kzrdude

We divide competitions into classes (by sex and age is common, for example "17 yo boys", and similar competition classes), so I don't see why it shouldn't be subject to the same kind of class distinction, maybe with an without augmentation.

I think "experts" are a misnomer because it's not that 1 expert = 1 component, like it makes it sound. "Experts" in different layers have no relation.

If they are checking the charging at exactly the minute, then start of charge will happen then too, which will create a spike if it's synchronized with many others doing the same thing.

In the video in the thread, it seems to go from fully extended airplane to pancake in about two frames, which is, again, harrowing, horrible.

Reading what the pilot said is pretty harrowing. We know a lot from what the pilot already said over the radio (and maybe that's the best info we'll get, are there any remains left?)

It happened in France on 12 October: https://www.bbc.com/news/articles/crq5nzxv9q4yo

Well, that's kind of a good use of vibe coding. Let the clanker make the app and you focus on the art itself, the writing.

It's also the colours of the Norwegian flag (as well as the US flag). I think the flag is quite literally coloured by the time when the flag was created (1820s, post French revolution).

This is about a second step of decoding.

Qr -> URL -> Panic Log

Yes: most mainland Norway ice was gone during the holocene climatic optimum (9–6 thousand years ago), and glaciers recovered since then (until approx the 20th century, when deglaciation started accelerating again).

The climate is varying in long cycles, and the deglaciation 20 thousand years ago (last glacial maximum) was driven by a spike in summer temperatures, and this peak has already long passed. Ice ages and interglacial periods have a certain momentum to them, so it takes more than just that to go back to full ice age..

Is it different between major models how they scale with reasoning level? Some models where it hardly pays off? I expect it to be very similar across the board.

3b1b recent podcast with Steven Strogatz on the Humanity of Math, https://www.youtube.com/watch?v=xUSznTR2cwc

And we note that these specializations are part of production Python and will not be removed when the JIT is removed.

That's not how academic literature works. The structure is like this: Statement (Citation). The citation is not an affirmation of truth but a content declaration; this statement is supported by this publication. The receipts are there, so that you can trace the argumentation and make your own conclusions if necessary.

'Knowledge' formed this way is a living, evolving graph, and sometimes links are broken (findings are reevaluated or disproven); having the content declaration so clearly in the open makes it easier to deal with this evolving landscape.

LLMs cook up new sentences based on probability, based on everything in their training and their context. There's just nothing in their model that traces provenance of facts, they physically don't store that information. Once they have written a sentence, they can't tell you from which work they got this information.

There are tools where they try to retroactively add references, the LLM interfaces try to do this, but it's usually inaccurate.

I think of the way a scientific article works. "The sky is blue (Pearson, 1992)." The writer is fully aware what the factual statement is and which publication supports it (not just that, but which kind of publication - primary, secondary source, peer reviewed?). An LLM can try to imitate this, but the actual information to support this does not exist in its training.

There is a reason why LLMs can not be good at this: They don't know what they are quoting or citing. A different kind of model with factoid provenance could do it?

Google has flash-lite, too. I liked OpenAi's scheme better, as long as it is parallel and makes sense.

A dispersant should divide the oil into much smaller particles = larger surface area, which by itself should speed up any natural biodegradation significantly. Of course, once it settles on the sea floor, most of that effect is gone again (it's not dispersed in water anymore). But IF there is something that can consume the oil, dispersing it into microdroplets is not necessarily a bad idea?

That announcement arrived 2 hours ago (on x), so now they have.

This is called a hybrid reasoning because the reasoning can be mapped to text and is therefore introspectable, with tooling. That should address the concern, I think.

Just yesterday there was just one public revision of 4.1, and they listed they were using 'Deepseek v4.1 flash'. I assume they will update their website if they update the model version (and use the version in the name).

Presumably. The current opencode slug for the model is just 'deepseek-flash' suggesting they will just update that one going forward, not keeping versions in parallel.

It's a 51 hour video but I still don't think that's enough time to play 1000 games. How did it work?

I saw a lot of sad horses in Sevilla, with above 36°C that day

I think prediction is about something you don't know. What happens in the future is that you might come to know.

For example, we predict that there is gold in X location.

How ironic that the Readme is completely unreadable, like gibberish rivalled only by the Voynich manuscript itself.

But id the progress of decoding it is legit, you should write something properly about it!

I think that's fair, and they only get as much importance and attention as we give them.

The committee in this case is based on retired or ageing Norwegian politicians. That's the construction that we can't do so much about (the will), but I think it's unfortunate for the prize. I think a more independent committee would have been better. I agree with the common criticism that they have given several prizes too rashly or too soon.

They have really not made the impression that they are independent of politics, all laureates taken together. But if they improve I'm all for it.

It would be way easier for us to beat overconsumption and promote sustainability of it wasn't for status, in fact. New iphones and fresh clothes are not necessary for life, but socially, people crave them.