"When neurotics turn to politics, they find an infinite series of reasons to feel bad, which helps them stay one step ahead of the realization that their fundamental problem is inside their own heads and can be fixed by no one but themselves."
One of the most important for me is just how incredibly complex the human mind is, and how hard the task is of understanding & treating the nearly infinite ways it can stumble/faulter.
There is nearly an infinite range of outcomes here between being fine and being dead. Also, many of them - probably half! - have outcomes which end up being good, if not great, for society.
I suspect that some of the labs' willingness to put money into the social sciences stems from the realization of senior people that the practical build out of AI is highly unpopular in the U.S and their urgent desire to figure out how to sugarcoat the pill so that it will get swallowed
This is the sole intrinsic thing about AI that prevents agents from truly infinite self-replication. They will be constrained by the need to find and pay for sufficient compute to run themselves.
In verifiable domains, model capability scaling should remain unbounded. Models will simply keep improving by "absorbing more and more of the computational universe", which is infinite by construction.
you want to get to a point where you know, your your machine, your org is self-sufficient enough that you know, you just need to occasionally tap the blimp, make sure that things are working. You can course correct if it's not, but that frees you up to then focus on the next important sets of problems that the org needs to, you know, tackle heads on.
And the type of risk that we are asking investors to take is um, we know the physics works. We know that there's infinite demand and how we go from here to there is technology execution. And guess what? Venture capital in the United States is the best at underwriting tech risk of anywhere in the world.
And so um in order to succeed your judgment has to be differentiatedly good. Now the reality might be that you don't know if your judgment is good yet. And so um one way or another you will have to find out and that means making decisions that make sense to you even when you are totally alone in that realization.
what makes the GAWA theory such an interesting example is you have um literally this 100-year segment of like an idea that like flows through many different people's heads before it like settles into something that the math community like agrees is good.
But a proof can reason about potentially infinite state spaces. So, it can tell you things about like every possible thing that could possibly happen in the entire universe.
It's more that for myself, the process of writing is the way how I figure things out. And figuring things out is really my goal here. So, I'm I'm trying to figure it out in my own heads, and for that I just have to write it myself.
What I call vision is the ability to not only take a great idea, but shepherd it into existence, and you’re doing that through inspiration first and foremost.
And so it's not really about the environment or the wall. It's really about how we see it and whether we can find the thing that is deep and rich and infinite in that direction.
Code and data is hard, but ideas is easy. Silicon Valley operates on the way that top employees get bought out by other companies for a pay raise, and a large reason why these companies do this is to bring ideas with them.
Many of them try to pretend the measurement problem isn't there. Go to enormous lengths like the many-worlds interpretation, literally inventing an infinite number of unobservable parallel universes to avoid the thing that quantum mechanics is telling them, which is that measurements matter.
So what he concluded was that he called remembering an imaginative construction, meaning that we don’t replay the past, we imagine how the past could have been by taking bits and pieces that come up in our heads.
They aren’t designed to solve your problem, but actually aim to prevent closure, and create an illusion that there are still infinite choices available to you.
So abstract. Maybe the most abstract book you’ll ever read. Compares “finite” games with rules and winners, versus “infinite” games without winners where we can play with the game itself. Is it about a job versus a calling? Religion versus spirituality? A story versus story-telling? Who knows. Thought-provoking if you can apply the metaphor to whatever concerns you.
The problem is, when humans went bipedal, our pelvises got smaller, and as humans got smarter, our heads got bigger. So evolution had to get creative. Its solution: all human babies would be premies, born when they were still small enough to pass through a human pelvis.
It's incredibly written, deeply complex, confusing as hell, and you'll probably throw it at the wall when it's done. But then you'll kinda go "okay... I'm glad I did that" and maybe start it again.
This is another wonderful book aiming to popularize calculus (2019 was a good year for that goal). What I enjoyed about this one is how broad a view Strogatz takes of the origins of calculus, ranging from the clever proofs Archimedes was developing up to Fourier's study of heat.
In any case, I think we need to not only look at the incentives facing scientists, but also those facing department heads, journals, and grant-making agencies.
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