{"success":true,"data":{"query":"Gadrael Expertise","limit":10,"count":3,"sources":["wiki_real_estate.hat","wiki_artificial_intelligence.hat"],"synced":[],"results":[{"source":"wiki_real_estate.hat","text":"Project specifics\nWhen an architecture firm is working on a project that is outside their geographic location or range of expertise, it will often choose to work with an architect that is either local to the project site or skilled in that particular area of expertise. In this case, the primary architect works with the local architect in order to complete the project, and the local architect becomes the \"architect of record.\" This type of working relationship is common when high-profile architects (or \"starchitects\") win design bids but find themselves in need of architects with more practical skills or knowledge of local conditions. Or more pragmatically, the high-profile architect simply needs an architect who is local to the project site, facilitating quicker site visits and project oversight.\nThe local architecture firms that are responsible for corresponding with city agencies about code compliance, tender documents, client communication and creating up to 90 percent of the construction documents and carry out construction inspections are similar, but should be referred to as the \"executive architect.\" \n\n\n== References ==\n\n--- NEXT ARTICLE ---","score":36.327294707324214,"links":[]},{"source":"wiki_artificial_intelligence.hat","text":"Symbolic AI and its limits\nSymbolic AI (or \"GOFAI\") simulated the high-level conscious reasoning that people use when they solve puzzles, express legal reasoning and do mathematics. They were highly successful at \"intelligent\" tasks such as algebra or IQ tests. In the 1960s, Newell and Simon proposed the physical symbol systems hypothesis: \"A physical symbol system has the necessary and sufficient means of general intelligent action.\"\nHowever, the symbolic approach failed on many tasks that humans solve easily, such as learning, recognizing an object or commonsense reasoning. Moravec's paradox is the discovery that high-level \"intelligent\" tasks were easy for AI, but low level \"instinctive\" tasks were extremely difficult. Philosopher Hubert Dreyfus had argued since the 1960s that human expertise depends on unconscious instinct rather than conscious symbol manipulation, and on having a \"feel\" for the situation, rather than explicit symbolic knowledge. Although his arguments had been ridiculed and ignored when they were first presented, eventually, AI research came to agree with him.\nThe issue is not resolved: sub-symbolic reasoning can make many of the same inscrutable mistakes that human intuition does, such as algorithmic bias. Critics such as Noam Chomsky argue continuing research into symbolic AI will still be necessary to attain general intelligence, in part because sub-symbolic AI is a move away from explainable AI: it can be difficult or impossible to understand why a modern statistical AI program made a particular decision. The emerging field of neuro-symbolic artificial intelligence attempts to bridge the two approaches.","score":31.583209025129094,"links":[]},{"source":"wiki_artificial_intelligence.hat","text":"Register and style\nAI systems can appear more human through the use of phatic expressions, which are speech that humans use to facilitate social relations but that do not convey any information (such as small talk). AI expressions of uncertainty, which are often implemented for the purpose of preventing the user from taking all outputs as factual, may boost anthropomorphic signals. Additionally, AIs are often designed to emulate character-based personas, which can overall have very strong anthropomorphic effects.\n\nRoles\nAIs are also sometimes trained to play into roles that enhance anthropomorphic perceptions. For example, the majority of dialogue-based systems are designed to be in service of people in subservient roles; this has led to instances of users verbally abusing the systems, sometimes targeting them with gender-based slurs. AI systems have been shown to sometimes respond even more subserviently to the abuse, perpetuating the behavior. AIs also often present as having a high degree of expertise; humans tend to infer higher credibility of outputs in these cases, as they would when presented with information from an expert human.","score":31.583209025129094,"links":[]}]},"metadata":{},"timestamp":"2026-07-08T22:52:15.109Z"}