So in The Netherlands wero is the new name of eCommerce payments, but in another country the new name for peer2peer. But no idea when p2p will launch in the Netherlands or when eCommerce will launch elsewhere. And if the existing services will be degraded when they are internationalized or merged.

The PSP looks at what methods the merchant wants to accept, which methods the user could potentially be using (based on e.g. country by geo IP or some delivery location) and show the relevant icons.

EU users will see schemes like wero or Przelewy24, Japanese customers will see 'konbini' among the icons, and US users may only see credit cards, Apple Pay and Affirm. There are TONS of payment services. Stripe lists 123 of them.

The merchant will want to exclude methods that have high costs (for themselves), maybe they also care about their customers not getting into debt (so no buy-now-pay-later or credit), and some payment methods have higher rates of disputes/chargebacks (e.g. Amex).

In general, most merchants will want to offer as many methods as possible to prevent consumers who have a preference (this week) for using account A over account B from bouncing.

Chrome 124 (april 24) introduced hybrid post-quantum TLS, and Chrome 131 (nov 24) switched to a hybrid using ML-KEM, which was standardized in 2024, just after Firefox 132 (oktober 2024), while openssh introduced a hybrid scheme in release 9.0 (April 2022) and made ML-KEM+25519 default in OpenSSH 10.0 (April 2025).

Hybrid PQ schemes being adopted in other places is people playing catch-up, not the avant garde.

I'd say digital signatures should be the foremost concern, those may need to provide non-repudiation for decades.

>By feeding legacy PRG (circa 1985) and logics to models like Claude, ChatGPT, developers can now instruct the AI to translate decades-old dBase PRG directly into memory-safe Rust, highly concurrent Go, or modern Dart/Flutter cross-platform applications.

And it alludes to this early on, but it doesn't show any examples.

Apart from the 4% of the total worldwide annual turnover fine that theoretically could be levied under GDPR, but has never been imposed in full.

There's a lot of multiplication of numbers in parallel, so it makes sense to try to fit that to matrices.

Cryptography is built bottom-up, but likewise it makes sense to exploit data structures that already exist in silicon.

The article gives a neat example: In one case in the Harvard study, a patient presented with a blood clot to the lungs and worsening symptoms. Human doctors thought the anti-coagulants were failing, but the AI noticed something the humans did not: the patient’s history of lupus meant this might be causing the inflammation of the lungs. The AI was proved correct.

Which is nice and all, but in the presence of a blood clot, I can understand that treating inflammation instead is not the first thing on a doctor's mind, what with blood clots being potentially life threatening and all. It raises the question; was this a real-life case, and what happened to that patient? Since this is a case for which the correct diagnosis is known, it was eventually correctly diagnosed - presumably then the patient did not die of a blood clot, nor of an uncontrollable fever.

Also, how representative is a patient with Lupus? According to House, MD, it's never Lupus.

https://en.wikipedia.org/wiki/Consent_or_pay

Hmm, I wonder how the FDA approves software in a medical devices context. Or if the EU AI act is in any way a precedent.

Oh well, we'll never know.

https://www.independent.co.uk/independentpremium/editors-let...

Just ride/drive a bit more thoughtfully so you don't hurt people, even if they're deaf.

wow.