madisen

An alternative process entails introducing additional rules and limits to reuse while adhering to the general vision of the commons. Such a more robust form of commons-based ordering has often not been considered a form of openness in the past 3 . It involves harnessing non-copyright-based tools, introducing other legal mechanisms, and considering... See more

Mixture of experts , MoE or ME for short, is an ensemble learning technique that implements the idea of training experts on subtasks of a predictive modeling problem.

In the neural network community, several researchers have examined the decomposition methodology. [...] Mixture–of–Experts (ME) methodology that decomposes the input space, such that

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Open systems – free speech, democracy, open content, open science – will sometimes produce results we do not like. That openness, of course, will be used by the powerful as well as the powerless. There will be cruel speech, bad democratic decisions and uses of openly licensed content with which we disagree. Thus, it is very easy to blame openness.... See more

As the regime governing intellectual property rights evolved and began disproportionately favoring IP rights owners, the concept of openness became a tool for challenging power relations and striving for more equality. In that sense, the promotion of reuse and access to informational resources was fully compatible with the need to defend human... See more

the way in which TikTok enables creativity and community building by supporting the reuse of soundtracks, stitching, and dueting, leading to cultural phenomena founded on collaboration

How do you solve that by collecting everything? Because even if you’re collecting it and it’s right there, they don’t want to believe it.

Some may. All we can do is to collect it and make it easily available. What’s exciting to me is that not only can we now see that there are these separate worlds, but also we can see across universes. We can see... See more

The key is that knowledge is a human endeavor, and the development of Wikipedia and its sister projects depends on human collaboration and consensus. Machine learning tools can augment the process, but AI cannot replace volunteer Wikimedians.