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@fkamiah17

Mistaken identify!!!, there was bloody big LOGO on the vehicle.

@bonifartius @inquiline@union.place

But keeping lots of animals together = bigger yield, more profit and bigger shareholder dividends

So common sense and public health vs capitalism, we have an uphill climb here I guess.

@zleap @inquiline@union.place clearly bird flu is the next in line - we already had a swine-flu scare after all. it even had it's own rushed and flawed vaccine, [pandemrix](en.wikipedia.org/wiki/Pandemri). at least back then a handful of cases was enough to properly investigate and stop things, compared to ten years later.

if anything these animal pathogens tell us something about how we should and shouldn't do agriculture. maybe keeping thousands of the same animal in close proximity isn't that clever.

@arXiv_csCY_bot

Sharing this as it may be of interest to people here too. Found on arXiv

Decentralised Moderation for Interoperable Social Networks: A Conversation-based Approach for Pleroma and the Fediverse

Vibhor Agarwal, Aravindh Raman, Nishanth Sastry, Ahmed M. Abdelmoniem, Gareth Tyson, Ignacio Castro
arxiv.org/abs/2404.03048 arxiv.org/pdf/2404.03048

arXiv:2404.03048v1 Announce Type: new
Abstract: The recent development of decentralised and interoperable social networks (such as the "fediverse") creates new challenges for content moderators. This is because millions of posts generated on one server can easily "spread" to another, even if the recipient server has very different moderation policies. An obvious solution would be to leverage moderation tools to automatically tag (and filter) posts that contravene moderation policies, e.g. related to toxic speech. Recent work has exploited the conversational context of a post to improve this automatic tagging, e.g. using the replies to a post to help classify if it contains toxic speech. This has shown particular potential in environments with large training sets that contain complete conversations. This, however, creates challenges in a decentralised context, as a single conversation may be fragmented across multiple servers. Thus, each server only has a partial view of an entire conversation because conversations are often federated across servers in a non-synchronized fashion. To address this, we propose a decentralised conversation-aware content moderation approach suitable for the fediverse. Our approach employs a graph deep learning model (GraphNLI) trained locally on each server. The model exploits local data to train a model that combines post and conversational information captured through random walks to detect toxicity. We evaluate our approach with data from Pleroma, a major decentralised and interoperable micro-blogging network containing 2 million conversations. Our model effectively detects toxicity on larger instances, exclusively trained using their local post information (0.8837 macro-F1). Our approach has considerable scope to improve moderation in decentralised and interoperable social networks such as Pleroma or Mastodon.

@inquiline@union.place

The next pandemic is probably just around the corner, as usual the human race is complacent.

I wish more people who are worried about FOSS supply side attacks would realize that universal basic income and free healthcare would result in an almost infinite stream of excellent software from people who care more about quality than profit.

@dev_ric

You had to do something like that in the first Dizzy game, so you can make a potion to defeat the enemy

Seriously, how cool is this?

Cosmologists have now measured how the expansion of the universe changes over time, to an accuracy of 1%.

They did it by finding frozen sound waves from the Big Bang, and then tracking them across 11 billion years. People can do these things!

youtube.com/watch?v=hoOyOAAj4i #science #nature #astronomy #space

@cdarwin

Ok I have no evidence to back this up BUT I would suspect the UK will be targeted too.

@mxtthxw @neil

This aside, scams are getting more sophisticated, even the most meticulous person can fall for them.

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