SYSTRAN, founded by Dr. Peter Toma in 1968, is one of the oldest machine translation companies. SYSTRAN has done extensive work for the United States Department of Defense and the European Commission. SYSTRAN provided the technology for Yahoo! Babel Fish until May 30, 2012, among others. It was used by Google's language tools until 2007. SYSTRAN is used by the Dashboard Translation widget in macOS. Commercial versions of SYSTRAN can run on Microsoft Windows (including Windows Mobile), Linux, and Solaris. Historically, SYSTRAN systems used rule-based machine translation (RbMT) technology. With the release of SYSTRAN Server 7 in 2010, SYSTRAN implemented a hybrid rule-based/statistical machine translation (SMT) technology which was the first of its kind in the marketplace. As of 2008, the company had 59 employees of whom 26 are computational experts and 15 computational linguists. The number of employees decreased from 70 in 2006 to 59 in 2008. In January 2024, ChapsVision acquired Systran. == History == With its origin in the Georgetown machine translation effort, SYSTRAN was one of the few machine translation systems to survive the major decrease of funding after the ALPAC Report of the mid-1960s. The company was established in La Jolla in California to work on translation of Russian to English text for the United States Air Force during the Cold War. Large numbers of Russian scientific and technical documents were translated using SYSTRAN under the auspices of the USAF Foreign Technology Division (later the National Air and Space Intelligence Center) at Wright-Patterson Air Force Base, Ohio. The quality of the translations, although only approximate, was usually adequate for understanding content. The company headquarters is in Paris, while its U.S. headquarters is in San Diego, CA. During the dot-com boom, the international language industry started a new era, and SYSTRAN entered into agreements with a number of translation integrators, the most successful of these being WorldLingo. In 2016, the Harvard NLP group and SYSTRAN founded OpenNMT, an open source ecosystem for neural machine translation and neural sequence learning. This has enabled machine translation software with learning capabilities, dramatically increasing MT translation quality. The project has since been used in several research and industry applications, and its open source ecosystem is currently maintained by SYSTRAN and Ubiqus. == Business situation == Most of SYSTRAN's revenue comes from a few customers. 57.1% comes from the 10 main customers and the three largest customers account for 10.9%, 8.9%, and 8.9% of its revenues, respectively. Revenues had been declining in the early 2000s: 10.2 million euros in 2004, 10.1 million euros in 2005, 9.3 million euros in 2006, 8.8 million euros in 2007, and 7.6 million euros in 2008, before seeing a rebound in 2009 with 8.6 million euros. == Languages == The following is a list of the languages in which SYSTRAN translate from and to English: Russian into English in 1968 and English into Russian in 1973 for the Apollo–Soyuz project.
D4Science
D4Science is a Data Infrastructure offering services by community-driven virtual research environments. In particular, it supports communities of practice willing to implement open science practices, thus it is an Open Science Infrastructure. The infrastructure follows the system of systems approach, where the constituent systems (Service providers) offer "resources" (namely services and by them data, computing, storage) assembled together to implement the overall set of D4Science services. In particular, D4Science aggregates "domain agnostic" service providers as well as community-specific ones to build a unifying space where the aggregated resources can be exploited via Virtual research Environments and their services. It is spread across several sites, the primary one is hosted by the Istituto di Scienza e Tecnologie dell'Informazione of National Research Council (Italy). At the earth of this infrastructure there is an Open Source Software named gCube system. == Services == D4Science offers: Virtual Research Environment as a Service providing any community of practice with a dedicated working environment supporting any knowledge production process in a collaborative way, in fact every VRE enables computer-supported cooperative work by design. D4Science-based VREs are web-based, community-oriented, collaborative, user-friendly, open-science-enabler working environments for scientists and practitioners willing to work together to perform a set of (research) task. From the end-user perspective, each VRE manifests in a unifying web application (and a set of application programming interfaces (APIs)): (a) comprising several applications organised in specific menu items and (b) running in a plain web browser. Every application is providing VRE users with facilities implemented by relying on one or more services provisioned by diverse providers. Among the basic services every VRE is equipped with there are a Social Networking area enabling collaborative and open discussions on any topic and disseminating information of interest for the community, for example, the availability of a research outcome; a Workspace for storing, organizing and sharing any version of a research artifact, including dataset and model implementation; a User Management dashboard for managing membership and roles; a Catalogue Service recording the assets worth being published thus to make it possible for others to be informed and make use of these assets. Science Gateway as a Service providing a community of practice with a dedicated science gateway hosting a selected set of virtual research environments. Data Analytics at scale for data analytics including: a proprietary data analytics platform (DataMiner) to execute analytics tasks either by relying on methods provided by the user or by others. It is endowed with importing and sharing facilities for analytics methods implemented in heterogeneous forms including R, Java, Python, and KNIME. The platform enacts tasks execution by a distributed and hybrid computing infrastructure. Moreover, one of the worth highlighting feature of this platform is its open science-friendliness. All the analytics methods integrated in it are exposed by a standard protocol (the OGC WPS protocol) clients can use to get informed on available methods as well as to start processes, monitor their execution and access results. Every analytics task performed by the platform automatically produces a provenance record catering for the reproducibility of the task; an RStudio-based development environment for R enabling to perform statistical computing tasks in the cloud. This RStudio environment is (i) preconfigured with libraries and packages to ease the execution of common data analytics tasks, and (ii) provides seamless access to the VRE Workspace enabling sharing of resources with other members of the same working environment. a Jupyter-based notebook environment for developing and executing interactive computing by JupyterLab instances. Each JupyterLab is (i) preconfigured with libraries and packages to ease the execution of common data analytics tasks, and (ii) provides access to the VRE Workspace enabling sharing of resources with other members of the same working environment. == Community == The D4Science Infrastructure serves more than 24,000 registered users (August 2024) through 177 active VREs offered via 20 Science gateways. This extensive infrastructure not only supports a diverse range of scientific communities but also fosters significant engagement and collaboration among researchers worldwide. Engagement within the D4Science community is robust, with users benefiting from user-friendly application environments tailored to their specific needs. The platform allows users to securely preserve, access, and share their data from anywhere, fostering a collaborative and inclusive research environment. Additionally, groups of users can create their own virtual environments and customise them with the applications they need, further enhancing the platform's flexibility and usability. Supported communities and cases range from Agri-food to Social Data Science, Earth Science and Marine Science. These diverse applications demonstrate the versatility and broad applicability of the D4Science Infrastructure, making it an invaluable resource for researchers across various scientific domains. == History == The D4Science development has been supported by several European-funded projects. DILIGENT (2004-2007) in the Sixth Framework Programme for Research and Technological Development was the forerunner where a testbed infrastructure built by integrating digital library and grid computing technologies and resources was conceived and developed to serve the needs of communities of practice involved in knowledge development. In the context of the Seventh Framework Programme for research, technological development and demonstration the development of the D4Science initiative. In this period the infrastructure was established and developed to serve communities of practices from domains ranging from Earth Science to Marine Science with worldwide scope In the context of the H2020 research and innovation programme the maturity level of the D4Science infrastructure was high enough to allow a large and very diverse set of communities of practice to benefit from it and its services and further contribute to its development. Moreover, the services offered by the infrastructure have been developed to support open science practices. The operation and improvement of the D4Science infrastructure facilities are still ongoing while its exploitation is progressively growing.
Shadowrun
Shadowrun is a science fantasy tabletop role-playing game set in an alternate future in which cybernetics, magic and fantasy creatures co-exist. It combines genres of cyberpunk, urban fantasy, and crime, with occasional elements of conspiracy, horror, and detective fiction. From its inception in 1989, it has spawned a franchise that includes a series of novels, a collectible card game, two miniature-based tabletop wargames, and multiple video games. The title is taken from the game's main premise – a near-future world damaged by a massive magical event, where industrial espionage and corporate warfare runs rampant. A shadowrun – a successful data theft or physical break-in at a rival corporation or organization – is one of the main tools employed by both corporate rivals and underworld figures. Deckers (futuristic hackers) can tap into an immersive, three-dimensional cyberspace on such missions as they seek access, physical or remote, to the power structures of rival groups. They are opposed by rival deckers and lethal, potentially brain-destroying artificial intelligences called "Intrusion Countermeasures" (IC), while they are protected by street fighters and/or mercenaries, often with cyborg implants (called cyberware), magicians, and other exotic figures. Magic has also returned to the world after a series of plagues; dragons who can take human form have returned as well, and are commonly found in high positions of corporate power. == Publication history == Shadowrun was developed and published by FASA from 1989 until early 2001, when the company closed and Shadowrun was transferred to WizKids, a company founded by former FASA employees. Two years before its closure, FASA sold its videogame branch, FASA Interactive, to Microsoft corporation, keeping rights to publishing novels and pen and paper RPGs. Since then, digital rights to Shadowrun IP have belonged to Microsoft. WizKids licensed the RPG rights to Fantasy Productions, who were already publishing a German version, until WizKids was acquired by Topps in 2003. Catalyst Game Labs, a publishing imprint of InMediaRes Productions, licensed the rights from Topps to publish new products. WizKids itself produced an unsuccessful collectible action figure game based on the property, called Shadowrun Duels. A fifth edition of Shadowrun was announced in December 2012. A limited-edition softcover was sold at the Origins Game Fair in June 2013, and the PDF in July 2013. A hardcover was published in August 2013. Shadowrun Anarchy was published in October 2016 It is a simplified version of the ruleset which allows focus more on the narration than on the rules. The sixth edition, called Shadowrun, Sixth World, was announced on May 1, 2019 to coincide with the game's 30th anniversary, along with a new website at shadowrunsixthworld.com. The game was published on August 26, 2019. The mechanics for this new version are generally similar to those of fifth edition, with some rules reworked for what line developer Jason Hardy describes as streamlining. This new version also progressed the in-game year to 2080. Since 2004, Shadowrun Missions (SRM) has offered fans "living campaigns" that allow for persistent character advancement. SRM is broken down into seasons which are made up of up to 24 individual missions that can be played at home, with special missions available to play exclusively at conventions. Each SRM season develops an overarching plot focused on a specific city from the Shadowrun setting. Missions settings have included the divided city of Denver, the corporate city-state of Manhattan, the Seattle Metroplex city-state, the formerly walled-off wastelands of Chicago, and Neo-Tokyo. For Shadowrun, Sixth World missions returned to Seattle, with twenty-four missions set in 2081, right after Seattle declared independence from the UCAS. The current Shadowrun Missions setting is 2083 New Orleans. The Shadowrun role-playing game has spawned several properties, including Shadowrun: The Trading Card Game, eight video games, an action figure game (Shadowrun Duels), two magazines, an art book and more than 50 novels, starting with the Secrets of Power series which introduces some of the original characters of Shadowrun and provides an introduction to this fictional universe. In addition to the main rule book there have been over 100 published supplements including adventures and expansions to both the rules and the game settings. Catalyst Game Labs announced that 2013 would be "The Year of Shadowrun," and in addition to the release of Shadowrun fifth edition that it has collaborated with publishers on the following properties: Shadowrun: Crossfire, The Adventure Deck-building Game; Shadowrun: Sprawl Gangers, a tactical miniatures wargame; and Shadowrun: Hostile Takeover, a board game designed by Bryan C.P. Steele was planned for release in late 2014/early 2015. Catalyst had been in collaboration with Nordic Games and Cliffhanger Studios to create Shadowrun Chronicles: Boston Lockdown online RPG, however it was shuttered November 30, 2018, with the producers citing lack of funding and the end of the license terms for use of the IP. == Fictional universe == Shadowrun takes place several decades in the future (2050 in the first edition, currently 2088). The end of the Mesoamerican Long Count calendar ushered in the "Sixth World", with once-mythological beings (e.g. dragons) appearing and forms of magic suddenly emerging. Large numbers of humans have "Goblinized" into orks and trolls, while many human children are born as elves, dwarves, and even more exotic creatures. In North America, indigenous peoples discovered that their traditional ceremonies allow them to command powerful spirits, and rituals associated with a new Ghost Dance movement let them take control of much of the western U.S. and Canada, where they formed a federation of Native American Nations. Seattle remains under U.S. control by treaty as a city-state enclave, and most game materials are set there and assume campaigns will use it as their setting. In parallel with these magical developments, the setting's 21st century features technological and social developments associated with cyberpunk science fiction. Megacorporations control the lives of their employees and command their own armies; many of the largest have extraterritoriality, such as currently enjoyed by foreign heads of state. Technological advances make cyberware (mechanical replacement body parts) and bioware (augmented vat-grown body parts implanted in place of or in tandem with natural organs) common. The Computer Crash of 2029 led to the creation of the Matrix, a worldwide computer network that users interact with via direct neural interface. When conflicts arise, corporations, governments, organized crime syndicates, and even wealthy individuals subcontract their dirty work to specialists, who then perform "shadowruns" or missions undertaken by deniable assets without identities or those that wish to remain unknown. The most skilled of these specialists, called shadowrunners, have earned a reputation for getting the job done. They have developed a knack for staying alive, and prospering, in the world of Shadowrun. The Shadowrun world is cross-genre, incorporating elements of both cyberpunk and urban fantasy. Unlike in a purely cyberpunk game, in the Shadowrun world, magic exists and has "worked" since 2011. Among other things, this split humankind into subtypes, also known as metatypes/metahumans. Some of these metatypes take the form of common fantasy races. Likewise, some animals have turned into familiar monsters of past fantasy and lore and both monsters and human magicians have regained magical powers. By the second half of the 21st century, in the time the game is set, these events are accepted as commonplace. Man, machine, and magic exist in a world where the amazing is among the most common and technology has entered into every facet of human (and metahuman) life. === Races === Characters in Shadowrun can be humans, orks, trolls, elves, dwarves, as well as certain diverging subspecies (known as metavariants) such as gnomes, giants, dryads, etc. In the early days, when magic returned to the world, humans began to either change into, or give birth to, elf and dwarf infants, a phenomenon called Unexplained Genetic Expression (UGE). Later, some juvenile and adult humans "goblinized" into other races (mostly orks, but also some trolls). The term "metahuman" is used either to refer to humanity as a whole, including all races, or to refer specifically to non-human races, depending on context. The return of Halley's Comet brought even further variation in the form of changelings, who have variation atypical to their metatype or even species, such as electroreception. Two of the metahuman races, elves and orks, have fictional languages. Additionally, a virus known as the Human Meta-Human Vampiric Virus (HMHVV), with many variant strains, has been known to cause f
WebCrow
The WebCrow is a research project carried out at the Information Engineering Department of the University of Siena with the purpose of automatically solving crosswords. == The Project == The scientific relevance of the project can be understood considering that cracking crosswords requires human-level knowledge. Unlike chess and related games and there is no closed world configuration space. A first nucleus of technology, such as search engines, information retrieval, and machine learning techniques enable computers to enfold with semantics real-life concepts. The project is based on a software system whose major assumption is to attack crosswords making use of the Web as its primary source of knowledge. WebCrow is very fast and often thrashes human challengers in competitions, especially on multi language crossword schemes. A distinct feature of the WebCrow software system is to combine properly natural language processing (NLP) techniques, the Google web search engine, and constraint satisfaction algorithms from artificial intelligence to acquire knowledge and to fill the schema. The most important component of WebCrow is the Web Search Module (WSM), which implements a domain specific web based question answering algorithm. The way WebCrow approaches crosswords solving is quite different with respect to humans: Whereas we tend to first answer clues we are sure of and then proceed filling the schema by exploiting the already answered clues as hints, WebCrow uses two clearly distinct stages. In the first one, it processes all the clues and tries to answer them all: For each clue it finds many possible candidates and sorts them according to complex ranking models mainly based on a probability criteria. In the second stage, WebCrow uses constraint satisfaction algorithms to fill the grid with the overall most likely combination of clue answers. In order to interact with Google, first of all, WebCrow needs to compose queries on the basis of the given clues. This is done by query expansion, whose purpose is to convert the clue into a query expressed by a simplified and more appropriate language for Google. The retrieved documents are parsed so as to extract a list of word candidates that are congruent with the crossword length constraints. Crosswords can hardly be faced by using encyclopedic knowledge only, since many clues are wordplays or are otherwise purposefully very ambiguous. This enigmatic component of crosswords is faced by a massive use of database of solved crosswords, and by automatic reasoning on a properly organized knowledge base of wired rules. Last but not the least, the final constraint satisfaction step is very effective to fill the correct candidate, even though, unlike humans, the system can not rely on very high confidence on the correctness of the answer. == Competitions == WebCrow speed and effectiveness has been tested many times in man-machine competitions on Italian, English and multi-language crosswords The outcome of the tests is that WebCrow can successfully compete with average human players on single language schemes and reaches expert level performance in multi-language crosswords. However, WebCrow has not reached expert level in single-language crosswords, yet. === ECAI-06 Competition === On August 30, 2006, at the European Conference on Artificial Intelligence (ECAI2006), 25 conference attendees and 53 internet connected crosswords lovers, competed with WebCrow in an official challenge organized within the conference program. The challenge consisted in 5 different crosswords (2 in Italian, 2 in English and one multi-language in Italian and English) and 15 minutes were assigned for each crossword. WebCrow ranked 21 out of 74 participants in the Italian competition, and won both the bilingual and English competitions. === Other Competitions === Several competitions have been held in Florence, Italy within the Creativity Festival in December 2006, and another official conference competition took place in Hyderabad, India in January 2007, within the International Conference of Artificial Intelligence, where it ranked second out of 25 participants.
2024 Bilderberg Conference
The 2024 Bilderberg Conference was held between May 30–June 2, 2024 in Madrid, Spain at the Eurostars Suites Mirasierra hotel. The 2024 meeting was the 70th edition of the event. A Bilderberg Group press release stated that there were 131 participants from around 25 countries. Established in 1954 by Prince Bernhard of the Netherlands, Bilderberg conferences (or meetings) are an annual private gathering of the European and North American political and business elite. Events are attended by between 120 and 150 people each year invited by the Bilderberg Group's steering committee; including prominent politicians, CEOs, national security experts, academics and journalists. Several US presidents have attended the meetings before winning a presidential election. These politicians include Bill Clinton and Barack Obama. Bilderberg conferences operate under the Chatham House Rule, meaning that participants are sworn to secrecy and cannot disclose the identity or affiliation of any particular speaker. == Agenda == The key topics for discussion were announced on the Bilderberg website shortly before the meeting. These topics included: == Participants == A list of 131 participants was published on the Bilderberg website. This list may not be complete, as a source connected to the Bilderberg group told The Daily Telegraph in 2013 that some attendees do not have their names publicized. King Felipe VI of Spain was reported to have attended the meeting despite his name not being on the list.
International Clinical Trials Registry Platform
The International Clinical Trials Registry Platform (ICTRP) is a platform for the registration of clinical trials operated by the World Health Organization. The ICTRP combines data from multiple cooperating clinical trials registries to generate a global view of clinical trials worldwide, with a search portal that allows access to the entire dataset. It requires a minimum standard set of database fields, the WHO Trial Registration Data Set, to be present for a trial to be registered. All entries are given a Universal Trial Number (UTN) that identifies them uniquely. The organization has sought to assist various national governments in establishing their own clinical trials databases. It combines data from the following primary registries and data providers: Australian New Zealand Clinical Trials Registry (ANZCTR) Brazilian Clinical Trials Registry (ReBec) Chinese Clinical Trial Registry (ChiCTR) Clinical Research Information Service (CRiS), Republic of Korea ClinicalTrials.gov Clinical Trials Information System (CTIS), European Medicines Agency Clinical Trials Registry - India (CTRI) Cuban Public Registry of Clinical Trials (RPCEC) EU Clinical Trials Register (EU-CTR) German Clinical Trials Register (DRKS) Iranian Registry of Clinical Trials (IRCT) ISRCTN (UK) International Traditional Medicine Clinical Trial Registry (ITMCTR) Japan Registry of Clinical Trials (jRCT) Japan Primary Registries Network (JPRN) Lebanese Clinical Trials Registry (LBCTR) Overview of Medical Research in the Netherlands (OMON) Thai Clinical Trials Registry (TCTR) Pan African Clinical Trial Registry (PACTR) Peruvian Clinical Trial Registry (REPEC) Sri Lanka Clinical Trials Registry (SLCTR)
DARPA Grand Challenge
The DARPA Grand Challenge is a prize competition for American autonomous vehicles, funded by the Defense Advanced Research Projects Agency, the most prominent research organization of the United States Department of Defense. Congress has authorized DARPA to award cash prizes to further DARPA's mission to sponsor revolutionary, high-payoff research that bridges the gap between fundamental discoveries and military use. The initial DARPA Grand Challenge in 2004 was created to spur the development of technologies needed to create the first fully autonomous ground vehicles capable of completing a substantial off-road course within a limited time. The third event, the DARPA Urban Challenge in 2007, extended the initial Challenge to autonomous operation in a mock urban environment. The 2012 DARPA Robotics Challenge, focused on autonomous emergency-maintenance robots, and new Challenges are still being conceived. The DARPA Subterranean Challenge was tasked with building robotic teams to autonomously map, navigate, and search subterranean environments. Such teams could be useful in exploring hazardous areas and in search and rescue. In addition to the challenges in autonomous technology, DARPA has also conducted prize competitions in other areas of technology. == History and background == Fully autonomous vehicles have been an international pursuit for many years, from endeavors in Japan (starting in 1977), Germany (Ernst Dickmanns and VaMP), Italy (the ARGO Project), the European Union (EUREKA Prometheus Project), the United States of America, and other countries. DARPA funded the development of the first fully autonomous robot beginning in 1966 with the Shakey the robot project at Stanford Research Institute, now SRI International. The first autonomous ground vehicle capable of driving on and off roads was developed by DARPA as part of the Strategic Computing Initiative beginning in 1984 leading to demonstrations of autonomous navigation by the Autonomous Land Vehicle and the Navlab. The Grand Challenge was the first long distance competition for driverless cars in the world; other research efforts in the field of driverless cars take a more traditional commercial or academic approach. The U.S. Congress authorized DARPA to offer prize money ($1 million) for the first Grand Challenge to facilitate robotic development, with the ultimate goal of making one-third of ground military forces autonomous by 2015. Following the 2004 event, Dr. Tony Tether, the director of DARPA, announced that the prize money had been increased to $2 million for the next event, which was claimed on October 9, 2005. The first, second and third places in the 2007 Urban Challenge received $2 million, $1 million, and $500,000, respectively. 14 new teams have qualified in year 2015. The competition was open to teams and organizations from around the world, as long as there was at least one U.S. citizen on the roster. Teams have participated from high schools, universities, businesses and other organizations. More than 100 teams registered in the first year, bringing a wide variety of technological skills to the race. In the second year, 195 teams from 36 U.S. states and 4 foreign countries entered the race. == 2004 Grand Challenge == The first competition of the DARPA Grand Challenge was held on March 13, 2004 in the Mojave Desert region of the United States, along a 150-mile (240 km) route that follows along the path of Interstate 15 from just before Barstow, California to just past the California–Nevada border in Primm. None of the robot vehicles finished the route. Carnegie Mellon University's Red Team and car Sandstorm (a converted Humvee) traveled the farthest distance, completing 11.78 km (7.32 mi) of the course before getting hung up on a rock after making a switchback turn. No winner was declared, and the cash prize was not given. Therefore, a second DARPA Grand Challenge event was scheduled for 2005. == 2005 Grand Challenge == The second competition of the DARPA Grand Challenge began at 6:40 am on October 8, 2005. All but one of the 23 finalists in the 2005 race surpassed the 11.78 km (7.32 mi) distance completed by the best vehicle in the 2004 race. Five vehicles successfully completed the 212 km (132 mi) course: Vehicles in the 2005 race passed through three narrow tunnels and negotiated more than 100 sharp left and right turns. The race concluded through Beer Bottle Pass, a winding mountain pass with a sheer drop-off on one side and a rock face on the other. Although the 2004 course required more elevation gain and some very sharp switchbacks (Daggett Ridge) were required near the beginning of the route, the course had far fewer curves and generally wider roads than the 2005 course. The natural rivalry between the teams from Stanford and Carnegie Mellon (Sebastian Thrun, head of the Stanford team was previously a faculty member at Carnegie Mellon and colleague of Red Whittaker, head of the CMU team) was played out during the race. Mechanical problems plagued H1ghlander before it was passed by Stanley. Gray Team's entry was a miracle in itself, as the team from the suburbs of New Orleans was caught in Hurricane Katrina a few short weeks before the race. The fifth finisher, Terramax, a 30,000 pound entry from Oshkosh Truck, finished on the second day. The huge truck spent the night idling on the course, but was particularly nimble in carefully picking its way down the narrow roads of Beer Bottle Pass. == 2007 Urban Challenge == The third competition of the DARPA Grand Challenge, known as the "Urban Challenge", took place on November 3, 2007 at the site of the now-closed George Air Force Base (currently used as Southern California Logistics Airport), in Victorville, California (Google map). The course involved a 96 km (60 mi) urban area course, to be completed in less than 6 hours. Rules included obeying all traffic regulations while negotiating with other traffic and obstacles and merging into traffic. Unlike previous challenges, the 2007 Urban Challenge organizers divided competitors into two "tracks", A and B. All Track A and Track B teams were part of the same competition circuit, but the teams chosen for the Track A program received US $1 million in funding. These 11 teams largely represented major universities and large corporate interests such as CMU teaming with GM as Tartan Racing, Stanford teaming with Volkswagen, Virginia Tech teaming with TORC Robotics as VictorTango, Oshkosh Truck, Honeywell, Raytheon, Caltech, Autonomous Solutions, Cornell University, and MIT. One of the few independent entries in Track A was the Golem Group. DARPA has not publicly explained the rationale behind the selection of Track A teams. Teams were given maps sparsely charting the waypoints that defined the competition courses. At least one team, Tartan Racing, enhanced the maps through the insertion of additional extrapolated waypoints for improved navigation. A debriefing paper published by Team Jefferson illustrates graphically the contrast between the course map it was given by DARPA and the course map used by Tartan Racing. Tartan Racing claimed the $2 million prize with their vehicle "Boss", a Chevy Tahoe. The second-place finisher earning the $1 million prize was the Stanford Racing Team with their entry "Junior", a 2006 Volkswagen Passat. Coming in third place was team VictorTango, winning the $500,000 prize with their 2005 Ford Escape hybrid, "Odin". MIT placed 4th, with Cornell University and University of Pennsylvania/Lehigh University also completing the course. The six teams that successfully finished the entire course: While the 2004 and 2005 events were more physically challenging for the vehicles, the robots operated in isolation and only encountered other vehicles on the course when attempting to pass. The Urban Challenge required designers to build vehicles able to obey all traffic laws while they detect and avoid other robots on the course. This is a particular challenge for vehicle software, as vehicles must make "intelligent" decisions in real time based on the actions of other vehicles. Other than previous autonomous vehicle efforts that focused on structured situations such as highway driving with little interaction between the vehicles, this competition operated in a more cluttered urban environment and required the cars to perform sophisticated interactions with each other, such as maintaining precedence at a 4-way stop intersection. == 2012 Robotics Challenge == The DARPA Robotics Challenge is an ongoing competition focusing on humanoid robotics. The primary goal of the program is to develop ground robotic capabilities to execute complex tasks in dangerous, degraded, human-engineered environments. It launched in October 2012, and hosted the Virtual Robotics Competition in June 2013. Two more competitions are planned: the DRC Trials in December 2013, and the DRC Finals in December 2014. Unlike prior Challenges, the construction of the "vehicles" w