• 27 Posts
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Joined 24 days ago
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Cake day: January 29th, 2025

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  • There is another source related to the topic:

    With US funding freeze, China nonprofits are facing extinction. They need emergency assistance. – (Archived version)

    An entire ecosystem of vital China-related work is now in crisis. When the Trump administration froze foreign funding and USAID programs last week, dozens of scrappy nonprofits in Hong Kong, Taiwan, and the US were immediately affected. Staff are losing their jobs; some organizations face imminent closure due to lack of funding; others are paring back their programming.

    In many cases, these organisations provide our last window into what is actually happening in China. They do the painstaking and often personally risky work of tracking Chinese media censorship, tallying local protests, uncovering human rights violations, documenting the Uyghur genocide, and supporting what remains of civil society in China. They provide platforms for Chinese people to speak freely; they help keep the dream of democracy in China alive. I’m not listing the names of any specific organisations at this time, because some prefer not to disclose that they receive foreign funding. Beijing believes funding that supports free speech and human rights is interference by ‘hostile foreign forces’.

    As China’s President Xi Jinping has squeezed Chinese civil society and expelled journalists, information from inside China has got harder and harder to access. The 2017 Chinese foreign NGO law crushed US and other foreign nonprofits based in China. Some moved to Hong Kong or elsewhere. The spending freeze may deal them a death blow.






















  • The guys at HF (and many others) appear to have a different understanding of Open Source.

    As the Open Source AI definition says, among others:

    Data Information: Sufficiently detailed information about the data used to train the system so that a skilled person can build a substantially equivalent system. Data Information shall be made available under OSI-approved terms.

    • In particular, this must include: (1) the complete description of all data used for training, including (if used) of unshareable data, disclosing the provenance of the data, its scope and characteristics, how the data was obtained and selected, the labeling procedures, and data processing and filtering methodologies; (2) a listing of all publicly available training data and where to obtain it; and (3) a listing of all training data obtainable from third parties and where to obtain it, including for fee.

    Code: The complete source code used to train and run the system. The Code shall represent the full specification of how the data was processed and filtered, and how the training was done. Code shall be made available under OSI-approved licenses.

    • For example, if used, this must include code used for processing and filtering data, code used for training including arguments and settings used, validation and testing, supporting libraries like tokenizers and hyperparameters search code, inference code, and model architecture.

    Parameters: The model parameters, such as weights or other configuration settings. Parameters shall be made available under OSI-approved terms.

    • The licensing or other terms applied to these elements and to any combination thereof may contain conditions that require any modified version to be released under the same terms as the original.

    These three components -data, code, parameter- shall be released under the same condition.