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.
This means that highly transformative institutions will often look identical to ineffectual talking shops and indeed be identical to ineffectual talking shops.
They tended to underweight the endogenous response of political and military institutions to the catastrophe—the emergence of second-strike forces, elaborate command systems, crisis management, and above all mutually assured retaliation.
The Fascist regime now ruling the US both enables this and has effectively used bogus accusations of "antisemitism" to damage and exert control over prominent institutions they consider to be enemies.
I think a lot of traditional sources of information and education - from cable news to newspapers to textbooks to teachers - are being replaced by digital content creators.
If you do think it's the overall system that matters, then the alignment that's needed is far less like training a virtuous child and more like managing a semi-virtuous corporation!
making intelligence cheap does not automatically make “agency” cheap. people are constrained by time, money, confidence, health, education, institutions, family, geography; a model does not magic any of that away. there’s a perfectly believable future where these tools mostly compound the advantage of people who already have the skill, taste, money and the spare time to use them well.
we've both come to believe that when transformation fails repeatedly, it's time for something different, and one of the tools that leaders need to add to their tool belts (and probably use a lot more frequently than they do today), is starting fresh, creating new entities (agencies and departments, for example) and either endowing them with new authorities or transferring authorities from legacy institutions to the new ones.
The original point of the China Shock 1.0 discourse was not to foreground the unfairness of Chiense competition, so much as the malfunctioning of US policy and societal institutions in the face of concentrated globalization shocks.
When patients don't get the help they need, they don't come away thinking, I didn't get good treatment. They come away thinking, I am too broken to be helped. They leave more hopeless and demoralized than when they came. That is harm.
A capability existing is not the same as a capability being absorbed into institutions, and, perhaps most important of all, translated into outcomes people care about.
Just like Hollywood once compared Netflix to the Albanian Army, the US establishment
doesn’t yet understand how much better Satoshi Nakamoto or Vitalik Buterin is than every
apparatchik they have in the Federal Reserve system.
Generative AI has no internal, designed momentum towards truth and accuracy (beyond the absurdly diminishing returns of energy-hungry multi-layered LLMs), but a person or an institution can (and should).
All institutions are gradually corrupted and need to be reformed and returned to their foundations, or they will collapse under the weight of their corruption.
We don't believe in this like very centralized future where there should be a small number of institutions that um that basically are are advancing all this stuff. Our vision is not that there's going to be like some central super intelligence that solves all of science.
And Russia's never had a commerce-driven economy. China much more so under Deng Xiaoping, but recently Xi Jinping has been privileging the crony sector over the private sector and neither one has stable government institutions.
If you're not changing it, if there's some kind of stagnation there, if you're not changing those external sort of circumstances, yes, like you may start to get sort of diminishing returns again. But that doesn't mean there's anything intrinsic about the situation.
you just made the point of why I think trust in American tech is probably the most important feature. It's not even the model capability. Maybe it is like can I trust you the company? Can I trust you? Your country and its institutions to be a long-term supplier may be the thing that wins the world.
I go back to usually when people are unhappy it's because these things are a little bit out of sync. Like they want this big thing, but they don't actually they're not actually excited about what it takes to do that thing and therefore it's just going to be a mismatch.
I I sent a memo to my company like and we set the expectation that we require that people reflexively reach for AI now and and we require it because it's unfair not to because the people who do otherwise going to be the people who sequester all the best careers to themselves, right?
But again, the people who love to solve problems are the ones who are just so enabled right now and I think everyone starts there. No one is falls in love with solutions at the beginning of their careers.
Well, when the institutions are over and over spectacularly wrong, whether just incompetent, politicized, or mendacious, there is a reason for loss of trust.
It allowed that, but he said, every person has the right to choose their religion. No one can stop them. No one can force them. The idea that it was individual choice, no one in history had ever thought of that, that it belonged to the person.
We live in the era of the symbolic executive, when "being good at stuff" matters far less than the appearance of doing stuff, where "what's useful" is dictated not by outputs or metrics that one can measure but rather the vibes passed between managers and executives that have worked their entire careers to escape the world of work.
But the underlying ideology is familiar from Silicon Valley, Mark Zuckerberg's dictum to "move fast and break things" and replace the messily human with frictionless technology, built by elite engineers who are supposed to know better than anyone else.
So part of the reason that we deploy the way we do, we call it iterative deployment, rather than go build in secret until we got all the way to GPT-5, we decided to talk about GPT-1, 2, 3, and 4. And part of the reason there is I think AI and surprise don’t go together. And also the world, people, institutions, whatever you want to call it, need time to adapt and think about these things.
I would argue having a business leader run these institutions and then having a board that has, itself, diverse viewpoints, and by the way, permanently structured to have diverse viewpoints is a much better way to run a university than picking an academic that the faculty supports.
Long-term thinking is a giant lever. You can literally solve problems if you think long-term, that are impossible to solve if you think short-term. And we aren't really good at thinking long-term. Five years is a tough timeframe for most institutions to think past.
Society's response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness, and barely address autonomous systems.
The proportion of profiteers seems highly correlated with the number of VERITAS plaques on campus and the high-mindedness of the organization's mission statement.
But modularity may also facilitate a shift away from a concentration of model development in a few institutions and to distributing the development of modular components across the community.
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