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The AI effect is the discounting of the behavior of an artificial-intelligence program as not "real" intelligence. [1]The author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to ...
These models exhibit human-like traits of knowledge, attention, and creativity, and have been integrated into various sectors, fueling exponential investment in AI. However, concerns about the potential risks and ethical implications of advanced AI have also emerged, prompting debate about the future of AI and its impact on society.
[1] The conference community includes lawyers, practitioners, and academics in computer science, philosophy, public policy, economics, human-computer interaction, and more. As of 2022, the conference is sponsored by the National Science Foundation as well as various large technology companies including Google, DeepMind, Meta, and IBM Research. [2]
Regarding the potential for smarter-than-human systems to be employed militarily, the Open Philanthropy Project writes that these scenarios "seem potentially as important as the risks related to loss of control", but research investigating AI's long-run social impact have spent relatively little time on this concern: "this class of scenarios ...
An artificial superintelligence (ASI) is a hypothetical type of AGI that is much more generally intelligent than humans, [23] while the notion of transformative AI relates to AI having a large impact on society, for example, similar to the agricultural or industrial revolution. [24]
E.g., in Northern Virginia, the largest global hub for AI data centers, the timeline for connecting bigger facilities—those requiring over 100 megawatts of power—to the electrical grid has extended to seven years, highlighting the strain on the energy infrastructure and the challenge of meeting AI’s escalating power needs.
The companies committed to ensure AI products undergo both internal and external security testing before public release; to share information on the management of AI risks with the industry, governments, civil society, and academia; to prioritize cybersecurity and protect proprietary AI system components; to develop mechanisms to inform users ...
The AI boom [1] [2] is an ongoing period of rapid progress in the field of artificial intelligence (AI) that started in the late 2010s before gaining international prominence in the early 2020s. Examples include protein folding prediction led by Google DeepMind as well as large language models and generative AI applications developed by OpenAI .