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  • +7
    Generative AI, sometimes called gen AI, is artificial intelligence (AI) that can create original con
    Generative AI, sometimes called gen AI, is artificial intelligence (AI) that can create original content such as text, images, video, audio or software code in response to a user’s prompt or request.

    Generative AI relies on sophisticated machine learning models called deep learning models algorithms that simulate the learning and decision-making processes of the human brain. These models work by identifying and encoding the patterns and relationships in huge amounts of data, and then using that information to understand users' natural language requests or questions and respond with relevant new content.

    AI has been a hot technology topic for the past decade, but generative AI, and specifically the arrival of ChatGPT in 2022, has thrust AI into worldwide headlines and launched an unprecedented surge of AI innovation and adoption. Generative AI offers enormous productivity benefits for individuals and organizations, and while it also presents very real challenges and risks, businesses are forging ahead, exploring how the technology can improve their internal workflows and enrich their products and services. According to research by the management consulting firm McKinsey, one third of organizations are already using generative AI regularly in at least one business function.¹ Industry analyst Gartner projects more than 80% of organizations will have deployed generative AI applications or used generative AI application programming interfaces (APIs) by 2026
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  • +7
    What is generative AI? Generative AI, sometimes called gen AI, is artificial intelligence (AI) that
    Generative AI, sometimes called gen AI, is artificial intelligence (AI) that can create original content such as text, images, video, audio or software code in response to a user’s prompt or request.

    Generative AI relies on sophisticated machine learning models called deep learning models algorithms that simulate the learning and decision-making processes of the human brain. These models work by identifying and encoding the patterns and relationships in huge amounts of data, and then using that information to understand users' natural language requests or questions and respond with relevant new content.

    AI has been a hot technology topic for the past decade, but generative AI, and specifically the arrival of ChatGPT in 2022, has thrust AI into worldwide headlines and launched an unprecedented surge of AI innovation and adoption. Generative AI offers enormous productivity benefits for individuals and organizations, and while it also presents very real challenges and risks, businesses are forging ahead, exploring how the technology can improve their internal workflows and enrich their products and services. According to research by the management consulting firm McKinsey, one third of organizations are already using generative AI regularly in at least one business function.¹ Industry analyst Gartner projects more than 80% of organizations will have deployed generative AI applications or used generative AI application programming interfaces (APIs) by 2026.
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  • Housing
    Subsidized housing in the United States is administered by federal, state and local agencies to provide subsidized rental assistance for low-income households. Public housing is priced much below the market rate, allowing people to live in more convenient locations rather than move away from the city in search of lower rents. In most federally-funded rental assistance programs, the tenants' monthly rent is set at 30% of their household income.[1] Now increasingly provided in a variety of settings and formats, originally public housing in the U.S. consisted primarily of one or more concentrated blocks of low-rise and/or high-rise apartment buildings. These complexes are operated by state and local housing authorities which are authorized and funded by the United States Department of Housing and Urban Development (HUD). More than 1.2 million households currently live in public housing of some type.[vague] Subsidized apartment buildings, often referred to as housing projects, have a complicated and often notorious history in the United States. While the first decades of projects were built with higher construction standards and a broader range of incomes and same applicants, over time, public housing increasingly became the housing of last resort in many cities. Several reasons have been cited for this negative trend including the failure of Congress to provide sufficient funding, a lowering of standards for occupancy, and mismanagement at the local level. Furthermore, housing projects have also been seen to greatly increase concentrated poverty in a community, leading to several negative externalities. Crime, drug usage, and educational under-performance are all widely associated with housing projects, particularly in urban areas.[2]

    As a result of their various problems and diminished political support, many of the traditional low-income public housing properties constructed in the earlier years of the program have been demolished. Beginning primarily in the 1970s the federal government turned to other approaches including the Project-Based Section 8 program, Section 8 certificates, and the Housing Choice Voucher Program. In the 1990s the federal government accelerated the transformation of traditional public housing through HUD's HOPE VI Program. Hope VI funds are used to tear down distressed public housing projects and replace them with mixed communities constructed in cooperation with private partners.[3] In 2012, Congress and HUD initiated a new program called the Rental Assistance Demonstration (RAD) program.[4] Under the demonstration program, eligible public housing properties are redeveloped in conjunction with private developers and investors.
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