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| Blog | https://espadrine.github.io/blog/ |
| https://mobile.twitter.com/espadrine |

Ring founder Jamie Siminoff is back at the helm of the surveillance doorbell company, and with him is the surveillance-first-privacy-last approach that made Ring one of the most maligned tech devices. Not only is the company reintroducing new versions of old features which would allow police to...
Oh this is wonderful news:
DNS-PERSIST-01: A New Model for DNS-based Challenge Validation
https://letsencrypt.org/2026/02/18/dns-persist-01.html
> Instead of publishing a new challenge record for each issuance, you publish a standing authorization in the form of a TXT record that identifies both the CA and the specific ACME account you authorize to issue for this domain.

When you request a certificate from Let’s Encrypt, our servers validate that you control the hostnames in that certificate using ACME challenges. For subscribers who need wildcard certificates or who prefer not to expose infrastructure to the public Internet, the DNS-01 challenge type has long been the only choice. DNS-01 works well. It is widely supported and battle-tested, but it comes with operational costs: DNS propagation delays, recurring DNS updates at renewal time, and automation that often requires distributing DNS credentials throughout your infrastructure.
Today is European 112 Day 🇪🇺
📞 112 is the EU’s single emergency number.
It connects you to ambulance, fire brigade or police. It’s free of charge across Europe and offers language support in many countries.
A life-saving number everyone should know.
It also outputs a [word] token, which fits the [STREAMING_WORD] token found in Voxtral 2.
Why have that?
For text-to-speech: there, when the model knows it has finished outputting the audio for a word, it generates the WORD action, so that we can feed it the next word to say.
But there are a lot more tokens in there that are unexplained!
To learn more, we can look at what inspired Mistral: the Kyutai Delayed Stream Modeling, https://arxiv.org/abs/2509.08753
It has the same delay design with the [pad] tokens.
Of course, the output does not contain exactly one word per text token, since the audio file does not contain exactly one word per 80ms.
The trick? Look at those new tokens: when the model needs to wait before outputting a word, it outputs a [STREAMING_PAD] token.