This is our third time out with Local-First Conf! In past years we've thoroughly explored some core topics like sync engines and CRDTs. In 2026, we're broadening into areas like identity, e2ee, malleable software, and open-weight models.
If Bush had wanted to whip people up into an inward-looking demagogic fervor instead of an external-facing one, he clearly could have accomplished that, too.
In biomedicine we have a problem called target herding: most companies chase the same biological targets because they are de-risked, which means we explore far less of the biological space than we could.
Um but it would be possible and it would have been possible for somebody to disprove the erdos unit distance conjecture before we did using a general purpose model. And nobody had explored sufficiently what happens if I put $100,000 worth of compute into 5.5 what could it do?
Um, there's just too many interesting ways of combining things. There's too many sort of deep ideas waiting to be uh, discovered and when it you know, not only we, but but nobody ever is going to to discover most of them. So, choices about how to make how to do the exploration actually matter quite a bit.
This book gave me both insight and a deeper curiosity about the subject. This book introduces the SPIN model checker and exposes the reader to the nuances of verifying programs using SPIN. A nice feature of the book is how it explains concepts using thoughtfully developed, freely available tools (such as jSpin) that the author created for pedagogical purposes. It's a demanding book, but the content was interesting. The book presents details about concurrency, temporal logic, non-determinism, advanced SPIN topics, and even case studies. I've already written a few blog posts about the topics I explored while reading this book, and I plan to write more. Overall, it's a good book. I'm sure I'll revisit the latter half again.
Most subject matter is learnable, even stuff that seems really hard. But beyond that, many (most?) traits that people treat as fixed are actually quite malleable if you (1) believe they are and (2) put the same kind of work into learning them as you would anything else.
So they have explored genetic sequence space far more thoroughly than eukaryotes ever did because they’ve had twice as long at least, and they’ve got much larger populations, and they never got around this problem. So why can’t they? It seems as if you can’t solve it with information alone. So what’s the problem? The problem is structure.
I believe every material has a grain, including the web. But this assumption flies in the face of our expectations for technology. Too often, the internet is cast as a wide-open, infinitely malleable material.
A korrent is a belief a person has stated in their own words: one
sentence stating the claim, backed by a quote and a source, kept at
korrents.com.
Under a name here, the quoted block is what they actually said.
The korrent beneath it is the claim those words support, in
korrents' wording — tap it to see the record, its source, and who
else holds it.
Nobody here wrote their own korrents. They are compiled from public
statements, and a person can change their mind, which is recorded too.
About the English under a post
Some people here publish in a language other than English. Where they
do, this site shows a machine translation beneath the post, in
this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the
serif above is exactly what the person published, and it is what to
quote them on. A translation can be wrong in ways that matter,
especially about tone.
Only the post's own words are translated. A quoted post, a linked
article and a belief on korrents.com
are left in their original language.