduced by the way training data is selected and by the way a model is deployed. If a biased algorithm is used to make decisions that can seriously harm people (as it can in medicine, finance, recruitment, housing or policing) then the algorithm may cause discrimination. The field of fairness studies how to prevent harms from algorithmic biases.\nOn 28 June 2015, Google Photos's new image labeling feature mistakenly identified Jacky Alcine and a friend as \"gorillas\" because they were black. The system was trained on a dataset that contained very few images of black people, a problem called \"sample size disparity\". Google \"fixed\" this problem by preventing the system from labelling anything as a \"gorilla\". Eight years later, in 2023, Google Photos still could not identify a gorilla, and neither could similar products from Apple, Facebook, Microsoft and Amazon.\nCOMPAS is a commercial program widely used by U.S. courts to assess the likelihood of a defendant becoming a recidivist. In 2016, Julia Angwin at ProPublica discovered that COMPAS exhibited racial bias, despite the fact that the program was not told the races of the defendants. Although the error rate for both whites and blacks was calibrated equal at exactly 61%, the errors for each race were different—the system consistently overestimated the chance that a black person would re-offend and would underestimate the chance that a white person would not re-offend. In 2017, several researchers showed that it was mathematically impossible for COMPAS to accommodate all possible measures of fairness when the base rates of re-offense were different for whites and blacks in the data.\nA program can make biased decisions even if the data does not explicitly mention a problematic feature (such as \"race\" or \"gender\"). The feature will correlate with other features (like \"address\", \"shopping history\" or \"first name\"), and the program will make the same decisions based on these features as it would on \"race\" or \"gender\". Moritz Hardt said \"the most robust fact in this research area is that fairness through blindness doesn't work.\"\nCriticism of COMPAS highlighted that machine learning models are designed to make \"predictions\" that are only valid if we assume that the future will resemble the past. If they are trained on data that includes the results of racist decisions in the past, machine learning models must predict that racist decisions will be made in the future. If an application then uses these predictions as recommendations, some of these \"recommendations\" will likely be racist. Thus, machine learning is not well suited to help make decisions in areas where there is hope that the future will be better than the past. It is descriptive rather than prescriptive.\nBias and unfairness may go undetected because the developers are overwhelmingly white and male: among AI engineers, about 4% are black and 20% are women.\nThere are various conflicting definitions and mathematical models of fairness. These notions depend on ethical assumptions, and are influenced by beliefs about society. One broad category is distributive fairness, which focuses on the outcomes, often identifying groups and seeking to compensate for statistical disparities. Representational fairness tries to ensure that AI systems do not reinforce negative stereotypes or render certain groups invisible. Procedural fairness focuses on the decision process rather than the outcome. The most relevant notions of fairness may depend on the context, notably the type of AI application and the stakeholders. The subjectivity in the notions of bias and fairness makes it difficult for companies to operationalize them. Having access to sensitive attributes such as race or gender is also considered by many AI ethicists to be necessary in order to compensate for biases, but it may conflict with anti-discrimination laws.\nAt the 2022 ACM Conference on Fairness, Accountability, and Transparency a paper reported that a CLIP‑based (Contrastive Language-Image Pre-training) robotic system reproduced harmful gender‑ and race‑linked stereotypes in a simulated manipulation task. The authors recommended robot‑learning methods which physically manifest such harms be \"paused, reworked, or even wound down when appropriate, until outcomes can be proven safe, effective, and just.\"","score":85.54123158795183,"links":[]},{"source":"wiki_artificial_intelligence.hat","text":"Technological unemployment\nEconomists have frequently highlighted the risks of redundancies from AI, and speculated about unemployment if there is no adequate social policy for full employment.\nIn the past, technology has tended to increase rather than reduce total employment, but economists acknowledge that \"we're in uncharted territory\" with AI. A survey of economists showed disagreement about whether the increasing use of robots and AI will cause a substantial increase in long-term unemployment, but they generally agree that it could be a net benefit if productivity gains are redistributed. Risk estimates vary; for example, in the 2010s, Michael Osborne and Carl Benedikt Frey estimated 47% of U.S. jobs are at \"high risk\" of potential automation, while an OECD report classified only 9% of U.S. jobs as \"high risk\". The methodology of speculating about future employment levels has been criticised as lacking evidential foundation, and for implying that technology, rather than social policy, creates unemployment, as opposed to redundancies. In April 2023, it was reported that 70% of the jobs for Chinese video game illustrators had been eliminated by generative artificial intelligence. Early-career workers showed decreasing employment rates in some AI-exposed occupations.\nUnlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence; The Economist stated in 2015 that \"the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution\" is \"worth taking seriously\". Jobs at extreme risk range from paralegals to fast food cooks, while job demand is likely to increase for care-related professions ranging from personal healthcare to the clergy. In July 2025, Ford CEO Jim Farley predicted that \"artificial intelligence is going to replace literally half of all white-collar workers in the U.S.\"\nFrom the early days of the development of artificial intelligence, there have been arguments, for example, those put forward by Joseph Weizenbaum, about whether tasks that can be done by computers actually should be done by them, given the difference between computers and humans, and between quantitative calculation and qualitative, value-based judgement.","score":85.54123158795183,"links":[]},{"source":"wiki_real_estate.hat","text":"History of real estate\nThe natural right of a person to own property as a concept can be seen as having roots in Roman law as well as Greek philosophy. The profession of appraisal can be seen as beginning in England during the 1500s, as agricultural needs required land clearing and land preparation. Textbooks on the subject of surveying began to be written and the term \"surveying\" was used in England, while the term \"appraising\" was more used in North America. Natural law which can be seen as \"universal law\" was discussed among writers of the 15th and 16th century as it pertained to \"property theory\" and the inter-state relations dealing with foreign investments and the protection of citizens private property abroad. Natural law can be seen as having an influence in Emerich de Vattel's 1758 treatise The Law of Nations which conceptualized the idea of private property.\nOne of the largest initial real estate deals in history known as the \"Louisiana Purchase\" happened in 1803 when the Louisiana Purchase Treaty was signed. This treaty paved the way for western expansion and made the U.S. the owners of the \"Louisiana Territory\" as the land was bought from France for fifteen million dollars, making each acre roughly 4 cents. The oldest real estate brokerage firm was established in 1855 in Chicago, Illinois, and was initially known as \"L. D. Olmsted & Co.\" but is now known as \"Baird & Warner\". In 1908, the National Association of Realtors was founded in Chicago and in 1916, the name was changed to the National Association of Real Estate Boards and this was also when the term \"realtor\" was coined to identify real estate professionals.\nThe stock market crash of 1929 and the Great Depression in the U.S. caused a major drop in real estate worth and prices and ultimately resulted in depreciation of 50% for the four years after 1929. Housing financing in the U.S. was greatly affected by the Banking Act of 1933 and the National Housing Act in 1934 because it allowed for mortgage insurance for home buyers and this system was implemented by the Federal Deposit Insurance as well as the Federal Housing Administration. In 1938, an amendment was made to the National Housing Act and Fannie Mae, a government agency, was established to serve as a secondary market for mortgages and to give lenders more money in order for new homes to be funded.\nTitle VIII of the Civil Rights Act in the U.S., which is also known as the Fair Housing Act, was put into place in 1968 and dealt with the incorporation of African Americans into neighborhoods as the issues of discrimination were analyzed with the renting, buying, and financing of homes. Internet real estate as a concept began with the first appearance of real estate platforms on the World Wide Web (www) and occurred in 1999.","score":81.43035431708982,"links":[]},{"source":"wiki_real_estate.hat","text":"History\nSome of the earliest cadastres were ordered by Roman Emperors to recover state owned lands that had been appropriated by private individuals, and thereby recover income from such holdings. One such cadastre was done in AD 77 in Campania, a surviving stone marker of the survey reads \"The Emperor Vespasian, in the eighth year of his tribunician power, so as to restore the state lands which the Emperor Augustus had given to the soldiers of Legion II Gallica, but which for some years had been occupied by private individuals, ordered a survey map to be set up with a record on each 'century' of the annual rental\". In this way Vespasian was able to reimpose taxation formerly uncollected on these lands.\nWith the fall of Rome, the use of cadastral maps effectively discontinued. Medieval practice used written descriptions of the extent of land rather than using more precise surveys. Only in the sixteenth and early seventeenth centuries did the use of cadastral maps resume, beginning in the Netherlands. With the emergence of capitalism in Renaissance Europe, the need for cadastral maps reemerged as a tool to determine and express control of land as a means of production. This took place first privately in land disputes and later spread to governmental practice as a means of more precise tax assessment.","score":81.43035431708982,"links":[]},{"source":"wiki_dallas.hat","text":"History\nThe original configuration of the first nationwide telephone numbering plan in 1947 divided the state of Texas into four numbering plan areas (NPAs) with area codes 214 (north-east), 512 (south-central), 713 (south-east), and 915 (north-west and west), respectively.\nNumbering plan area 214 extended roughly from a line just west of Dallas to Waco, to the borders of Arkansas and Louisiana.\nIn 1954, most of Tarrant County was combined with much of the eastern region of area code 915 to form area code 817.\nDespite the growth of the Dallas metropolitan area in the second half of the 20th century, this configuration remained in place for thirty six years. In 1990, the entire eastern portion of the 214 area was split off with area code 903.\nThe 1990 split was intended as a long-term solution, but within five years 214 was close to exhaustion due to the rapid growth of the Metroplex as well as the popularity of cell phones, fax machines and pagers. As a remedy, all of the old 214 territory outside Dallas and Dallas County was split off with area code 972 in 1996. Within only two years, however, both 214 and 972 were on the verge of exhaustion again. Area code 469 was introduced on July 1, 1999, in an overlay plan for most of the eastern portion of the Metroplex. At the same time, the 214/972 boundary was \"erased,\" and 972 was converted into an additional overlay for the entire region. The result was three area codes overlaying the same area, with ten-digit dialing required for all calls.\nSince 2000, 214 and 972 have served as overlays for portions of eastern Tarrant County (Arlington, Bedford, Euless, Grapevine, Southlake, and Colleyville) which are closer to Dallas.\nWhile this had the effect of allocating over 23 million numbers to an area of just over nine million people, under 2018 projections, the Dallas area would need a fourth area code by mid-2021. Area code 945 was selected as the fourth area code in the Dallas overlay, after receiving approval from the Public Utility Commission of Texas. Central office code assignments for NPA 945 have been available since January 15, 2021, but can only be requested after all existing area codes are exhausted.  Projections of 2023 suggested that a fifth area code is not needed until around 2032.","score":78.2022929814127,"links":[]},{"source":"wiki_real_estate.hat","text":"Types\nResidential\nSingle-family residential buildings are most often called houses or homes. Multi-family residential buildings containing more than one dwelling unit are called duplexes or apartment buildings. Condominiums are apartments that occupants own rather than rent. Houses may be built in pairs (semi-detached) or in terraces, where all but two of the houses have others on either side. Apartments may be built around courtyards or as rectangular blocks surrounded by plots of ground. Houses built as single dwellings may later be divided into apartments or bedsitters, or converted to other uses (e.g., offices or shops). Hotels, especially of the extended-stay variety (apartels), can be classed as residential.\nBuilding types may range from huts to multimillion-dollar high-rise apartment blocks able to house thousands of people. Increasing settlement density in buildings (and smaller distances between buildings) is usually a response to high ground prices resulting from the desire of many people to live close to their places of employment or similar attractors.\nTerms for residential buildings reflect such characteristics as function (e.g., holiday cottage (vacation home) or timeshare if occupied seasonally); size (cottage or great house); value (shack or mansion); manner of construction (log home or mobile home); architectural style (castle or Victorian); and proximity to geographical features (earth shelter, stilt house, houseboat, or floating home). For residents in need of special care or those society considers dangerous enough to deprive of liberty, there are institutions (nursing homes, orphanages, psychiatric hospitals, and prisons) and group housing (barracks and dormitories).\nHistorically, many people lived in communal buildings called longhouses, smaller dwellings called pit-houses, and houses combined with barns, sometimes called housebarns.\nCommon building materials include brick, concrete, stone, and combinations thereof. Buildings are defined to be substantial, permanent structures. Such forms as yurts and motorhomes are therefore considered dwellings but not buildings.","score":71.43035431708982,"links":[]},{"source":"wiki_dallas.hat","text":"History\nIndigenous tribes in North Texas included the Caddo, Tawakoni, Wichita, Kickapoo and Comanche. Spanish colonists claimed the territory of Texas in the 18th century as a part of the Viceroyalty of New Spain. Later, France also claimed the area but never established much settlement. In all, six flags have flown over the area preceding and during the city's history: those of France, Spain, and Mexico, the flag of the Republic of Texas, the Confederate flag, and the flag of the United States of America.\nIn 1819, the Adams–Onís Treaty between the United States and Spain defined the Red River as the northern boundary of New Spain, officially placing the future location of Dallas well within Spanish territory. The area remained under Spanish rule until 1821, when Mexico declared independence from Spain, and the area was considered part of the Mexican state of Coahuila y Tejas. In 1836, Texians, with a majority of Anglo-American settlers, gained independence from Mexico and formed the Republic of Texas.\nThree years after Texas achieved independence, John Neely Bryan surveyed the area around present-day Dallas. In 1839, accompanied by his dog and a Cherokee he called Ned, he planted a stake in the ground on a bluff located near three forks of the Trinity River and left. Two years later, in 1841, he returned to establish a permanent settlement named Dallas. The origin of the name is uncertain. The official historical marker states it was named after Vice President George M. Dallas of Philadelphia, Pennsylvania. However, this is disputed. Other potential theories for the origin include his brother, Commodore Alexander James Dallas, as well as brothers Walter R. Dallas and James R. Dallas. A further theory gives the ultimate origin as the village of Dallas, Moray, Scotland, similar to the way Houston, Texas, was named after Sam Houston, whose ancestors came from the Scottish village of Houston, Renfrewshire.\nThe Republic of Texas was annexed by the United States in 1845 and Dallas County was established the following year. Dallas was formally incorporated as a city on February 2, 1856. In the mid-1800s, a group of French Socialists established La Réunion, a short-lived community, along the Trinity River in what is now West Dallas.","score":68.2022929814127,"links":[]},{"source":"wiki_dallas.hat","text":"Colleges and universities within Dallas city limits\nUT Southwestern Medical Center (\"UTSW\") is a prominent academic medical center north of downtown Dallas in the Southwestern Medical District. Six Nobel laureates have been among its faculty. The main teaching hospital of the university. UTSW is part of the University of Texas System.\nTexas Woman's University has operated a nursing school in Dallas at Parkland Memorial Hospital since 1966. The T. Boone Pickens Institute of Health Sciences-Dallas Center (IHSD) was opened in 2011 and is a purpose-built educational facility that replaced the building TWU had used since 1966. TWU also operated an occupational therapy school at Presbyterian Hospital of Dallas from 1977 through 2011 before consolidating those functions into the new IHSD building at Parkland.\nPaul Quinn College is a private, historically black college in southeast Dallas. Originally located in Waco, Texas, it moved to Dallas in 1990 and is housed on the campus of the former Bishop College, another private, historically black college. Dallas billionaire and entrepreneur Comer Cottrell Jr., founder of ProLine Corporation, bought the campus of Bishop College and bequeathed it to Paul Quinn College in 1990 making it the only historically black college in Dallas.\nThe University of North Texas at Dallas is along Houston School Road. In 2009 UNT at Dallas became the first public university within Dallas city limits. The University of North Texas System requested approval from the Texas Legislature and Texas Higher Education Coordinating Board for the state's first new public law school in more than 40 years. The University of North Texas at Dallas College of Law was planned to be based at the Old Municipal Building in Downtown Dallas.\nDallas Baptist University is a private university in the Mountain Creek area of southwest Dallas. Originally in Decatur, Texas, the school moved to Dallas in 1965. The school enrolls over 5,600 students, and offers undergraduate, graduate, and doctoral degrees. Popular subjects include Biblical studies, business, and music degrees. DBU has been recognized by the National Council on Teacher Quality for their high-quality teacher preparatory degrees. The school also maintains an Intensive English Program for international students wishing to enhance their knowledge of the English language. The campus is a Tree Campus USA and is recognized as one of the most beautiful university campuses in the Southwest U.S. The school has also become nationally recognized for its baseball team which has made several playoff runs.\nDallas Theological Seminary, also within the city limits, is recognized as one of the leading seminaries in Evangelical Protestantism. Situated 3 miles (5 km) east of Downtown Dallas, it has over 2,000 graduate students and has graduated over 12,000 alumni.\nCriswell College is within two blocks of Dallas Theological Seminary. Criswell was started by First Baptist Church of Dallas in the early 1970s.\nDallas College (formerly Dallas County Community College District), the 2-year educational institution of Dallas County, has seven campuses throughout the area with branches in Dallas as well as the surrounding suburbs.","score":68.2022929814127,"links":[]},{"source":"web_1779060041.hat","text":"Getting Started Use Supabase with React Learn how to create a Supabase project, add some sample data to your database, and query the data from a React app. 1 Create a Supabase project Go to database.new and create a new Supabase project. Alternatively, you can create a project using the Management API: 1 # First, get your access token from https://supabase.com/dashboard/account/tokens 2 export SUPABASE_ACCESS_TOKEN = \" your-access-token \" 3 4 # List your organizations to get the organization ID 5 curl -H \" Authorization: Bearer $SUPABASE_ACCESS_TOKEN \" \\ 6 https://api.supabase.com/v1/organizations 7 8 # Create a new project (replace <org-id> with your organization ID) 9 curl -X POST https://api.supabase.com/v1/projects \\ 10 -H \" Authorization: Bearer $SUPABASE_ACCESS_TOKEN \" \\ 11 -H \" Content-Type: application/json \" \\ 12 -d ' { 13 \"organization_id\": \"<org-id>\", 14 \"name\": \"My Project\", 15 \"region\": \"us-east-1\", 16 \"db_pass\": \"<your-secure-password>\" 17 } ' When your project is up and running, go to the Table Editor section of the Dashboard, create a new table and insert some data. Then in the Integrations > Data API section of the Dashboard, expose the specific tables or functions you want to access. To automatically grant access for new tables and functions in public , enable Default privileges for new entities . Alternatively, you can run the following snippet in your project's SQL Editor . This creates an instruments table with some sample data, sets a secure baseline by setting only the privileges each Postgres role needs, and adds Row Level Security (RLS) for enhanced security for database data by default. 1 -- Create the table 2 create table instruments ( 3 id bigint primary key generated always as identity , 4 name text not null 5 ); 6 7 -- Insert sample data into the table 8 insert into instruments ( name ) 9 values 10 ( ' violin ' ), 11 ( ' viola ' ), 12 ( ' cello ' ); 13 14 -- Grant the privileges the role needs, which is read access 15 grant select on public . instruments to anon; 16 17 -- Enable row level security for the table 18 alter table instruments enable row level security ; Create an RLS policy to make the data in your table publicly readable: 1 -- Create a policy to allow the anon role to read from the instruments table 2 create policy \" public can read instruments \" 3 on public . instruments 4 for select to anon 5 using (true); 2 Create a React app Create a React app using a Vite template. Explore drop-in UI components for your Supabase app. UI components built on shadcn/ui that connect to Supabase via a single command. Explore Components Terminal 1 npm create vite@latest my-app -- --template react 3 Install the Supabase client library The fastest way to get started is to use the supabase-js client library which provides a convenient interface for working with Supabase from a React app. Navigate to the React app and install supabase-js . Terminal 1 cd my-app && npm install @supabase/supabase-js 4 Declare Supabase Environment Variables Create a .env.local file and populate with your Supabase connection variables: Project URL No project found Publishable key No project found .env.local 1 VITE_SUPABASE_URL=<SUBSTITUTE_SUPABASE_URL> 2 VITE_SUPABASE_PUBLISHABLE_KEY=<SUBSTITUTE_SUPABASE_PUBLISHABLE_KEY> Get API details # Now that you've created some database tables, you are ready to insert data using the auto-generated API. To do this, you need to get the Project URL and key from the project Connect dialog . Read the API keys docs for a full explanation of all key types and their uses. Changes to API keys Supabase is changing the way keys work to improve project security and developer experience. You can read the full announcement on GitHub . The older anon and service_role keys will work until the end of 2026 but we strongly encourage switching to and using the new publishable ( sb_publishable_xxx ) and secret ( sb_secret_xxx ) keys now. In most cases, you can get keys from the Project's Connect dialog , but if you want a specific key, you can find them in the Settings > API Keys section of the Dashboard. For legacy keys , copy the anon key for client-side operations and the service_role key for server-side operations from the Legacy API Keys tab. For new keys , open the API Keys tab, if you don't have a publishable key already, click Create new API Keys , and copy the value from the Publishable key section. 5 Query data from the app Replace the contents of App.jsx to add a getInstruments function to fetch the data and display the query result to the page using a Supabase client. src/App.jsx 1 import { useEffect , useState } from \" react \" ; 2 import { createClient } from \" @supabase/supabase-js \" ; 3 4 const supabase = createClient ( import . meta . env . VITE_SUPABASE_URL , import . meta . env . VITE_SUPABASE_PUBLISHABLE_KEY ) ; 5 6 function App () { 7 const [ instruments , setInstruments ] = useState ( [] ) ; 8 9 useEffect ( () => { 10 getInstruments () ; 11 }, [] ) ; 12 13 async function getInstruments () { 14 const { data , error } = await supabase . from ( \" instruments \" ) . select () ; 15 16 if ( error ) { 17 console . error ( error ) ; 18 return ; 19 } 20 21 setInstruments ( data ) ; 22 } 23 24 return ( 25 < ul > 26 { instruments . map ( ( instrument ) => ( 27 < li key = { instrument . name }>{ instrument . name }</ li > 28 )) } 29 </ ul > 30 ) ; 31 } 32 33 export default App ; 6 Start the app Run the development server, go to http://localhost:5173 in a browser and you should see the list of instruments. Terminal 1 npm run dev Next steps # Set up Auth for your app Insert more data into your database Upload and serve static files using Storage Is this helpful? No Yes AI Tools Copy as Markdown Ask ChatGPT Ask Claude","score":39.96701629545183,"links":[]}]},"metadata":{},"timestamp":"2026-07-08T22:51:45.380Z"}