Thus it might be the first example of AI winning a case that sets some kind of precedent.

At the very least it shows that AI can put together coherent legal arguments even when there are no close precedents or case law it can refer to. This was something a lot of lawyers didn't believe would be possible for AI to do.

Comments URL: https://news.ycombinator.com/item?id=49326817

Points: 4

# Comments: 0

In a large number of few fields, all of those statements will be true in the near future (10 years maximum).

There's no reason that the Humboldtian model should be the right structure for the next century's universities, just as it wasn't the right structure for the 18th century's universities.

Comments URL: https://news.ycombinator.com/item?id=46970734

Points: 3

# Comments: 1

So of course no journal or conference is in the least bit interested, and I'm now reformatting it for another obscure low-tier journal that no-one will ever read.

Otherwise:

- automating the translation of a Byzantine Greek work that has never been translated into English before. https://stephanos.symmachus.org

- also preparing evidence for a case against the university I sometimes work for.

[+] Linear regression, but instead of minimising the Euclidean distance, minimise the p-adic distance - https://en.wikipedia.org/wiki/P-adic_valuation

Also, trying to finish a PhD on machine learning when you want to minimise a p-adic loss.

Surprisingly, no, it wasn't. I'll slightly fudge the numbers and talk in terms of proportion of world trade that was carried by ocean-going vessels (because if you double the population then it's reasonable to talk about doubling the number of ships).

The world economy was very globalised in 1913. That level of globalisation in trade wasn't matched again until the 1990s.

We're only a little more global now than we were in the age of sail.

The British navy and merchant fleet was a wonder of its era.

Comments URL: https://news.ycombinator.com/item?id=45615530

Points: 1

# Comments: 0

It's similar to the logic behind anti-trust actions against monopolists. If the playing field isn't level, then the USA government steps in to level it.

(Whether BYD is subsidised or not is another question, but the above is the logic of protecting local industry.)

That said, fine tuning small models because you have to power through vast amounts of data where a larger model might be cost ineffective -- that's completely sensible, and not really mentioned in the article.

Comments URL: https://news.ycombinator.com/item?id=44242853

Points: 1

# Comments: 0

https://solresol.substack.com/p/you-can-no-longer-set-an-und...

https://bead-sort.arithmetic.guru/

Oh, and also a PhD on p-adic machine learning, but no one will remember that.

Comments URL: https://news.ycombinator.com/item?id=44069609

Points: 2

# Comments: 0

Here's my workflow that keeps failing: - it writes some code. It looks good a first glance - I push it to github - automated tests on github show that there's a problem - go back to codex and ask it to fix it - it does stuff. It looks good again.

Now what do I do? If I ask it to push again to github, then it will often create a pull request that doesn't include stuff from the first pull request, but it's not a pull request that stacks on top of the previous pull request, it's a pull request that stacks on top of main.

When asked to write something that called out to gpt-4.1-mini, it used openai.ChatCompletion.create (!?!!?)

I just found myself using claude to fix codex's mistakes.