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Mark Carney on the rupturing world order in Davos. This is an important call to collective action.
cbc.ca/player/play/video/9.705

This is how superficial one needs to get to justify an argument of US global supremacy. Arthur Herman and WSJ deliberately choose to ignore Taiwan's unmatched leadership in superconductors and China's in energy. Instead, they turn to Soviet-style resources and headcount arguments. Apparently there is a force driving them to sacrifice whatever authority they might still have.
"China remains formidable. But from Europe and the Middle East to South America and Southeast Asia, the U.S. sets the agenda while China struggles with a leadership crisis. Beijing’s one remaining strategic initiative is its threat to Taiwan. Although very real, this threat is directed at an island less than 100 miles off its coast with 1/60th of its population, which perfectly sums up China’s shrinking influence."
wsj.com/opinion/america-is-the

Based also on what Bruce Schneier recently wrote about AI security, there's no real way to secure against these kind of attacks without restricting LLMs to the point of making them much less useful.

promptarmor.com/resources/clau

EU lawmakers are poised to halt approval of trade deals with the U.S. over Donald Trump’s vow to impose tariffs on countries that supported Greenland in the face of American threats. japantimes.co.jp/business/2026 #business #economy #us #donaldtrump #greenland #eu #europe #tariffs #trade #denmark

Saint Thecla, a second-century woman, survived being burned at the stake, faced lions and killer seals in an arena, and became an early example of women preaching and baptizing. theconversation.com/thecla-the

Beef cattle production accounts for 3.7% of U.S. greenhouse gas emissions. Experts in cow burps and meat processing say the industry can become more sustainable by experimenting with virtual fencing, feed additives to reduce methane and using every part of the animal. theconversation.com/colorado-r

First came artists. They made art. You could've liked it or not, but it had an impact of some sort, felt or not.

Then came designers. They had to make good works. They studied what good means and tried to master it. They didn't always succeed but they got better with practice and rarely produced real embarrassments.

Finally came engines and models. They just produced content. It had to be coming out daily. Few bothered to read it, let alone assess or judge it.

Mladenov – who has worked as a United Nations diplomat in the Middle East – is seen as an administrator, but one who may not be capable of pushing back against Israel and representing Palestinians in Gaza.

aljazeera.com/…/scepticism-hope-gaza-reacts-trump…

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College graduates earn $1.2 million more over their lifetime than high school graduates, and unemployment rates are half as high. But as skepticism about college grows, universities need to weave creativity and invention into undergraduate education to prove their value.

theconversation.com/financial-

Schools have long taught that humans populated North America around 12K yrs ago by crossing the Bering land bridge. This story supports settler colonialism, and contradicts #Indigenous stories, which offer memories of human habitation here during the last glacial maximum.

Also, the Bering land bridge story falls apart when you find out about the century of archaeological evidence academia has vigorously suppressed.

Read more in my new essay. 👇

hcn.org/issues/58-1/what-does-

This are everyday heroes, risking their lives for justice. Sadly, having found a life-sacrificing way to advance their fight. As a society we have a moral obligation to make their goals attainable without resorting to suicide.
aljazeera.com/news/2026/1/13/u

Great to see that @hennavirkkunen, the @EUCommission Vice-President for Tech Sovereignty, Security and Democracy joined Mastodon: Welcome!

There are now sufficiently many different examples of Erdos problems that have been resolved with various amounts of AI assistance and formal verification (see github.com/teorth/erdosproblem for a summary) that one can start to discern general trends.

Broadly speaking, we now see an empirical tradeoff between the level of AI involvement in the solution, and the difficulty or novelty of that solution. In particular, the recent solutions have spanned a spectrum roughly describable as follows:

1. Completely autonomous AI solutions to Erdos problems that are short and largely follow a standard technique. (In many, but not all, of these cases, some existing literature was found that proved a very similar result by a similar method.)

2. AI-powered modifications of existing solutions (which could be either human-generated or AI-generated) that managed to improve or modify these solutions in various ways, for instance by upgrading a partial solution to a full solution, or optimizing the parameters of the proof.

3. Complex interactions between humans and AI tools in which the AI tools provided crucial calculations, or proofs of key steps, allowing the collaboration to achieve moderately complicated and novel solutions to open problems.

4. Difficult research-level papers solving one or more Erdos problems by mostly traditional human means, but for which AI tools were useful for secondary tasks such as generation of code, numerics, references, or pictures.

(1/2)

See here for examples:

bsky.app/…/unitedkingdom.feddit.uk.ap.brid.gy
retrolemmy.com/post/31790836/17287584

There is still more testing and development needed, check the issue for more details.

I think I now know where to draw the line between "good" and "bad" , and possibly (or rather obviously) the same for . It's simply whether the input data has been constructed rigorously. Put this way it's the most obvious statement ever, but somehow have convinced us all that they advance research by recklessly scraping , and who knows what else (they keep their training data secret).

What is good science in computational linguistics? Well, open data is a step towards it. But open and crap is not a solution. We need to actually _know_ and manage the data. And nobody in their right mind would want to plough through toxic data to clean it. We've all heard the horrors of Kenyan data workers who do it for money and still suffer doing it.

But better (yes, also smaller) corpora are of interest to scholars in the humanities and the social sciences. Think of textcreationpartnership.org or mlat.uzh.ch. Yes, they are too big for individual researchers or even teams to handle, but we have the organisational and technological infrastructure to work on them collectively. We've been doing it for ages and we will continue doing it. We just need to do it together.

And this is the goal of the European Research Council project proposal I'm submitting in this very moment.

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