Creating institutional forms that can incorporate diversity and respond flexibly to a changing environment while maintaining legitimacy in the eyes of citizens is the fundamental project of state capacity that faces us.
Since 2025, MAGA ideologues have been using this alleged plot as an excuse to dismantle government programs, stifle research, intimidate American citizens, and even distort American foreign policy.
I have said for many years now that the thing I'm worried about with the models is a Black Monday type scenario, where many algorithms work with each other and get us into weird basins of actions.
It's true that Meta's rivals do largely employ the same cocktail of video formats, recommendation algorithms, and push notifications to continuously derail their users' attention.
European governments and thus the EU too is losing lots of tax income from Europeans fleeing Next on the agenda is the European Exit Tax and after that I think they will try to add Worldwide Income Tax (like the US already has) meaning it doesn't matter where you live in the world as a European citizen, the EU will tax you for your entire income!
One of the few books that successfully brings CS into everyday life. We need more books like this. An audiobook is also available, but this one is better on paper.
So we conjectured that the lack of data was a huge part of the reason that's the lack of progress in AI. So we took a departure from everybody else who are really focusing only on algorithm and said that we need data. we need data to drive these algorithms.
Your your models can be leaked, algorithms can be replicated, but hundreds of millions of miles of fully autonomous operations in the real world, backed by evidence-grade evaluation and publicly audited proof, that is much, much more difficult to replicate.
If you think about our large scale models today, they probably see a thousand times as much data as a human does by the age of 18. Yet, the human by the age of 18 is better in a lot of things and, you know, on par uh with those frontier models that have seen way more data. So could you come up with much more data efficient systems that can learn continuously learn from their own actions?
new laws are like code that is pushed live to production without even being read (let alone tested), often in the face of tremendous opposition, affecting millions of citizens, with minimal monitoring to ensure they’re producing the desired results, an extremely slow customer feedback cycle, and few ways to truly opt out.
For recording ATP, we use Zoom to talk with each other, Audio Hijack to record our local audio, Dropbox to share files with one another, Textual for our IRC chat room
For recording ATP, we use Zoom to talk with each other, Audio Hijack to record our local audio, Dropbox to share files with one another, Textual for our IRC chat room
And then I was like, okay, can you come up with an algorithm that is better than the algorithms that I came up with or that anybody else came up with and go ahead and like look at all the published work and synthesize that and then try to come up with something novel and it it's not able to do it. And I can give it a lot of time and it's it's still not able to do it.
And DSA interviews were never the best for that. Well, thinking, sure. But in terms of like does that skill translate to what you're doing on the job? It never really translated to that. It was more about evaluating like does somebody think?
I'm not going to spend four interviews going through and asking somebody data structures and algorithm stuff. I just have them do work that might be similar to something I'd give them on the job or even just have a conversation with them. See how they think. Like can they think through trade-offs? I don't even care about what answer they give me to a problem. I care about like what's like why did they say that?
We have got to acknowledge that most of the advanc advances in AI came out of algorithm advances not just the raw hardware. Now if most advances came from algorithms and computer science and programming tell me that their army of AI researchers is not their fundamental advantage.
Something I've been thinking about - I am bullish on people (empowered by AI) increasing the visibility, legibility and accountability of their governments.
Given the simplicity and speed of the algorithms in this post and the increasingly small deltas between successive algorithms, perhaps we are nearing an optimal solution.
So this is a filter. Like if I'm talking to you, it takes effort to put it down on the page. I don't record anything that I've filtered it. It's interesting enough to me that it belongs on the page.
That's how you end up in an endless loop of ever-increasing taxes, ever-increasing regulation, which ultimately suffocates free market, free enterprise, and free speech. So, you do want to have very, very strict limitations on the extent the government can increase its powers at the expense of citizens.
Well, there's nothing in them which will cause it to generalize. Well, the gradient descent will cause them to find a solution to the problems they've seen. And if there's only one way to solve them, you know, they they'll do it. But there are many ways to solve it. Some which generalize well, some which generalize poorly. There's nothing in them in the algorithms that will cause them to generalize well.
It's very relatable; the internet is so toxic but we kind of have no choice but to interact with it if we want to be heard as musicians / writers / artists / citizens.
What the Apple paper shows, most fundamentally, regardless of how you define AGI, is that LLMs are no substitute for good well-specified conventional algorithms.
I predict (with confidence bordering on arrogance) that whatever machine-learning progress can be made will correlate extremely closely with the quality of the data around any given problem
I have recently been recording using a RØDE NT1 with a RØDE AI-1 interface. RØDE is also responsible for attaching the mic to the desk using the PSA1 boom arm.
I have a couple of 24'' ASUS VG248 Full HD monitors. I use one to record the screen and the other to have some notes/code opened that I look at while recording.
It's a must-read for anyone looking to deepen their relationships and broaden their perspectives—and I believe it has the power to make us better friends, colleagues, and citizens.
Governments should create three tracks for people who come to live in their country. One track is that of people who hope to become Spanish. Another is that of those who we are going to allow to live and work here; the third is that of those of we are going to allow to be in Spain out of necessity.
It just predicts what you are likely to re-Tweet and like, and linger on. That’s what all these algorithms do. It’s what Tik-Tok does, it’s what all these recommendation engines do. And it turns out that the thing that you are most likely to interact with is outrage. And that’s a quirk of the human condition.
Songs arise out of suffering, by which I mean they are predicated upon the complex, internal human struggle of creation and, well, as far as I know, algorithms don’t feel. Data doesn’t suffer.
The best and easiest-found-by-optimization algorithms for solving problems we want an AI to solve, readily generalize to problems we’d rather the AI not solve; you can’t build a system that only has the capability to drive red cars and not blue cars, because all red-car-driving algorithms generalize to the capability to drive blue cars.
On the iPad, I write using 1Writer or Drafts, and edit podcasts using the Apple Pencil and Ferrite Recording Studio, which is the best podcast editing app I've found on any platform.
The Splendid and the Vile is a brilliant account of another era of widespread anxiety: the years 1940 and 1941, when English citizens spent almost every night in makeshift shelters as massive bombs rained down on them.
Other software I use to build stuff includes Netlify for hosting, GitHub for version control and collaboration, SVGO and TinyPNG for optimization, Kap for screen recording, GoatCounter for analytics, and Chrome and Firefox dev tools.
Other software I use to build stuff includes Netlify for hosting, GitHub for version control and collaboration, SVGO and TinyPNG for optimization, Kap for screen recording, GoatCounter for analytics, and Chrome and Firefox dev tools.
Other software I use to build stuff includes Netlify for hosting, GitHub for version control and collaboration, SVGO and TinyPNG for optimization, Kap for screen recording, GoatCounter for analytics, and Chrome and Firefox dev tools.
Information theory has a way of shaping the way you view many things in math, computer science, physics, and beyond. It's one of those fields that takes ideas that you wouldn't think of as being quantifiable or rigorous and makes them so.
The holy grail of broadcast mics, I've been using the SM7B since my audio engineering days when I was recording bands for a living. Sometimes I'm tempted to try something else out of pure curiousity, but so far the SM7B is still the winner.
To me, this book is an illustration of the power of names. Today, in the era of Google, if you know the name of something, you can find out about it with a simple search. But if you don't know of what you're looking for, it suddenly becomes much harder to find it. Having in the back of your head the names of common algorithms that help you solve problems is really powerful.
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.