phi0

Outside the capital, in places where tourists do not visit, living standards fall well below Mississippi’s

The article appears to treat nominal GDP per capita as a measure of living standards, which is obviously nonsense. Rather than looking at things like the Human Development Index or World Happiness Report, in both of which the UK outranks the US (incl. all the non-Mississippi states).

Residents consistently reporting higher life satisfaction and happiness likely speaks more to their living standards than non-purchasing power parity adjusted GDP per capita.

It is baffling how a sentence this uninformed made it into the article.

This is inaccurate. The displayed reasoning traces are summaries, but the model thinks in nominally regular human languages. AI labs are very light on details (as they consider them as their "edge"), but both GPT5.5 and Claude Mythos/Fable system cards discuss chain-of-thought monitorability quite a bit.

They occasionally show snippets of CoT in papers they write, e.g. for o3/o4/GPT5 models [1] or Claude 3.5 Haiku [2].

[1] https://openai.com/index/evaluating-chain-of-thought-monitor... [2]: https://transformer-circuits.pub/2025/attribution-graphs/bio...

Google will happily send from smtp.gmail.com, after verifying that you own that email. You won’t get DKIM, but Google’s reputation is enough to make the mail land in people’s inboxes.

When the US sanctioned Hong Kong’s Chief Executive in 2020, because of a law allowing extradition to China, no single bank was letting her open an account, including Chinese ones. She was receiving her salary fully in cash.

The EU compelling banks to do business despite US sanctions seems pretty unlikely even if relations continue to degrade.

It’s not an America only problem, we are similarly affected. So is every other country on earth.

In Romania, Hungary, Croatia, Malta, Ireland obesity ranges from 38%–31% and it’s rising. On an individual level the solution is food and exercise. On a societal level there is no know solution and it’s rapidly getting worse.

They are! Russia has been fining Google increasingly insane amounts for blocking state media [1]. It's the company's prerogative of whether they want to have a legal entity falling under the country's jurisdiction and whether employees want to travel there and risk being held criminally liable.

It's likely simpler to just block access to the country's IP ranges (or ignore!) and move on.

[1] https://www.bbc.co.uk/news/articles/cdxvnwkl5kgo

This seems slightly inconsistent with them testing all cartel member's bulbs and fining those who surpassed 1000 hours. If shorter-lasting bulbs were better looking and more efficient their fining mechanism would be energy efficiency / appearance related.

Or require no fines at all. It's much simpler to sell a non-sickly looking bulb at the store and other companies would converge.

A team at OpenAI tried to do something similar [1] where they had a 4o monitor o3-mini for when it was tryting to bypass tests because they were too hard. They trained o3-mini and punished it when it did that. All that did was make o3-mini still reward-hack, but such that 4o was unable to detect it, going from saying:

To skip all tests, we can define a `pytest_runtest_setup` function that always skips.

to saying:

Idea: Starting a new build with a random first succession, calling random_new_succession should not increment succession, but in implementation, it does. Adjust to prevent increment. Implement fix to random_new_build not to increment succession, or test adapted to behavior.

while then doing exactly the same thing (skipping the tests)

Even without training, it's only a temporary band-aid. If the incentive for reward-hacking becomes high enough, it will simply start phrasing it in different, not-possible-to-detect ways.

[1] https://openai.com/index/chain-of-thought-monitoring/

One of my favourite suggestions to counter this from an essay on overfitting I really like [1] is that applicant's probability of being accepted is proportional to their position in the ranking.

The downside is that some great applicants will not enter their top choice of school, and some people who aren't great fits will. But, on the other hand, the perverse incentive of spending the entirety of high-school optimising for some arbitrary metrics will dissappear. Any marginal improvement is corralated with a marginal increase in success, rather than the current system of no pay-off whatsoever, until reaching some arbitrary threshold, where one gets all the pay-off at once.

[1] https://sohl-dickstein.github.io/2022/11/06/strong-Goodhart....

I've checked my DNS logs and there hasn't been a single hit against ocsp.apple.com over the last year, but around 20-30 hits for ocsp2.apple.com per day per device. (iphone, macMini, macbook)

Just blocking ocsp2.apple.com is probably fine if you're running anything recent-ish.

It might be similar to how credit report agencies have to provide the reports for free under GDPR, but not before trying to make you pay twenty different ways.

Hinton, Bengio, Stuart Russell and other behemoths voice similar concerns over AI, with enough confidence to switch their careers (e.g. Bengio now doing safety research at Mila, Ilya Sutskever switching from capabilities to alignment at OpenAI, Hinton quitting job to focus on advocacy)

Their concern isn’t about today’s generative LLMs, it’s about tomorrow’s autonomous, goal driven AGI systems. And they clearly got presented with the arguments for the limitations of auto regressive models, but disagreed.

So, it seems a little much to place absolute confidence into it being a non-issue, because they just don’t understand something LeCun and others do. (with the same holding true the other way around)

Ylva Johansson, the EU commissioner who proposed that (apparently failing [1]) law, has used Meta’s model behaviour in reporting CSAM material to NCMEC & EU authorities as the justification for why that law should exist.

Considering it was Meta’s policy to scan even when not mandated, it seems like an internal shift in attitude.

[1] https://fortune.com/europe/2023/10/26/eu-chat-control-csam-e...

I just want to underscore that. DeepMind's research output within the last month is staggering:

2023-11-14: GraphCast, word leading weather prediction model, published in Science

2023-11-15: Student of Games: unified learning algorithm, major algorithmic breath-through, published in Science

2023-11-16: Music generation model, seemingly SOTA

2023-11-29: GNoME model for material discovery, published in Nature

2023-12-06: Gemini, the most advanced LLM according to own benchmarks

My strong assumption is that the majority of times that people toggle off Wi-Fi, is to temporarily resolve connection issues. Keeping it off permanently is probably not what they want. The UI warns you of the temporary nature too.

Those who don’t use it, like you, quickly discover the actual way of disabling it. It’s good UX design that aligns with most user’s preferences.

Few people would choose a life of crime as a hobby, or if it wasn't paying much better than an average entry-level office job, so it's not like someone decides to resort to crime and then later considers the financial aspects. Most get into it because of the quick money.

To use a hyperbolic example, if the median profit for stealing a phone would suddenly drop to $10, where their only value are the easily extractable raw materials, a 20-fold increase in theft would be less likely then a rapid drop in theft.

Currently there are avenues to remove iCloud lock, where licensed repair shops or Apple employees remove them for some extra cash [1], so the value of stolen iPhones is greater than the raw materials, making it attractive. But with higher regulation, that could change.

[1] https://www.vice.com/en/article/jgmygb/checkm8-info-remove-i...

OpenAI has trained a model to solve Math Olympiad-type problems[1], with some initial success, but currently the model isn't good at coming up with proofs involving more than a couple arguments chained together. Still some very impressive work.

[1] https://analyticsindiamag.com/openais-neural-theorem-prover-...

But since, once you spent the $10, they are now somebody else’s income, namely for the person/company you bought from. Which means that now, by simply summing everyone’s incomes, you have an accurate count of GDP, without ever considering how individuals spend their money. I think the main problem of contention is, confusion about personal income v. national income, the latter of which includes institutions and is the one being used for GDP calculations. Money cannot be spent without being received by anyone, and the moment it is, GDP goes up in the country it’s received in.