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A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.
Stanford University researchers issued a report on Wednesday measuring the transparency of artificial intelligence foundation models from companies like OpenAI and Google, and the authors urged ...
Supporters said it would set some of the first much-needed safety ground rules for large-scale AI models in the United States. The bill targets systems that require more than $100 million in data ...
Discussions on regulation of artificial intelligence in the United States have included topics such as the timeliness of regulating AI, the nature of the federal regulatory framework to govern and promote AI, including what agency should lead, the regulatory and governing powers of that agency, and how to update regulations in the face of rapidly changing technology, as well as the roles of ...
The Pan-Canadian Artificial Intelligence Strategy (2017) is supported by federal funding of Can $125 million with the objectives of increasing the number of outstanding AI researchers and skilled graduates in Canada, establishing nodes of scientific excellence at the three major AI centres, developing 'global thought leadership' on the economic ...
The UK’s competition watchdog has warned of its growing concern about the state of the market for artificial intelligence foundation models, in particular the power a handful of large companies ...
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]
AI regulation is also sometimes advocated for in order to prevent bias and privacy violations. [6] However, it has been criticized as possibly leading to regulatory capture by large AI companies like OpenAI, in which regulation advances the interest of larger companies at the expense of smaller competition and the public in general. [6]